Publications
Selected publications
- <i>L<sub>p</sub></i>-norm minimization for stochastic process power spectrum estimation subject to incomplete data (Journal article - 2018)
- An open toolbox for the reduction, inference computation and sensitivity analysis of Credal Networks (Journal article - 2018)
- Component importance measures for complex repairable system (Conference Paper - 2016)
- Learning from accidents: interactions between human factors, technology and organisations as a central element to validate risk studies (Journal article - 2017)
- Imprecise system reliability and component importance based on survival signature (Journal article - 2016)
2025
Multi-point Bayesian active learning reliability analysis
Zhou, T., Zhu, X., Guo, T., Dong, Y., & Beer, M. (2025). Multi-point Bayesian active learning reliability analysis. Structural Safety, 114, 102557. doi:10.1016/j.strusafe.2024.102557
Unsupervised graph transfer network with hybrid attention mechanism for fault diagnosis under variable operating conditions
Lei, Z., Tian, F., Su, Y., Wen, G., Feng, K., Chen, X., . . . Yang, C. (2025). Unsupervised graph transfer network with hybrid attention mechanism for fault diagnosis under variable operating conditions. Reliability Engineering & System Safety, 255, 110684. doi:10.1016/j.ress.2024.110684
Efficient variational Bayesian model updating by Bayesian active learning
Hong, F., Wei, P., Bi, S., & Beer, M. (2025). Efficient variational Bayesian model updating by Bayesian active learning. Mechanical Systems and Signal Processing, 224, 112113. doi:10.1016/j.ymssp.2024.112113
Extraction of instantaneous frequencies for signals with intersecting and intermittent trajectories
Li, Y., Geng, C., Yang, Y., Chen, S., Feng, K., & Beer, M. (2025). Extraction of instantaneous frequencies for signals with intersecting and intermittent trajectories. Mechanical Systems and Signal Processing, 223, 111835. doi:10.1016/j.ymssp.2024.111835
A stratified beta-sphere sampling method combined with important sampling and active learning for rare event analysis
Hong, F., Song, J., Wei, P., Huang, Z., & Beer, M. (2025). A stratified beta-sphere sampling method combined with important sampling and active learning for rare event analysis. Structural Safety, 112, 102546. doi:10.1016/j.strusafe.2024.102546
Resilience-Based Decision Criteria for Optimal Regeneration
Salomon, J., Broggi, M., & Beer, M. (2025). Resilience-Based Decision Criteria for Optimal Regeneration. In Regeneration of Complex Capital Goods (pp. 393-422). Springer International Publishing. doi:10.1007/978-3-031-51395-4_20
Streaming variational inference-empowered Bayesian nonparametric clustering for online structural damage detection with transmissibility function
Mei, L. -F., Yan, W. -J., Yuen, K. -V., & Beer, M. (2025). Streaming variational inference-empowered Bayesian nonparametric clustering for online structural damage detection with transmissibility function. Mechanical Systems and Signal Processing, 222, 111767. doi:10.1016/j.ymssp.2024.111767
2024
Physics-informed neural network classification framework for reliability analysis
Shi, Y., & Beer, M. (2024). Physics-informed neural network classification framework for reliability analysis. Expert Systems with Applications, 258, 125207. doi:10.1016/j.eswa.2024.125207
A novel directional simulation method for estimating failure possibility
Jiang, X., Lu, Z., & Beer, M. (2024). A novel directional simulation method for estimating failure possibility. Aerospace Science and Technology, 155, 109627. doi:10.1016/j.ast.2024.109627
Deep learning-driven interval uncertainty propagation for aeronautical structures
SHI, Y., & BEER, M. (n.d.). Deep learning-driven interval uncertainty propagation for aeronautical structures. Chinese Journal of Aeronautics, 37(12), 71-86. doi:10.1016/j.cja.2024.05.009
A sub-convex similarity-based model updating method considering multivariate uncertainties
Zhao, Y., Sun, B., Bi, S., Beer, M., & Moens, D. (2024). A sub-convex similarity-based model updating method considering multivariate uncertainties. Engineering Structures, 318, 118752. doi:10.1016/j.engstruct.2024.118752
Spectral incremental dynamic methodology for nonlinear structural systems endowed with fractional derivative elements subjected to fully non-stationary stochastic excitation
Ni, P., Mitseas, I. P., Fragkoulis, V. C., & Beer, M. (2024). Spectral incremental dynamic methodology for nonlinear structural systems endowed with fractional derivative elements subjected to fully non-stationary stochastic excitation. Structural Safety, 111, 102525. doi:10.1016/j.strusafe.2024.102525
Survival probability surfaces of hysteretic fractional order structures exposed to non-stationary code-compliant stochastic seismic excitation
Mitseas, I. P., Ni, P., Fragkoulis, V. C., & Beer, M. (2024). Survival probability surfaces of hysteretic fractional order structures exposed to non-stationary code-compliant stochastic seismic excitation. Engineering Structures, 318, 118755. doi:10.1016/j.engstruct.2024.118755
Computational modeling of near-fault earthquake-induced landslides considering stochastic ground motions and spatially varying soil
Wang, R., Chen, G., Liu, Y., & Beer, M. (2024). Computational modeling of near-fault earthquake-induced landslides considering stochastic ground motions and spatially varying soil. Engineering Structures, 316, 118580. doi:10.1016/j.engstruct.2024.118580
Reliability evaluation of a multi-state system with dependent components and imprecise parameters: A structural reliability treatment
Yang, L., Zhang, X., Lu, Z., Fu, Y., Moens, D., & Beer, M. (2024). Reliability evaluation of a multi-state system with dependent components and imprecise parameters: A structural reliability treatment. Reliability Engineering & System Safety, 250, 110240. doi:10.1016/j.ress.2024.110240
Sampling and active learning methods for network reliability estimation using K-terminal spanning tree
Ding, C., Wei, P., Shi, Y., Liu, J., Broggi, M., & Beer, M. (2024). Sampling and active learning methods for network reliability estimation using K-terminal spanning tree. Reliability Engineering & System Safety, 250, 110309. doi:10.1016/j.ress.2024.110309
Vibration control and energy harvesting of offshore wind turbines installed with TMDI under dynamical loading
Elias, S., & Beer, M. (2024). Vibration control and energy harvesting of offshore wind turbines installed with TMDI under dynamical loading. Engineering Structures, 315, 118459. doi:10.1016/j.engstruct.2024.118459
Interval Predictor Model for the Survival Signature Using Monotone Radial Basis Functions
Behrensdorf, J., Broggi, M., & Beer, M. (2024). Interval Predictor Model for the Survival Signature Using Monotone Radial Basis Functions. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 10(3). doi:10.1061/ajrua6.rueng-1219
Novel gradient-enhanced Bayesian neural networks for uncertainty propagation
Shi, Y., Chai, R., & Beer, M. (2024). Novel gradient-enhanced Bayesian neural networks for uncertainty propagation. Computer Methods in Applied Mechanics and Engineering, 429, 117188. doi:10.1016/j.cma.2024.117188
Seismic topology optimization considering first-passage probability by incorporating probability density evolution method and bi-directional evolutionary structural optimization
Yang, J. -S., Chen, J. -B., & Beer, M. (2024). Seismic topology optimization considering first-passage probability by incorporating probability density evolution method and bi-directional evolutionary structural optimization. Engineering Structures, 314, 118382. doi:10.1016/j.engstruct.2024.118382
Directional filter combined with active learning for rare failure events
Song, J., Cui, Y., Wei, P., Rashki, M., Zhang, W., & Beer, M. (2024). Directional filter combined with active learning for rare failure events. Computer Methods in Applied Mechanics and Engineering, 428, 117105. doi:10.1016/j.cma.2024.117105
Efficient reliability analysis of stochastic dynamic first-passage problems by probability density evolution analysis with subset supported point selection
Bittner, M., Broggi, M., & Beer, M. (2024). Efficient reliability analysis of stochastic dynamic first-passage problems by probability density evolution analysis with subset supported point selection. Engineering Structures, 312, 118210. doi:10.1016/j.engstruct.2024.118210
Efficiency comparison of MCMC and Transport Map Bayesian posterior estimation for structural health monitoring
Grashorn, J., Broggi, M., Chamoin, L., & Beer, M. (2024). Efficiency comparison of MCMC and Transport Map Bayesian posterior estimation for structural health monitoring. Mechanical Systems and Signal Processing, 216, 111440. doi:10.1016/j.ymssp.2024.111440
Efficient stochastic modal decomposition methods for structural stochastic static and dynamic analyses
Zheng, Z., Beer, M., & Nackenhorst, U. (2024). Efficient stochastic modal decomposition methods for structural stochastic static and dynamic analyses. International Journal for Numerical Methods in Engineering, 125(12). doi:10.1002/nme.7469
Determining the significant contributing factors to the occurrence of human errors in the urban construction projects: A Delphi-SWARA study approach
Sarvari, H., Baghbaderani, A. B., Chan, D. W. M., & Beer, M. (2024). Determining the significant contributing factors to the occurrence of human errors in the urban construction projects: A Delphi-SWARA study approach. Technological Forecasting and Social Change, 205, 123512. doi:10.1016/j.techfore.2024.123512
Namazu: Low-Cost Tunable Shaking Table for Vibration Experiments Under Generic Signals
Grashorn, J., Bittner, M., Banse, M., Chang, X., Beer, M., & Fau, A. (2024). Namazu: Low-Cost Tunable Shaking Table for Vibration Experiments Under Generic Signals. Experimental Techniques. doi:10.1007/s40799-024-00727-8
An effective approach based on reliability methods for high-dimensional Bayesian model updating of dynamical nonlinear structures
Jerez, D. J., Jensen, H. J., Beer, M., & Figueroa, C. (2024). An effective approach based on reliability methods for high-dimensional Bayesian model updating of dynamical nonlinear structures. Journal of Physics: Conference Series, 2647(19), 192001. doi:10.1088/1742-6596/2647/19/192001
Bayesian active learning line sampling with log-normal process for rare-event probability estimation
Dang, C., Valdebenito, M. A., Wei, P., Song, J., & Beer, M. (2024). Bayesian active learning line sampling with log-normal process for rare-event probability estimation. Reliability Engineering & System Safety, 246, 110053. doi:10.1016/j.ress.2024.110053
Efficient time-dependent reliability analysis for a railway bridge model
Bittner, M., Fritsch, L., Hirzinger, B., Broggi, M., & Beer, M. (2024). Efficient time-dependent reliability analysis for a railway bridge model. Journal of Physics: Conference Series, 2647(6), 062002. doi:10.1088/1742-6596/2647/6/062002
Probability of failure of nonlinear oscillators with fractional derivative elements subject to imprecise Gaussian loads
Ni, P., Jerez, D. J., Fragkoulis, V. C., Mitseas, I. P., Faes, M. G. R., Valdebenito, M. A., & Beer, M. (2024). Probability of failure of nonlinear oscillators with fractional derivative elements subject to imprecise Gaussian loads. Journal of Physics: Conference Series, 2647(6), 062005. doi:10.1088/1742-6596/2647/6/062005
Resilience Assessment under Imprecise Probability
Wang, C., Beer, M., Faes, M. G. R., & Feng, D. -C. (2024). Resilience Assessment under Imprecise Probability. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 10(2). doi:10.1061/ajrua6.rueng-1244
Structural reliability analysis using imprecise evolutionary power spectral density functions
Behrendt, M., Dang, C., Faes, M. G. R., Valdebenito, M. A., & Beer, M. (2024). Structural reliability analysis using imprecise evolutionary power spectral density functions. Journal of Physics: Conference Series, 2647(6), 062003. doi:10.1088/1742-6596/2647/6/062003
rLSTM-AE for dimension reduction and its application to active learning-based dynamic reliability analysis
Zhang, Y., Dong, Y., & Beer, M. (2024). rLSTM-AE for dimension reduction and its application to active learning-based dynamic reliability analysis. Mechanical Systems and Signal Processing, 215, 111426. doi:10.1016/j.ymssp.2024.111426
Cost and competitiveness of green hydrogen and the effects of the European Union regulatory framework
Brandt, J., Iversen, T., Eckert, C., Peterssen, F., Bensmann, B., Bensmann, A., . . . Hanke-Rauschenbach, R. (2024). Cost and competitiveness of green hydrogen and the effects of the European Union regulatory framework. Nature Energy, 9(6), 703-713. doi:10.1038/s41560-024-01511-z
Perceived barriers to implementing building information modeling in Iranian Small and Medium-Sized Enterprises (SMEs): a Delphi survey of construction experts
Sarvari, H., Asaadsamani, P., Olawumi, T. O., Chan, D. W. M., Rashidi, A., & Beer, M. (n.d.). Perceived barriers to implementing building information modeling in Iranian Small and Medium-Sized Enterprises (SMEs): a Delphi survey of construction experts. Architectural Engineering and Design Management, 1-21. doi:10.1080/17452007.2024.2329687
An efficient method for reliability-based design optimization of structures under random excitation by mapping between reliability and operator norm
Jiang, Y., Zhang, X., Beer, M., Zhou, H., & Leng, Y. (2024). An efficient method for reliability-based design optimization of structures under random excitation by mapping between reliability and operator norm. Reliability Engineering and System Safety, 245. doi:10.1016/j.ress.2024.109972
Parallelization of adaptive Bayesian cubature using multimodal optimization algorithms
Hong, F., Wei, P., & Beer, M. (2024). Parallelization of adaptive Bayesian cubature using multimodal optimization algorithms. Engineering Computations, 41(2), 413-437. doi:10.1108/ec-12-2023-0957
Efficient slope reliability analysis under soil spatial variability using maximum entropy distribution with fractional moments
Feng, C., Valdebenito, M. A., Chwała, M., Liao, K., Broggi, M., & Beer, M. (2024). Efficient slope reliability analysis under soil spatial variability using maximum entropy distribution with fractional moments. Journal of Rock Mechanics and Geotechnical Engineering, 16(4), 1140-1152. doi:10.1016/j.jrmge.2023.09.006
Health prognosis of bearings based on transferable autoregressive recurrent adaptation with few-shot learning
Zhuang, J., Jia, M., Huang, C. G., Beer, M., & Feng, K. (2024). Health prognosis of bearings based on transferable autoregressive recurrent adaptation with few-shot learning. Mechanical Systems and Signal Processing, 211. doi:10.1016/j.ymssp.2024.111186
Peridynamics-based large-deformation simulations for near-fault landslides considering soil uncertainty
Wang, R., Li, S., Liu, Y., Hu, X., Lai, X., & Beer, M. (2024). Peridynamics-based large-deformation simulations for near-fault landslides considering soil uncertainty. Computers and Geotechnics, 168. doi:10.1016/j.compgeo.2024.106128
Refined parallel adaptive Bayesian quadrature for estimating small failure probabilities
Wang, L., Hu, Z., Dang, C., & Beer, M. (2024). Refined parallel adaptive Bayesian quadrature for estimating small failure probabilities. Reliability Engineering & System Safety, 244, 109953. doi:10.1016/j.ress.2024.109953
Relaxed evolutionary power spectral density functions: A probabilistic approach to model uncertainties of non-stationary stochastic signals
Bittner, M., Behrendt, M., & Beer, M. (2024). Relaxed evolutionary power spectral density functions: A probabilistic approach to model uncertainties of non-stationary stochastic signals. Mechanical Systems and Signal Processing, 211. doi:10.1016/j.ymssp.2024.111210
Structural reliability analysis with extremely small failure probabilities: A quasi-Bayesian active learning method
Dang, C., Cicirello, A., Valdebenito, M. A., Faes, M. G. R., Wei, P., & Beer, M. (2024). Structural reliability analysis with extremely small failure probabilities: A quasi-Bayesian active learning method. Probabilistic Engineering Mechanics, 76, 103613. doi:10.1016/j.probengmech.2024.103613
Multiaxial fatigue life prediction using an improved Smith‐Watson‐Topper model
Li, J., Shao, F., He, Z., Ma, J., Qiu, Y., & Beer, M. (2024). Multiaxial fatigue life prediction using an improved Smith‐Watson‐Topper model. Fatigue & Fracture of Engineering Materials & Structures. doi:10.1111/ffe.14285
Dconformer: A denoising convolutional transformer with joint learning strategy for intelligent diagnosis of bearing faults
Li, S., Ji, J. C., Xu, Y., Feng, K., Zhang, K., Feng, J., . . . Wang, Y. (2024). Dconformer: A denoising convolutional transformer with joint learning strategy for intelligent diagnosis of bearing faults. Mechanical Systems and Signal Processing, 210, 111142. doi:10.1016/j.ymssp.2024.111142
Partially Bayesian active learning cubature for structural reliability analysis with extremely small failure probabilities
Dang, C., Faes, M. G. R., Valdebenito, M. A., Wei, P., & Beer, M. (2024). Partially Bayesian active learning cubature for structural reliability analysis with extremely small failure probabilities. Computer Methods in Applied Mechanics and Engineering, 422. doi:10.1016/j.cma.2024.116828
Deep learning-based prediction of wind-induced lateral displacement response of suspension bridge decks for structural health monitoring
Wang, Z. -W., Lu, X. -F., Zhang, W. -M., Fragkoulis, V. C., Zhang, Y. -F., & Beer, M. (2024). Deep learning-based prediction of wind-induced lateral displacement response of suspension bridge decks for structural health monitoring. Journal of Wind Engineering and Industrial Aerodynamics, 247, 105679. doi:10.1016/j.jweia.2024.105679
Experimental model updating of slope considering spatially varying soil properties and dynamic loading
Wang, R., Ouyang, J., Fragkoulis, V. C., Liu, Y., & Beer, M. (2024). Experimental model updating of slope considering spatially varying soil properties and dynamic loading. Earthquake Engineering and Resilience, 3(1), 33-53. doi:10.1002/eer2.70
Hybrid uncertainty propagation based on multi-fidelity surrogate model
Liu, J., Shi, Y., Ding, C., & Beer, M. (2024). Hybrid uncertainty propagation based on multi-fidelity surrogate model. Computers & Structures, 293, 107267. doi:10.1016/j.compstruc.2023.107267
Similarity quantification of soil spatial variability between two cross-sections using auto-correlation functions
Hu, Y., Wang, Y., Phoon, K. -K., & Beer, M. (2024). Similarity quantification of soil spatial variability between two cross-sections using auto-correlation functions. Engineering Geology, 331, 107445. doi:10.1016/j.enggeo.2024.107445
Failure probability estimation of dynamic systems employing relaxed power spectral density functions with dependent frequency modeling and sampling
Behrendt, M., Lyu, M. -Z., Luo, Y., Chen, J. -B., & Beer, M. (2024). Failure probability estimation of dynamic systems employing relaxed power spectral density functions with dependent frequency modeling and sampling. Probabilistic Engineering Mechanics, 75, 103592. doi:10.1016/j.probengmech.2024.103592
Improving the performance of low-frequency magnetic energy harvesters using an internal magnetic-coupled mechanism
You, Z., Miao, H., Shi, Y., & Beer, M. (2024). Improving the performance of low-frequency magnetic energy harvesters using an internal magnetic-coupled mechanism. Journal of Applied Physics, 135(8). doi:10.1063/5.0195091
Estimation of Response Expectation Bounds under Parametric P-Boxes by Combining Bayesian Global Optimization with Unscented Transform
Ding, C., Dang, C., Broggi, M., & Beer, M. (2024). Estimation of Response Expectation Bounds under Parametric P-Boxes by Combining Bayesian Global Optimization with Unscented Transform. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 10(2). doi:10.1061/ajrua6.rueng-1169
Data-driven and physics-based interval modelling of power spectral density functions from limited data
Behrendt, M., Dang, C., & Beer, M. (2024). Data-driven and physics-based interval modelling of power spectral density functions from limited data. Mechanical Systems and Signal Processing, 208, 111078. doi:10.1016/j.ymssp.2023.111078
Operator norm-based determination of failure probability of nonlinear oscillators with fractional derivative elements subject to imprecise stationary Gaussian loads
Jerez, D. J., Fragkoulis, V. C., Ni, P., Mitseas, I. P., Valdebenito, M. A., Faes, M. G. R., & Beer, M. (2024). Operator norm-based determination of failure probability of nonlinear oscillators with fractional derivative elements subject to imprecise stationary Gaussian loads. Mechanical Systems and Signal Processing, 208, 111043. doi:10.1016/j.ymssp.2023.111043
A full‐probabilistic cloud analysis for structural seismic fragility via decoupled M‐PDEM
Lyu, M., Feng, D., Cao, X., & Beer, M. (2024). A full‐probabilistic cloud analysis for structural seismic fragility via decoupled M‐PDEM. Earthquake Engineering & Structural Dynamics. doi:10.1002/eqe.4093
Climate Change Impacts on the Risk Assessment of Concrete Civil Infrastructures
Feng, D. -C., Ding, J. -Y., Xie, S. -C., Li, Y., Akiyama, M., Lu, Y., . . . Li, J. (2024). Climate Change Impacts on the Risk Assessment of Concrete Civil Infrastructures. ASCE OPEN: Multidisciplinary Journal of Civil Engineering, 2(1). doi:10.1061/aomjah.aoeng-0026
Network reliability analysis through survival signature and machine learning techniques
Shi, Y., Behrensdorf, J., Zhou, J., Hu, Y., Broggi, M., & Beer, M. (2024). Network reliability analysis through survival signature and machine learning techniques. Reliability Engineering & System Safety, 242, 109806. doi:10.1016/j.ress.2023.109806
Optimal borehole placement for the design of rectangular shallow foundation systems under undrained soil conditions: A stochastic framework
Jerez, D. J., Chwała, M., Jensen, H. A., & Beer, M. (2024). Optimal borehole placement for the design of rectangular shallow foundation systems under undrained soil conditions: A stochastic framework. Reliability Engineering & System Safety, 242, 109771. doi:10.1016/j.ress.2023.109771
Tensor representation-based transferability analytics and selective transfer learning of prognostic knowledge for remaining useful life prediction across machines
Mao, W., Zhang, W., Feng, K., Beer, M., & Yang, C. (2024). Tensor representation-based transferability analytics and selective transfer learning of prognostic knowledge for remaining useful life prediction across machines. Reliability Engineering and System Safety, 242, 109695. doi:10.1016/j.ress.2023.109695
Reliability assessment of freight wagon passing through railway turnouts using adaptive Kriging surrogate model
Lai, J., Wang, K., Shi, Y., Xu, J., Chen, J., Wang, P., & Beer, M. (2024). Reliability assessment of freight wagon passing through railway turnouts using adaptive Kriging surrogate model. International Journal of Rail Transportation, 1-20. doi:10.1080/23248378.2024.2304000
A sequential sampling-based Bayesian numerical method for reliability-based design optimization
Hong, F., Wei, P., Fu, J., & Beer, M. (2024). A sequential sampling-based Bayesian numerical method for reliability-based design optimization. Reliability Engineering & System Safety, 244, 109939. doi:10.1016/j.ress.2024.109939
A non-iterative partitioned computational method with the energy conservation property for time-variant dynamic systems
Yuan, P., Yuen, K. -V., Beer, M., Cai, C. S., & Yan, W. (2024). A non-iterative partitioned computational method with the energy conservation property for time-variant dynamic systems. Mechanical Systems and Signal Processing, 209, 111105. doi:10.1016/j.ymssp.2024.111105
Assessing updated seismic performance of existing structures by stochastic model updating
Kitahara, M., Bi, S., Broggi, M., & Beer, M. (2022). Assessing updated seismic performance of existing structures by stochastic model updating. In 8th International Symposium on Reliability Engineering and Risk Management (pp. 265-270). Research Publishing Services. doi:10.3850/978-981-18-5184-1_ms-09-086-cd
Bounding Failure Probabilities in Imprecise Stochastic FE models
G. R. Faes, M., Fina, M., Valdebenito, M. A., Lauff, C., Wagner, W., Freitag, S., & Beer, M. (2022). Bounding Failure Probabilities in Imprecise Stochastic FE models. In 8th International Symposium on Reliability Engineering and Risk Management (pp. 498-501). Research Publishing Services. doi:10.3850/978-981-18-5184-1_ms-15-141-cd
Classification of power spectra from data sets with high spectral variance for reliability, analysis of dynamic structures
Behrendt, M., Kitahara, M., Kitahara, T., Comerford, L., & Beer, M. (2022). Classification of power spectra from data sets with high spectral variance for reliability, analysis of dynamic structures. In 8th International Symposium on Reliability Engineering and Risk Management (pp. 323-328). Research Publishing Services. doi:10.3850/978-981-18-5184-1_ms-11-160-cd
Comparison of state of the art sampling-based Bayesian Updating techniques
Dodt, M. B., Kitahara, M., Broggi, M., & Beer, M. (2022). Comparison of state of the art sampling-based Bayesian Updating techniques. In 8th International Symposium on Reliability Engineering and Risk Management (pp. 59-66). Research Publishing Services. doi:10.3850/978-981-18-5184-1_ms-02-146-cd
Entropy Indicators of Cascading Failures Risk in Gaussian Interconnected Network Structures
Tyrsin, A. N., Kashcheev, S. E., Beer, M., & Gerget, O. M. (2024). Entropy Indicators of Cascading Failures Risk in Gaussian Interconnected Network Structures. In Studies in Systems, Decision and Control (pp. 219-234). Springer Nature Switzerland. doi:10.1007/978-3-031-67911-7_17
Estimation of First Excursion Probability in Stochastic Linear Dynamics by means of, Multidomain Line Sampling
Valdebenito, M., Wei, P., Song, J., Beer, M., & Broggi, M. (2022). Estimation of First Excursion Probability in Stochastic Linear Dynamics by means of, Multidomain Line Sampling. In 8th International Symposium on Reliability Engineering and Risk Management (pp. 369-372). Research Publishing Services. doi:10.3850/978-981-18-5184-1_ms-12-153-cd
Estimation of Second-order Statistics of Buckling Loads Applying Linear and Nonlinear Analysis
Fina, M., G. R. Faes, M., Valdebenito, M. A., Wagner, W., Broggi, M., Beer, M., & Freitag, S. (2022). Estimation of Second-order Statistics of Buckling Loads Applying Linear and Nonlinear Analysis. In 8th International Symposium on Reliability Engineering and Risk Management (pp. 502-507). Research Publishing Services. doi:10.3850/978-981-18-5184-1_ms-15-145-cd
Estimation of response expectation function under hybrid uncertainties by parallel Bayesian quadrature optimization
Dang, C., Wei, P., Faes, M., & Beer, M. (2022). Estimation of response expectation function under hybrid uncertainties by parallel Bayesian quadrature optimization. In 8th International Symposium on Reliability Engineering and Risk Management (pp. 160-165). Research Publishing Services. doi:10.3850/978-981-18-5184-1_ms-06-123-cd
First-passage Probability Estimation of Stochastic Dynamic Systems by a Parametric Approach
Ding, C., Dang, C., Broggi, M., & Beer, M. (2022). First-passage Probability Estimation of Stochastic Dynamic Systems by a Parametric Approach. In 8th International Symposium on Reliability Engineering and Risk Management (pp. 40-46). Research Publishing Services. doi:10.3850/978-981-18-5184-1_ms-01-175-cd
Frequency comparison of the pulse-like and non-pulse ground motions
Chen, G., Liu, Y., & Beer, M. (2022). Frequency comparison of the pulse-like and non-pulse ground motions. In 8th International Symposium on Reliability Engineering and Risk Management (pp. 277-281). Research Publishing Services. doi:10.3850/978-981-18-5184-1_ms-09-134-cd
How to Be Certain: Using Known Relations and Trust Discount to Determine Confidence About the Degree of Uncertainty
Winnewisser, N. R., Potthast, T., Mett, F., Perin, A., Broggi, M., & Beer, M. (n.d.). How to Be Certain: Using Known Relations and Trust Discount to Determine Confidence About the Degree of Uncertainty. In e-Journal of Nondestructive Testing Vol. 29. NDT.net GmbH & Co. KG. doi:10.58286/29669
Model Parameter Updating of the Seismic-Isolated Bridge Pier Using Modified TMCMC
Kitahara, T., Kitahara, M., & Beer, M. (2022). Model Parameter Updating of the Seismic-Isolated Bridge Pier Using Modified TMCMC. In 8th International Symposium on Reliability Engineering and Risk Management (pp. 309-312). Research Publishing Services. doi:10.3850/978-981-18-5184-1_ms-11-085-cd
Multi-taper S-transform method for estimating Wigner-Ville and Loève spectra of quasi-stationary harmonizable processes
Huang, Z., Chen, G., & Beer, M. (2024). Multi-taper S-transform method for estimating Wigner-Ville and Loève spectra of quasi-stationary harmonizable processes. Mechanical Systems and Signal Processing, 206, 110880. doi:10.1016/j.ymssp.2023.110880
Parallel Bayesian probabilistic integration for structural reliability analysis with small failure probabilities
Hu, Z., Dang, C., Wang, L., & Beer, M. (2024). Parallel Bayesian probabilistic integration for structural reliability analysis with small failure probabilities. Structural Safety, 106, 102409. doi:10.1016/j.strusafe.2023.102409
Physic-informed probabilistic analysis with Bayesian machine learning in augmented space
Hong, F., Wei, P., Song, J., G.R. Faes, M., Valdebenito, M. A., & Beer, M. (2022). Physic-informed probabilistic analysis with Bayesian machine learning in augmented space. In 8th International Symposium on Reliability Engineering and Risk Management (pp. 152-159). Research Publishing Services. doi:10.3850/978-981-18-5184-1_ms-06-055-cd
Preface
Beer, M., Zio, E., Phoon, K. K., & Ayyub, B. M. (2024). Preface. Proceedings of the 8th International Symposium on Reliability Engineering and Risk Management, ISRERM 2022, v-vi. doi:10.3850/978-981-18-5184-1_prelims
Probability distributions for dynamic and extreme responses of linear elastic structures under quasi-stationary harmonizable loads
Huang, Z., & Beer, M. (2024). Probability distributions for dynamic and extreme responses of linear elastic structures under quasi-stationary harmonizable loads. Probabilistic Engineering Mechanics, 75, 103590. doi:10.1016/j.probengmech.2024.103590
Random Failure Mechanism Method in Optimal Borehole Placement for Shallow Foundation Design Under Spatially Variable Conditions
Chwała, M., Jerez, D. J., Jensen, H. A., & Beer, M. (2022). Random Failure Mechanism Method in Optimal Borehole Placement for Shallow Foundation Design Under Spatially Variable Conditions. In 8th International Symposium on Reliability Engineering and Risk Management (pp. 439-446). Research Publishing Services. doi:10.3850/978-981-18-5184-1_ms-13-188-cd
Random-interval hybrid reliability analysis by a parallel active learning Kriging method with a pseudo weighted expected risk function
Liu, J., Dang, C., & Beer, M. (2022). Random-interval hybrid reliability analysis by a parallel active learning Kriging method with a pseudo weighted expected risk function. In 8th International Symposium on Reliability Engineering and Risk Management (pp. 508-514). Research Publishing Services. doi:10.3850/978-981-18-5184-1_ms-15-221-cd
Reliability analysis of landslides based on the random finite element method (ISRERM 2022)
Feng, C., Broggi, M., & Beer, M. (2022). Reliability analysis of landslides based on the random finite element method (ISRERM 2022). In 8th International Symposium on Reliability Engineering and Risk Management (pp. 600-605). Research Publishing Services. doi:10.3850/978-981-18-5184-1_ms-18-103-cd
Resilience Decision-Making for Complex and Substructured Systems
Salomon, J., Behrensdorf, J., Winnewisser, N., Broggi, M., & Beer, M. (2022). Resilience Decision-Making for Complex and Substructured Systems. In 8th International Symposium on Reliability Engineering and Risk Management (pp. 530-537). Research Publishing Services. doi:10.3850/978-981-18-5184-1_ms-16-191-cd
Response of an MDOF Nonlinear System with Constraints Under Combined Deterministic and Non-stationary Stochastic Excitation
Ni, P., Fragkoulis, V. C., Kong, F., Mitseas, I. P., & Beer, M. (2022). Response of an MDOF Nonlinear System with Constraints Under Combined Deterministic and Non-stationary Stochastic Excitation. In 8th International Symposium on Reliability Engineering and Risk Management (pp. 22-26). Research Publishing Services. doi:10.3850/978-981-18-5184-1_ms-01-139-cd
Robust SHM: Redundancy approach with different sensor integration levels for long life monitoring systems
Bartels, J. -H., Potthast, T., Möller, S., Grießmann, T., Rolfes, R., Beer, M., & Marx, S. (n.d.). Robust SHM: Redundancy approach with different sensor integration levels for long life monitoring systems. In e-Journal of Nondestructive Testing Vol. 29. NDT.net GmbH & Co. KG. doi:10.58286/29699
Simulation and risk evaluation of possible superstorms hitting Europe's north sea coast
Sun, Y., Bittner, M., Zhang, Y., & Beer, M. (2022). Simulation and risk evaluation of possible superstorms hitting Europe's north sea coast. In 8th International Symposium on Reliability Engineering and Risk Management (pp. 629-634). Research Publishing Services. doi:10.3850/978-981-18-5184-1_ms-19-105-cd
Stochastic Response Analysis of a Piezoelectric Harvesting Device Subjected to Non-stationary Wind Loading
Pasparakis, G. D., Fragkoulis, V. C., Kong, F., & Beer, M. (2022). Stochastic Response Analysis of a Piezoelectric Harvesting Device Subjected to Non-stationary Wind Loading. In 8th International Symposium on Reliability Engineering and Risk Management (pp. 27-33). Research Publishing Services. doi:10.3850/978-981-18-5184-1_ms-01-140-cd
Stochastic process generation from relaxed power spectra utilising stochastic harmonic functions
Behrendt, M., Bittner, M., & Beer, M. (2022). Stochastic process generation from relaxed power spectra utilising stochastic harmonic functions. In 8th International Symposium on Reliability Engineering and Risk Management (pp. 52-58). Research Publishing Services. doi:10.3850/978-981-18-5184-1_ms-01-220-cd
The Log-Rayleigh Distribution for Local Maxima of spectrally Represented Log-normal Processes
Grashorn, J., Bittner, M., Wang, C., & Beer, M. (2022). The Log-Rayleigh Distribution for Local Maxima of spectrally Represented Log-normal Processes. In 8th International Symposium on Reliability Engineering and Risk Management (pp. 793-799). Research Publishing Services. doi:10.3850/978-981-18-5184-1_gs-05-108-cd
Uncertainty Quantification Over Spectral Estimation of Stochastic Processes Subject to Gapped Missing Data Using Variational Bayesian Inference
Chen, Y., Patelli, E., Beer, M., & Edwards, B. (2022). Uncertainty Quantification Over Spectral Estimation of Stochastic Processes Subject to Gapped Missing Data Using Variational Bayesian Inference. In 8th International Symposium on Reliability Engineering and Risk Management (pp. 173-178). Research Publishing Services. doi:10.3850/978-981-18-5184-1_ms-06-179-cd
2023
Time-Dependent Resilience in the Presence of Interacting Multiple Hazards in a Changing Climate
Wang, C., Ayyub, B. M., Zhang, H., & Beer, M. (2023). Time-Dependent Resilience in the Presence of Interacting Multiple Hazards in a Changing Climate. ASCE OPEN: Multidisciplinary Journal of Civil Engineering, 1. doi:10.1061/aomjah.aoeng-0024
A KDE-based non-parametric cloud approach for efficient seismic fragility estimation of structures under non-stationary excitation
Cao, X. -Y., Feng, D. -C., & Beer, M. (2023). A KDE-based non-parametric cloud approach for efficient seismic fragility estimation of structures under non-stationary excitation. Mechanical Systems and Signal Processing, 205, 110873. doi:10.1016/j.ymssp.2023.110873
Imprecise Survival Signature Approximation Using Interval Predictor Models
Behrensdorf, J., Broggi, M., & Beer, M. (2023). Imprecise Survival Signature Approximation Using Interval Predictor Models. In 2023 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 506-511). IEEE. doi:10.1109/ssci52147.2023.10371939
A failure probability assessment method for train derailments in railway yards based on IFFTA and NGBN
Lai, J., Wang, K., Xu, J., Wang, P., Chen, R., Wang, S., & Beer, M. (2023). A failure probability assessment method for train derailments in railway yards based on IFFTA and NGBN. Engineering Failure Analysis, 154. doi:10.1016/j.engfailanal.2023.107675
Collaborative and Adaptive Bayesian Optimization for bounding variances and probabilities under hybrid uncertainties
Hong, F., Wei, P., Song, J., Valdebenito, M. A., Faes, M. G. R., & Beer, M. (2023). Collaborative and Adaptive Bayesian Optimization for bounding variances and probabilities under hybrid uncertainties. Computer Methods in Applied Mechanics and Engineering, 417, 116410. doi:10.1016/j.cma.2023.116410
Performance assessment of borehole arrangements for the design of rectangular shallow foundation systems
Chwała, M., Jerez, D. J., Jensen, H. A., & Beer, M. (2023). Performance assessment of borehole arrangements for the design of rectangular shallow foundation systems. Journal of Rock Mechanics and Geotechnical Engineering, 15(12), 3291-3304. doi:10.1016/j.jrmge.2023.05.009
Stochastic Model Updating with Uncertainty Quantification: An Overview and Tutorial
Bi, S., Beer, M., Cogan, S., & Mottershead, J. (2023). Stochastic Model Updating with Uncertainty Quantification: An Overview and Tutorial. Mechanical Systems and Signal Processing, 204. doi:10.1016/j.ymssp.2023.110784
Response to discussion of “Seismic damage analysis due to near‐fault multipulse ground motion”
Chen, G., Yang, J., Wang, R., Li, K., Liu, Y., & Beer, M. (2023). Response to discussion of “Seismic damage analysis due to near‐fault multipulse ground motion”. Earthquake Engineering & Structural Dynamics. doi:10.1002/eqe.4046
Transmissibility-based damage detection with hierarchical clustering enhanced by multivariate probabilistic distance accommodating uncertainty and correlation
Mei, L. -F., Yan, W. -J., Yuen, K. -V., Ren, W. -X., & Beer, M. (2023). Transmissibility-based damage detection with hierarchical clustering enhanced by multivariate probabilistic distance accommodating uncertainty and correlation. Mechanical Systems and Signal Processing, 203, 110702. doi:10.1016/j.ymssp.2023.110702
Machine Learning Assisted Network Resilience Design
Shi, Y., & Beer, M. (2023). Machine Learning Assisted Network Resilience Design. In ASCE Inspire 2023 (pp. 673-682). American Society of Civil Engineers. doi:10.1061/9780784485163.079
Resilience Capacity of Civil Structures and Infrastructure Systems
Wang, C., Ayyub, B. M., & Beer, M. (2023). Resilience Capacity of Civil Structures and Infrastructure Systems. In ASCE Inspire 2023 (pp. 459-466). American Society of Civil Engineers. doi:10.1061/9780784485163.055
The Concept of Diagonal Approximated Signature: New Surrogate Modeling Approach for Continuous-State Systems
Winnewisser, N. R., Salomon, J., Broggi, M., & Beer, M. (2023). The Concept of Diagonal Approximated Signature: New Surrogate Modeling Approach for Continuous-State Systems. In ASCE Inspire 2023 (pp. 258-266). American Society of Civil Engineers. doi:10.1061/9780784485163.031
Adaptive decoupled robust design optimization
Shi, Y., Huang, H. -Z., Liu, Y., & Beer, M. (2023). Adaptive decoupled robust design optimization. Structural Safety, 105, 102378. doi:10.1016/j.strusafe.2023.102378
SPECTRAL DENSITY ESTIMATION OF STOCHASTIC PROCESSES UNDER MISSING DATA AND UNCERTAINTY QUANTIFICATION WITH BAYESIAN DEEP LEARNING
Chen, Y., Patelli, E., Edwards, B., & Beer, M. (2023). SPECTRAL DENSITY ESTIMATION OF STOCHASTIC PROCESSES UNDER MISSING DATA AND UNCERTAINTY QUANTIFICATION WITH BAYESIAN DEEP LEARNING. In UNCECOMP Proceedings.
A Bayesian Augmented-Learning framework for spectral uncertainty quantification of incomplete records of stochastic processes
Chen, Y., Patelli, E., Edwards, B., & Beer, M. (2023). A Bayesian Augmented-Learning framework for spectral uncertainty quantification of incomplete records of stochastic processes. Mechanical Systems and Signal Processing, 200, 110573. doi:10.1016/j.ymssp.2023.110573
A graph-guided collaborative convolutional neural network for fault diagnosis of electromechanical systems
Xu, Y., Ji, J. C., Ni, Q., Feng, K., Beer, M., & Chen, H. (2023). A graph-guided collaborative convolutional neural network for fault diagnosis of electromechanical systems. Mechanical Systems and Signal Processing, 200, 110609. doi:10.1016/j.ymssp.2023.110609
An efficient meta-model-based method for uncertainty propagation problems involving non-parameterized probability-boxes
Zhang, K., Chen, N., Liu, J., Yin, S., & Beer, M. (2023). An efficient meta-model-based method for uncertainty propagation problems involving non-parameterized probability-boxes. Reliability Engineering & System Safety, 238, 109477. doi:10.1016/j.ress.2023.109477
An iterative multi-fidelity scheme for simulating multi-dimensional non-Gaussian random fields
Zheng, Z., Beer, M., & Nackenhorst, U. (2023). An iterative multi-fidelity scheme for simulating multi-dimensional non-Gaussian random fields. Mechanical Systems and Signal Processing, 200, 110643. doi:10.1016/j.ymssp.2023.110643
Probabilistic risk assessment of earth dams with spatially variable soil properties using random adaptive finite element limit analysis
Liao, K., Wu, Y., Miao, F., Pan, Y., & Beer, M. (n.d.). Probabilistic risk assessment of earth dams with spatially variable soil properties using random adaptive finite element limit analysis. Engineering with Computers. doi:10.1007/s00366-022-01752-0
Structural design optimization under dynamic reliability constraints based on probability density evolution method and quantum-inspired optimization algorithm
Weng, L. -L., Yang, J. -S., Chen, J. -B., & Beer, M. (2023). Structural design optimization under dynamic reliability constraints based on probability density evolution method and quantum-inspired optimization algorithm. Probabilistic Engineering Mechanics, 74, 103494. doi:10.1016/j.probengmech.2023.103494
Seismic damage analysis due to near‐fault multipulse ground motion
Chen, G., Yang, J., Wang, R., Li, K., Liu, Y., & Beer, M. (2023). Seismic damage analysis due to near‐fault multipulse ground motion. Earthquake Engineering & Structural Dynamics. doi:10.1002/eqe.4003
Special Section on Community Resilience to Disruptive Events: Models and Analyses, Lessons Learned, and Case Studies
Wang, C., Faes, M. G. R., Beer, M., Zio, E., & van de Lindt, J. W. (2023). Special Section on Community Resilience to Disruptive Events: Models and Analyses, Lessons Learned, and Case Studies. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 9(3). doi:10.1115/1.4062982
Structural reliability analysis by line sampling: A Bayesian active learning treatment
Dang, C., Valdebenito, M. A., Faes, M. G. R., Song, J., Wei, P., & Beer, M. (2023). Structural reliability analysis by line sampling: A Bayesian active learning treatment. Structural Safety, 104, 102351. doi:10.1016/j.strusafe.2023.102351
Uncertainty Propagation of Missing Data Signals with the Interval Discrete Fourier Transform
Behrendt, M., de Angelis, M., & Beer, M. (2023). Uncertainty Propagation of Missing Data Signals with the Interval Discrete Fourier Transform. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 9(3). doi:10.1061/ajrua6.rueng-1048
Effects of response spectrum of pulse-like ground motion on stochastic seismic response of tunnel
Chen, G., Liu, Y., & Beer, M. (2023). Effects of response spectrum of pulse-like ground motion on stochastic seismic response of tunnel. Engineering Structures, 289, 116274. doi:10.1016/j.engstruct.2023.116274
From Reliability-Based Design to Resilience-Based Design
Wang, C., Ayyub, B. M., & Beer, M. (2023). From Reliability-Based Design to Resilience-Based Design. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 9(3). doi:10.1115/1.4062997
Deep learning-based reconstruction of missing long-term girder-end displacement data for suspension bridge health monitoring
Wang, Z. -W., Lu, X. -F., Zhang, W. -M., Fragkoulis, V. C., Beer, M., & Zhang, Y. -F. (2023). Deep learning-based reconstruction of missing long-term girder-end displacement data for suspension bridge health monitoring. Computers & Structures, 284, 107070. doi:10.1016/j.compstruc.2023.107070
Cost and competitiveness of green hydrogen in Europe: Effects of the European Union regulatory framework
Application of Interval Field Method to the Stability Analysis of Slopes in the Presence of Uncertainties
Feng, C., Faes, M., Broggi, M., & Beer, M. (2023). Application of Interval Field Method to the Stability Analysis of Slopes in the Presence of Uncertainties. In GEO-RISK 2023: ADVANCES IN MODELING UNCERTAINTY AND VARIABILITY Vol. 347 (pp. 287-297). Retrieved from https://www.webofscience.com/
Consistent seismic hazard and fragility analysis considering combined capacity-demand uncertainties via probability density evolution method
Cao, X. -Y., Feng, D. -C., & Beer, M. (2023). Consistent seismic hazard and fragility analysis considering combined capacity-demand uncertainties via probability density evolution method. Structural Safety, 103, 102330. doi:10.1016/j.strusafe.2023.102330
Estimation of small failure probabilities by partially Bayesian active learning line sampling: Theory and algorithm
Dang, C., Valdebenito, M. A., Song, J., Wei, P., & Beer, M. (2023). Estimation of small failure probabilities by partially Bayesian active learning line sampling: Theory and algorithm. Computer Methods in Applied Mechanics and Engineering, 412, 116068. doi:10.1016/j.cma.2023.116068
Simulation of random fields on random domains
Zheng, Z., Valdebenito, M., Beer, M., & Nackenhorst, U. (2023). Simulation of random fields on random domains. Probabilistic Engineering Mechanics, 73, 103455. doi:10.1016/j.probengmech.2023.103455
Uncertainty analysis of structural output with closed-form expression based on surrogate model
Chen, Y. -L., Shi, Y., Huang, H. -Z., Sun, D., & Beer, M. (2023). Uncertainty analysis of structural output with closed-form expression based on surrogate model. PROBABILISTIC ENGINEERING MECHANICS, 73. doi:10.1016/j.probengmech.2023.103482
Distribution-free stochastic model updating with staircase density functions
Kitahara, M., Kitahara, T., Bi, S., Broggi, M., & Beer, M. (2023). Distribution-free stochastic model updating with staircase density functions. In Life-Cycle of Structures and Infrastructure Systems (pp. 670-677). CRC Press. doi:10.1201/9781003323020-81
Efficient posterior estimation for stochastic SHM using transport maps
Grashorn, J., Broggi, M., Chamoin, L., & Beer, M. (2023). Efficient posterior estimation for stochastic SHM using transport maps. In Life-Cycle of Structures and Infrastructure Systems (pp. 678-685). CRC Press. doi:10.1201/9781003323020-82
Environmental influence on structural health monitoring systems
Bartels, J. -H., Kitahara, M., Marx, S., & Beer, M. (2023). Environmental influence on structural health monitoring systems. In Life-Cycle of Structures and Infrastructure Systems (pp. 662-669). CRC Press. doi:10.1201/9781003323020-80
A new reliability method combining adaptive Kriging and active variance reduction using multiple importance sampling
Persoons, A., Wei, P., Broggi, M., & Beer, M. (2023). A new reliability method combining adaptive Kriging and active variance reduction using multiple importance sampling. Structural and Multidisciplinary Optimization, 66(6). doi:10.1007/s00158-023-03598-6
Combining data and physical models for probabilistic analysis: A Bayesian Augmented Space Learning perspective
Hong, F., Wei, P., Song, J., Faes, M. G. R., Valdebenito, M. A., & Beer, M. (2023). Combining data and physical models for probabilistic analysis: A Bayesian Augmented Space Learning perspective. PROBABILISTIC ENGINEERING MECHANICS, 73. doi:10.1016/j.probengmech.2023.103474
Efficient System Reliability Analysis for Layered Soil Slopes with Multiple Failure Modes Using Sequential Compounding Method
Liao, K., Wu, Y., Miao, F., Zhang, L., & Beer, M. (2023). Efficient System Reliability Analysis for Layered Soil Slopes with Multiple Failure Modes Using Sequential Compounding Method. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 9(2). doi:10.1061/ajrua6.rueng-1022
The Typhoon Wind Hazard Assessment Considering the Correlation among the Key Random Variables Using the Copula Method
Hong, X., Song, Y., Kong, F., & Beer, M. (2023). The Typhoon Wind Hazard Assessment Considering the Correlation among the Key Random Variables Using the Copula Method. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 9(2). doi:10.1061/ajrua6.rueng-1018
Transport map Bayesian parameter estimation for dynamical systems
Grashorn, J., Urrea-Quintero, J. -H., Broggi, M., Chamoin, L., & Beer, M. (2023). Transport map Bayesian parameter estimation for dynamical systems. PAMM, 23(1). doi:10.1002/pamm.202200136
Universal source-free domain adaptation method for cross-domain fault diagnosis of machines
Zhang, Y., Ren, Z., Feng, K., Yu, K., Beer, M., & Liu, Z. (2023). Universal source-free domain adaptation method for cross-domain fault diagnosis of machines. Mechanical Systems and Signal Processing, 191, 110159. doi:10.1016/j.ymssp.2023.110159
Efficient decoupling approach for reliability-based optimization based on augmented Line Sampling and combination algorithm
Yuan, X., Valdebenito, M. A., Zhang, B., Faes, M. G. R., & Beer, M. (2023). Efficient decoupling approach for reliability-based optimization based on augmented Line Sampling and combination algorithm. Computers and Structures, 280, 107003. doi:10.1016/j.compstruc.2023.107003
Identification of near-fault multi-pulse ground motion
Chen, G., Liu, Y., & Beer, M. (2023). Identification of near-fault multi-pulse ground motion. Applied Mathematical Modelling, 117, 609-624. doi:10.1016/j.apm.2023.01.002
Soil-expended seismic metamaterial with ultralow and wide bandgap
Bai, Y., Li, X., Zhou, X., Li, P., & Beer, M. (2023). Soil-expended seismic metamaterial with ultralow and wide bandgap. Mechanics of Materials, 180, 104601. doi:10.1016/j.mechmat.2023.104601
The concept of diagonal approximated signature: new surrogate modeling approach for continuous-state systems in the context of resilience optimization
Winnewisser, N. R., Salomon, J., Broggi, M., & Beer, M. (n.d.). The concept of diagonal approximated signature: new surrogate modeling approach for continuous-state systems in the context of resilience optimization. Disaster Prevention and Resilience, 3(2), 4. doi:10.20517/dpr.2023.03
Random dynamic responses of solar array under thermal-structural coupling based on the isogeometric analysis
Ma, J., Dai, C., Wang, B., Beer, M., & Wang, A. (2023). Random dynamic responses of solar array under thermal-structural coupling based on the isogeometric analysis. Acta Mechanica Sinica, 39(4). doi:10.1007/s10409-023-22338-x
Estimation of an imprecise power spectral density function with optimised bounds from scarce data for epistemic uncertainty quantification
Behrendt, M., Faes, M. G. R., Valdebenito, M. A., & Beer, M. (2023). Estimation of an imprecise power spectral density function with optimised bounds from scarce data for epistemic uncertainty quantification. Mechanical Systems and Signal Processing, 189, 110072. doi:10.1016/j.ymssp.2022.110072
A single-loop time-variant reliability evaluation via a decoupling strategy and probability distribution reconstruction
Zhang, Y., Xu, J., & Beer, M. (2023). A single-loop time-variant reliability evaluation via a decoupling strategy and probability distribution reconstruction. Reliability Engineering & System Safety, 232, 109031. doi:10.1016/j.ress.2022.109031
Bayesian maximum entropy method for stochastic model updating using measurement data and statistical information
Wang, C., Yang, L., Xie, M., Valdebenito, M., & Beer, M. (2023). Bayesian maximum entropy method for stochastic model updating using measurement data and statistical information. Mechanical Systems and Signal Processing, 188, 110012. doi:10.1016/j.ymssp.2022.110012
Efficient inner-outer decoupling scheme for non-probabilistic model updating with high dimensional model representation and Chebyshev approximation
Mo, J., Yan, W. -J., Yuen, K. -V., & Beer, M. (2023). Efficient inner-outer decoupling scheme for non-probabilistic model updating with high dimensional model representation and Chebyshev approximation. Mechanical Systems and Signal Processing, 188, 110040. doi:10.1016/j.ymssp.2022.110040
Non-stationary response of nonlinear systems with singular parameter matrices subject to combined deterministic and stochastic excitation
Ni, P., Fragkoulis, V. C., Kong, F., Mitseas, I. P., & Beer, M. (2023). Non-stationary response of nonlinear systems with singular parameter matrices subject to combined deterministic and stochastic excitation. Mechanical Systems and Signal Processing, 188, 110009. doi:10.1016/j.ymssp.2022.110009
Three-dimensional ori-kirigami metamaterials with multistability.
Bai, Y., Wang, S., Zhou, X., & Beer, M. (2023). Three-dimensional ori-kirigami metamaterials with multistability.. Physical review. E, 107(3-2), 035004. doi:10.1103/physreve.107.035004
A physics-informed Bayesian framework for characterizing ground motion process in the presence of missing data
Chen, Y., Patelli, E., Edwards, B., & Beer, M. (2023). A physics-informed Bayesian framework for characterizing ground motion process in the presence of missing data. EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS. doi:10.1002/eqe.3877
Digital twin-driven intelligent assessment of gear surface degradation
Feng, K., Ji, J. C., Zhang, Y., Ni, Q., Liu, Z., & Beer, M. (2023). Digital twin-driven intelligent assessment of gear surface degradation. Mechanical Systems and Signal Processing, 186, 109896. doi:10.1016/j.ymssp.2022.109896
Global failure probability function estimation based on an adaptive strategy and combination algorithm
Yuan, X., Qian, Y., Chen, J., Faes, M. G. R., Valdebenito, M. A., & Beer, M. (2023). Global failure probability function estimation based on an adaptive strategy and combination algorithm. RELIABILITY ENGINEERING & SYSTEM SAFETY, 231. doi:10.1016/j.ress.2022.108937
Scalable risk assessment of large infrastructure systems with spatially correlated components
Zeng, D., Zhang, H., Dai, H., & Beer, M. (2023). Scalable risk assessment of large infrastructure systems with spatially correlated components. Structural Safety, 101, 102311. doi:10.1016/j.strusafe.2022.102311
A new method for stochastic analysis of structures under limited observations
Dai, H., Zhang, R., & Beer, M. (2023). A new method for stochastic analysis of structures under limited observations. Mechanical Systems and Signal Processing, 185, 109730. doi:10.1016/j.ymssp.2022.109730
A stochastic finite element scheme for solving partial differential equations defined on random domains
Zheng, Z., Valdebenito, M., Beer, M., & Nackenhorst, U. (2023). A stochastic finite element scheme for solving partial differential equations defined on random domains. Computer Methods in Applied Mechanics and Engineering, 405, 115860. doi:10.1016/j.cma.2022.115860
First-passage probability estimation of high-dimensional nonlinear stochastic dynamic systems by a fractional moments-based mixture distribution approach
Ding, C., Dang, C., Valdebenito, M. A., Faes, M. G. R., Broggi, M., & Beer, M. (2023). First-passage probability estimation of high-dimensional nonlinear stochastic dynamic systems by a fractional moments-based mixture distribution approach. Mechanical Systems and Signal Processing, 185, 109775. doi:10.1016/j.ymssp.2022.109775
An energy-frequency parameter for earthquake ground motion intensity measure
Chen, G., Yang, J., Liu, Y., Kitahara, T., & Beer, M. (2023). An energy-frequency parameter for earthquake ground motion intensity measure. EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS, 52(2), 271-284. doi:10.1002/eqe.3752
Efficient structural reliability analysis via a weak-intrusive stochastic finite element method
Zheng, Z., Dai, H., & Beer, M. (2023). Efficient structural reliability analysis via a weak-intrusive stochastic finite element method. Probabilistic Engineering Mechanics, 71, 103414. doi:10.1016/j.probengmech.2023.103414
A Two-Phase Sampling Approach for Reliability-Based Optimization in Structural Engineering
Jerez, D. J., Jensen, H. A., & Beer, M. (2023). A Two-Phase Sampling Approach for Reliability-Based Optimization in Structural Engineering. In Springer Series in Reliability Engineering (pp. 21-48). Springer Nature Switzerland. doi:10.1007/978-3-031-28859-3_2
A review of vibration-based gear wear monitoring and prediction techniques
Feng, K., Ji, J. C., Ni, Q., & Beer, M. (2023). A review of vibration-based gear wear monitoring and prediction techniques. Mechanical Systems and Signal Processing, 182, 109605. doi:10.1016/j.ymssp.2022.109605
An explicit integration method with third-order accuracy for linear and nonlinear dynamic systems
Liu, W., Ye, T., Yuan, P., Beer, M., & Tong, X. (2023). An explicit integration method with third-order accuracy for linear and nonlinear dynamic systems. Engineering Structures, 274, 115013. doi:10.1016/j.engstruct.2022.115013
Bayesian updating with two-step parallel Bayesian optimization and quadrature
Kitahara, M., Dang, C., & Beer, M. (2023). Bayesian updating with two-step parallel Bayesian optimization and quadrature. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 403. doi:10.1016/j.cma.2022.115735
Fourier Transform and Other Quadratic Problems Under Interval Uncertainty
Galindo, O., Ibarra, C., Kreinovich, V., & Beer, M. (2023). Fourier Transform and Other Quadratic Problems Under Interval Uncertainty. In Studies in Systems, Decision and Control (pp. 251-256). Springer International Publishing. doi:10.1007/978-3-031-16415-6_37
Fuzzy Probability Theory
Beer, M. (2023). Fuzzy Probability Theory. In Encyclopedia of Complexity and Systems Science Series (pp. 51-75). Springer US. doi:10.1007/978-1-0716-2628-3_237
Regression Models for Machine Learning
Wei, P., & Beer, M. (2023). Regression Models for Machine Learning. In Computational Methods in Engineering & the Sciences (pp. 341-371). Springer International Publishing. doi:10.1007/978-3-031-36644-4_9
Reliability Evaluation of RC Columns with Wind-Dominated Combination Considering Random Biaxial Eccentricity
Jiang, Y., Li, Z., Zhou, H., Wang, F., Beer, M., & Zheng, J. (2023). Reliability Evaluation of RC Columns with Wind-Dominated Combination Considering Random Biaxial Eccentricity. Journal of Structural Engineering, 149(1). doi:10.1061/(asce)st.1943-541x.0003507
Resilience of structural infrastructure
Beer, M. (2023). Resilience of structural infrastructure. Bauingenieur, 98(5), A-3.
Robust SHM Systems Using Bayesian Model Updating
Bartels, J. H., Potthast, T., Kitahara, M., Marx, S., & Beer, M. (2023). Robust SHM Systems Using Bayesian Model Updating. In Proceedings of the International Offshore and Polar Engineering Conference (pp. 272-278).
Sample regeneration algorithm for structural failure probability function estimation
Yuan, X., Wang, S., Valdebenito, M. A., Faes, M. G. R., & Beer, M. (2023). Sample regeneration algorithm for structural failure probability function estimation. PROBABILISTIC ENGINEERING MECHANICS, 71. doi:10.1016/j.probengmech.2022.103387
UNCERTAINTYQUANTIFICATION.JL: A NEW FRAMEWORK FOR UNCERTAINTY QUANTIFICATION IN JULIA
Behrensdorf, J., Gray, A., Broggi, M., & Beer, M. (2023). UNCERTAINTYQUANTIFICATION.JL: A NEW FRAMEWORK FOR UNCERTAINTY QUANTIFICATION IN JULIA. In Proceedings of the 5th International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2019) (pp. 419-436). Institute of Structural Analysis and Antiseismic Research National Technical University of Athens. doi:10.7712/120223.10347.19810
Virtual process for evaluating the influence of real combined module variations on the overall performance of an aircraft engine
Goeing, J., Seehausen, H., Stania, L., Nuebel, N., Salomon, J., Ignatidis, P., . . . Friedrichs, J. (n.d.). Virtual process for evaluating the influence of real combined module variations on the overall performance of an aircraft engine. Journal of the Global Power and Propulsion Society, 7, 95-112. doi:10.33737/jgpps/160055
2022
Determining the effective factors leading to incidence of human error accidents in industrial parks construction projects: results of a fuzzy Delphi survey
Rafieyan, A., Sarvari, H., Beer, M., & Chan, D. W. M. (2022). Determining the effective factors leading to incidence of human error accidents in industrial parks construction projects: results of a fuzzy Delphi survey. International Journal of Construction Management, 1-13. doi:10.1080/15623599.2022.2159630
Structural novelty detection with Laplace asymptotic expansion of the Bhattacharyya distance of transmissibility and Bayesian resampling scheme
Mei, L. -F., Yan, W. -J., Yuen, K. -V., & Beer, M. (2022). Structural novelty detection with Laplace asymptotic expansion of the Bhattacharyya distance of transmissibility and Bayesian resampling scheme. Journal of Sound and Vibration, 540, 117277. doi:10.1016/j.jsv.2022.117277
An efficient reliability analysis method for structures with hybrid time-dependent uncertainty
Zhang, K., Chen, N., Zeng, P., Liu, J., & Beer, M. (2022). An efficient reliability analysis method for structures with hybrid time-dependent uncertainty. RELIABILITY ENGINEERING & SYSTEM SAFETY, 228. doi:10.1016/j.ress.2022.108794
New Cycle of the ASCE Journals’ Early Career Editorial Board
Beer, M. (2022). New Cycle of the ASCE Journals’ Early Career Editorial Board. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 8(4). doi:10.1061/ajrua6.0001268
Non-stationary response determination of nonlinear systems subjected to combined deterministic and evolutionary stochastic excitations
Han, R., Fragkoulis, V. C., Kong, F., Beer, M., & Peng, Y. (2022). Non-stationary response determination of nonlinear systems subjected to combined deterministic and evolutionary stochastic excitations. INTERNATIONAL JOURNAL OF NON-LINEAR MECHANICS, 147. doi:10.1016/j.ijnonlinmec.2022.104192
Special Section on Decommissioning and Life Extension of Complex Industrial Assets
Moura, R., Beer, M., de Souza, G. F. M., & Patelli, E. (2022). Special Section on Decommissioning and Life Extension of Complex Industrial Assets. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 8(4). doi:10.1115/1.4055799
Structural Time-Dependent Reliability Assessment: Advanced Approaches for Engineered Structures
Wang, C., Zhang, H., & Beer, M. (2022). Structural Time-Dependent Reliability Assessment: Advanced Approaches for Engineered Structures. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART A-CIVIL ENGINEERING, 9(1). doi:10.1061/AJRUA6.RUENG-1010
Multidimensional resilience decision-making for complex and substructured systems
Salomon, J., Behrensdorf, J., Winnewisser, N., Broggi, M., & Beer, M. (2022). Multidimensional resilience decision-making for complex and substructured systems. Resilient Cities and Structures, 1(3), 61-78. doi:10.1016/j.rcns.2022.10.005
An approximate stochastic dynamics approach for design spectrum based response analysis of nonlinear structural systems with fractional derivative elements
Kougioumtzoglou, I. A., Ni, P., Mitseas, I. P., Fragkoulis, V. C., & Beer, M. (2022). An approximate stochastic dynamics approach for design spectrum based response analysis of nonlinear structural systems with fractional derivative elements. International Journal of Non-Linear Mechanics, 146, 104178. doi:10.1016/j.ijnonlinmec.2022.104178
An efficient approach for dynamic-reliability-based topology optimization of braced frame structures with probability density evolution method
Yang, J. -S., Chen, J. -B., Beer, M., & Jensen, H. (2022). An efficient approach for dynamic-reliability-based topology optimization of braced frame structures with probability density evolution method. Advances in Engineering Software, 173, 103196. doi:10.1016/j.advengsoft.2022.103196
Structural reliability analysis: A Bayesian perspective
Dang, C., Valdebenito, M. A., Faes, M. G. R., Wei, P., & Beer, M. (2022). Structural reliability analysis: A Bayesian perspective. STRUCTURAL SAFETY, 99. doi:10.1016/j.strusafe.2022.102259
Application of interval field method to the stability analysis of slopes in presence of uncertainties
Feng, C., Faes, M., Broggi, M., Dang, C., Yang, J., Zheng, Z., & Beer, M. (2022). Application of interval field method to the stability analysis of slopes in presence of uncertainties. Computers and Geotechnics, 105060. doi:10.1016/j.compgeo.2022.105060
Probabilistic analysis of resistance for RC columns with wind-dominated combination considering random biaxial eccentricity
Jiang, Y., Zheng, J., Yang, K., Zhou, H., & Beer, M. (2022). Probabilistic analysis of resistance for RC columns with wind-dominated combination considering random biaxial eccentricity. Structure and Infrastructure Engineering, 1-11. doi:10.1080/15732479.2022.2131842
A novel similarity-based status characterization methodology for gear surface wear propagation monitoring
Feng, K., Ni, Q., Beer, M., Du, H., & Li, C. (2022). A novel similarity-based status characterization methodology for gear surface wear propagation monitoring. TRIBOLOGY INTERNATIONAL, 174. doi:10.1016/j.triboint.2022.107765
An enhanced PDEM-based framework for reliability analysis of structures considering multiple failure modes and limit states
Feng, D. -C., Cao, X. -Y., & Beer, M. (2022). An enhanced PDEM-based framework for reliability analysis of structures considering multiple failure modes and limit states. Probabilistic Engineering Mechanics, 70, 103367. doi:10.1016/j.probengmech.2022.103367
Bayesian probabilistic propagation of hybrid uncertainties: Estimation of response expectation function, its variable importance and bounds
Dang, C., Wei, P., Faes, M. G. R., & Beer, M. (2022). Bayesian probabilistic propagation of hybrid uncertainties: Estimation of response expectation function, its variable importance and bounds. COMPUTERS & STRUCTURES, 270. doi:10.1016/j.compstruc.2022.106860
Data-driven reliability assessment of dynamic structures based on power spectrum classification
Behrendt, M., Kitahara, M., Kitahara, T., Comerford, L., & Beer, M. (2022). Data-driven reliability assessment of dynamic structures based on power spectrum classification. ENGINEERING STRUCTURES, 268. doi:10.1016/j.engstruct.2022.114648
On the use of Directional Importance Sampling for reliability-based design and optimum design sensitivity of linear stochastic structures
Jerez, D. J., Jensen, H. A., Valdebenito, M. A., Misraji, M. A., Mayorga, F., & Beer, M. (2022). On the use of Directional Importance Sampling for reliability-based design and optimum design sensitivity of linear stochastic structures. Probabilistic Engineering Mechanics, 103368. doi:10.1016/j.probengmech.2022.103368
Virtual Process for Evaluating the Influence of Real Combined Module Variations on the Overall Performance of an Aircraft Engine
Goeing, J., Seehausen, H., Stania, L., Nuebel, N., Salomon, J., Ignatidis, P., . . . Friedrichs, J. (2022). Virtual Process for Evaluating the Influence of Real Combined Module Variations on the Overall Performance of an Aircraft Engine. In Proceedings of Global Power & Propulsion Society. GPPS. doi:10.33737/gpps22-tc-89
A weak-intrusive stochastic finite element method for stochastic structural dynamics analysis
Zheng, Z., Beer, M., Dai, H., & Nackenhorst, U. (2022). A weak-intrusive stochastic finite element method for stochastic structural dynamics analysis. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 399. doi:10.1016/j.cma.2022.115360
An effective implementation of reliability methods for Bayesian model updating of structural dynamic models with multiple uncertain parameters
Jerez, D. J., Jensen, H. A., & Beer, M. (2022). An effective implementation of reliability methods for Bayesian model updating of structural dynamic models with multiple uncertain parameters. RELIABILITY ENGINEERING & SYSTEM SAFETY, 225. doi:10.1016/j.ress.2022.108634
Modeling response spectrum compatible pulse-like ground motion
Chen, G., Beer, M., & Liu, Y. (2022). Modeling response spectrum compatible pulse-like ground motion. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 177. doi:10.1016/j.ymssp.2022.109177
Parallel adaptive Bayesian quadrature for rare event estimation
Dang, C., Wei, P., Faes, M. G. R., Valdebenito, M. A., & Beer, M. (2022). Parallel adaptive Bayesian quadrature for rare event estimation. RELIABILITY ENGINEERING & SYSTEM SAFETY, 225. doi:10.1016/j.ress.2022.108621
An efficient reduced-order method for stochastic eigenvalue analysis
Zheng, Z., Beer, M., & Nackenhorst, U. (2022). An efficient reduced-order method for stochastic eigenvalue analysis. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING. doi:10.1002/nme.7092
Hazard-Resilient Infrastructure: Analysis and Design
Beer, M. (2022). Hazard-Resilient Infrastructure: Analysis and Design. NATURAL HAZARDS REVIEW, 23(3). doi:10.1061/(ASCE)NH.1527-6996.0000562
Interval uncertainty propagation by a parallel Bayesian global optimization method
Dang, C., Wei, P., Faes, M. G. R., Valdebenito, M. A., & Beer, M. (2022). Interval uncertainty propagation by a parallel Bayesian global optimization method. Applied Mathematical Modelling, 108, 220-235. doi:10.1016/j.apm.2022.03.031
Distribution-free P-box processes based on translation theory: Definition and simulation
Faes, M. G. R., Broggi, M., Chen, G., Phoon, K. -K., & Beer, M. (2022). Distribution-free P-box processes based on translation theory: Definition and simulation. Probabilistic Engineering Mechanics, 69, 103287. doi:10.1016/j.probengmech.2022.103287
Distribution-free stochastic model updating of dynamic systems with parameter dependencies
Kitahara, M., Bi, S., Broggi, M., & Beer, M. (2022). Distribution-free stochastic model updating of dynamic systems with parameter dependencies. Structural Safety, 97, 102227. doi:10.1016/j.strusafe.2022.102227
Elucidating appealing features of differentiable auto-correlation functions: A study on the modified exponential kernel
Faes, M. G. R., Broggi, M., Spanos, P. D., & Beer, M. (2022). Elucidating appealing features of differentiable auto-correlation functions: A study on the modified exponential kernel. Probabilistic Engineering Mechanics, 69, 103269. doi:10.1016/j.probengmech.2022.103269
Special issue on Advances in performance-based design optimization of stochastic dynamical systems
Jensen, H., Beer, M., Chen, J., & Spence, S. (2022). Special issue on Advances in performance-based design optimization of stochastic dynamical systems. Mechanical Systems and Signal Processing, 173, 108972. doi:10.1016/j.ymssp.2022.108972
Editorial: Recent advances in stochastic model updating
Bi, S., Beer, M., & Mottershead, J. (2022). Editorial: Recent advances in stochastic model updating. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 172. doi:10.1016/j.ymssp.2022.108971
Projecting interval uncertainty through the discrete Fourier transform: An application to time signals with poor precision
Behrendt, M., de Angelis, M., Comerford, L., Zhang, Y., & Beer, M. (2022). Projecting interval uncertainty through the discrete Fourier transform: An application to time signals with poor precision. Mechanical Systems and Signal Processing, 172, 108920. doi:10.1016/j.ymssp.2022.108920
A new perspective on the simulation of cross-correlated random fields
Dai, H., Zhang, R., & Beer, M. (2022). A new perspective on the simulation of cross-correlated random fields. Structural Safety, 96, 102201. doi:10.1016/j.strusafe.2022.102201
Method to generate artificial earthquake accelerations with time domain enhancement and attenuation characteristics
Zhang, H., Bittner, M., & Beer, M. (2022). Method to generate artificial earthquake accelerations with time domain enhancement and attenuation characteristics. AIN SHAMS ENGINEERING JOURNAL, 13(3). doi:10.1016/j.asej.2021.09.031
Excitation–response relationships for linear structural systems with singular parameter matrices: A periodized harmonic wavelet perspective
Pasparakis, G. D., Kougioumtzoglou, I. A., Fragkoulis, V. C., Kong, F., & Beer, M. (2022). Excitation–response relationships for linear structural systems with singular parameter matrices: A periodized harmonic wavelet perspective. Mechanical Systems and Signal Processing, 169, 108701. doi:10.1016/j.ymssp.2021.108701
A GRU-based ensemble learning method for time-variant uncertain structural response analysis
Zhang, K., Chen, N., Liu, J., & Beer, M. (2022). A GRU-based ensemble learning method for time-variant uncertain structural response analysis. Computer Methods in Applied Mechanics and Engineering, 391, 114516. doi:10.1016/j.cma.2021.114516
Joint Statistics of Natural Frequencies Corresponding to Structural Systems with Singular Random Parameter Matrices
Fragkoulis, V. C., Kougioumtzoglou, I. A., Pantelous, A. A., & Beer, M. (2022). Joint Statistics of Natural Frequencies Corresponding to Structural Systems with Singular Random Parameter Matrices. JOURNAL OF ENGINEERING MECHANICS, 148(3). doi:10.1061/(ASCE)EM.1943-7889.0002081
Reliability-based design optimization of structural systems under stochastic excitation: An overview
Jerez, D. J., Jensen, H. A., & Beer, M. (2022). Reliability-based design optimization of structural systems under stochastic excitation: An overview. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 166. doi:10.1016/j.ymssp.2021.108397
Seismic Response Meta-model of High-Rise Fame Structure Based on Time-Delay Neural Network
Zhang, H., Bittner, M., & Beer, M. (2022). Seismic Response Meta-model of High-Rise Fame Structure Based on Time-Delay Neural Network. KSCE Journal of Civil Engineering. doi:10.1007/s12205-022-0878-7
Relaxed power spectrum estimation from multiple data records utilising subjective probabilities
Behrendt, M., Bittner, M., Comerford, L., Beer, M., & Chen, J. (2022). Relaxed power spectrum estimation from multiple data records utilising subjective probabilities. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 165. doi:10.1016/j.ymssp.2021.108346
Towards the NASA UQ Challenge 2019: Systematically forward and inverse approaches for uncertainty propagation and quantification
Bi, S., He, K., Zhao, Y., Moens, D., Beer, M., & Zhang, J. (2022). Towards the NASA UQ Challenge 2019: Systematically forward and inverse approaches for uncertainty propagation and quantification. Mechanical Systems and Signal Processing, 165, 108387. doi:10.1016/j.ymssp.2021.108387
A feature mapping strategy of metamodelling for nonlinear stochastic dynamical systems with low to high-dimensional input uncertainties
Wan, Z., Chen, J., Tao, W., Wei, P., Beer, M., & Jiang, Z. (2023). A feature mapping strategy of metamodelling for nonlinear stochastic dynamical systems with low to high-dimensional input uncertainties. Mechanical Systems and Signal Processing, 184, 109656. doi:10.1016/j.ymssp.2022.109656
Identification of human errors and influencing factors: A machine learning approach
Morais, C., Yung, K. L., Johnson, K., Moura, R., Beer, M., & Patelli, E. (2022). Identification of human errors and influencing factors: A machine learning approach. Safety Science, 146, 105528. doi:10.1016/j.ssci.2021.105528
Robust data-driven human reliability analysis using credal networks
Morais, C., Estrada-Lugo, H. D., Tolo, S., Jacques, T., Moura, R., Beer, M., & Patelli, E. (2022). Robust data-driven human reliability analysis using credal networks. Reliability Engineering & System Safety, 218, 107990. doi:10.1016/j.ress.2021.107990
Transfer prior knowledge from surrogate modelling: A meta-learning approach
Cheng, M., Dang, C., Frangopol, D. M., Beer, M., & Yuan, X. -X. (2022). Transfer prior knowledge from surrogate modelling: A meta-learning approach. Computers & Structures, 260, 106719. doi:10.1016/j.compstruc.2021.106719
Nonparametric Bayesian stochastic model updating with hybrid uncertainties
Kitahara, M., Bi, S., Broggi, M., & Beer, M. (2022). Nonparametric Bayesian stochastic model updating with hybrid uncertainties. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 163. doi:10.1016/j.ymssp.2021.108195
A Distributionally Robust Approach for Mixed Aleatory and Epistemic Uncertainties Propagation
Kitahara, M., Song, J., Wei, P., Broggi, M., & Beer, M. (2022). A Distributionally Robust Approach for Mixed Aleatory and Epistemic Uncertainties Propagation. AIAA JOURNAL, 60(7), 4471-4477. doi:10.2514/1.J061394
A new scheme combining adaptive Kriging with adaptative variance-reduction using Gaussian mixture importance sampling
Persoons, A., Wei, P., Bogaerts, L., Moens, D., Broggi, M., & Beer, M. (2022). A new scheme combining adaptive Kriging with adaptative variance-reduction using Gaussian mixture importance sampling. In Proceedings of ISMA 2022 - International Conference on Noise and Vibration Engineering and USD 2022 - International Conference on Uncertainty in Structural Dynamics (pp. 4985-4998).
Assessing the Severity of Missing Data Problems with the Interval Discrete Fourier Transform Algorithm
Behrendt, M., Angelis, M. D., Comerford, L., & Beer, M. (2022). Assessing the Severity of Missing Data Problems with the Interval Discrete Fourier Transform Algorithm. In Book of Extended Abstracts for the 32nd European Safety and Reliability Conference (pp. 2553-2560). Research Publishing Services. doi:10.3850/978-981-18-5183-4_s14-05-243-cd
Asymptotic Bayesian Optimization: A Markov sampling-based framework for design optimization
Jerez, D. J., Jensen, H. A., Beer, M., & Chen, J. (2022). Asymptotic Bayesian Optimization: A Markov sampling-based framework for design optimization. PROBABILISTIC ENGINEERING MECHANICS, 67. doi:10.1016/j.probengmech.2021.103178
Bayesian inversion for imprecise probabilistic models using a novel entropy-based uncertainty quantification metric
Yang, L., Bi, S., Faes, M. G. R., Broggi, M., & Beer, M. (2022). Bayesian inversion for imprecise probabilistic models using a novel entropy-based uncertainty quantification metric. Mechanical Systems and Signal Processing, 162, 107954. doi:10.1016/j.ymssp.2021.107954
Capturing Epistemic Uncertainties in the Power Spectral Density for Limited Data Sets
Behrendt, M., Faes, M. G. R., Valdebenito, M. A., & Beer, M. (2022). Capturing Epistemic Uncertainties in the Power Spectral Density for Limited Data Sets. In Probabilistic Safety Assessment and Management, PSAM 2022.
Epistemic Uncertainty Quantification of Localised Seismic Power Spectral Densities
Bittner, M., Behrendt, M., Behrensdorf, J., & Beer, M. (2022). Epistemic Uncertainty Quantification of Localised Seismic Power Spectral Densities. In Probabilistic Safety Assessment and Management, PSAM 2022.
Overview of Stochastic Model Updating in Aerospace Application Under Uncertainty Treatment
Bi, S., & Beer, M. (2022). Overview of Stochastic Model Updating in Aerospace Application Under Uncertainty Treatment. In SpringerBriefs in Statistics (pp. 115-129). Springer International Publishing. doi:10.1007/978-3-030-83640-5_8
Polyphase uncertainty analysis through virtual modelling technique
Wang, Q., Feng, Y., Wu, D., Yang, C., Yu, Y., Li, G., . . . Gao, W. (2022). Polyphase uncertainty analysis through virtual modelling technique. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 162. doi:10.1016/j.ymssp.2021.108013
Structural synthesis considering mixed discrete-continuous design variables: A Bayesian framework
Jensen, H. A., Jerez, D. J., & Beer, M. (2022). Structural synthesis considering mixed discrete-continuous design variables: A Bayesian framework. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 162. doi:10.1016/j.ymssp.2021.108042
Uncertainty Quantification Over Spectral Density Estimation for Strong Motion Process with Missing Data
Chen, Y., Patelli, E., Edwards, B., Beer, M., & Sunny, J. (2022). Uncertainty Quantification Over Spectral Density Estimation for Strong Motion Process with Missing Data. In Book of Extended Abstracts for the 32nd European Safety and Reliability Conference (pp. 1852-1858). Research Publishing Services. doi:10.3850/978-981-18-5183-4_s02-04-389-cd
Wind data extrapolation and stochastic field statistics estimation via compressive sampling and low rank matrix recovery methods
Pasparakis, G. D., dos Santos, K. R. M., Kougioumtzoglou, I. A., & Beer, M. (2022). Wind data extrapolation and stochastic field statistics estimation via compressive sampling and low rank matrix recovery methods. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 162. doi:10.1016/j.ymssp.2021.107975
2021
Uncertainty: Ideas Behind Neural Networks Lead Us Beyond KL-Decomposition and Interval Fields
Beer, M., Kosheleva, O., & Kreinovich, V. (2021). Uncertainty: Ideas Behind Neural Networks Lead Us Beyond KL-Decomposition and Interval Fields. In 2021 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (IEEE SSCI 2021). doi:10.1109/SSCI50451.2021.9660145
Efficient reliability analysis of complex systems in consideration of imprecision
Salomon, J., Winnewisser, N., Wei, P., Broggi, M., & Beer, M. (2021). Efficient reliability analysis of complex systems in consideration of imprecision. Reliability Engineering & System Safety, 216, 107972. doi:10.1016/j.ress.2021.107972
Response Determination of Nonlinear Systems with Singular Matrices Subject to Combined Stochastic and Deterministic Excitations
Ni, P., Fragkoulis, V. C., Kong, F., Mitseas, I. P., & Beer, M. (2021). Response Determination of Nonlinear Systems with Singular Matrices Subject to Combined Stochastic and Deterministic Excitations. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 7(4), 04021049. doi:10.1061/ajrua6.0001167
Time-Dependent Reliability of Aging Structures: Overview of Assessment Methods
Wang, C., Beer, M., & Ayyub, B. M. (2021). Time-Dependent Reliability of Aging Structures: Overview of Assessment Methods. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 7(4), 03121003. doi:10.1061/ajrua6.0001176
An efficient importance sampling approach for reliability analysis of time-variant structures subject to time-dependent stochastic load
Yuan, X., Liu, S., Faes, M., Valdebenito, M. A., & Beer, M. (2021). An efficient importance sampling approach for reliability analysis of time-variant structures subject to time-dependent stochastic load. Mechanical Systems and Signal Processing, 159, 107699. doi:10.1016/j.ymssp.2021.107699
Contaminant source identification in water distribution networks: A Bayesian framework
Jerez, D. J., Jensen, H. A., Beer, M., & Broggi, M. (2021). Contaminant source identification in water distribution networks: A Bayesian framework. Mechanical Systems and Signal Processing, 159, 107834. doi:10.1016/j.ymssp.2021.107834
Efficient procedure for failure probability function estimation in augmented space
Yuan, X., Liu, S., Valdebenito, M. A., Gu, J., & Beer, M. (2021). Efficient procedure for failure probability function estimation in augmented space. Structural Safety, 92, 102104. doi:10.1016/j.strusafe.2021.102104
Failure probability estimation of a class of series systems by multidomain Line Sampling
Valdebenito, M. A., Wei, P., Song, J., Beer, M., & Broggi, M. (2021). Failure probability estimation of a class of series systems by multidomain Line Sampling. RELIABILITY ENGINEERING & SYSTEM SAFETY, 213. doi:10.1016/j.ress.2021.107673
Non-probabilistic uncertainty quantification for dynamic characterization functions using complex ratio interval arithmetic operation of multidimensional parallelepiped model
Zhao, M. -Y., Yan, W. -J., Yuen, K. -V., & Beer, M. (2021). Non-probabilistic uncertainty quantification for dynamic characterization functions using complex ratio interval arithmetic operation of multidimensional parallelepiped model. Mechanical Systems and Signal Processing, 156, 107559. doi:10.1016/j.ymssp.2020.107559
Sensitivity Analysis of an Aircraft Engine Model Under Consideration of Dependent Variables
Salomon, J., Göing, J., Lück, S., Broggi, M., Friedrichs, J., & Beer, M. (2021). Sensitivity Analysis of an Aircraft Engine Model Under Consideration of Dependent Variables. In Volume 1: Aircraft Engine; Fans and Blowers; Marine; Wind Energy; Scholar Lecture. American Society of Mechanical Engineers. doi:10.1115/gt2021-58905
Application of a Reduced Order Model for Fuzzy Analysis of Linear Static Systems
Valdebenito, M. A., Jensen, H. A., Wei, P., Beer, M., & Beck, A. T. (2021). Application of a Reduced Order Model for Fuzzy Analysis of Linear Static Systems. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 7(2). doi:10.1115/1.4050159
Efficient imprecise reliability analysis using the Augmented Space Integral
Yuan, X., Faes, M. G. R., Liu, S., Valdebenito, M. A., & Beer, M. (2021). Efficient imprecise reliability analysis using the Augmented Space Integral. RELIABILITY ENGINEERING & SYSTEM SAFETY, 210. doi:10.1016/j.ress.2021.107477
Optimization or Bayesian Strategy? Performance of the Bhattacharyya Distance in Different Algorithms of Stochastic Model Updating
Bi, S., Beer, M., Zhang, J., Yang, L., & He, K. (2021). Optimization or Bayesian Strategy? Performance of the Bhattacharyya Distance in Different Algorithms of Stochastic Model Updating. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 7(2). doi:10.1115/1.4050168
Special Section: Nonprobabilistic and Hybrid Approaches for Uncertainty Quantification and Reliability Analysis
Faes, M. G. R., Moens, D., Beer, M., Zhang, H., & Phoon, K. -K. (2021). Special Section: Nonprobabilistic and Hybrid Approaches for Uncertainty Quantification and Reliability Analysis. ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg, 7(2). doi:10.1115/1.4050256
Augmented reliability analysis for estimating imprecise first excursion probabilities in stochastic linear dynamics
Faes, M. G. R., Valdebenito, M. A., Yuan, X., Wei, P., & Beer, M. (2021). Augmented reliability analysis for estimating imprecise first excursion probabilities in stochastic linear dynamics. ADVANCES IN ENGINEERING SOFTWARE, 155. doi:10.1016/j.advengsoft.2021.102993
Bounds optimization of model response moments: a twin-engine Bayesian active learning method
Wei, P., Hong, F., Phoon, K. -K., & Beer, M. (2021). Bounds optimization of model response moments: a twin-engine Bayesian active learning method. COMPUTATIONAL MECHANICS, 67(5), 1273-1292. doi:10.1007/s00466-021-01977-8
Operator norm theory as an efficient tool to propagate hybrid uncertainties and calculate imprecise probabilities
Faes, M. G. R., Valdebenito, M. A., Moens, D., & Beer, M. (2021). Operator norm theory as an efficient tool to propagate hybrid uncertainties and calculate imprecise probabilities. Mechanical Systems and Signal Processing, 152, 107482. doi:10.1016/j.ymssp.2020.107482
History Matching and Robust Design through Subset Simulation
Gong, Z., DiazDelaO, F. A., Hristov, P., & Beer, M. (2021). History Matching and Robust Design through Subset Simulation. International Journal for Uncertainty Quantification. doi:10.1615/int.j.uncertaintyquantification.2021033543
Seismic collapse fragility of low-rise steel moment frames with mass irregularity based on shaking table test
Bai, Y., Li, Y., Tang, Z., Bittner, M., Broggi, M., & Beer, M. (2021). Seismic collapse fragility of low-rise steel moment frames with mass irregularity based on shaking table test. Bulletin of Earthquake Engineering. doi:10.1007/s10518-021-01076-2
Functional perspective of uncertainty quantification for stochastic parametric systems and global sensitivity analysis
Wan, Z., Chen, J., & Beer, M. (2021). Functional perspective of uncertainty quantification for stochastic parametric systems and global sensitivity analysis. Lixue Xuebao/Chinese Journal of Theoretical and Applied Mechanics, 53(3), 837-854. doi:10.6052/0459-1879-20-336
A probability-box-based method for propagation of multiple types of epistemic uncertainties and its application on composite structural-acoustic system
Zhu, W., Chen, N., Liu, J., & Beer, M. (2021). A probability-box-based method for propagation of multiple types of epistemic uncertainties and its application on composite structural-acoustic system. Mechanical Systems and Signal Processing, 149, 107184. doi:10.1016/j.ymssp.2020.107184
Bayesian probabilistic propagation of imprecise probabilities with large epistemic uncertainty
Wei, P., Liu, F., Valdebenito, M., & Beer, M. (2021). Bayesian probabilistic propagation of imprecise probabilities with large epistemic uncertainty. Mechanical Systems and Signal Processing, 149, 107219. doi:10.1016/j.ymssp.2020.107219
Harmonic wavelets based response evolutionary power spectrum determination of linear and nonlinear structural systems with singular matrices
Pasparakis, G. D., Fragkoulis, V. C., & Beer, M. (2021). Harmonic wavelets based response evolutionary power spectrum determination of linear and nonlinear structural systems with singular matrices. Mechanical Systems and Signal Processing, 149, 107203. doi:10.1016/j.ymssp.2020.107203
Classical and Bayesian estimation of stress-strength reliability of a component having multiple states
Siju, K. C., Kumar, M., & Beer, M. (2021). Classical and Bayesian estimation of stress-strength reliability of a component having multiple states. INTERNATIONAL JOURNAL OF QUALITY & RELIABILITY MANAGEMENT, 38(2), 528-535. doi:10.1108/IJQRM-01-2020-0009
Active learning line sampling for rare event analysis
Song, J., Wei, P., Valdebenito, M., & Beer, M. (2021). Active learning line sampling for rare event analysis. Mechanical Systems and Signal Processing, 147. doi:10.1016/j.ymssp.2020.107113
A PDEM-COM framework for uncertainty quantification of backward issues involving both aleatory and epistemic uncertainties
Wan, Z. Q., Chen, J. B., & Beer, M. (2021). A PDEM-COM framework for uncertainty quantification of backward issues involving both aleatory and epistemic uncertainties. In IOP Conference Series: Materials Science and Engineering Vol. 1043 (pp. 052058). IOP Publishing. doi:10.1088/1757-899x/1043/5/052058
A general two-phase Markov chain Monte Carlo approach for constrained design optimization: Application to stochastic structural optimization
Jensen, H., Jerez, D., & Beer, M. (2021). A general two-phase Markov chain Monte Carlo approach for constrained design optimization: Application to stochastic structural optimization. Computer Methods in Applied Mechanics and Engineering, 373, 113487. doi:10.1016/j.cma.2020.113487
Handling the Uncertainty with Confidence in Human Reliability Analysis
Morais, C., Ferson, S., Moura, R., Tolo, S., Beer, M., & Patelli, E. (2021). Handling the Uncertainty with Confidence in Human Reliability Analysis. In Proceedings of the 31st European Safety and Reliability Conference (ESREL 2021) (pp. 3312-3318). Research Publishing Services. doi:10.3850/978-981-18-2016-8_575-cd
RESIDUAL SEISMIC PERFORMANCE ESTIMATION OF SEISMIC-ISOLATED BRIDGES BASED ON MODEL UPDATING USING APPROXIMATE BAYESIAN COMPUTATION
KITAHARA, M., BROGGI, M., & BEER, M. (2021). RESIDUAL SEISMIC PERFORMANCE ESTIMATION OF SEISMIC-ISOLATED BRIDGES BASED ON MODEL UPDATING USING APPROXIMATE BAYESIAN COMPUTATION. Journal of Japan Society of Civil Engineers, Ser. A1 (Structural Engineering & Earthquake Engineering (SE/EE)), 77(4), I_61-I_70. doi:10.2208/jscejseee.77.4_i_61
STOCHASTIC NONLINEAR RESPONSE OF STRUCTURAL SYSTEMS ENDOWED WITH SINGULAR MATRICES SUBJECT TO COMBINED PERIODIC AND STOCHASTIC EXCITATIONS
Ni, P., Fragkoulis, V. C., Kong, F., Mitseas, I. P., Beer, M., & Fragiadakis, M. (2021). STOCHASTIC NONLINEAR RESPONSE OF STRUCTURAL SYSTEMS ENDOWED WITH SINGULAR MATRICES SUBJECT TO COMBINED PERIODIC AND STOCHASTIC EXCITATIONS. In Proceedings of the 8th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COMPDYN 2015) (pp. 5367-5373). Institute of Structural Analysis and Antiseismic Research National Technical University of Athens. doi:10.7712/120121.8872.20780
2020
Adaptive reliability analysis for rare events evaluation with global imprecise line sampling
Song, J., Wei, P., Valdebenito, M., & Beer, M. (2020). Adaptive reliability analysis for rare events evaluation with global imprecise line sampling. Computer Methods in Applied Mechanics and Engineering, 372, 113344. doi:10.1016/j.cma.2020.113344
Estimation of failure probability in braced excavation using Bayesian networks with integrated model updating
He, L., Liu, Y., Bi, S., Wang, L., Broggi, M., & Beer, M. (2020). Estimation of failure probability in braced excavation using Bayesian networks with integrated model updating. Underground Space, 5(4), 315-323. doi:10.1016/j.undsp.2019.07.001
A unified scheme to solving arbitrary complex-valued ratio distribution with application to statistical inference for raw frequency response functions and transmissibility functions
Yan, W. -J., Zhao, M. -Y., Beer, M., Ren, W. -X., & Chronopoulos, D. (2020). A unified scheme to solving arbitrary complex-valued ratio distribution with application to statistical inference for raw frequency response functions and transmissibility functions. Mechanical Systems and Signal Processing, 145, 106886. doi:10.1016/j.ymssp.2020.106886
Barriers to development of private sector investment in water and sewage industry
Sarvari, H., Chan, D. W. M., Banaitiene, N., Noor, N. M., & Beer, M. (2020). Barriers to development of private sector investment in water and sewage industry. Built Environment Project and Asset Management, ahead-of-print(ahead-of-print). doi:10.1108/bepam-11-2019-0110
Bounding the first excursion probability of linear structures subjected to imprecise stochastic loading
Faes, M. G. R., Valdebenito, M. A., Moens, D., & Beer, M. (2020). Bounding the first excursion probability of linear structures subjected to imprecise stochastic loading. Computers & Structures, 239. doi:10.1016/j.compstruc.2020.106320
A global sensitivity index based on Fréchet derivative and its efficient numerical analysis
Chen, J., Wan, Z., & Beer, M. (2020). A global sensitivity index based on Fréchet derivative and its efficient numerical analysis. Probabilistic Engineering Mechanics, 62, 103096. doi:10.1016/j.probengmech.2020.103096
Special Section on Uncertainty Management in Complex Multiphysics Structural Dynamics
Special Section on Uncertainty Management in Complex Multiphysics Structural Dynamics (2020). (Vol. 6).
Cumulative Component Damages on Collapse Capacity of Ductile Steel and CFT Moment Resisting Frames under Over-design Ground Motions
Bai, Y., Ma, X., Wang, B., Cao, G., & Beer, M. (2020). Cumulative Component Damages on Collapse Capacity of Ductile Steel and CFT Moment Resisting Frames under Over-design Ground Motions. Journal of Earthquake Engineering, 1-22. doi:10.1080/13632469.2020.1784315
Bayesian Updating of Soil–Water Character Curve Parameters Based on the Monitor Data of a Large-Scale Landslide Model Experiment
Feng, C., Tian, B., Lu, X., Beer, M., Broggi, M., Bi, S., . . . He, T. (n.d.). Bayesian Updating of Soil–Water Character Curve Parameters Based on the Monitor Data of a Large-Scale Landslide Model Experiment. Applied Sciences, 10(16), 5526. doi:10.3390/app10165526
Adaptive experiment design for probabilistic integration
Wei, P., Zhang, X., & Beer, M. (2020). Adaptive experiment design for probabilistic integration. Computer Methods in Applied Mechanics and Engineering, 365, 113035. doi:10.1016/j.cma.2020.113035
Guest Editorial
Feng, G., Beer, M., Coolen, F. P. A., Ayyub, B. M., & Phoon, K. K. (2020). Guest Editorial. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 6(2).
Optimal Regulation of the Construction of Reliable Sea Defenses
Nieto-Cerezo, O., Wenzelburger, J., Patelli, E., & Beer, M. (2020). Optimal Regulation of the Construction of Reliable Sea Defenses. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 6(2), 04020023. doi:10.1061/ajrua6.0001065
Special section on resilience of engineering systems
Feng, G., Beer, M., Coolen, F. P. A., Ayyub, B. M., & Phoon, K. -K. (2020). Special Section on Resilience of Engineering Systems. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 6(2). doi:10.1115/1.4046473
Non-intrusive imprecise stochastic simulation by line sampling
Song, J., Valdebenito, M., Wei, P., Beer, M., & Lu, Z. (2020). Non-intrusive imprecise stochastic simulation by line sampling. Structural Safety, 84, 101936. doi:10.1016/j.strusafe.2020.101936
Analysis and Estimation of Human Errors From Major Accident Investigation Reports
Morais, C., Moura, R., Beer, M., & Patelli, E. (2020). Analysis and Estimation of Human Errors From Major Accident Investigation Reports. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 6(1). doi:10.1115/1.4044796
Fuzzy failure probability estimation applying intervening variables
Valdebenito, M. A., Beer, M., Jensen, H. A., Chen, J., & Wei, P. (2020). Fuzzy failure probability estimation applying intervening variables. Structural Safety, 83, 101909. doi:10.1016/j.strusafe.2019.101909
Special Issue on Human Performance and Decision-Making in Complex Industrial Environments
Moura, R., Beer, M., & Podofillini, L. (2020). Special Issue on Human Performance and Decision-Making in Complex Industrial Environments. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 6(1). doi:10.1115/1.4045557
A PDEM-COM framework for quantification of epistemic uncertainty
Wan, Z., Chen, J., Li, J., & Beer, M. (2020). A PDEM-COM framework for quantification of epistemic uncertainty. In Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019 (pp. 2622-2627). doi:10.3850/978-981-11-2724-30969-cd
BAYESIAN MODEL UPDATING FOR EXISTING SEISMIC-ISOLATED BRIDGES USING OBSERVED ACCELERATION RESPONSE DATA
Kitahara, M., Broggi, M., & Beer, M. (2020). BAYESIAN MODEL UPDATING FOR EXISTING SEISMIC-ISOLATED BRIDGES USING OBSERVED ACCELERATION RESPONSE DATA. In Proceedings of the XI International Conference on Structural Dynamics (pp. 3558-3566). EASD. doi:10.47964/1120.9291.18937
Breaking the Double Loop: Operator Norm Theory as a Tool to Compute with Imprecise Probabilities
Faes, M. G. R., Valdebenito, M. A., Moens, D., & Beer, M. (2020). Breaking the Double Loop: Operator Norm Theory as a Tool to Compute with Imprecise Probabilities. In Proceedings of the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference (pp. 4957-4963). Research Publishing Services. doi:10.3850/978-981-14-8593-0_5707-cd
Common cause failure importance analysis for aerospace systems
Mi, J., Beer, M., Li, Y. F., Broggi, M., & Cheng, Y. (2020). Common cause failure importance analysis for aerospace systems. In Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019 (pp. 2325-2331). doi:10.3850/978-981-11-2724-30855-cd
Components Importance Ranking Considering the Effect of Epistemic Uncertainty
Song, J., Lu, Z., & Beer, M. (2019). Components Importance Ranking Considering the Effect of Epistemic Uncertainty. In Proceedings of the 29th European Safety and Reliability Conference (ESREL) (pp. 1743-1749). Research Publishing Services. doi:10.3850/978-981-11-2724-3_0724-cd
Decision Making for Optimal Primary-Support Selection to Minimise Tunnel- Squeezing Risk
Chen, Y., Patelli, E., Zeng, P., Edwards, B., Li, T., & Beer, M. (2020). Decision Making for Optimal Primary-Support Selection to Minimise Tunnel- Squeezing Risk. In Proceedings of the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference (pp. 2257-2264). Research Publishing Services. doi:10.3850/978-981-14-8593-0_4170-cd
Decision making for optimal primary-support selection to minimise tunnel-squeezing risk
Chen, Y., Patelli, E., Zeng, P., Edwards, B., Li, T., & Beer, M. (2020). Decision making for optimal primary-support selection to minimise tunnel-squeezing risk. In 30th European Safety and Reliability Conference, ESREL 2020 and 15th Probabilistic Safety Assessment and Management Conference, PSAM 2020 (pp. 2257-2264).
Efficient Reliability Analysis of an Axial Compressor in Consideration of Epistemic Uncertainty
Salomon, J., Winnewisser, N., Wei, P., Broggi, M., & Beer, M. (2020). Efficient Reliability Analysis of an Axial Compressor in Consideration of Epistemic Uncertainty. In Proceedings of the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference (pp. 4791-4798). Research Publishing Services. doi:10.3850/978-981-14-8593-0_3685-cd
Efficient propagation of imprecise probability models by imprecise line sampling
Wei, P., Song, J., Valdebenito, M. A., & Beer, M. (2020). Efficient propagation of imprecise probability models by imprecise line sampling. In Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019 (pp. 2072-2077). doi:10.3850/978-981-11-0745-00994-cd
Efficient reliability analysis of an axial compressor in consideration of epistemic uncertainty
Salomon, J., Winnewisser, N., Wei, P., Broggi, M., & Beer, M. (2020). Efficient reliability analysis of an axial compressor in consideration of epistemic uncertainty. In 30th European Safety and Reliability Conference, ESREL 2020 and 15th Probabilistic Safety Assessment and Management Conference, PSAM 2020 (pp. 4791-4798).
IMPORTANCE MEASURE OF PROBABILISTIC COMMON CAUSE FAILURES UNDER SYSTEM HYBRID UNCERTAINTY BASED ON BAYESIAN NETWORK
Mi, J., Li, Y. -F., Beer, M., Broggi, M., & Cheng, Y. (2020). IMPORTANCE MEASURE OF PROBABILISTIC COMMON CAUSE FAILURES UNDER SYSTEM HYBRID UNCERTAINTY BASED ON BAYESIAN NETWORK. EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY, 22(1), 112-120. doi:10.17531/ein.2020.1.13
Imprecise stochastic dynamics via operator norm theory
Faes, M. G. R., Valdebenito, M. A., Beer, M., & Moens, D. (2020). Imprecise stochastic dynamics via operator norm theory. In PROCEEDINGS OF INTERNATIONAL CONFERENCE ON NOISE AND VIBRATION ENGINEERING (ISMA2020) / INTERNATIONAL CONFERENCE ON UNCERTAINTY IN STRUCTURAL DYNAMICS (USD2020) (pp. 3707-3717). Retrieved from https://www.webofscience.com/
Measuring systemic risk for mechanical structures using conditional probability
Eckert, C., & Beer, M. (2020). Measuring systemic risk for mechanical structures using conditional probability. In Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019 (pp. 4316-4320). doi:10.3850/978-981-11-0745-0-1137-cd
Model updating of model parameters and model form error in a uniform framework
Bi, S., Wagner, N., Beer, M., & Ouisse, M. (2020). Model updating of model parameters and model form error in a uniform framework. In Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019 (pp. 2679-2684). doi:10.3850/978-981-11-2724-30972-cd
Multidimensional resilience decision-making on a multistage high-speed axial compressor
Salomon, J., Behrensdorf, J., Broggi, M., Weber, S., & Beer, M. (2020). Multidimensional resilience decision-making on a multistage high-speed axial compressor. In Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019 (pp. 1357-1364). doi:10.3850/978-981-11-2724-30992-cd
PARAMETER INVESTIGATION OF RELAXED UNCERTAIN POWER SPECTRA FOR STOCHASTIC DYNAMIC SYSTEMS
Behrendt, M., Bittner, M., Comerford, L., Broggi, M., & Beer, M. (2020). PARAMETER INVESTIGATION OF RELAXED UNCERTAIN POWER SPECTRA FOR STOCHASTIC DYNAMIC SYSTEMS. In Proceedings of the XI International Conference on Structural Dynamics (pp. 3803-3815). EASD. doi:10.47964/1120.9311.18861
Preface
Beer, M., & Zio, E. (2020). Preface. In Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019.
Probabilistic modelling for frequency response functions and transmissibility functions with complex ratio statistics
Zhao, M. Y., Yan, W. J., Ren, W. X., & Beer, M. (2020). Probabilistic modelling for frequency response functions and transmissibility functions with complex ratio statistics. In Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019 (pp. 2714-2718). doi:10.3850/978-981-11-2724-30827-cd
Rare event modelling for stochastic dynamic systems approximated by the probability density evolution method
Bittner, M., Broggi, M., & Beer, M. (2020). Rare event modelling for stochastic dynamic systems approximated by the probability density evolution method. In Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019 (pp. 2719-2726). doi:10.3850/978-981-11-2724-30735-cd
Reliability evaluation of reinforced concrete columns designed by Eurocode for wind-dominated combination considering random loads eccentricity
Jiang, Y., Peng, S., Beer, M., Wang, L., & Zhang, J. (2020). Reliability evaluation of reinforced concrete columns designed by Eurocode for wind-dominated combination considering random loads eccentricity. ADVANCES IN STRUCTURAL ENGINEERING, 23(1), 146-159. doi:10.1177/1369433219866089
Tackling the lack of data for human error probability with Credal network
Morais, C., Tolo, S., Moura, R., Beer, M., & Patelli, E. (2020). Tackling the lack of data for human error probability with Credal network. In Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019 (pp. 382-386). doi:10.3850/978-981-11-2724-30746-cd
Which Distributions (or Families of Distributions) Best Represent Interval Uncertainty: Case of Permutation-Invariant Criteria
Beer, M., Urenda, J., Kosheleva, O., & Kreinovich, V. (2020). Which Distributions (or Families of Distributions) Best Represent Interval Uncertainty: Case of Permutation-Invariant Criteria. In Unknown Conference (pp. 70-79). Springer International Publishing. doi:10.1007/978-3-030-50146-4_6
Why Spiking Neural Networks Are Efficient: A Theorem
Beer, M., Urenda, J., Kosheleva, O., & Kreinovich, V. (n.d.). Why Spiking Neural Networks Are Efficient: A Theorem. In Unknown Conference (pp. 59-69). Springer International Publishing. doi:10.1007/978-3-030-50146-4_5
2019
Development of a Relaxed Stationary Power Spectrum using Imprecise Probabilities with Application to High-rise Buildings
Behrendt, M., Comerford, L., & Beer, M. (2019). Development of a Relaxed Stationary Power Spectrum using Imprecise Probabilities with Application to High-rise Buildings. In 2019 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (IEEE SSCI 2019) (pp. 784-790). Retrieved from https://www.webofscience.com/
Modeling asymmetric dependences among multivariate soil data for the geotechnical analysis – The asymmetric copula approach
Zhang, Y., Gomes, A. T., Beer, M., Neumann, I., Nackenhorst, U., & Kim, C. -W. (2019). Modeling asymmetric dependences among multivariate soil data for the geotechnical analysis - The asymmetric copula approach. SOILS AND FOUNDATIONS, 59(6), 1960-1979. doi:10.1016/j.sandf.2019.09.001
On the Robust Estimation of Small Failure Probabilities for Strong Nonlinear Models
Faes, M., Sadeghi, J., Broggi, M., de AngDelis, M., Patelli, E., Beer, M., & Moens, D. (2019). On the Robust Estimation of Small Failure Probabilities for Strong Nonlinear Models. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 5(4). doi:10.1115/1.4044044
Sensitivity analysis of prior beliefs in advanced Bayesian networks
He, L., Beer, M., Broggi, M., Wei, P., & Gomes, A. T. (2019). Sensitivity analysis of prior beliefs in advanced Bayesian networks. In 2019 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (IEEE SSCI 2019) (pp. 776-783). Retrieved from https://www.webofscience.com/
Structural Time-Dependent Reliability Assessment with New Power Spectral Density Function
Wang, C., Zhang, H., & Beer, M. (2019). Structural Time-Dependent Reliability Assessment with New Power Spectral Density Function. JOURNAL OF STRUCTURAL ENGINEERING, 145(12). doi:10.1061/(ASCE)ST.1943-541X.0002476
Vibration Performance of a Flow Energy Converter behind Two Side-by-Side Cylinders
Rasani, M. R., Moria, H., Beer, M., & Ariffin, A. K. (2019). Vibration Performance of a Flow Energy Converter behind Two Side-By-Side Cylinders. JOURNAL OF MARINE SCIENCE AND ENGINEERING, 7(12). doi:10.3390/jmse7120435
Fragility analysis of nonproportionally damped inelastic MDOF structural systems exposed to stochastic seismic excitation
Mitseas, I. P., & Beer, M. (2019). Fragility analysis of nonproportionally damped inelastic MDOF structural systems exposed to stochastic seismic excitation. Computers and Structures. doi:10.1016/j.compstruc.2019.106129
Resilience Decision-Making for Complex Systems
Beer, M. (2019). Resilience Decision-Making for Complex Systems. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering. doi:10.1115/1.4044907
Computation of Hybrid Uncertainty and Dependent Failure in System Reliability Analysis and Assessment
Song, Y. -F., Mi, J., Cheng, Y., Beer, M., & Broggi, M. (2019). Computation of Hybrid Uncertainty and Dependent Failure in System Reliability Analysis and Assessment. In 2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE) (pp. 774-782). IEEE. doi:10.1109/qr2mse46217.2019.9021202
Non-stationary response statistics of nonlinear oscillators with fractional derivative elements under evolutionary stochastic excitation
Fragkoulis, V. C., Kougioumtzoglou, I. A., Pantelous, A. A., & Beer, M. (2019). Non-stationary response statistics of nonlinear oscillators with fractional derivative elements under evolutionary stochastic excitation. Nonlinear Dynamics. doi:10.1007/s11071-019-05124-0
Non-intrusive stochastic analysis with parameterized imprecise probability models: II. Reliability and rare events analysis
Wei, P., Song, J., Bi, S., Broggi, M., Beer, M., Lu, Z., & Yue, Z. (2019). Non-intrusive stochastic analysis with parameterized imprecise probability models: II. Reliability and rare events analysis. Mechanical Systems and Signal Processing, 126, 227-247. doi:10.1016/j.ymssp.2019.02.015
Failure Analysis of Soil Slopes with Advanced Bayesian Networks
He, L., Gomes, A. T., Broggi, M., & Beer, M. (2019). Failure Analysis of Soil Slopes with Advanced Bayesian Networks. PERIODICA POLYTECHNICA-CIVIL ENGINEERING, 63(3), 763-774. doi:10.3311/PPci.14092
Reliability analysis with consideration of asymmetrically dependent variables: Discussion and application to geotechnical examples
Zhang, Y., Gomes, A. T., Beer, M., Neumann, I., Nackenhorst, U., & Kim, C. -W. (2019). Reliability analysis with consideration of asymmetrically dependent variables: Discussion and application to geotechnical examples. RELIABILITY ENGINEERING & SYSTEM SAFETY, 185, 261-277. doi:10.1016/j.ress.2018.12.025
The Bhattacharyya distance: Enriching the P-box in stochastic sensitivity analysis
Bi, S., Broggi, M., Wei, P., & Beer, M. (2019). The Bhattacharyya distance: Enriching the P-box in stochastic sensitivity analysis. Mechanical Systems and Signal Processing, 129, 265-281. doi:10.1016/j.ymssp.2019.04.035
A multivariate interval approach for inverse uncertainty quantification with limited experimental data
Faes, M., Broggi, M., Patelli, E., Govers, Y., Mottershead, J., Beer, M., & Moens, D. (2019). A multivariate interval approach for inverse uncertainty quantification with limited experimental data. Mechanical Systems and Signal Processing, 118, 534-548. doi:10.1016/j.ymssp.2018.08.050
Approaches to Risk Identification in Public–Private Partnership Projects: Malaysian Private Partners’ Overview
Sarvari, H., Valipour, A., Yahya, N., Noor, N. M. D., Beer, M., & Banaitiene, N. (2019). Approaches to Risk Identification in Public-Private Partnership Projects: Malaysian Private Partners' Overview. ADMINISTRATIVE SCIENCES, 9(1). doi:10.3390/admsci9010017
The role of the Bhattacharyya distance in stochastic model updating
Bi, S., Broggi, M., & Beer, M. (2019). The role of the Bhattacharyya distance in stochastic model updating. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 117, 437-452. doi:10.1016/j.ymssp.2018.08.017
Hybrid interval and random analysis for structural-acoustic systems including periodical composites and multi-scale bounded hybrid uncertain parameters
Chen, N., Xia, S., Yu, D., Liu, J., & Beer, M. (2019). Hybrid interval and random analysis for structural-acoustic systems including periodical composites and multi-scale bounded hybrid uncertain parameters. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 115, 524-544. doi:10.1016/j.ymssp.2018.06.016
A collocation scheme for deep uncertainty treatment
Dannert, M. M., Fau, A., Fleury, R. M. N., Broggi, M., Nackenhorst, U., & Beer, M. (2019). A collocation scheme for deep uncertainty treatment. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
A collocation scheme for deep uncertainty treatment
Dannert, M. M., Fau, A., Fleury, R. M. N., Broggi, M., Nackenhorst, U., & Beer, M. (2019). A collocation scheme for deep uncertainty treatment. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
A collocation scheme for deep uncertainty treatment
Dannert, M. M., Fau, A., Fleury, R. M. N., Broggi, M., Nackenhorst, U., & Beer, M. (2019). A collocation scheme for deep uncertainty treatment. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
A collocation scheme for deep uncertainty treatment
Dannert, M. M., Fau, A., Fleury, R. M. N., Broggi, M., Nackenhorst, U., & Beer, M. (2019). A collocation scheme for deep uncertainty treatment. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
An efficient complex modal decomposition method for inelastic stochastic design spectrum-based analysis
Mitseas, I. P., Kougioumtzoglou, I. A., & Beer, M. (2019). An efficient complex modal decomposition method for inelastic stochastic design spectrum-based analysis. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
An efficient complex modal decomposition method for inelastic stochastic design spectrum-based analysis
Mitseas, I. P., Kougioumtzoglou, I. A., & Beer, M. (2019). An efficient complex modal decomposition method for inelastic stochastic design spectrum-based analysis. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
An efficient complex modal decomposition method for inelastic stochastic design spectrum-based analysis
Mitseas, I. P., Kougioumtzoglou, I. A., & Beer, M. (2019). An efficient complex modal decomposition method for inelastic stochastic design spectrum-based analysis. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
An efficient complex modal decomposition method for inelastic stochastic design spectrum-based analysis
Mitseas, I. P., Kougioumtzoglou, I. A., & Beer, M. (2019). An efficient complex modal decomposition method for inelastic stochastic design spectrum-based analysis. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Identification of system matrices based on experimental modal analysis and its application in structural health monitoring
Bi, S., Beer, M., Ouisse, M., & Foltête, E. (2019). Identification of system matrices based on experimental modal analysis and its application in structural health monitoring. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Identification of system matrices based on experimental modal analysis and its application in structural health monitoring
Bi, S., Beer, M., Ouisse, M., & Foltête, E. (2019). Identification of system matrices based on experimental modal analysis and its application in structural health monitoring. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Identification of system matrices based on experimental modal analysis and its application in structural health monitoring
Bi, S., Beer, M., Ouisse, M., & Foltête, E. (2019). Identification of system matrices based on experimental modal analysis and its application in structural health monitoring. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Identification of system matrices based on experimental modal analysis and its application in structural health monitoring
Bi, S., Beer, M., Ouisse, M., & Foltête, E. (2019). Identification of system matrices based on experimental modal analysis and its application in structural health monitoring. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Inverse quantification of epistemic uncertainty under scarce data: Bayesian or Interval approach?
Faes, M., Broggi, M., Patelli, E., Govers, Y., Mottershead, J., Beer, M., & Moens, D. (2019). Inverse quantification of epistemic uncertainty under scarce data: Bayesian or Interval approach?. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Inverse quantification of epistemic uncertainty under scarce data: Bayesian or Interval approach?
Faes, M., Broggi, M., Patelli, E., Govers, Y., Mottershead, J., Beer, M., & Moens, D. (2019). Inverse quantification of epistemic uncertainty under scarce data: Bayesian or Interval approach?. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Inverse quantification of epistemic uncertainty under scarce data: Bayesian or Interval approach?
Faes, M., Broggi, M., Patelli, E., Govers, Y., Mottershead, J., Beer, M., & Moens, D. (2019). Inverse quantification of epistemic uncertainty under scarce data: Bayesian or Interval approach?. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Inverse quantification of epistemic uncertainty under scarce data: Bayesian or Interval approach?
Faes, M., Broggi, M., Patelli, E., Govers, Y., Mottershead, J., Beer, M., & Moens, D. (2019). Inverse quantification of epistemic uncertainty under scarce data: Bayesian or Interval approach?. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Pathways for uncertainty quantification through stochastic damage constitutive models of concrete
Wan, Z., Chen, J., & Beer, M. (2019). Pathways for uncertainty quantification through stochastic damage constitutive models of concrete. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Pathways for uncertainty quantification through stochastic damage constitutive models of concrete
Wan, Z., Chen, J., & Beer, M. (2019). Pathways for uncertainty quantification through stochastic damage constitutive models of concrete. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Pathways for uncertainty quantification through stochastic damage constitutive models of concrete
Wan, Z., Chen, J., & Beer, M. (2019). Pathways for uncertainty quantification through stochastic damage constitutive models of concrete. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Pathways for uncertainty quantification through stochastic damage constitutive models of concrete
Wan, Z., Chen, J., & Beer, M. (2019). Pathways for uncertainty quantification through stochastic damage constitutive models of concrete. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
RELAXED STATIONARY POWER SPECTRUM MODEL USING IMPRECISE PROBABILITIES
Behrendt, M., Comerford, L., & Beer, M. (2019). RELAXED STATIONARY POWER SPECTRUM MODEL USING IMPRECISE PROBABILITIES. In Proceedings of the 7th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COMPDYN 2015) (pp. 592-599). Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece. doi:10.7712/120119.6941.19045
Rare failure event analysis of structures under mixed uncertainties
Wei, P., Bi, S., Zhang, Y., & Beer, M. (2019). Rare failure event analysis of structures under mixed uncertainties. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Rare failure event analysis of structures under mixed uncertainties
Wei, P., Bi, S., Zhang, Y., & Beer, M. (2019). Rare failure event analysis of structures under mixed uncertainties. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Rare failure event analysis of structures under mixed uncertainties
Wei, P., Bi, S., Zhang, Y., & Beer, M. (2019). Rare failure event analysis of structures under mixed uncertainties. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Rare failure event analysis of structures under mixed uncertainties
Wei, P., Bi, S., Zhang, Y., & Beer, M. (2019). Rare failure event analysis of structures under mixed uncertainties. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Stochastic processes identification from data ensembles via power spectrum classification
Behrendt, M., Comerford, L., & Beer, M. (2019). Stochastic processes identification from data ensembles via power spectrum classification. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Stochastic processes identification from data ensembles via power spectrum classification
Behrendt, M., Comerford, L., & Beer, M. (2019). Stochastic processes identification from data ensembles via power spectrum classification. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Stochastic processes identification from data ensembles via power spectrum classification
Behrendt, M., Comerford, L., & Beer, M. (2019). Stochastic processes identification from data ensembles via power spectrum classification. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Stochastic processes identification from data ensembles via power spectrum classification
Behrendt, M., Comerford, L., & Beer, M. (2019). Stochastic processes identification from data ensembles via power spectrum classification. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Tightening the bound estimate of structural reliability under imprecise probability information
Wang, C., Zhang, H., & Beer, M. (2019). Tightening the bound estimate of structural reliability under imprecise probability information. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Tightening the bound estimate of structural reliability under imprecise probability information
Wang, C., Zhang, H., & Beer, M. (2019). Tightening the bound estimate of structural reliability under imprecise probability information. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Tightening the bound estimate of structural reliability under imprecise probability information
Wang, C., Zhang, H., & Beer, M. (2019). Tightening the bound estimate of structural reliability under imprecise probability information. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
Tightening the bound estimate of structural reliability under imprecise probability information
Wang, C., Zhang, H., & Beer, M. (2019). Tightening the bound estimate of structural reliability under imprecise probability information. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019.
2018
A polynomial expansion approach for response analysis of periodical composite structural-acoustic problems with multi-scale mixed aleatory and epistemic uncertainties
Chen, N., Hu, Y., Yu, D., Liu, J., & Beer, M. (2018). A polynomial expansion approach for response analysis of periodical composite structural-acoustic problems with multi-scale mixed aleatory and epistemic uncertainties. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 342, 509-531. doi:10.1016/j.cma.2018.08.021
Extending the survival signature paradigm to complex systems with non-repairable dependent failures
George-Williams, H., Feng, G., Coolen, F. P. A., Beer, M., & Patelli, E. (2018). Extending the survival signature paradigm to complex systems with non-repairable dependent failures. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability. doi:10.1177/1748006X18808085
Surface crack growth prediction under fatigue load using probabilistic S-version finite element model
Akramin, M. R. M., Ariffin, A. K., Kikuchi, M., Beer, M., Shaari, M. S., & Husnain, M. N. M. (2018). Surface crack growth prediction under fatigue load using probabilistic S-version finite element model. JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING, 40(11). doi:10.1007/s40430-018-1442-8
Computing tight bounds of structural reliability under imprecise probabilistic information
Wang, C., Zhang, H., & Beer, M. (2018). Computing tight bounds of structural reliability under imprecise probabilistic information. COMPUTERS & STRUCTURES, 208, 92-104. doi:10.1016/j.compstruc.2018.07.003
A Novel Application of System Survival Signature in Reliability Assessment of Offshore Structures
Regenhardt, T. E., Azad, M. S., Punurai, W., & Beer, M. (2018). A Novel Application of System Survival Signature in Reliability Assessment of Offshore Structures. In Advances in Intelligent Systems and Computing Vol. 866 (pp. 11-20). doi:10.1007/978-3-030-00979-3_2
Efficient Reliability and Risk Analysis of Complex Interconnected Systems
Behrensdorf, J., Broggi, M., & Beer, M. (2018). Efficient Reliability and Risk Analysis of Complex Interconnected Systems. In RESILIENCE ENGINEERING FOR URBAN TUNNELS (pp. 43-54). Retrieved from https://www.webofscience.com/
Reliability of Critical Infrastructure Networks: Challenges
Zuev, K. M., & Beer, M. (2018). Reliability of Critical Infrastructure Networks: Challenges. In RESILIENCE ENGINEERING FOR URBAN TUNNELS (pp. 71-82). Retrieved from https://www.webofscience.com/
Utilising database-driven interactive software to enhance independent home-study in a flipped classroom setting: going beyond visualising engineering concepts to ensuring formative assessment
Comerford, L., Mannis, A., DeAngelis, M., Kougioumtzoglou, I. A., & Beer, M. (2018). Utilising database-driven interactive software to enhance independent home-study in a flipped classroom setting: going beyond visualising engineering concepts to ensuring formative assessment. EUROPEAN JOURNAL OF ENGINEERING EDUCATION, 43(4), 522-537. doi:10.1080/03043797.2017.1293617
An efficient reliability analysis on complex non-repairable systems with common-cause failures
Feng, G., George-Williams, H., Patelli, E., Coolen, F. P. A., & Beer, M. (2018). An efficient reliability analysis on complex non-repairable systems with common-cause failures. In SAFETY AND RELIABILITY - SAFE SOCIETIES IN A CHANGING WORLD (pp. 2531-2537). Retrieved from https://www.webofscience.com/
Application of fuzzy finite element method in addressing the presence of uncertainties
Yusmye, A. Y. N., Ariffin, A. K., Abdullah, S., Singh, S. S. K., & Beer, M. (2018). Application of fuzzy finite element method in addressing the presence of uncertainties. In SAFETY AND RELIABILITY - SAFE SOCIETIES IN A CHANGING WORLD (pp. 2701-2706). Retrieved from https://www.webofscience.com/
Human reliability analysis-accounting for human actions and external factors through the project life cycle
Morais, C., Moura, R., Beer, M., & Patelli, E. (2018). Human reliability analysis-accounting for human actions and external factors through the project life cycle. In SAFETY AND RELIABILITY - SAFE SOCIETIES IN A CHANGING WORLD (pp. 329-338). Retrieved from https://www.webofscience.com/
Imprecise reliability analysis of complex interconnected networks
Behrensdorf, J., Broggi, M., & Beer, M. (2018). Imprecise reliability analysis of complex interconnected networks. In SAFETY AND RELIABILITY - SAFE SOCIETIES IN A CHANGING WORLD (pp. 2589-2594). Retrieved from https://www.webofscience.com/
A novel stochastic linearization framework for seismic demand estimation of hysteretic MDOF systems subject to linear response spectra
Mitseas, I. P., Kougioumtzoglou, I. A., Giaralis, A., & Beer, M. (2018). A novel stochastic linearization framework for seismic demand estimation of hysteretic MDOF systems subject to linear response spectra. STRUCTURAL SAFETY, 72, 84-98. doi:10.1016/j.strusafe.2017.12.008
Constrained non-linear multi-objective optimisation of preventive maintenance scheduling for offshore wind farms
Zhong, S., Pantelous, A. A., Beer, M., & Zhou, J. (2018). Constrained non-linear multi-objective optimisation of preventive maintenance scheduling for offshore wind farms. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 104, 347-369. doi:10.1016/j.ymssp.2017.10.035
Hybrid Uncertain Analysis for Exterior Acoustic Field Prediction with Interval Random Parameters
Chen, N., Yu, D., Xia, B., & Beer, M. (2018). Hybrid Uncertain Analysis for Exterior Acoustic Field Prediction with Interval Random Parameters. INTERNATIONAL JOURNAL OF COMPUTATIONAL METHODS, 15(2). doi:10.1142/S0219876218500068
<i>L<sub>p</sub></i>-norm minimization for stochastic process power spectrum estimation subject to incomplete data
Zhang, Y., Comerford, L., Kougioumtzoglou, I. A., & Beer, M. (2018). <i>L<sub>p</sub></i>-norm minimization for stochastic process power spectrum estimation subject to incomplete data. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 101, 361-376. doi:10.1016/j.ymssp.2017.08.017
An open toolbox for the reduction, inference computation and sensitivity analysis of Credal Networks
Tolo, S., Patelli, E., & Beer, M. (2018). An open toolbox for the reduction, inference computation and sensitivity analysis of Credal Networks. ADVANCES IN ENGINEERING SOFTWARE, 115, 126-148. doi:10.1016/j.advengsoft.2017.09.003
Attempt to predict human error probability in different industry sectors using data from major accidents and Bayesian networks
Morais, C., Moura, R., Beer, M., & Patelli, E. (2018). Attempt to predict human error probability in different industry sectors using data from major accidents and Bayesian networks. In PSAM 2018 - Probabilistic Safety Assessment and Management.
Bayesian model updating using stochastic distances as uncertainty quantification metrics
Bi, S., Broggi, M., Beer, M., & Zhang, Y. (2018). Bayesian model updating using stochastic distances as uncertainty quantification metrics. In PROCEEDINGS OF INTERNATIONAL CONFERENCE ON NOISE AND VIBRATION ENGINEERING (ISMA2018) / INTERNATIONAL CONFERENCE ON UNCERTAINTY IN STRUCTURAL DYNAMICS (USD2018) (pp. 5157-5167). Retrieved from https://www.webofscience.com/
Extrapolation of extreme traffic load effects on a cable-stayed bridge based on weigh-in-motion measurements
Lu, N., Liu, Y., & Beer, M. (2018). Extrapolation of extreme traffic load effects on a cable-stayed bridge based on weigh-in-motion measurements. In International Journal of Reliability and Safety Vol. 12 (pp. 69). Inderscience Publishers. doi:10.1504/ijrs.2018.092504
What If We Do Not Know Correlations?
Beer, M., Gong, Z., Neumann, I., Sriboonchitta, S., & Kreinovich, V. (2018). What If We Do Not Know Correlations?. In ECONOMETRICS FOR FINANCIAL APPLICATIONS (Vol. 760, pp. 78-85). doi:10.1007/978-3-319-73150-6_5
2017
Options-based negotiation management of PPP–BOT infrastructure projects
Attarzadeh, M., Chua, D. K. H., Beer, M., & Abbott, E. L. S. (2017). Options-based negotiation management of PPP-BOT infrastructure projects. CONSTRUCTION MANAGEMENT AND ECONOMICS, 35(11-12), 676-692. doi:10.1080/01446193.2017.1325962
Fatigue Stress Spectra and Reliability Evaluation of Short- to Medium-Span Bridges under Stochastic and Dynamic Traffic Loads
Yan, D., Luo, Y., Lu, N., Yuan, M., & Beer, M. (2017). Fatigue Stress Spectra and Reliability Evaluation of Short- to Medium-Span Bridges under Stochastic and Dynamic Traffic Loads. JOURNAL OF BRIDGE ENGINEERING, 22(12). doi:10.1061/(ASCE)BE.1943-5592.0001137
Robust vulnerability analysis of nuclear facilities subject to external hazards
Tolo, S., Patelli, E., & Beer, M. (2017). Robust vulnerability analysis of nuclear facilities subject to external hazards. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 31(10), 2733-2756. doi:10.1007/s00477-016-1360-1
Uncertainty Quantification of Power Spectrum and Spectral Moments Estimates Subject to Missing Data
Zhang, Y., Comerford, L., Kougioumtzoglou, I. A., Patelli, E., & Beer, M. (2017). Uncertainty Quantification of Power Spectrum and Spectral Moments Estimates Subject to Missing Data. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART A-CIVIL ENGINEERING, 3(4). doi:10.1061/AJRUA6.0000925
Learning from accidents: interactions between human factors, technology and organisations as a central element to validate risk studies
Moura, R., beer, M., Patelli, E., Lewis, J., & Knoll, F. (2017). Learning from accidents: interactions between human factors, technology and organisations as a central element to validate risk studies. Safety Science, 99(Part B), 196-214. doi:10.1016/j.ssci.2017.05.001
Learning from major accidents: Graphical representation and analysis of multi-attribute events to enhance risk communication
Moura, R., Beer, M., Patelli, E., & Lewis, J. (2017). Learning from major accidents: Graphical representation and analysis of multi-attribute events to enhance risk communication. SAFETY SCIENCE, 99, 58-70. doi:10.1016/j.ssci.2017.03.005
Lifetime Deflections of Long-Span Bridges under Dynamic and Growing Traffic Loads
Lu, N., Beer, M., Noori, M., & Liu, Y. (2017). Lifetime Deflections of Long-Span Bridges under Dynamic and Growing Traffic Loads. JOURNAL OF BRIDGE ENGINEERING, 22(11). doi:10.1061/(ASCE)BE.1943-5592.0001125
Fuzzy Randomness Simulation of Long-Term Infrastructure Projects
Attarzadeh, M., Chua, D. K. H., Beer, M., & Abbott, E. L. S. (2017). Fuzzy Randomness Simulation of Long-Term Infrastructure Projects. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 3(3), 04017002. doi:10.1061/AJRUA6.0000902
Comparison of Bayesian and interval uncertainty quantification: Application to the AIRMOD test structure
Broggi, M., Faes, M., Patelli, E., Govers, Y., Moens, D., & Beer, M. (2017). Comparison of Bayesian and interval uncertainty quantification: Application to the AIRMOD test structure. In 2017 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE. doi:10.1109/ssci.2017.8280882
How Accurate Are Expert Estimations of Correlation?
Beer, M., Gong, Z., Diaz De La, O. F. A., & Kreinovich, V. (2017). How Accurate Are Expert Estimations of Correlation?. In 2017 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 1-9). IEEE. doi:10.1109/ssci.2017.8280790
Imprecise probability analysis of steel structures subject to atmospheric corrosion
Zhang, H., Ha, L., Li, Q., & Beer, M. (2017). Imprecise probability analysis of steel structures subject to atmospheric corrosion. Structural Safety, 67, 62-69. doi:10.1016/j.strusafe.2017.04.001
Revealing prediction uncertainty in artificial neural network based reconstruction of missing data in stochastic process records utilizing extreme learning machines
Comerford, L., Beer, M., & Lu, N. (2017). Revealing prediction uncertainty in artificial neural network based reconstruction of missing data in stochastic process records utilizing extreme learning machines. In 2017 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 1-7). IEEE. doi:10.1109/ssci.2017.8285295
Forced Monte Carlo Simulation Strategy for the Design of Maintenance Plans with Multiple Inspections
de Angelis, M., Patelli, E., & Beer, M. (2017). Forced Monte Carlo Simulation Strategy for the Design of Maintenance Plans with Multiple Inspections. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART A-CIVIL ENGINEERING, 3(2). doi:10.1061/AJRUA6.0000868
Risk Assessment of Spent Nuclear Fuel Facilities Considering Climate Change
Tolo, S., Patelli, E., & Beer, M. (2017). Risk Assessment of Spent Nuclear Fuel Facilities Considering Climate Change. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART A-CIVIL ENGINEERING, 3(2). doi:10.1061/AJRUA6.0000874
Special Issue on Complex Engineered Networks: Reliability, Risk, and Uncertainty
Zuev, K. M., & Beer, M. (2017). Special Issue on Complex Engineered Networks: Reliability, Risk, and Uncertainty. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART B-MECHANICAL ENGINEERING, 3(2). doi:10.1115/1.4036240
Compressive sensing with an adaptive wavelet basis for structural system response and reliability analysis under missing data
Comerford, L., Jensen, H. A., Mayorga, F., Beer, M., & Kougioumtzoglou, I. A. (2017). Compressive sensing with an adaptive wavelet basis for structural system response and reliability analysis under missing data. COMPUTERS & STRUCTURES, 182, 26-40. doi:10.1016/j.compstruc.2016.11.012
Robustness of Load and Resistance Design Factors for RC Columns with Wind-Dominated Combination Considering Random Eccentricity
Jiang, Y., Zhou, H., Beer, M., Wang, L., Zhang, J., & Zhao, L. (2017). Robustness of Load and Resistance Design Factors for RC Columns with Wind-Dominated Combination Considering Random Eccentricity. JOURNAL OF STRUCTURAL ENGINEERING, 143(4). doi:10.1061/(ASCE)ST.1943-541X.0001720
Bayesian model calibration using subset simulation
Gong, Z. T., DiazDelaO, F. A., & Beer, M. (2017). Bayesian model calibration using subset simulation. In Risk, Reliability and Safety: Innovating Theory and Practice - Proceedings of the 26th European Safety and Reliability Conference, ESREL 2016 (pp. 50).
Bayesian model calibration using subset simulation
Gong, Z. T., DiazDelaO, F. A., & Beer, M. (2017). Bayesian model calibration using subset simulation. In RISK, RELIABILITY AND SAFETY: INNOVATING THEORY AND PRACTICE (pp. 293-298). Retrieved from https://www.webofscience.com/
Comparison of Bayesian and Interval Uncertainty Quantification: Application to the AIRMOD Test Structure
Broggi, M., Faes, M., Patelli, E., Govers, Y., Moens, D., & Beer, M. (2017). Comparison of Bayesian and Interval Uncertainty Quantification: Application to the AIRMOD Test Structure. In 2017 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI) (pp. 1684-1691). Retrieved from https://www.webofscience.com/
Component importance measures for complex repairable system
Feng, G., Patelli, E., Beer, M., & Coolen, F. P. A. (2017). Component importance measures for complex repairable system. In Risk, Reliability and Safety: Innovating Theory and Practice - Proceedings of the 26th European Safety and Reliability Conference, ESREL 2016 (pp. 252).
EFFICIENT RELIABILITY AND UNCERTAINTY ASSESSMENT ON LIFELINE NETWORKS USING THE SURVIVAL SIGNATURE
Feng, G., Reed, S., Patelli, E., Beer, M., & Coolen, F. P. A. (2017). EFFICIENT RELIABILITY AND UNCERTAINTY ASSESSMENT ON LIFELINE NETWORKS USING THE SURVIVAL SIGNATURE. In Proceedings of the 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2017) (pp. 90-99). Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece. doi:10.7712/120217.5354.16865
How Accurate Are Expert Estimations of Correlation?
Beer, M., Gong, Z., Diaz De La, F. A. O., & Kreinovich, V. (2017). How Accurate Are Expert Estimations of Correlation?. In 2017 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI) (pp. 883-891). Retrieved from https://www.webofscience.com/
Human factors influencing decision-making: Tendencies from first-line management decisions and implications to reduce major accidents
Moura, R., Patelli, E., Lewis, J., Morais, C., & Beer, M. (2017). Human factors influencing decision-making: Tendencies from first-line management decisions and implications to reduce major accidents. In Safety and Reliability – Theory and Applications (pp. 44). CRC Press. doi:10.1201/9781315210469-34
Learning from accidents: Investigating the genesis of human errors in multi-attribute settings to improve the organisation of design
Moura, R., Beer, M., Patelli, E., Lewis, J., & Knoll, F. (2017). Learning from accidents: Investigating the genesis of human errors in multi-attribute settings to improve the organisation of design. In Risk, Reliability and Safety: Innovating Theory and Practice - Proceedings of the 26th European Safety and Reliability Conference, ESREL 2016 (pp. 38).
Meta-models for fatigue damage estimation of offshore wind turbines jacket substructures
Brandt, S., Broggi, M., Haefele, J., Gebhardt, C. G., Rolfes, R., & Beer, M. (2017). Meta-models for fatigue damage estimation of offshore wind turbines jacket substructures. In X INTERNATIONAL CONFERENCE ON STRUCTURAL DYNAMICS (EURODYN 2017) Vol. 199 (pp. 1158-1163). doi:10.1016/j.proeng.2017.09.292
Multiple response surfaces method with advanced classification of samples for structural failure function fitting
Jiang, Y., Zhao, L., Beer, M., Patelli, E., Broggi, M., Luo, J., . . . Zhang, J. (2017). Multiple response surfaces method with advanced classification of samples for structural failure function fitting. STRUCTURAL SAFETY, 64, 87-97. doi:10.1016/j.strusafe.2016.10.002
Numerically efficient reliability analysis of interdependent networks
Behrensdorf, J., Broggi, M., Brandt, S., & Beer, M. (2017). Numerically efficient reliability analysis of interdependent networks. In Safety and Reliability – Theory and Applications (pp. 342). CRC Press. doi:10.1201/9781315210469-298
Revealing Prediction Uncertainty in Artificial Neural Network Based Reconstruction of Missing Data in Stochastic Process Records utilizing Extreme Learning Machines
Comerford, L., Beer, M., & Lu, N. (2017). Revealing Prediction Uncertainty in Artificial Neural Network Based Reconstruction of Missing Data in Stochastic Process Records utilizing Extreme Learning Machines. In 2017 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI) (pp. 871-877). Retrieved from https://www.webofscience.com/
SAMPLING SCHEMES FOR HISTORY MATCHING USING SUBSET SIMULATION
Gong, Z., Díaz De la O, F. A., & Beer, M. (2017). SAMPLING SCHEMES FOR HISTORY MATCHING USING SUBSET SIMULATION. In Proceedings of the 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2017) (pp. 154-164). Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece. doi:10.7712/120217.5359.16948
Sensitivity Analysis of Material and Load Parameters to Fatigue Stresses of an Offshore Wind Turbine Monopile Substructure
Glisic, A., Schaumann, P., Broggi, M., & Beer, M. (2017). Sensitivity Analysis of Material and Load Parameters to Fatigue Stresses of an Offshore Wind Turbine Monopile Substructure. In X INTERNATIONAL CONFERENCE ON STRUCTURAL DYNAMICS (EURODYN 2017) Vol. 199 (pp. 1228-1233). doi:10.1016/j.proeng.2017.09.255
Sensitivity analysis for bayesian networks with interval probabilities
Tolo, S., Patelli, E., & Beer, M. (2017). Sensitivity analysis for bayesian networks with interval probabilities. In Risk, Reliability and Safety: Innovating Theory and Practice - Proceedings of the 26th European Safety and Reliability Conference, ESREL 2016 (pp. 52).
Survival signature approach for the reliability analysis of an axial compressor
Miro, S., Broggi, M., Beer, M., Willeke, T., & Seume, J. (2017). Survival signature approach for the reliability analysis of an axial compressor. In Safety and Reliability – Theory and Applications (pp. 344). CRC Press. doi:10.1201/9781315210469-300
2016
Interval spectral stochastic finite element analysis of structures with aggregation of random field and bounded parameters
Duy, M. D., Gao, W., Song, C., & Beer, M. (2016). Interval spectral stochastic finite element analysis of structures with aggregation of random field and bounded parameters. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, 108(10), 1198-1229. doi:10.1002/nme.5251
Uncertainty analysis of a structural-acoustic problem using imprecise probabilities based on p-box representations
Chen, N., Yu, D., Xia, B., & Beer, M. (2016). Uncertainty analysis of a structural-acoustic problem using imprecise probabilities based on p-box representations. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 80, 45-57. doi:10.1016/j.ymssp.2016.04.009
Component importance measures for complex repairable system
Feng, G., Patelli, E., Beer, M., & Coolen, F. P. A. (2017). Component importance measures for complex repairable system. In RISK, RELIABILITY AND SAFETY: INNOVATING THEORY AND PRACTICE (pp. 1580-1585). Retrieved from https://www.webofscience.com/
Learning from accidents: Investigating the genesis of human errors in multi-attribute settings to improve the organisation of design
Moura, R., Beer, M., Patelli, E., Lewis, J., & Knoll, F. (2017). Learning from accidents: Investigating the genesis of human errors in multi-attribute settings to improve the organisation of design. In RISK, RELIABILITY AND SAFETY: INNOVATING THEORY AND PRACTICE (pp. 228-236). Retrieved from https://www.webofscience.com/
Sensitivity analysis for Bayesian networks with interval probabilities
Tolo, S., Patelli, E., & Beer, M. (2017). Sensitivity analysis for Bayesian networks with interval probabilities. In RISK, RELIABILITY AND SAFETY: INNOVATING THEORY AND PRACTICE (pp. 306-312). Retrieved from https://www.webofscience.com/
Nuanced Robustness Analysis with Limited Information
Zhang, M. Q., Beer, M., Koh, C. G., & Jensen, H. A. (2016). Nuanced Robustness Analysis with Limited Information. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART A-CIVIL ENGINEERING, 2(3). doi:10.1061/AJRUA6.0000821
Nonlinear MDOF system Survival Probability Determination Subject to Evolutionary Stochastic Excitation
Mitseas, I. P., Kougioumtzoglou, I. A., Spanos, P. D., & Beer, M. (2016). Nonlinear MDOF system Survival Probability Determination Subject to Evolutionary Stochastic Excitation. STROJNISKI VESTNIK-JOURNAL OF MECHANICAL ENGINEERING, 62(7-8), 440-451. doi:10.5545/sv-jme.2016.3752
Imprecise system reliability and component importance based on survival signature
Feng, G., Patelli, E., Beer, M., & Coolen, F. P. A. (2016). Imprecise system reliability and component importance based on survival signature. RELIABILITY ENGINEERING & SYSTEM SAFETY, 150, 116-125. doi:10.1016/j.ress.2016.01.019
Softening Duffing Oscillator Reliability Assessment Subject to Evolutionary Stochastic Excitation
Kougioumtzoglou, I. A., Zhang, Y., & Beer, M. (2016). Softening Duffing Oscillator Reliability Assessment Subject to Evolutionary Stochastic Excitation. ASCE-ASME JOURNAL OF RISK AND UNCERTAINTY IN ENGINEERING SYSTEMS PART A-CIVIL ENGINEERING, 2(2). doi:10.1061/AJRUA6.0000828
Reliability Analysis of Complex Systems with Uncertainties by Monte Carlo Simulation Method
Feng, G., Patelli., & Beer. (2016). Reliability Analysis of Complex Systems with Uncertainties by Monte Carlo Simulation Method. In Tongji University Press (pp. 353-358). Shanghai, China.
An approximate stochastic dynamics approach for nonlinear structural system performance-based multi-objective optimum design
Mitseas, I. P., Kougioumtzoglou, I. A., & Beer, M. (2016). An approximate stochastic dynamics approach for nonlinear structural system performance-based multi-objective optimum design. STRUCTURAL SAFETY, 60, 67-76. doi:10.1016/j.strusafe.2016.01.003
Compressive sensing based stochastic process power spectrum estimation subject to missing data
Comerford, L., Kougioumtzoglou, I. A., & Beer, M. (2016). Compressive sensing based stochastic process power spectrum estimation subject to missing data. In PROBABILISTIC ENGINEERING MECHANICS Vol. 44 (pp. 66-76). doi:10.1016/j.probengmech.2015.09.015
Learning from major accidents to improve system design
Moura, R., Beer, M., Patelli, E., Lewis, J., & Knoll, F. (2016). Learning from major accidents to improve system design. Safety Science, 84, 37-45. doi:10.1016/j.ssci.2015.11.022
Why Modified exponential covariance kernel is empirically successful: A theoretical explanation
Kosheleva, O., & Beer, M. (2016). Why Modified exponential covariance kernel is empirically successful: A theoretical explanation. Journal of Uncertain Systems, 10(1), 10-14.
Approximate fuzzy analysis of linear structural systems applying intervening variables
Valdebenito, M. A., Perez, C. A., Jensen, H. A., & Beer, M. (2016). Approximate fuzzy analysis of linear structural systems applying intervening variables. COMPUTERS & STRUCTURES, 162, 116-129. doi:10.1016/j.compstruc.2015.08.020
2015
Special Issue: Civil-Comp
Tsompanakis, Y., Ivanyi, P., Beck, A. T., Beer, M., Costa Neves, L. F., Girardi, M., . . . Topping, B. H. V. (2015). Special Issue: Civil-Comp. ADVANCES IN ENGINEERING SOFTWARE, 89, 1-2. doi:10.1016/j.advengsoft.2015.08.007
Compressive Sensing for power spectrum estimation of multi-dimensional processes under missing data
Zhang, Y., Comerford, L., Beer, M., & Kougioumtroglou, L. (2015). Compressive Sensing for power spectrum estimation of multi-dimensional processes under missing data. In 2015 INTERNATIONAL CONFERENCE ON SYSTEMS, SIGNALS AND IMAGE PROCESSING (IWSSIP 2015) (pp. 162-165). Retrieved from https://www.webofscience.com/
Enhanced Bayesian Network approach to sea wave overtopping hazard quantification
Tolo, S., Patelli, E., & Beer, M. (2015). Enhanced Bayesian Network approach to sea wave overtopping hazard quantification. In Unknown Conference (pp. 1983-1990). CRC Press. doi:10.1201/b19094-258
Human factors and quality control procedures: An example from the offshore oil & gas industry
Morais, C., Moura, R., Beer, M., & Lewi, J. (2015). Human factors and quality control procedures: An example from the offshore oil & gas industry. In Unknown Conference (pp. 3835-3841). CRC Press. doi:10.1201/b19094-502
Learning from accidents: Analysis of multi-attribute events and implications to improve design and reduce human errors
Moura, R., Beer, M., Patelli, E., Lewis, J., & Knoll, F. (2015). Learning from accidents: Analysis of multi-attribute events and implications to improve design and reduce human errors. In Unknown Conference (pp. 3049-3056). CRC Press. doi:10.1201/b19094-402
Optimal risk regulatory policy in the development of a geological disposal facility
Nieto-Cerezo, O., Patelli, E., & Beer, M. (2015). Optimal risk regulatory policy in the development of a geological disposal facility. In Unknown Conference (pp. 2781-2788). CRC Press. doi:10.1201/b19094-364
Reliability assessments and remaining life of pipelines subject to combined loadings using imprecise probabilities
Opeyemi, D., Patelli, E., Beer, M., & Timashev, S. (2015). Reliability assessments and remaining life of pipelines subject to combined loadings using imprecise probabilities. In Unknown Conference (pp. 2789-2796). CRC Press. doi:10.1201/b19094-365
Robust design of inspection schedules by means of probability boxes for structural systems prone to damage accumulation
de Angelis, M., Patelli, E., & Beer, M. (2015). Robust design of inspection schedules by means of probability boxes for structural systems prone to damage accumulation. In Unknown Conference (pp. 2733-2741). CRC Press. doi:10.1201/b19094-358
Survival signature-based sensitivity analysis of systems with epistemic uncertainties
Feng, G., Patelli, E., & Beer, M. (2015). Survival signature-based sensitivity analysis of systems with epistemic uncertainties. In Unknown Conference (pp. 1547-1552). CRC Press. doi:10.1201/b19094-202
A nonlinear model of failure function for reliability analysis of RC frame columns with tension failure
Jiang, Y., Sun, G., He, Y., Beer, M., & Zhang, J. (2015). A nonlinear model of failure function for reliability analysis of RC frame columns with tension failure. ENGINEERING STRUCTURES, 98, 74-80. doi:10.1016/j.engstruct.2015.04.030
Special Issue: Computational Stochastic Dynamics Prologue
Beer, M., Kougioumtzoglou, I. A., & Naess, A. (2014). Special Issue: Computational Stochastic Dynamics Prologue. PROBABILISTIC ENGINEERING MECHANICS, 38, 102. doi:10.1016/j.probengmech.2014.11.004
Analysis of a major-accident dataset by Association Rule Mining to minimise unsafe interfaces
Doell, C., Held, P., Moura, R., Kruse, R., & Beer, M. (n.d.). Analysis of a major-accident dataset by Association Rule Mining to minimise unsafe interfaces. In The 13th International Probabilistic Workshop (IPW2015). Liverpool, UK.
Long-term performance assessment and design of offshore structures
Zhang, Y., Beer, M., & Quek, S. T. (2015). Long-term performance assessment and design of offshore structures. COMPUTERS & STRUCTURES, 154, 101-115. doi:10.1016/j.compstruc.2015.02.029
A COMPUTATIONAL TOOL FOR BAYESIAN NETWORKS ENHANCED WITH RELIABILITY METHODS
Tolo, S., Patelli, E., Beer, M., & Kang, Z. (2015). A COMPUTATIONAL TOOL FOR BAYESIAN NETWORKS ENHANCED WITH RELIABILITY METHODS. In Proceedings of the 1st International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2015) (pp. 908-923). Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece. doi:10.7712/120215.4316.546
A Clustering Approach to a Major-Accident Data Set: Analysis of Key Interactions to Minimise Human Errors
Moura, R., Beer, M., Doell, C., & Kruse, R. (2015). A Clustering Approach to a Major-Accident Data Set: Analysis of Key Interactions to Minimise Human Errors. In 2015 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (IEEE SSCI) (pp. 1838-1843). doi:10.1109/SSCI.2015.256
Advanced Line Sampling for efficient robust reliability analysis
de Angelis, M., Patelli, E., & Beer, M. (2015). Advanced Line Sampling for efficient robust reliability analysis. STRUCTURAL SAFETY, 52, 170-182. doi:10.1016/j.strusafe.2014.10.002
An artificial neural network approach for stochastic process power spectrum estimation subject to missing data
Comerford, L., Kougioumtzoglou, I. A., & Beer, M. (2015). An artificial neural network approach for stochastic process power spectrum estimation subject to missing data. STRUCTURAL SAFETY, 52, 150-160. doi:10.1016/j.strusafe.2014.10.001
Communicating risk in major incidents: The public's perception
Swan, L., Waring, S., Alison, L., & Beer, M. (2015). Communicating risk in major incidents: The public's perception. In 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015.
Comparative studies on assessment of corrosion rates in pipelines as semi-probabilistic and fully stochastic values
Opeyemi, D. A., Patelli, E., Beer, M., & Timashev, S. A. (2015). Comparative studies on assessment of corrosion rates in pipelines as semi-probabilistic and fully stochastic values. In 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015.
Editorial: Engineering analysis with vague and imprecise information
Beer, M., & Patelli, E. (2015). Editorial: Engineering analysis with vague and imprecise information. STRUCTURAL SAFETY, 52, 143. doi:10.1016/j.strusafe.2014.11.001
Enhanced Bayesian Networks approach to risk assessment of spent fuel ponds
Tolo, S., Patelli, E., Beer, M., & Broggi, M. (2015). Enhanced Bayesian Networks approach to risk assessment of spent fuel ponds. In 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015.
Learning from accidents: Analysis and representation of human errors in multi-attribute events
Moura, R., Beer, M., Lewis, J., & Patelli, E. (2015). Learning from accidents: Analysis and representation of human errors in multi-attribute events. In 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015.
Limit State Imprecise Interval Analysis in Geotechnical Engineering
Marques, S. H., Beer, M., Gomes, A. T., & Henriques, A. A. (2015). Limit State Imprecise Interval Analysis in Geotechnical Engineering. In GEOTECHNICAL SAFETY AND RISK V (pp. 383-388). doi:10.3233/978-1-61499-580-7-383
Limit State Imprecise Probabilistic Analysis in Geotechnical Engineering
Marques, S. H., Beer, M., Gomes, A. T., & Henriques, A. A. (2015). Limit State Imprecise Probabilistic Analysis in Geotechnical Engineering. In GEOTECHNICAL SAFETY AND RISK V (pp. 269-274). doi:10.3233/978-1-61499-580-7-269
Nonlinear stochastic dynamic analysis for performance based multi-objective optimum design considering life cycle seismic loss estimation
Mitseas, I. P., Kougioumtzoglou, I. A., & Beer, M. (2015). Nonlinear stochastic dynamic analysis for performance based multi-objective optimum design considering life cycle seismic loss estimation. In 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015.
Reliability analysis of systems based on survival signature
Feng, G., Patelli, E., & Beer, M. (2015). Reliability analysis of systems based on survival signature. In 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015.
Structural system response and reliability analysis under incomplete earthquake records
Comerford, L., Jensen, H., Beer, M., Mayorga, C., Kougioumtzoglou, I., & Kusanovic, D. (2015). Structural system response and reliability analysis under incomplete earthquake records. In 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015.
Uncertainty management of safety-critical systems: A solution to the back-propagation problem
De Angelis, M., Patelli, E., & Beer, M. (2015). Uncertainty management of safety-critical systems: A solution to the back-propagation problem. In 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015.
2014
Human error analysis: Review of past accidents and implications for improving robustness of system design
Human error analysis: Review of past accidents and implications for improving robustness of system design (2014). In Safety and Reliability: Methodology and Applications (pp. 1073-1082). CRC Press. doi:10.1201/b17399-150
Human error analysis: Review of past accidents and implications for improving robustness of system design
Moura, R., Beer, M., Patelli, E., Lewis, J., & Knoll, F. (2015). Human error analysis: Review of past accidents and implications for improving robustness of system design. In SAFETY AND RELIABILITY: METHODOLOGY AND APPLICATIONS (pp. 1037-1046). Retrieved from https://www.webofscience.com/
Mechanism design for risk allocation and benefit sharing in the development of a Geological Disposal Facility for nuclear radioactive waste
Nieto-Cerezo, O., Patelli, E., Wenzelburger, J., & Beer, M. (2015). Mechanism design for risk allocation and benefit sharing in the development of a Geological Disposal Facility for nuclear radioactive waste. In SAFETY AND RELIABILITY: METHODOLOGY AND APPLICATIONS (pp. 481-486). Retrieved from https://www.webofscience.com/
Mechanism design for risk allocation and benefit sharing in the development of a Geological Disposal Facility for nuclear radioactive waste
Mechanism design for risk allocation and benefit sharing in the development of a Geological Disposal Facility for nuclear radioactive waste (2014). In Safety and Reliability: Methodology and Applications (pp. 517-522). CRC Press. doi:10.1201/b17399-73
Approximation Concepts for Fuzzy Structural Analysis
Valdebenito, M. A., Jensen, H. A., Beer, M., & Pérez, C. A. (2014). Approximation Concepts for Fuzzy Structural Analysis. In Vulnerability, Uncertainty, and Risk (pp. 135-144). American Society of Civil Engineers. doi:10.1061/9780784413609.014
Bayesian Network Approach for Risk Assessment of a Spent Nuclear Fuel Pond
Tolo, S., Patelli, E., & Beer, M. (2014). Bayesian Network Approach for Risk Assessment of a Spent Nuclear Fuel Pond. In Unknown Book (pp. 598-607). American Society of Civil Engineers. doi:10.1061/9780784413609.061
Line Sampling for Assessing Structural Reliability with Imprecise Failure Probabilities
de Angelis, M., Patelli, E., & Beer, M. (2014). Line Sampling for Assessing Structural Reliability with Imprecise Failure Probabilities. In Unknown Book (pp. 915-924). American Society of Civil Engineers. doi:10.1061/9780784413609.093
OpenCossan: An Efficient Open Tool for Dealing with Epistemic and Aleatory Uncertainties
Patelli, E., Broggi, M., Angelis, M. D., & Beer, M. (2014). OpenCossan: An Efficient Open Tool for Dealing with Epistemic and Aleatory Uncertainties. In Unknown Book (pp. 2564-2573). American Society of Civil Engineers. doi:10.1061/9780784413609.258
Robust Design Optimization of Structural Systems Under Evolutionary Stochastic Seismic Excitation
Mitseas, I. P., Kougioumtzoglou, I. A., Beer, M., Patelli, E., & Mottershead, J. E. (2014). Robust Design Optimization of Structural Systems Under Evolutionary Stochastic Seismic Excitation. In Unknown Book (pp. 215-224). American Society of Civil Engineers. doi:10.1061/9780784413609.022
Towards Efficient Ways of Estimating Failure Probability of Mechanical Structures Under Interval Uncertainty
Beer, M., de Angelis, M., & Kreinovich, V. (2014). Towards Efficient Ways of Estimating Failure Probability of Mechanical Structures Under Interval Uncertainty. In Vulnerability, Uncertainty, and Risk (pp. 320-329). American Society of Civil Engineers. doi:10.1061/9780784413609.033
Uncertainty Quantification in Power Spectrum Estimation of Stochastic Processes Subject to Missing Data
Comerford, L., Kougioumtzoglou, I. A., & Beer, M. (2014). Uncertainty Quantification in Power Spectrum Estimation of Stochastic Processes Subject to Missing Data. In Vulnerability, Uncertainty, and Risk (pp. 370-377). American Society of Civil Engineers. doi:10.1061/9780784413609.038
Vulnerability, Uncertainty, and Risk
Vulnerability, Uncertainty, and Risk (2014). In Second International Conference on Vulnerability and Risk Analysis and Management (ICVRAM) and the Sixth International Symposium on Uncertainty, Modeling, and Analysis (ISUMA). American Society of Civil Engineers. doi:10.1061/9780784413609
Compressive sensing based power spectrum estimation from incomplete records by utilizing an adaptive basis
Comerford, L. A., Beer, M., & Kougioumtzoglou, I. A. (2014). Compressive sensing based power spectrum estimation from incomplete records by utilizing an adaptive basis. In 2014 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE FOR ENGINEERING SOLUTIONS (CIES) (pp. 117-124). Retrieved from https://www.webofscience.com/
An artificial neural network based approach for power spectrum estimation subject to limited and/or missing data
Comerford, L., Kougioumtzoglou, I., & Beer, M. (2014). An artificial neural network based approach for power spectrum estimation subject to limited and/or missing data. In Unknown Conference (pp. 1083-1090). CRC Press. doi:10.1201/b16387-159
Long-term reliability assessment of offshore structures in complex environment
Zhang, Y., Quek, S., & Beer, M. (2014). Long-term reliability assessment of offshore structures in complex environment. In Unknown Conference (pp. 2209-2216). CRC Press. doi:10.1201/b16387-321
A compressive sensing based approach for estimating stochastic process power spectra subject to missing data
Comerford, L., Kougioumtzoglou, I. A., & Beer, M. (2014). A compressive sensing based approach for estimating stochastic process power spectra subject to missing data. In EURODYN 2014: IX INTERNATIONAL CONFERENCE ON STRUCTURAL DYNAMICS (pp. 2995-2999). Retrieved from https://www.webofscience.com/
A pilot-study investigating the assessment and allocation of risks in public-private partnership transportation projects in Vietnam
Nhat, M. N., Lewis, J., Beer, M., & Boussabaine, A. (2014). A pilot-study investigating the assessment and allocation of risks in public-private partnership transportation projects in Vietnam. In Proceedings 30th Annual Association of Researchers in Construction Management Conference, ARCOM 2014 (pp. 1419-1428).
An open approach to educational resource development, with a specific example from structural engineering
Comerford, L., DeAngelis, M., Mannis, A., Beer, M., & Kougioumtzoglou, I. (2014). An open approach to educational resource development, with a specific example from structural engineering. In SEFI Annual Conference 2014.
Modified linear estimation method for generating multi-dimensional multi-variate Gaussian field in modelling material properties
Liu, Y., Lee, F. -H., Quek, S. -T., & Beer, M. (2014). Modified linear estimation method for generating multi-dimensional multi-variate Gaussian field in modelling material properties. PROBABILISTIC ENGINEERING MECHANICS, 38, 42-53. doi:10.1016/j.probengmech.2014.09.001
Optimal design of nonlinear structures under evolutionary stochastic earthquake excitations
Mitseas, I. P., Kougioumtzoglou, I. A., & Beer, M. (2014). Optimal design of nonlinear structures under evolutionary stochastic earthquake excitations. In OPT-i 2014 - 1st International Conference on Engineering and Applied Sciences Optimization, Proceedings (pp. 2213-2233).
Preface
Beer, M., Au, S. K., & Hall, J. W. (2014). Preface. doi:10.1061/9780784413609.291
2013
An efficient strategy for computing interval expectations of risk
De Angelis, M., Patelli, E., & Beer, M. (2013). An efficient strategy for computing interval expectations of risk. In Safety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures - Proceedings of the 11th International Conference on Structural Safety and Reliability, ICOSSAR 2013 (pp. 2225-2232).
Comparing intervals and moments for the quantification of coarse information
Beer, M., & Kreinovich, V. (2013). Comparing intervals and moments for the quantification of coarse information. In Safety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures - Proceedings of the 11th International Conference on Structural Safety and Reliability, ICOSSAR 2013 (pp. 375-381).
An artificial neural network based approach for power spectrum estimation and simulation of stochastic processes subject to missing data
Comerford, L. A., Kougioumtzoglou, I. A., & Beer, M. (2013). An artificial neural network based approach for power spectrum estimation and simulation of stochastic processes subject to missing data. In PROCEEDINGS OF THE 2013 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE FOR ENGINEERING SOLUTIONS (CIES) (pp. 118-124). Retrieved from https://www.webofscience.com/
Bayesian approach for inconsistent information
Stein, M., Beer, M., & Kreinovich, V. (2013). Bayesian approach for inconsistent information. INFORMATION SCIENCES, 245, 96-111. doi:10.1016/j.ins.2013.02.024
Interval or moments: which carry more information?
Beer, M., & Kreinovich, V. (2013). Interval or moments: which carry more information?. SOFT COMPUTING, 17(8), 1319-1327. doi:10.1007/s00500-013-1002-1
Verified stochastic methods Markov set-chains and dependency modeling of mean and standard deviation
Rebner, G., Beer, M., Auer, E., & Stein, M. (2013). Verified stochastic methods Markov set-chains and dependency modeling of mean and standard deviation. SOFT COMPUTING, 17(8), 1415-1423. doi:10.1007/s00500-013-1009-7
Imprecise probabilities in engineering analyses
Beer, M., Ferson, S., & Kreinovich, V. (2013). Imprecise probabilities in engineering analyses. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 37(1-2), 4-29. doi:10.1016/j.ymssp.2013.01.024
Special issue of Mechanical Systems and Signal Processing "Imprecise probabilities-What can they add to engineering analyses?" Foreword
Beer, M., & Ferson, S. (2013). Special issue of Mechanical Systems and Signal Processing "Imprecise probabilities-What can they add to engineering analyses?" Foreword. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 37(1-2), 1-3. doi:10.1016/j.ymssp.2013.03.018
Structural reliability analysis on the basis of small samples: An interval quasi-Monte Carlo method
Zhang, H., Dai, H., Beer, M., & Wang, W. (2013). Structural reliability analysis on the basis of small samples: An interval quasi-Monte Carlo method. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 37(1-2), 137-151. doi:10.1016/j.ymssp.2012.03.001
Reliability analysis with scarce information: Comparing alternative approaches in a geotechnical engineering context
Beer, M., Zhang, Y., Quek, S. T., & Phoon, K. K. (2013). Reliability analysis with scarce information: Comparing alternative approaches in a geotechnical engineering context. STRUCTURAL SAFETY, 41, 1-10. doi:10.1016/j.strusafe.2012.10.003
Computational Intelligence in Structural Analysis and Design
Beer, M. (2013). Computational Intelligence in Structural Analysis and Design. In PROCEEDINGS OF THE 2013 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE FOR ENGINEERING SOLUTIONS (CIES) (pp. IV-V). Retrieved from https://www.webofscience.com/
Special issue "Uncertainty quantification in structural analysis and design: To commemorate Professor Gerhart I. Schueller for his life-time contribution in the area of computational stochastic mechanics"
Jensen, H. A., & Beer, M. (2013). Special issue "Uncertainty quantification in structural analysis and design: To commemorate Professor Gerhart I. Schueller for his life-time contribution in the area of computational stochastic mechanics". COMPUTERS & STRUCTURES, 126, 1-2. doi:10.1016/j.compstruc.2013.04.002
2012
Interval Analysis for System Identification of Linear MDOF Structures in the Presence of Modeling Errors
Zhang, M. Q., Beer, M., & Koh, C. G. (2012). Interval Analysis for System Identification of Linear MDOF Structures in the Presence of Modeling Errors. JOURNAL OF ENGINEERING MECHANICS, 138(11), 1326-1338. doi:10.1061/(ASCE)EM.1943-7889.0000433
Fuzzy Probability Theory
Beer, M. (2012). Fuzzy Probability Theory. In Computational Complexity (pp. 1240-1252). Springer New York. doi:10.1007/978-1-4614-1800-9_76
CUDA Accelerated Fault Tree Analysis with C-XSC
Rebner, G., & Beer, M. (2012). CUDA Accelerated Fault Tree Analysis with C-XSC. In Unknown Conference (pp. 539-549). Springer Berlin Heidelberg. doi:10.1007/978-3-642-33362-0_41
Life-cycle financial modelling of long term infrastructure projects "PPP-BOT projects" under uncertainty and risk
Attarzadeh, M., Chua, D. K. H., Zhu, L., & Beer, M. (2012). Life-cycle financial modelling of long term infrastructure projects "PPP-BOT projects" under uncertainty and risk. In Life-Cycle and Sustainability of Civil Infrastructure Systems - Proceedings of the 3rd International Symposium on Life-Cycle Civil Engineering, IALCCE 2012 (pp. 991-996).
Dealing with scarce information on engineering systems
de Angelis, M., Patelli, E., & Beer, M. (2012). Dealing with scarce information on engineering systems. In 6th EUROPEAN CONGRESS ON COMPUTATIONAL METHODS IN APPLIED SCIENCES AND ENGINEERING (ECCOMAS 2012) (pp. -).
Dealing with scarce information on engineering systems
Patelli, E. (2012). Dealing with scarce information on engineering systems. N/A, N/A, N/A.
Proceedings of the 5th Asian-Pacific Symposium on Structural Reliability and its Applications (APSSRA2012): Sustainable Civil Infrastructures - Hazards, Risk, Uncertainty
Phoon, K. K., Beer, M., Quek, S. T., & Pang, S. D. (Eds.) (2012). Proceedings of the 5th Asian-Pacific Symposium on Structural Reliability and its Applications (APSSRA2012): Sustainable Civil Infrastructures - Hazards, Risk, Uncertainty. In 5th Asian-Pacific Symposium on Structural Reliability and its Applications (APSSRA2012) (pp. 1-780). Singapore: Research Publishing Singapore.
Safety and robustness assessment of structures with generalized data uncertainty
Beer, M., Graf, W., & Kaliske, M. (2012). Safety and robustness assessment of structures with generalized data uncertainty. GACM Report, 7, 23-28.
Safety and robustness assessment of structures with generalized data uncertainty
Beer, M., Graf, W., & Kaliske, M. (2012). Safety and robustness assessment of structures with generalized data uncertainty. GACM Report, 7, 23-28.
2011
Bayesian quantification of inconsistent information
Stein, M., & Beer, M. (2011). Bayesian quantification of inconsistent information. In Applications of Statistics and Probability in Civil Engineering -Proceedings of the 11th International Conference on Applications of Statistics and Probability in Civil Engineering (pp. 463-470).
Structural Reliability Assessment with Fuzzy Probabilities
Beer, M., Zhang, M., Tong, Q. S., & Ferson, S. (2011). Structural Reliability Assessment with Fuzzy Probabilities. In ISIPTA '11 - PROCEEDINGS OF THE SEVENTH INTERNATIONAL SYMPOSIUM ON IMPRECISE PROBABILITY: THEORIES AND APPLICATIONS (pp. 61-70). Retrieved from https://www.webofscience.com/
Uncertainty analysis in geotechnical engineering-a comparative study of selected approaches
Beer, M., Zhang, Y., Quek, S. T., & Phoon, K. K. (2011). Uncertainty analysis in geotechnical engineering-a comparative study of selected approaches. In APPLICATIONS OF STATISTICS AND PROBABILITY IN CIVIL ENGINEERING (pp. 2768-2775). Retrieved from https://www.webofscience.com/
Introduction
Kruse, R., Beer, M., & Zadeh, L. A. (2011). Introduction. INTEGRATED COMPUTER-AIDED ENGINEERING, 18(3), 201-202. doi:10.3233/ICA-2011-0377
Fuzzy Probability in Engineering Analyses
Beer, M., & Ferson, S. (2011). Fuzzy Probability in Engineering Analyses. In Vulnerability, Uncertainty, and Risk (pp. 53-61). American Society of Civil Engineers. doi:10.1061/41170(400)7
Risk Management of Asalouye Desalination Project
Attarzadeh, M., Chua, D. K. H., & Beer, M. (2011). Risk Management of Asalouye Desalination Project. In Vulnerability, Uncertainty, and Risk (pp. 805-812). American Society of Civil Engineers. doi:10.1061/41170(400)98
Risk Management of Long Term Infrastructure Projects "PPP-BOT Projects" by Using Uncertainty, Probabilistic and Stochastic Methods, and Models
Attarzadeh, M., Chua, D. K. H., & Beer, M. (2011). Risk Management of Long Term Infrastructure Projects "PPP-BOT Projects" by Using Uncertainty, Probabilistic and Stochastic Methods, and Models. In Vulnerability, Uncertainty, and Risk (pp. 360-367). American Society of Civil Engineers. doi:10.1061/41170(400)44
A new approach for robustness assessment of fixed offshore structures under imprecise marine corrosion
Zhang, M. Q., Beer, M., Koh, C. G., Hirokane, M., & IEEE. (2014). A new approach for robustness assessment of fixed offshore structures under imprecise marine corrosion. In 2014 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2014) (pp. 2919-2926). Retrieved from http://gateway.webofknowledge.com/
BAYESIAN UPDATE WITH FUZZY INFORMATION
Beer, M., & Stein, M. (2012). BAYESIAN UPDATE WITH FUZZY INFORMATION. In PROCEEDINGS OF THE ASME INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION, 2011, VOL 9 (pp. 821-829). Retrieved from https://www.webofscience.com/
Identification of Representative Paths in Noisy Processes
Liebscher, M., Reuter, U., Beer, M., & Mehmood, Z. (2011). Identification of Representative Paths in Noisy Processes. In PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON STRUCTURAL DYNAMICS, EURODYN 2011 (pp. 2907-2912). Retrieved from https://www.webofscience.com/
Identification of Representative Paths in Noisy Processes
Liebscher, M., Reuter, U., Beer, M., Mehmood, Z., & IEEE. (2014). Identification of Representative Paths in Noisy Processes. In 2014 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2014) (pp. 2907-2912). Retrieved from http://gateway.webofknowledge.com/
Statics
Ang, K. K., Beer, M., & Wang, C. M. (2011). Statics. Singapore: McGraw-Hill.
2010
A Summary on Fuzzy Probability Theory
Beer, M. (2010). A Summary on Fuzzy Probability Theory. In 2010 IEEE International Conference on Granular Computing (pp. 5-6). IEEE. doi:10.1109/grc.2010.78
Comparison of uncertainty models in reliability analysis of offshore structures under marine corrosion
Zhang, M. Q., Beer, M., Quek, S. T., & Choo, Y. S. (2010). Comparison of uncertainty models in reliability analysis of offshore structures under marine corrosion. STRUCTURAL SAFETY, 32(6), 425-432. doi:10.1016/j.strusafe.2010.04.003
Special Issue "Modeling and Analysis of Rare and Imprecise Information" Foreword
Beer, M., Kwang, P. K., & Tong, Q. S. (2010). Special Issue "Modeling and Analysis of Rare and Imprecise Information" Foreword. STRUCTURAL SAFETY, 32(6), 357. doi:10.1016/j.strusafe.2010.09.004
Discrete-continuous variable structural optimization of systems under stochastic loading
Jensen, H. A., & Beer, M. (2010). Discrete-continuous variable structural optimization of systems under stochastic loading. STRUCTURAL SAFETY, 32(5), 293-304. doi:10.1016/j.strusafe.2010.03.007
Detection of branching points in noisy processes
Beer, M., & Liebscher, M. (2010). Detection of branching points in noisy processes. COMPUTATIONAL MECHANICS, 45(4), 363-374. doi:10.1007/s00466-009-0458-4
4th International Workshop on Reliable Engineering Computing (REC2010), Robust Design - Coping with Hazards, Risk and Uncertainty
Beer, M., Muhanna, R. L., & Mullen, R. L. (Eds.) (2010). 4th International Workshop on Reliable Engineering Computing (REC2010), Robust Design - Coping with Hazards, Risk and Uncertainty. In International Workshop on Reliable Engineering Computing (REC2010) (pp. 808). Singapore: Research Publishing.
Detection of branching points in noisy processes
Beer, M., & Liebscher, M. (2010). Detection of branching points in noisy processes. Computational Mechanics, 45(4), 363-374. doi:10.1007/s00466-009-0458-4
2009
Uncertainty and robustness in structural design
Beer, M., & Liebscher, M. (2009). Uncertainty and robustness in structural design. In Proceedings of the 12th International Conference on Civil, Structural and Environmental Engineering Computing.
Lifetime prediction using accelerated test data and neural networks
Freitag, S., Beer, M., Graf, W., & Kaliske, M. (2009). Lifetime prediction using accelerated test data and neural networks. COMPUTERS & STRUCTURES, 87(19-20), 1187-1194. doi:10.1016/j.compstruc.2008.12.007
A neural network approach for simulating stationary stochastic processes
Beer, M., & Spanos, P. D. (2009). A neural network approach for simulating stationary stochastic processes. STRUCTURAL ENGINEERING AND MECHANICS, 32(1), 71-94. doi:10.12989/sem.2009.32.1.071
Engineering quantification of inconsistent information
Beer, M. (2009). Engineering quantification of inconsistent information. International Journal of Reliability and Safety, 3(1/2/3), 174. doi:10.1504/ijrs.2009.026840
Fuzzy Probability Theory
Beer, M. (2009). Fuzzy Probability Theory. In R. Meyers (Ed.), Encyclopedia of Complexity and Systems Science (Vol. 6, pp. 4047-4059). New York: Springer.
Non-traditional Prospects in the Simultaneous Treatment of Uncertainty and Imprecision
Beer, M. (2009). Non-traditional Prospects in the Simultaneous Treatment of Uncertainty and Imprecision. In B. H. V. Topping, & Y. Tsompanakis (Eds.), Soft Computing in Civil and Structural Engineering (Vol. 23, pp. 247-266). Stirlingshire: Saxe-Coburg Publications.
2008
Designing robust structures - A nonlinear simulation based approach
Beer, M., & Liebscher, M. (2008). Designing robust structures - A nonlinear simulation based approach. COMPUTERS & STRUCTURES, 86(10), 1102-1122. doi:10.1016/j.compstruc.2007.05.037
Engineering computation under uncertainty -: Capabilities of non-traditional models
Moeller, B., & Beer, M. (2008). Engineering computation under uncertainty -: Capabilities of non-traditional models. COMPUTERS & STRUCTURES, 86(10), 1024-1041. doi:10.1016/j.compstruc.2007.05.041
Special issue -: Uncertainty in structural analysis -: Their effect on robustness, sensitivity and design
Moeler, B., & Beer, M. (2008). Special issue -: Uncertainty in structural analysis -: Their effect on robustness, sensitivity and design. COMPUTERS & STRUCTURES, 86(10), 1023. doi:10.1016/j.compstruc.2007.10.001
2007
Fuzzy structural analysis in view of numerical efficiency
Liebscher, M., Beer, M., Moeller, B., & Graf, W. (2007). Fuzzy structural analysis in view of numerical efficiency. In APPLICATIONS OF STATISICS AND PROBABILITY IN CIVIL ENGINEERING (pp. 249-250). Retrieved from https://www.webofscience.com/
Karhunen-loeve expansion of stochastic processes with a modified exponential covariance kernel
Spanos, P. D., Beer, M., & Red-Horse, J. (2007). Karhunen-loeve expansion of stochastic processes with a modified exponential covariance kernel. JOURNAL OF ENGINEERING MECHANICS, 133(7), 773-779. doi:10.1061/(ASCE)0733-9399(2007)133:7(773)
Lifetime prediction with neural networks
Freitag, S., Beer, M., Graf, W., & Kaliske, M. (2007). Lifetime prediction with neural networks. In Civil-Comp Proceedings Vol. 87.
Model-free sampling
Beer, M. (2007). Model-free sampling. STRUCTURAL SAFETY, 29(1), 49-65. doi:10.1016/j.strusafe.2006.01.001
2006
Time-dependent reliability of textile-strengthened RC structures under consideration of fuzzy randomness
Möller, B., Beer, M., Graf, W., & Sickert, J. U. (2006). Time-dependent reliability of textile-strengthened RC structures under consideration of fuzzy randomness. COMPUTERS & STRUCTURES, 84(8-9), 585-603. doi:10.1016/j.compstruc.2005.10.006
Zum Einfluß der Datenbasis auf Tragwerkssicherheit und Versagensrisiko
Graf, W., Möller, B., & Beer, M. (2006). Zum Einfluß der Datenbasis auf Tragwerkssicherheit und Versagensrisiko. Wissenschaftliche Zeitschrift der Technischen Universität Dresden, 55(3-4), 49-53.
2004
Uncertain structural design based on nonlinear fuzzy analysis
Beer, M. (2004). Uncertain structural design based on nonlinear fuzzy analysis. ZEITSCHRIFT FUR ANGEWANDTE MATHEMATIK UND MECHANIK, 84(10-11), 740-753. doi:10.1002/zamm.200410154
Discussion on "Structural reliability analysis through fuzzy number approach, with application to stability"
Möller, B., Graf, W., & Beer, M. (2004). Discussion on "Structural reliability analysis through fuzzy number approach, with application to stability". COMPUTERS & STRUCTURES, 82(2-3), 325-327. doi:10.1016/S0045-7949(03)00336-5
Fuzzy Randomness
Möller, B., & Beer, M. (2004). Fuzzy Randomness. Springer Berlin Heidelberg. doi:10.1007/978-3-662-07358-2
2003
Safety assessment of structures in view of fuzzy randomness
Möller, B., Graf, W., & Beer, M. (2003). Safety assessment of structures in view of fuzzy randomness. COMPUTERS & STRUCTURES, 81(15), 1567-1582. doi:10.1016/S0045-7949(03)00147-0
Fuzzy stochastic finite element method
Möller, B., Graf, W., Beer, M., & Sickert, J. U. (2003). Fuzzy stochastic finite element method. In Unknown Book (pp. 2074-2077). Retrieved from https://www.webofscience.com/
Fuzzy probabilistic structural analysis considering fuzzy random functions
Sickert, J. U., Beer, M., Graf, W., & Möller, B. (2003). Fuzzy probabilistic structural analysis considering fuzzy random functions. In APPLICATIONS OF STATISTICS AND PROBABILITY IN CIVIL ENGINEERING, VOLS 1 AND 2 (pp. 379-386). Retrieved from https://www.webofscience.com/
Processing uncertainty in structural analysis, design and safety assessment
Beer, M., Moller, B., & Liebscher, M. (2003). Processing uncertainty in structural analysis, design and safety assessment. In ISUMA 2003: FOURTH INTERNATIONAL SYMPOSIUM ON UNCERTAINTY MODELING AND ANALYSIS (pp. 34-39). doi:10.1109/ISUMA.2003.1236137
2001
Fuzzy finite element method and its application
Möller, B., Beer, M., Graf, W., & Sickert, J. U. (2001). Fuzzy finite element method and its application. In TRENDS IN COMPUTATIONAL STRUCTURAL MECHANICS (pp. 529-538). Retrieved from https://www.webofscience.com/
2000
Fuzzy structural analysis using α-level optimization
Möller, B., Graf, W., & Beer, M. (2000). Fuzzy structural analysis using α-level optimization. COMPUTATIONAL MECHANICS, 26(6), 547-565. doi:10.1007/s004660000204
RC-folded plate structures with textile reinforcement
Möller, B., Beer, M., Graf, W., & Hoffmann, A. (2000). RC-folded plate structures with textile reinforcement. In European Congress on Computational Methods in Applied Sciences and Engineering, ECCOMAS 2000.
Fuzzy-Tragwerksanalyse - Tragwerksanalyse mit unscharfen Parametern
Möller, B., Graf, W., & Beer, M. (2000). Fuzzy-Tragwerksanalyse - Tragwerksanalyse mit unscharfen Parametern. Bauingenieur, 75(11), 697-708.
Modellierung von Unschärfe im Ingenieurbau
Möller, B., Beer, M., Graf, W., Hoffmann, A., & Sickert, J. U. (2000). Modellierung von Unschärfe im Ingenieurbau. Bauinformatik Journal, 3, 21-25.
1999
Possibility Theory Based Safety Assessment
Moller, B., Beer, M., Graf, W., & Hoffmann, A. (1999). Possibility Theory Based Safety Assessment. Computer-Aided Civil and Infrastructure Engineering, 14(2), 81-91. doi:10.1111/0885-9507.00132
Ultimate limit loads of RC-folded plate structures with textile reinforcement
Möller, B., Graf, W., Hoffmann, A., & Beer, M. (1999). Ultimate limit loads of RC-folded plate structures with textile reinforcement. In COMPUTATIONAL METHODS AND EXPERIMENTAL MEASUREMENTS IX (pp. 453-462). Retrieved from https://www.webofscience.com/
1998
Safety assessment using fuzzy theory
Möller, B., & Beer, M. (1998). Safety assessment using fuzzy theory. In COMPUTING IN CIVIL ENGINEERING (pp. 756-759). Retrieved from https://www.webofscience.com/
1997
Uncertainty analysis in civil engineering using fuzzy modeling
Moeller, B., & Beer, M. (1997). Uncertainty analysis in civil engineering using fuzzy modeling. In PROCEEDINGS OF THE SEVENTH INTERNATIONAL CONFERENCE ON COMPUTING IN CIVIL AND BUILDING ENGINEERING, VOLS 1-4 (pp. 1425-1430). Retrieved from https://www.webofscience.com/
1995
New varioram intake system of the Porsche 911 engine
Beer, M., Kling, J., Pelters, S., Rutschmann, E., & Scheiba, J. (1995). New varioram intake system of the Porsche 911 engine. MTZ Motortechnische Zeitschrift, 56(9).