Publikationen von Prof. Dr.-Ing. Michael Beer

Salomon, J., Broggi, M., & Beer, M. (2024): Resilience-based decision criteria for optimal regeneration.,  J. R. Seume, B. Denkena, & P. Gilge, Regeneration of Complex Capital Goods. Springer International Publishing.
ISBN: 978-3-031-51394-7

Beer, M. (2023): Fuzzy Probability Theory,  Lin, Tsau-Young; Liau, Churn-Jung; Kacprzyk, Janusz (eds.), Granular, Fuzzy, and Soft Computing, Springer US, New York, NY. (Invited Chapter), pages 51–75.
DOI: 10.1007/978-1-0716-2628-3_237

Jerez, D.J.; Jensen, H.A.; Beer, M. (2023): A Two-Phase Sampling Approach for Reliability-Based Optimization in Structural Engineering,  Liu, Y.; Wang, D.; Mi, J.H; Li, H. (eds): Advances in Reliability and Maintainability Methods and Engineering Applications; Essays in Honor of Professor Hong-Zhong Huang on his 60th Birthday, Springer Series in Reliability Engineering (RELIABILITY), Springer, Cham, pages 21–48.
DOI: 10.1007/978-3-031-28859-3

Wei, P.F.; Beer, M. (2023): Regression Models for Machine Learning,  Rabczuk, T.; Bathe, K.-J. (eds), Machine Learning in Modeling and Simulation, Methods and Applications; Springer book series on Computational Methods in Engineering & the Sciences, Springer, Cham, Chapter 9, pages 341–371.
ISSN: 2662-4877

Bi, S.F.; Beer, M. (2022): Overview of Stochastic Model Updating in Aerospace Application Under Uncertainty Treatment,  In: Aslett, L.J.M.; Coolen, F.P.A.; De Bock, J. (eds), Uncertainty in Engineering; Introduction to Methods and Applications, SpringerBriefs in Statistics book series, Springer, Cham, Chapter 8, pages 115–129.
DOI: 10.1007/978-3-030-83640-5

Salomon J.; Behrensdorf J.; Beer M. (2022): Resilienz baulicher Infrastruktur - sicher und wirtschaftlicher durch Dick und Dünn,  26. Dresdner Baustatik - Seminar – „Realität-Modellierung-Tragwerksplanung“, Institut für Statik und Dynamik der Tragwerke, TU Dresden
ISSN: 1615-9705

Beer, M. (2021): Fuzzy Probability Theory,  In: Meyers, R. (ed.), Encyclopedia of Complexity and Systems Science,Springer, Berlin, Heidelberg. (Invited Chapter), pages 1–25.
DOI: https://doi.org/10.1007/978-3-642-27737-5_237-2

Beer, M.; Ayyub, B.M.; Phoon, K.K. (2018): Research Recommendation “Resilience Engineering at System Scale”,  In: Beer, M.; Huang, H.W.; Ayyub, B.M.; Zhang, D.M.; Phillips, B.M. (eds.), Resilience Engineering for Urban Tunnels, American Society of Civil Engineers, Infrastructure Resilience Publications (IRP) IRP 2, 99-102.
DOI: 10.1061/9780784415139.ch09

Beer, M.; Gong, Z.T.; Neumann, I.; Sriboonchitta, S.; Kreinovich, V. (2018): What If We Do Not Know Correlations?,  In: Anh, L.H.; Dong, L.S.; Kreinovich, V.; Nguyen, N.T. (eds.), Econometrics for Financial Applications, Springer, Cham, Switzerland, pp 78-85.
DOI: 10.1007/978-3-319-73150-6_5
ISBN: 978-3-319-73149-0

Behrensdorf, J.; Broggi, M.; Beer, M. (2018): Efficient Reliability and Risk Analysis of Complex Interconnected Systems,  In: Beer, M.; Huang, H.W.; Ayyub, B.M.; Zhang, D.M.; Phillips, B.M. (eds.), Resilience Engineering for Urban Tunnels, American Society of Civil Engineers, Infrastructure Resilience Publications (IRP) IRP 2, 43–54.
DOI: 10.1061/9780784415139.ch04

Zuev, K.M.; Beer, M. (2018): Reliability of Critical Infrastructure Networks: Challenges,  In: Beer, M.; Huang, H.W.; Ayyub, B.M.; Zhang, D.M.; Phillips, B.M. (eds.), Resilience Engineering for Urban Tunnels, American Society of Civil Engineers, Infrastructure Resilience Publications (IRP) IRP 2, 71-82.
DOI: 10.1061/9780784415139.ch06

Hong, F.Q.; Wei, P.F.; Bi, S.F.; Beer, M. (2025): Efficient variational Bayesian model updating by Bayesian active learning,  Mechanical Systems and Signal Processing, in press

Mo, J.; Yan, W.J.; Yuen, K.V.; Beer, M. (2025): Efficient non-probabilistic parallel model updating based on analytical correlation propagation formula and derivative-aware deep neural network metamodel,  Computer Methods in Applied Mechanics and Engineering, in press

Song, J.W.; Liang, Z.H.; Wei, P.F.; Beer, M. (2025): Sampling-based Adaptive Bayesian Quadrature for Probabilistic Model Updating,  Computer Methods in Applied Mechanics and Engineering, 433, Part A, Article 117467

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, Article 111078
DOI: 10.1016/j.ymssp.2023.111078

Behrendt, M.; Dang, C.; Faes, M.G.R.; Valdebenito, M.A.; Beer, M. (2024): Structural reliability analysis using imprecise evolutionary power spectral density functions,  XII. International Conference on Structural Dynamics, Journal of Physics: Conference Series, 2647, 062003
DOI: 10.1088/1742-6596/2647/6/062003

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, Article 103592
DOI: 10.1016/j.probengmech.2024.103592

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, in press.

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, Article 111210
DOI: 10.1016/j.ymssp.2024.111210

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, Article 118210

Bittner, M.; Fritsch, L.; Hirzinger, B.; Broggi, M.; Beer, M. (2024): Efficient time-dependent reliability analysis for a railway bridge model,  XII. International Conference on Structural Dynamics, Journal of Physics: Conference Series 2647, Article 062002
DOI: 10.1088/1742-6596/2647/6/062002

Brandt, J.; Iversen, T.; Eckert, C.; Peterssen, F.; Bensmann, B.; Bensmann, A.; Beer, M.; Weyer, H.; Hanke-Rauschenbach, R. (2024): Cost and competitiveness of green hydrogen and the effects of the European Union regulatory framework,  Nature Energy, in press

Dang, C.; Beer, M. (2024): Semi-Bayesian active learning quadrature for estimating extremely low failure probabilities,  Reliability Engineering and System Safety, 246, Article 110052
DOI: 10.1016/j.ress.2024.110052

Dang, C.; Cicirello, A.; Valdebenito, M.A.; Faes, M.G.R.; Wei, P.F.; Beer, M. (2024): Structural reliability analysis with extremely small failure probabilities: A quasi-Bayesian active learning method,  Probabilistic Engineering Mechanics, 76, Article 103613
DOI: 10.1016/j.probengmech.2024.103613

Dang, C.; Faes, M.G.R.; Valdebenito, M.A.; Wei, P.F.; 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, Article 116828.
DOI: 10.1016/j.cma.2024.116828

Dang, C.; Valdebenito, M.A.; Wei, P.F.; Song, J.W.; Beer, M. (2024): Bayesian active learning line sampling with log-normal process for rare-event probability estimation,  Reliability Engineering and System Safety, 246, Article 110053
DOI: 10.1016/j.ress.2024.110053

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), Article 04024017
DOI: 10.1061/AJRUA6/RUENG-1169

Ding, C.; Wei, P.F.; Shi, Y.; Liu, J.X.; Broggi, M.; Beer, M. (2024): Sampling and active learning methods for network reliability estimation using K-terminal spanning tree,  Reliability Engineering & System Safety, 250, Article 110309
DOI: 10.1016/j.ress.2024.110309

Elias, S.; Beer, M. (2024): Vibration Control and Energy Harvesting of Offshore Wind Turbines installed with TMDI under Dynamical Loading,  Engineering Structures, 315, Article 118459.

Feng, D.C.; Ding, J.Y.; Xie, S.C.; Li, Y.; Akiyama, M.; Lu, Y.; Beer, M.; Li, J. (2024): Climate Change Impacts on the Risk Assessment of Concrete Civil Infrastructures: a State-of-the-Art Review,  ASCE Open: Multidisciplinary Journal of Civil Engineering, in press.

Grashorn, J.; Bittner, M.; Banse, M.; Chang, X.Y.; Beer, M.; Fau, A. (2024): Namazu: Low-cost tunable shaking table for vibration experiments under generic signals,  Experimental Techniques, in press.

Grashorn, J.; Broggi, M.; Ludovic, C.; Beer, M. (2024): Efficiency comparison of MCMC and Transport Map Bayesian posterior estimation for structural health monitoring,  Mechanical Systems and Signal Processing, 216, Article 111440
DOI: 10.1016/j.ymssp.2024.111440

Hong, F.Q.; Wei, P.F.; Beer, M. (2024): Parallelization of Adaptive Bayesian Cubature Using Multimodal Optimization Algorithms,  Engineering Computations, 41(2), 413–437

Hong, F.Q; Wei, P.F.; Fu, J.F.; Beer, M. (2024): A sequential sampling-based Bayesian numerical method for reliability-based design optimization,  Reliability Engineering and System Safety, 244, Article 109939
DOI: 10.1016/j.ress.2024.109939

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, Article 107445
DOI: 10.1016/j.enggeo.2024.107445

Hu, Z.; Dang, C.; Wang, L.; Beer, M. (2024): Parallel Bayesian probabilistic integration for structural reliability analysis with small failure probabilities,  Structural Safety, 106, Article 102409
DOI: 10.1016/j.strusafe.2023.102409

Huang, Z.F.; Beer, M. (2024): Probability distributions for dynamic and extreme responses of linear elastic structures under quasi-stationary harmonizable loads,  Probabilistic Engineering Mechanics, 75, Article 103590
DOI: 10.1016/j.probengmech.2024.103590

Jerez, D.; Fragkoulis, V.; Ni, P.H.; Mitseas, I.; Valdebenito, M.; Faes, M.; 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, Article 111043
DOI: 10.2139/ssrn.4586140

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 and System Safety, 242, Article 109771
DOI: 10.1016/j.ress.2023.109771

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,  XII. International Conference on Structural Dynamics, Journal of Physics: Conference Series 2647, Article 192001
DOI: 10.1088/1742-6596/2647/19/192001

Jiang, X.; Lu, Z.Z.; Beer, M. (2024): A novel directional simulation method for estimating failure possibility,  Aerospace Science and Technology, 155, Article 109627
DOI: 10.1016/j.ast.2024.109627

Jiang, Y.B.; Zhang, X.Y.; 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, Article 109972
DOI: 10.1016/j.ress.2024.109972

Lai, J.; Wang, K.; Shi, Y.; Xu, J.M.; Chen, J.Y.; Wang, P.; Beer, M. (2024): Reliability assessment of freight wagon passing through railway turnouts using adaptive Kriging surrogate model,  International Journal of Rail Transportation,
DOI: 10.1080/23248378.2024.2304000

Li, J.; Shao, F.S.; He, Z.W.; Ma, J.; Qiu, Y.Y.; Beer, M. (2024): Multiaxial fatigue life prediction using an improved SWT model,  Fatigue & Fracture of Engineering Materials & Structures, 47, 1944–1961
DOI: 10.1111/ffe.14285

Li, S.; Ji, J.C.; Xu, Y,D.; Feng, K.; Zhang, K.; Feng, J.C.; Beer, M.; Ni, Q.; Wang, Y.L. (2024): Dconformer: A Denoising Convolutional Transformer with Joint Learning Strategy for Intelligent Diagnosis of Bearing Faults,  Mechanical Systems and Signal Processing, 210, Article 111142

Li, Y.F.; Geng, C.Q.; Chen, S.Q.; Feng, K.; Beer, M. (2024): Extraction of instantaneous frequencies for signals with intersecting and intermittent trajectories,  Mechanical Systems and Signal Processing, 223, Article 111835
DOI: 10.1016/j.ymssp.2024.111835

Liao, K.; Wu, Y.P.; Miao, F.S.; Pan, Y.T.; Beer, M. (2024): Quantitative risk assessment of seismically loaded slopes in spatially variable soils with depth dependent strength,  International Journal of Geomechanics, in press.

Liu, J.X.; Shi, Y.; Chen, D.; Beer, M. (2024): Hybrid uncertainty propagation based on multi-fidelity surrogate model,  Computers and Structures, 293, Article 107267
DOI: 10.1016/j.compstruc.2023.107267

Lyu, M.Z.; Feng, D.C.; Cao, X.Y.; Beer, M. (2024): A full-probabilistic cloud analysis for structural seismic fragility via decoupled M-PDEM,  Earthquake Engineering & Structural Dynamics, 53(5), 1677-1929
DOI: 10.1002/eqe.4093

Mei, L.F.; Yan, W.J.; Yuen, K.V.; Beer, M. (2024): Streaming Variational Inference-empowered Bayesian Nonparametric Clustering for Online Structural Damage Detection with Transmissibility Function,  Mechanical Systems and Signal Processing, 222, Article 111767
DOI: 10.1016/j.ymssp.2024.111767

Mitseas, I.P.; Ni, P.H.; 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, Article 118755
DOI: 10.1016/j.engstruct.2024.118755

Ni, P.H.; 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, Article 102525
DOI: 10.1016/j.strusafe.2024.102525

Rafieyan, A.; Sarvari, H.; Beer, M.; Chan, D.W.M. (2024): 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, 24(7), 748–760
DOI: 10.1080/15623599.2022.2159630

Sarvari, H.; Asaadsamani, P.; Olawumi, T.O. , Chan, D.W.M.; Rashidi, A.; Beer, M. (2024): Perceived Barriers to Implementing Building Information Modelling in Iranian Small and Medium-Sized Enterprises (SMEs): A Delphi Survey of Construction Experts,  Architectural Engineering and Design Management TAEM, 20(3), 673–693
DOI: 10.1080/17452007.2024.2329687

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 & Social Change, 205, Article 123512
DOI: 10.1016/j.techfore.2024.123512

Shi, Y.; Beer, M. (2024): Physics-informed Neural Network Classification Framework for Reliability Analysis,  Expert Systems with Applications, 258, Article 125207
DOI: 10.1016/j.eswa.2024.125207

Shi, Y.; Beer, M. (2024): Deep learning-driven interval uncertainty propagation for aeronautical structures,  Chinese Journal of Aeronautics, in press.

Shi, Y.; Behrensdorf, J.; Zhou, J.Y.; Hu, Y.; Broggi, M.; Beer, M. (2024): Network Reliability Analysis through Survival Signature and Machine Learning Techniques,  Reliability Engineering and System Safety, 242, Article 109806
DOI: 10.1016/j.ress.2023.109806

Shi, Y.; Chai, R.; Beer, M. (2024): Novel Gradient-enhanced Bayesian Neural Networks for Uncertainty Propagation,  Computer Methods in Applied Mechanics and Engineering, 429, Article 117188

Song, J.W.; Cui, Y.F.; Wei, P.F.; Rashki, M.; Zhang, W.H.; Beer, M. (2024): Directional filter combined with active learning for rare failure events,  Computer Methods in Applied Mechanics and Engineering, 428, Article 117105
DOI: 10.1016/j.cma.2024.117105

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, in press.

Wang, L.; Hu, Z.; Dang, C.; Beer, M. (2024): Refined parallel adaptive Bayesian quadrature for estimating small failure probabilities,  Reliability Engineering and System Safety, 244, Article 109953

Wang, R.H.; 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, Article 118580

Wang, R.H.; Li, S.F.; 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, Article 106128
DOI: 10.1016/j.compgeo.2024.106128

Wang, R.H.; Ouyang, J.Y.; 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

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 & Industrial Aerodynamics, 247, Article 105679
DOI: 10.1016/j.jweia.2024.105679

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, Article 118382
DOI: 10.1016/j.engstruct.2024.118382

Yang, L.C.; Zhang, X.Y.; Lu, Z.T.; Fu, Y.Q.; 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, Article 110240
DOI: 10.1016/j.ress.2024.110240

You, Z.X.; Miao, H.N.; 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, Article 084101
DOI: 10.1063/5.0195091

Yuan, P.; Yuen, K.V.; Beer, M.; Cai, C.S.; Yan, W.J. (2024): A non-iterative partitioned computational method with the energy conservation property for time-variant dynamic systems,  Mechanical Systems and Signal Processing, 209, Article 111105
DOI: 10.1016/j.ymssp.2024.111105

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, Article 111426
DOI: 10.1016/j.ymssp.2024.111426

Zhao, Y.L.; Sun, B.; Bi, S.F.; Beer, M.; Moens, D. (2024): A Sub-Convex Similarity-Based Model Updating Method Considering Multivariate Uncertainties,  Engineering Structures, 318, Article 118752.

Zheng, Z.B.; Beer, M.; Nackenhorst, U. (2024): Efficient stochastic modal decomposition methods for structural stochastic static and dynamic analyses,  International Journal for Numerical Methods in Engineering, in press

Zhou, T.; Guo, T.; Dang, C.; Beer, M. (2024): Bayesian reinforcement learning reliability analysis,  Computer Methods in Applied Mechanics and Engineering, 424, Article 116902

Zhuang, J.C.; Jia, M.P.; 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, Article 111186.
DOI: 10.1016/j.ymssp.2024.111186

Bai, Y.T.; Li, X.L.; Zhou, X.H.; Li, P.; Beer, M. (2023): Soil-expended seismic metamaterial with ultralow and wide bandgap,  Mechanics of Materials, 180, Article 104601.
DOI: 10.1016/j.mechmat.2023.104601

Bai, Y.T.; Wang, S.H.; Zhou, X.H.; Beer, M. (2023): Three-dimensional ori-kirigami metamaterials with multistability,  Physical Review E, 107, Article 035004.
DOI: 10.1103/PhysRevE.107.035004

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), Article 04023022
DOI: 10.1061/AJRUA6.RUENG-1048

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, Article 110072.
DOI: 10.1016/j.ymssp.2022.110072

Bi, S.F.; Beer, M.; Cogan, S.; Mottershead J.E (2023): Stochastic Model Updating with Uncertainty Quantification: An Overview and Tutorial,  Mechanical Systems and Signal Processing, 20, Article 110784.
DOI: 10.2139/ssrn.4460552

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, Article 110873.

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, Article 102330.
DOI: 10.1016/j.strusafe.2023.102330

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

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, Article 116274.
DOI: 10.1016/j.engstruct.2023.116274

Chen, G.; Yang, J.S. Liu, Y.; Kitahara, T.; Beer, M. (2023): An energy-frequency parameter for earthquake ground motion intensity measure,  Earthquake Engineering and Structural Dynamics, 52(2), 271-284.
DOI: 10.1002/eqe.3752

Chen, G.; Yang, J.S.; Wang, R.H.; Li, K.Q.; Liu, Y.; Beer, M. (2023): Seismic damage analysis due to near-fault multi-pulse ground motion,  Earthquake Engineering and Structural Dynamics, 52(15), 5099-5116
DOI: 10.1002/eqe.4003

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 and Structural Dynamics, 52, 2179–2195.
DOI: 10.1002/eqe.3877

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, Article 110573
DOI: 10.1016/j.ymssp.2023.110573

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, Article 103482.
DOI: 10.1016/j.probengmech.2023.103482

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, in press.
DOI: 10.1016/j.jrmge.2023.05.009

Dai, H.Z.; Zhang, R.J.; Beer, M. (2023): A new method for stochastic analysis of structures under limited observations,  Mechanical Systems and Signal Processing, 185, Article 109730.
DOI: 10.1016/j.ymssp.2022.109730

Dang, C.; Valdebenito, M.A.; Faes, M.G.R.; Song, J.W.; Wei, P.F.; Beer, M. (2023): Structural reliability analysis by line sampling: A Bayesian active learning treatment,  Structural Safety, 104, Article 102351.
DOI: 10.1016/j.strusafe.2023.102351

Dang, C.; Valdebenito, M.A.; Song, J.W.; Wei, P.F.; 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, Article 116068.
DOI: 10.1016/j.cma.2023.116068

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, Article 109775.
DOI: 10.1016/j.ymssp.2022.109775

Feng, C.X.; Faes, M.; Broggi, M.; Dang, C.; Yang, J.S.; Zheng, Z.B.; Beer, M. (2023): Application of interval field method to the stability analysis of slopes in presence of uncertainties,  Computers and Geotechnics, 153, Article 105060.
DOI: 10.1016/j.compgeo.2022.105060

Feng, C.X.; Valdebenito, M.A.; Chwala, M.; Liao, K.; Broggi, M.; Beer, M. (2023): Efficient slope reliability analysis under soil spatial variability using maximum entropy distribution with fractional moments,  Journal of Rock Mechanics and Geotechnical Engineering, in press.

Feng, K.; Ji, J.C.; Zhang, Y.C.; Ni, Q.; Liu, Z.; Beer, M. (2023): Digital twin-driven intelligent assessment of gear surface degradation,  Mechanical Systems and Signal Processing, 186, Article, 109896.
DOI: 10.1016/j.ymssp.2022.109896

Goeing J., Seehausen H., Stania L., Nuebel N., Salomon J., Ignatidis P., Dinkelacker F., Beer M., Denkena B., Seume J. R., Friedrichs J. (2023): 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

Grashorn, J.; Urrea-Quintero, J.-H.; Broggi, M.; Chamoin, L.; Beer, M. (2023): Transport map Bayesian parameter estimation for dynamical systems,  Proceedings in Applied Mathematics and Mechanics, 23(1), Article e202200136
DOI: 10.1002/pamm.202200136

Hong, F.Q.; Wei, P.F.; Song, J.W.; 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, Article 103474.
DOI: 10.1016/j.probengmech.2023.103474

Hong, F.Q.; Wei, P.F.; Song, J.W.; 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, Article 116410.
DOI: 10.1016/j.cma.2023.116410

Hong, X.; Song, Y.P.; 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), Article 04023013.
DOI: 10.1061/AJRUA6.RUENG-1018

Huang, Z.F.; Chen, G.; Beer, M (2023): Multi-taper S-transform method for estimating Wigner-Ville and Loève spectra of quasi-stationary harmonizable processes,  Mechanical Systems and Signal Processing, 206, Article 110880.
DOI: 10.2139/ssrn.4508067

Kitahara, M.; Kitahara, T.; Beer M. (2023): Hierarchical Bayesian Model Updating for Quantifying Uncertainties in Model Parameters,  Journal of JSCE, 79(15) (in Japanese).

Lai, J.; Wang, K.; Xu, J.M.; Wang, P.; Chen, R.; Wang, S.G.; Beer, M. (2023): A failure probability assessment method for train derailments in railway yards based on IFFTA and NGBN,  Engineering Failure Analysis, 154, Articel 107675.

Liao, K.; Wu, Y.P.; Miao, F.S.; Zhang, L.F.; 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), Article 04023015.
DOI: 10.1061/AJRUA6.RUENG-1022

Ma, J.; Dai, C.P.; Wang, B.; Beer, M.; Wang, A.Y. (2023): Random dynamic responses of solar array under thermal-structural coupling based on the isogeometric analysis,  Acta Mechanica Sinica, 39, Article 722338.
DOI: 10.1007/s10409-023-22338-x

Mao, W.T.; Zhang, W.; Feng, K.; Beer, M.; Yang, C.S. (2023): 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, Article 109695.
DOI: 10.1016/j.ress.2023.109695

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, Article 110702
DOI: 10.1016/j.ymssp.2023.110702

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, Article 110040.
DOI: 10.1016/j.ymssp.2022.110040

Ni, P.H.; 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, Article 110009
DOI: 10.1016/j.ymssp.2022.110009

Persoons, A.; Wei, P.F.; 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, Article 144.
DOI: 10.1007/s00158-023-03598-6

Rafieyan, A.; Sarvari, H.; Beer, M.; Chan, D.W.M. (2023): 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, in press.
DOI: 10.1080/15623599.2022.2159630

Shi, Y.; Huang, H.Z.; Liu, Y.; Beer, M. (2023): Adaptive decoupled robust design optimization,  Structural Safety, 105, Article 102378
DOI: 10.1016/j.strusafe.2023.102378

Wan, Z.Q.; Chen, J.B.; Tao, W.F.; Wei, P.F.; Beer, M.; Jiang, Z.M. (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, Article 109656.
DOI: 10.1016/j.ymssp.2022.109656

Wang, C,X.; Yang, L.C.; Xie, M.; Valdebenito, M.A.; Beer, M. (2023): Bayesian maximum entropy method for stochastic model updating using measurement data and statistical information,  Mechanical Systems and Signal Processing, 188, Article 110012.
DOI: 10.1016/j.ymssp.2022.110012

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, Article 04023006
DOI: 10.1016/j.rcns.2022.10.001

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 and Structures, 284, Article 107070.
DOI: 10.1016/j.compstruc.2023.107070

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, Article 103494.
DOI: 10.1016/j.probengmech.2023.103494

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 the Context of Resilience Optimization,  Disaster Prevention and Resilience, 2(2):4.
DOI: 10.20517/dpr.2023.03

Xu, Y.D.; Ji, J.C.; Ni, Q.; Feng, K.; Beer, M.; Chen, H.T. (2023): A graph-guided collaborative convolutional neural network for fault diagnosis of electromechanical systems,  Mechanical Systems and Signal Processing, 200, Article 110609.
DOI: 10.1016/j.ymssp.2023.110609

Yuan, X.K.; Valdebenito, M.A.; Zhang, B.Q.; 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, Article 107003.
DOI: 10.1016/j.compstruc.2023.107003

Yuan, X.K.; Wang, S.L.; Valdebenito, M.A.; Faes, M.G.R.; Beer, M. (2023): Sample Regeneration Algorithm for Structural Failure Probability Function Estimation,  Probabilistic Engineering Mechanics, 71, Article 103387.
DOI: 10.1016/j.probengmech.2022.103387

Zeng, D.Q.; Zhang, H.; Dai, H.Z.; Beer, M. (2023): Scalable risk assessment of large infrastructure systems with spatially correlated components,  Structural Safety, 101, Article 102311.
DOI: 10.1016/j.strusafe.2022.102311

Zhang, K.; Chen, N.; Liu, J.; Yin, S.H.; Beer, M. (2023): An efficient meta-model-based method for uncertainty propagation problems involving non-parameterized probability-boxes,  Reliability Engineering and System Safety, 238, Article 109477
DOI: 10.1016/j.ress.2023.109477

Zhang, Y.; Xu, J.; Beer, M. (2023): A single-loop time-variant reliability evaluation via a decoupling strategy and probability distribution reconstruction,  Reliability Engineering and System Safety, 232, Article 109031.
DOI: 10.1016/j.ress.2022.109031

Zhang, Y.C.; Ren, Z.H.; 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, Article 110159.
DOI: 10.1016/j.ymssp.2023.110159

Zheng, Z.B.; Beer, M.; Nackenhorst, U. (2023): An iterative multi-fidelity scheme for simulating multi-dimensional non-Gaussian random fields,  Mechanical Systems and Signal Processing, 200, Article 110643
DOI: 10.1016/j.ymssp.2023.110643

Zheng, Z.B.; Dai, H.Z.; Beer, M. (2023): Efficient structural reliability analysis via a weak-intrusive stochastic finite element method,  Probabilistic Engineering Mechanics, 71, Article 103414.
DOI: 10.1016/j.probengmech.2023.103414

Zheng, Z.B.; Valdebenito, M.A.; 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, Article 115860.
DOI: 10.1016/j.cma.2022.115860

Zheng, Z.B.; Valdebenito, M.A.; Beer, M.; Nackenhorst, U. (2023): Simulation of random fields on random domains,  Probabilistic Engineering Mechanics, 73, Article 103455.
DOI: 10.1016/j.probengmech.2023.103455

Behrendt, M.; Bittner, M.; Comerford, L.; Beer, M.; Chen, J.B. (2022): Relaxed Power Spectrum Estimation from Multiple Data Records utilising Subjective Probabilities,  Mechanical Systems and Signal Processing, 165, Article 108346.
DOI: 10.1016/j.ymssp.2021.108346

Behrendt, M.; de Angelis, M.; Comerford, L.A.; Zhang, Y.J.; Beer, M. (2022): Projecting interval uncertainty through the discrete Fourier transform: an application to time signals with poor precision,  Mechanical Systems and Signal Processing, Volume 172, 1 June 2022, 108920.
DOI: 10.1016/j.ymssp.2022.108920

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, 114648.
DOI: 10.1016/j.engstruct.2022.114648

Chen, G.; Beer, M.; Liu, Y. (2022): Modeling response spectrum compatible pulse-like ground motion,  Mechanical Systems and Signal Processing, 177, Article 109177.
DOI: 10.1016/j.ymssp.2022.109177

Chen, G.; Yang, J.S. Liu, Y.; Kitahara, T.; Beer, M. (2022): An energy-frequency parameter for earthquake ground motion intensity measure,  Earthquake Engineering and Structural Dynamics, 1- 14.
DOI: 10.1002/eqe.3752

Cheng, M.H.; Dang, C.; Frangopol, D.M.; Beer, M.; Yuan, X.X. (2022): Transfer prior knowledge from surrogate modelling: A meta-learning approach,  Computers & Structures, 260, Article 106719.
DOI: 10.1016/j.compstruc.2021.106719

Dai, H.Z.; Zhang, R.J.; Beer, M. (2022): A new perspective on the simulation of cross-correlated random fields,  Structural Safety 96, Article 102201.
DOI: 10.1016/j.strusafe.2022.102201

Dang, C.; Valdebenito, M.A.; Faes, M.G.R.; Wei, P.F.; Beer, M. (2022): Structural reliability analysis: A Bayesian perspective,  Structural Safety, 99, Article 102259.
DOI: 10.1016/j.strusafe.2022.102259

Dang, C.; Wei, P.F.; Faes, M.G.R.; Beer, M. (2022): Bayesian probabilistic propagation of hybrid uncertainties: Estimation of response expectation function, its variable importance and bounds,  Computers and Structures, 270, Article 106860.
DOI: 10.1016/j.compstruc.2022.106860

Dang, C.; Wei, P.F.; 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

Dang, C.; Wei, P.F.; Faes, M.G.R.; Valdebenito, M.A.; Beer, M. (2022): Parallel adaptive Bayesian quadrature for rare event estimation,  Reliability Engineering and System Safety, 225, Article 108621.
DOI: 10.1016/j.ress.2022.108621

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, Article 103287.
DOI: 10.1016/j.probengmech.2022.103287

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, Article 103269.
DOI: 10.1016/j.probengmech.2022.103269

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, Article 103367
DOI: 10.1016/j.probengmech.2022.103367

Feng, K.; Ji; J.C., Ni, Q.; Beer, M. (2022): A review of vibration-based gear wear monitoring and prediction techniques,  Mechanical Systems and Signal Processing, 182, Article 109605.
DOI: 10.1016/j.ymssp.2022.109605

Feng, K.; Ni, Q.; Beer, M.; Du, H.P.; Li, C. (2022): A novel similarity-based status characterization methodology for gear surface wear propagation monitoring,  Tribology International, 174, Article 107765.

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,  ASCE Journal of Engineering Mechanics, 148(3). Article 04022001.

Han, R.; Fragkoulis, V.C.; Kong, F.; Beer, M.; Peng, Y.B. (2022): Non-stationary response determination of nonlinear systems subjected to combined deterministic and evolutionary stochastic excitations,  International Journal of Non-Linear Mechanics, 147, Article 104192, (Special Issue, Invited).
DOI: 10.1016/j.ijnonlinmec.2022.104192

He, Z.; Bittner, M.; Beer, M (2022): Seismic Response Meta-Model of High-Rise Frame Structure Based on Time-delay Neural Network,  KSCE Journal of Civil Engineering.
DOI: 10.1007/s12205-022-0878-7

Jerez, D.; Jensen, H.; Beer, M. (2022): Reliability-Based Design Optimization of Structural Systems under Stochastic Excitation: An Overview,  Mechanical Systems and Signal Processing, 166, Article 108397.

Jerez, D.J.; Jensen, H.A.; Beer, M.; Chen, J.B. (2022): Asymptotic Bayesian Optimization: AMarkov sampling-based framework for design optimization,  Probabilistic Engineering Mechanics, 67, Article 103178.

Jerez, D.J.; Jensen, H.A.; Beer, M.; Chen, J.B. (2022): An effective implementation of reliability methods for Bayesian model updating of structural dynamic models with multiple uncertain parameters,  Reliability Engineering and System Safety, 225, Article 108634.

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, 22, Article 103368
DOI: 10.1016/j.probengmech.2022.103368

Jiang, Y.B.; Li, Z.M.; Zhou, H.; Wang, F.M.; Beer, M.; Zheng, J.L. (2022): Reliability evaluation of RC columns with wind-dominated combination considering random biaxial eccentricity,  ASCE Journal of Structural Engineering, 49(1), Article 06022007.

Jiang, Y.B.; Zheng, J.L.; Yang, K.L.; Zhou, H.; Beer, M. (2022): Probabilistic analysis of resistance for RC columns with wind-dominated combination considering random biaxial eccentricity,  Structure and Infrastructure Engineering, 20(5), 30–740
DOI: 10.1080/15732479.2022.2131842

Kitahara, M.; Bi, S.F.; Broggi, M.; Beer, M. (2022): Nonparametric Bayesian stochastic model updating with hybrid uncertainties,  Mechanical Systems and Signal Processing, 163, Article 108195.

Kitahara, M.; Dang, C.; Beer, M. (2022): Bayesian updating with two-step parallel Bayesian optimization and quadrature,  Computer Methods in Applied Mechanics and Engineering, 403, Article 115735.

Kitahara, M.; Song, J.W.; Wei, P.F.; Broggi, M.; Beer, M. (2022): A distributionally robust approach for mixed aleatory and epistemic uncertainties propagation,  AIAA Journal, in press.

Kitahara, M.;Bi, S.F.; Broggi, M.; Beer, M. (2022): Distribution-free stochastic model updating of dynamic systems with parameter dependencies,  Structural Safety, 97, Article 102227

Kougioumtzoglou, I.A., Ni, P.H.; 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, Article 104178.
DOI: 10.1016/j.ijnonlinmec.2022.104178

Liao, K.; Wu, Y.P.; Miao, F.S.; Pan, Y.T.; Beer, M. (2022): 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

Liu, W.; Ye, T.X.; Yuan, P.; Beer, M.; Tong, X.L. (2022): An explicit integration method with third-order accuracy for linear and nonlinear dynamic systems,  Engineering Structures, 274, Article 115013.

Mei, L.F.; Yan, W.J.; Yuen, K.V.; Beer, M. (2022): Structural Novelty Detection Based on Laplace Asymptotic Expansion of the Bhattacharyya Distance of Transmissibility Function and Bayesian Resampling Scheme,  Journal of Sound and Vibration, 540, Article 117277.

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, Article 105528.

Ni, P.H.; Jerez, D.J.; Fragkoulis, V.C.; Faes, M.G.R.; Valdebenito, M.A.; Beer, M. (2022): Operator Norm-based Statistical Linearization to Bound the First Excursion Probability of Nonlinear Structures Subjected to Imprecise Stochastic Loading,  ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 8(1), Article 04021086.

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, Article 108701.

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, 61–78.
DOI: 10.1016/j.rcns.2022.10.005

Yang, J.S.; Chen, J.B.; Beer, M.; Jensen, H.A. (2022): An Efficient Approach for Dynamic-Reliability-Based Topology Optimization of Braced Frame Structures with Probability Density Evolution Method,  Advances in Engineering Software, 173, Article 103196

Yuan, X.K.; Qian, Y.G.; Chen, J.Q.; Faes, M.G.R.; Valdebenito, M.A.; Beer, M. (2022): Global failure probability function estimation based on an adaptive strategy and combination algorithm,  Reliability Engineering and System Safety, 231, Article 108937.

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, Article 114516.

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 and System Safety, 228, Article 108794.

Zheng, Z.B.; Beer, M.; Dai, H.Z.; Nackenhorst, U. (2022): A weak-intrusive stochastic finite element method for stochastic structural dynamics analysis,  Computer Methods in Applied Mechanics and Engineering, 399, Article 115360.

Zheng, Z.B.; Beer, M.; Nackenhorst, U. (2022): An efficient reduced-order method for stochastic eigenvalue analysis,  International Journal for Numerical Methods in Engineering, in press

Bai, Y.T.; Li, Y.S.; Tang, Z.Y.; 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

Behrensdorf, J.; Regenhardt, T.-E.; Broggi, M.; Beer, M. (2021): Numerically efficient computation of the survival signature for the reliability analysis of large networks,  Reliability Engineering and System Safety, 216, Article 107935.
DOI: 10.1016/j.ress.2021.107935

Bi, S.F.; Beer, M.; Zhang, J.G.; 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), Article 020903.
DOI: https://doi.org/10.1115/1.4050168

Bi, S.F.; He, K.; Zhao, Y.L.; Moens, D.; Beer, M.; Zhang, J.R. (2021): Towards the NASA UQ Challenge 2019: Systematically forward and inverse approaches for uncertainty propagation and quantification,  Mechanical Systems and Signal Processing, 165, Article 108387.

Dang, C.; Wei, P.F.; Beer, M. (2021): An approach for evaluation of EVD and small failure probabilities of uncertain nonlinear structures under stochastic seismic excitations,  Mechanical Systems and Signal Processing, 152, Article 107468.

Dang, C.; Wei, P.F.; Song, J.W.; Beer, M. (2021): Estimation of failure probability function under imprecise probabilities by active learning augmented probabilistic integration,  ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 7(4), Article 04021054.

Faes, M.; Valdebenito, M.A., Yuan, X.K.; Wie, P.F.; Beer, M. (2021): Efficient imprecise reliability analysis using the Augmented Space Integral,  Reliability Engineering and System Safety, 210, Artice 107477.
DOI: https://doi.org/10.1016/j.ress.2021.107477

Faes, M.; 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, Article 107482.
DOI: https://doi.org/10.1016/j.ymssp.2020.107482

Faes, M.G.R., Daub, M.; Marelli, S.; Patelli, E.; Beer, M. (2021): Engineering analysis with probability boxes: a review on computational methods,  Structural Safety, 93, Article 102092.

Faes, M.G.R.; Valdebenito, M.A.; Yuan, X.K.; Wie, P.F.; Beer, M. (2021): Augmented Reliability Analysis for Estimating Imprecise First Excursion Probabilities in Stochastic Linear Dynamics,  Advances in Engineering Software, 155, Article 102993.
DOI: https://doi.org/10.1016/j.advengsoft.2021.102993

Gong, Z.T.; DiazDelaO, F.A.; Hristov, P.O.; Beer, M. (2021): History matching with subset simulation,  International Journal for Uncertainty Quantification, 11(5), 19–38.

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, Article 113487.
DOI: https://doi.org/10.1016/j.cma.2020.113487

Jensen, H.A.; Jerez, D.J.; Beer, M. (2021): Structural Synthesis Considering Mixed Discrete-Continuous Design Variables: A Bayesian Framework,  Mechanical Systems and Signal Processing, 162, Article 108042.

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, Article 107834.
DOI: https://doi.org/10.1016/j.ymssp.2021.107834

Kitahara, M.; Bi, S.F.; Broggi, M.; Beer, M. (2021): Bayesian Model Updating in Time Domain with Metamodel-based Reliability Method,  ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 7(3), Article 04021030.

Kitahara, M.; Broggi, B.; 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, part A1 (Structural Engineering & Earthquake Engineering), 77, I_61–I_70.

Mitseas, I. P.; Beer, M. (2021): First-excursion stochastic incremental dynamics methodology for hysteretic structural systems subject to seismic excitation,  Computers and Structures, vol. 242.
DOI: 10.1016/j.compstruc.2020.106359

Morais, C.; Estrada-Lugo, H.D.; Tolo, S.; Jacques, T.; Moura, R.; Beer, M.; Patelli, E. (2021): Robust data-driven human reliability analysis using credal networks,  Reliability Engineering and System Safety, 218, Article 107990.

Ni, P.H.; 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), Article 04021049.

Pasparakis, G.D.; dos Santos, K.R.M.; Kougioumtzoglou, I.A.; Beer, M. (2021): Wind data extrapolation and stochastic field statistics estimation via compressive sampling and low rank matrix recovery methods,  Mechanical Systems and Signal Processing, 162, Article 107975.

Salomon, J.; Winnewisser, N.; Wei, P.F.; Broggi, M.; Beer, M. (2021): Efficient Reliability Analysis of Complex Systems in Consideration of Imprecision,  Reliability Engineering and System Safety, 216, Article 107972.
DOI: 10.1016/j.ress.2021.107972

Sarvari, H.; Chan, D.W.M.; Banaitiene, N.; Noor, N.M.; Beer, M. (2021): Barriers to development of private sector investment in water and sewage industry,  Built Environment Project and Asset Management, 11(1), 52–70.
DOI: https://doi.org/10.1108/BEPAM-11-2019-0110

Song, J.W.; Wei, P.F.; Valdebenito, M.A.; Faes, M.G.R.; Beer, M. (2021): Data-driven and Active Learning of Variance-based Sensitivity Indices with Bayesian Probabilistic Integration,  Mechanical Systems and Signal Processing, 163, Article 108106.

Valdebenito, M.A.; Wei, P.F.; Song, J.W.; Beer, M.; Broggi, M. (2021): Failure Probability Estimation of a Class of Series Systems by Multidomain Line Sampling,  Reliability Engineering and System Safety, 213, Article 107673.

Wan, Z.Q.; Chen, J.B.; Beer, M. (2021): Functional Perspective of Uncertainty Quantification for Stochastic Parametric Systems and Global Sensitivity Analysis,  Chinese Journal of Theoretical and Applied Mechanics, 53(3), 837–854 (in Chinese).

Wang, C.; Beer, M.; Ayyub, B.M. (2021): Time-dependent Reliability of Aging Structures: An Overview of Assessment Methods,  ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 7(4), Article 03121003.

Wang, Q.; Feng, Y.; Wu, D.; Yang, C.; Yu, Y.; Li, G.; Beer, M.; Gao, W. (2021): Polyphase Uncertainty Analysis through Virtual Modelling Technique,  Mechanical Systems and Signal Processing, 162, Article 108013.

Wei, P.F.; Hong, F.Q.; Phoon, K.K.; Beer, M. (2021): Bounds optimization of model response moments: a twin-engine Bayesian active learning method,  Computational Mechanics, 67, 1273–1292.
DOI: https://doi.org/10.1007/s00466-021-01977-8

Yang, L.; Wang, P.D.; Wang, Q.; Bi, S.F.; Peng, R.; Behrensdorf, J.; Beer, M. (2021): Reliability analysis of a complex system with hybrid structures and multi-level dependent life metrics,  Reliability Engineering and System Safety, 209, 107469.
DOI: https://doi.org/10.1016/j.ress.2021.107469

Yang, L.C.; Bi, S.F.; Faes, M.G.R.; Broggi, M.; Beer, M. (2021): Bayesian inversion for imprecise probabilistic models using a novel entropy-based uncertainty quantification metric,  Mechanical Systems and Signal Processing, 162, Article 107954.

Yuan, X.K.; Liu, S.L.; Faes, M.; Valdebenito, M.; 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, Article 107699.
DOI: https://doi.org/10.1016/j.ymssp.2021.107699

Yuan, X.K.; Liu, S.L.; Valdebenito, M.A.; Faes, M.G.R.; Jerez, D.J.; Jensen, H.A.; Beer, M. (2021): Decoupled reliability-based optimization using Markov chain Monte Carlo in augmented space,  Advances in Engineering Software 157–158, Article 103020.

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, Article 107559.
DOI: https://doi.org/10.1016/j.ymssp.2020.107559

Zhu, W.Q.; 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, Article 107184.
DOI: https://doi.org/10.1016/j.ymssp.2020.107184

Zhu, W.Q.; Hu, Y.B.; Chen, N.; Liu, J.; Beer, M. (2021): A fuzzy and random moment-based arbitrary polynomial chaos method for response analysis of composite structural-acoustic system with multi-scale uncertainties,  Applied Acoustics, 177, Article 107913.

Bai, Y.T.; 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, 26(6), 3012–3033.
DOI: 10.1080/13632469.2020.1784315

Chen, J.B.; Comerford, L.; Peng, Y.B; Beer, M.; Li, J. (2020): Reduction of random variables in the Stochastic Harmonic Function representation via spectrum-relative dependent random frequencies,  Mechanical Systems and Signal Processing, 141, Article 106718.
DOI: https://doi.org/10.1016/j.ymssp.2020.106718

Chen, J.B.; Wan, Z.Q.; Beer, M. (2020): A Global Sensitivity Index Based on Fréchet Derivative and Its Efficient Numerical Analysis,  Probabilistic Engineering Mechanics, 62, Article 103096.
DOI: https://doi.org/10.1016/j.probengmech.2020.103096

Eckert, C., Beer, M.; Spanos, P.D. (2020): A Polynomial Chaos Method for Arbitrary Random Inputs using B-Splines,  Probabilistic Engineering Mechanics, 60, Article 103051.
DOI: 10.1016/j.probengmech.2020.103051

Faes, M.; Valdebenito, M.A.; Moens, D.; Beer, M. (2020): Bounding the First Excursion Probability of Linear Structures Subjected to Imprecise Stochastic Loading,  Computers and Structures, 239, Article 106320.
DOI: https://doi.org/10.1016/j.compstruc.2020.106320

Jiang, Y.B.; Peng, S.X.; Beer, M.; Wang, L.; Zhang, J.R. (2020): Reliability evaluation of RC columns designed by Eurocode for wind dominated combination considering random eccentricity,  Advances in Structural Engineering, 23(1), 146–159.
DOI: 10.1177/1369433219866089

Jiang, Y.B.; Zhao, L.J.; Beer, M.; Wang, L.; Zhang, J.R. (2020): Dominant failure mode analysis using representative samples obtained by multiple response surfaces method,  Probabilistic Engineering Mechanics, 59, Article 103005.
DOI: 10.1016/j.probengmech.2019.103005

Kitahara, M.; Broggi, M.; Beer, M. (2020): Efficient seismic performance estimation method by surrogate modeling based on adaptive Kriging and Markov chain Monte Carlo,  Journal of Japan Society of Civil Engineers, part A2 (Applied Mechanics), 76, 75–86.

Mi, J.H, Beer, M.; Li, Y.F.; Broggi, M.; Cheng, Y.H. (2020): Reliability and Importance Analysis of Uncertain System with Common Cause Failures Based on Survival Signature,  Reliability Engineering and System Safety, 201, Article 106988.
DOI: https://doi.org/10.1016/j.ress.2020.106988

Mi, J.H; Li, Y.F.; Beer, M.; Broggi, M.; Cheng, Y.H. (2020): Importance measure of probabilistic common cause failures under system hybrid uncertainty based on bayesian network,  Maintenance and reliability, 22 (1), 112–120.
DOI: https://doi.org/10.17531/ein.2020.1.13

Mitseas, I. P.; Beer, M. (2020): Fragility analysis of nonproportionally damped inelastic MDOF structural systems exposed to stochastic seismic excitation,  Computers and Structures, vol. 226.
DOI: 10.1016/j.compstruc.2019.106129

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, 011014-1, 1–16.
DOI: 10.1115/1.4044796

Nieto-Cerezo, O.; Wenzelburger, J.; Patelli, E.; Beer, M. (2020): Optimal regulation of the construction of reliable sea defences,  ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 6(2), Article, 04020023, 1–12.

Pasparakis, G.; Fragkoulis, V.; Beer, M. (2020): Harmonic wavelets based response evolutionary power spectrum determination of linear and nonlinear structural systems with singular matrices,  Mechanical Systems and Signal Processing, 149, Article 107203. | Datei |
DOI: 10.1016/j.ymssp.2020.107203

Siju, K.C.; Kumar, M.; Beer, M. (2020): 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: https://doi.org/10.1108/IJQRM-01-2020-0009

Song, J.W.; Valdebenito, M.; Wei, P.F.; Beer, M.; Lu, Z.Z. (2020): Non-intrusive imprecise stochastic simulation by line sampling,  Structural Safety, 84, Article 101936.
DOI: https://doi.org/10.1016/j.strusafe.2020.101936

Song, J.W.; Wei, P.F.; Valdebenito, M.; Beer, M. (2020): Active Learning Line Sampling for Rare Event Analysis,  Mechanical Systems and Signal Processing, 147, Article 107113.
DOI: https://doi.org/10.1016/j.ymssp.2020.107113

Song, J.W.; Wei, P.F.; 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, Article 113344.
DOI: https://doi.org/10.1016/j.cma.2020.113344

Valdebenito, M.A.; Beer, M.; Jensen, H.A.; Chen, J.B.; Wei, P.F. (2020): Fuzzy Failure Probability Estimation Applying Intervening Variables,  Structural Safety, Structural Safety, 83, Article 101909.
DOI: 10.1016/j.strusafe.2019.101909

Valdebenito, M.A.; Jensen, H.A.; Wei, P.F.; Beer, M.; Beck, A.T. (2020): Application of a Reduced Order Model for Fuzzy Analysis of Linear Static Systems, Special Issue: Non probabilistic and hybrid approaches for uncertainty quantification and reliability analysis,  ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 7(2), Article 020904
DOI: https://doi.org/10.1115/1.4050159

Wei, P.F.; Liu, F.C.; Valdebenito, M.; Beer, M. (2020): Bayesian Probabilistic Propagation of Imprecise Probabilities with Large Epistemic Uncertainty,  Mechanical Systems and Signal Processing, 149, Article 107219.
DOI: https://doi.org/10.1016/j.ymssp.2020.107219

Wei, P.F.; Zhang, X.; Beer, M. (2020): Adaptive Experiment Design for Probabilistic Integration,  Computer Methods in Applied Mechanics and Engineering, 365, Article 113035.
DOI: 10.1016/j.cma.2020.113035

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 Frequency Response Functions and Transmissibility Functions,  Mechanical Systems and Signal Processing, 145, Article 106886.

Yuan, X.K.; Liu, S.L.; Valdebenito, M.A.; Gu, J.; Beer, M. (2020): Efficient procedure for failure probability function estimation in augmented space,  Structural Safety, 92, Article 102104.

Beer, M.; Gholami, A.; Kreinovich, V. (2019) (2019): A Theoretical Explanation for the Efficiency of Generalized Harmonic Wavelets in Engineering and Seismic Spectral Analysis,  Mathematical Structures and Modeling, 3(51), 97–104.

Behrensdorf, J.; Broggi, M.; Beer, M. (2019): Reliability analysis of networks interconnected with copulas,  ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 5(4), Article 041006.
DOI: 10.1115/1.4044043

Bi, S.F.; Broggi, M.; Wei, P.F.; Beer, M. (2019): The Bhattacharyya distance: enriching the P-box in stochastic sensitivity analysis,  Mechanical Systems and Signal Processing, 129, pp. 265-281.
DOI: 10.1016/j.ymssp.2019.04.035

Chen, J.B.; Chen, Y.W.; Peng, Y.B.; Zhu, S.Y.; Beer, M.; Comerford, L. (2019): Stochastic harmonic function based wind field simulation and wind-induced reliability of super high-rise buildings,  Mechanical Systems and Signal Processing, 133, 106264, 20 pages.
DOI: 10.1016/j.ymssp.2019.106264

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

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

Faes, M.; Sadeghi, J.; Broggi, M.; De Angelis, M.; Patelli, E.; Beer, M.; Moens, D. (2019): On the robust estimation of small failure probabilities for strong non-linear models,  ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 5, Article 041007.
DOI: 10.1115/1.4044044

Feng, J.W.; Liu, L.; Wu, D.; Li, G.Y.; Beer, M.; Gao, W. (2019): Dynamic reliability analysis using the extended support vector regression (X-SVR),  Mechanical Systems and Signal Processing, 126, 368-391.
DOI: 10.1016/j.ymssp.2019.02.027

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, 7, 1–13, doi 10.1007/s11071-019-05124-0.

George-Williams, H.; Feng, G.; Coolen, F.P.A.; Beer, M.; Patelli, E. (2019): 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, 233(4), 505–519.

He, L.X.; Gomes, A.T.; Broggi, M.; Beer, M. (2019): Failure Analysis of Soil Slopes with Advanced Bayesian Networks,  Periodica Polytechnica Civil Engineering.
DOI: 10.3311/PPci.14092

He, L.X.; Wang, L.; Beer, M.; Liu, Y.; Broggi, M.; Bi, S.F. (2019): Estimation of failure probability in a braced excavation by Bayesian networks integrating with model updating approaches,  Underground Space, 5(4), 315–323.

Miro, S.; Willeke, T.; Broggi, M.; Seume, J.R.; Beer, M. (2019): Reliability Analysis of an Axial Compressor Based on One-Dimensional Flow Modeling and Survival Signature,  ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 5(3), art. no. 031003.
DOI: 10.1115/1.4043150

Mitseas, I.P.; Beer, M. (2019): Modal decomposition method for response spectrum based analysis of nonlinear and non-classically damped systems,  Mechanical Systems and Signal Processing, 131:469-485.
DOI: 10.1016/j.ymssp.2019.05.056

Salomon, J.; Broggi, M.; Kruse, S.; Weber, S.; Beer, M. (2019): Resilience Decision-Making Method For Complex Systems,  ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 6(2), Article 020901. | Datei |
DOI: 10.1115/1.4044907

Sarvari, H.; Valipour, A.; Yahya, N.; Noor, N.MD.; Beer, M.; Banaitiene, N. (2019): Approaches to Risk Identification in Public–Private Partnership Projects: Malaysian Private Partners’ Overview,  Administrative Sciences, 9, 17, 1-18.
DOI: 10.3390/admsci9010017

Song, J.W.; Wei, P.F.; Valdebenito, M.; Bi, S.F.; Broggi, M.; Beer, M.; Lei, Z.X. (2019): Generalization of non-intrusive imprecise stochastic simulation for mixed uncertain variables,  Mechanical Systems and Signal Processing, 134, 106316, 17 pages.

Song, Y.P.; Chen, J.B.; Beer, M.; Comerford, L. (2019): Wind Speed Field Simulation via Stochastic Harmonic Function Representation based on Wavenumber-Frequency Spectrum,  ASCE Journal of Engineering Mechanics, 145(11), 04019086.

Wang, C.; Zhang, H.; Beer, M. (2019): Structural Time-dependent Reliability Assessment with A New Power Spectral Density Function,  ASCE's Journal of Structural Engineering, 145(12): 04019163, 10 pages.
DOI: 10.1061/(ASCE)ST.1943-541X.0002476

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

Wei, P.F.; Song, J.W.; Bi, S.F.; Broggi, M.; Beer, M.; Lu, Z.Z.; Yue, Z.F. (2019): Non-intrusive stochastic analysis with parameterized imprecise probability models: I. Performance estimation,  Mechanical Systems and Signal Processing, 124, 349-368.
DOI: 10.1016/j.ymssp.2019.01.058

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.

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 and System Safety, 185, 261-277.
DOI: 10.1016/j.ress.2018.12.025

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):522.
DOI: 10.1007/s40430-018-1442-8

Bi, S.F.; Broggi, M.; Beer, M. (2018): 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

Chen, N.; Hu, Y.B.; Yu, D.J.; 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

Comerford, L.A.; Mannis, A.; de Angelis, M.; Kougioumtzoglou, I.A.; Beer, M. (2018): Utilising database-driven interactive software to enhance independent home study in a flipped classroom setting: going beyond visualizing engineering concepts to ensuring formative assessment,  European Journal of Engineering Education, 43(4), 522–537.
DOI: 10.1080/03043797.2017.1293617

Lu, N., Liu, Y., Beer, M. (2018): Extrapolation of extreme traffic load effects on a cable-stayed bridge based on weigh-in-motion measurements,  International Journal of Reliability and Safety, 12(1-2), pp. 69-85.
DOI: 10.1504/IJRS.2018.092504

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

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

Wang, C.; Zhang, H.; Beer, M. (2018): Computing tight bounds of structural reliability under imprecise probabilistic information,  Computers and Structures, 208, 92–104.
DOI: 10.1016/j.compstruc.2018.07.003

Zhang, D.M.; Du, F.; Huang, H.W.; Zhang, F.; Ayyub, B.M.; Beer, M. (2018): Resiliency Assessment of Urban Rail Transit Networks: Shanghai Metro as an Example,  Safety Science, 106: 230-243.

Zhang, Y.; Kim, C.-W.; Beer, M.; Dai, H.L.; Soares, C.G. (2018): Modeling multivariate ocean data using asymmetric copulas,  Coastal Engineering, 135: 91-111.
DOI: 10.1016/j.coastaleng.2018.01.008

Zhang, Y.J.; Comerford, L.A.; Kougioumtzoglou, I.A.; Beer, M. (2018): Lp-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

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

Attarzadeh, M.; Chua, D.; 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

Attarzadeh, M.; Chua, D.; 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, 04017002, 1–15.
DOI: 10.1061/AJRUA6.0000902

Chen, N; Yu, D.J.; Xia, B.Z.; Beer, M. (2017): Hybrid Uncertain Analysis for Exterior Acoustic Field Prediction with Interval Random Parameters,  International Journal of Computational Methods 15(1), 1850006-1 – 1850006-23.
DOI: 10.1142/S0219876218500068

Comerford, L.; Jensen, H.A.; Mayorgab, 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 and Structures; 182: 26-40.
DOI: 10.1016/j.compstruc.2016.11.012

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), D4016001, 1–9.
DOI: 10.1061/AJRUA6.0000868

Jiang, Y.B.; Luo, J.; Beer, M.; Patelli, E.; Broggi, M.; He, Y.H.; Zhang, J.R. (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

Lu, N.W.; Beer, M.; Noori, M.; Liu, Y. (2017): Lifetime deflections of long-span bridges under dynamic and growing traffic load,  ASCE Journal of Bridge Engineering, 22(11), 04017086, 1–12.
DOI: 10.1061/(ASCE)BE.1943-5592.0001125

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, Volume 99, Part A, Pages 58-70.
DOI: 10.1016/j.ssci.2017.03.005

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, 196–214.
DOI: 10.1016/j.ssci.2017.05.001

Opeyemi, D.; Timashev, S.A.; Bushinskaya, A.V.; Patelli, E.; Beer, M. (2017): Method of reliability assessment of arctic pipelines in the space of loads,  Russian Journal of Construction Science and Technology, 3(1), 49-59.
DOI: 10.15826/rjcst.2017.1.007

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), G4016003, 1–15.
DOI: 10.1061/AJRUA6.0000874

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.

Yan, D.H.; Luo, Y; Lu, N.W.; Yuan, M.; Beer, M. (2017): Fatigue stress spectra and reliability evaluation of short- to medium- span bridges under stochastic and dynamic traffic load,  ASCE Journal of Bridge Engineering, 22(12), 04017102, 1–11.
DOI: 10.1061/(ASCE)BE.1943-5592.0001137

Zhang, H.; Ha, L.; Li, Q.W.; 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

Zhang, Y.J.; Comerford, L.A.; 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, Vol. 3, Issue 4, 04017020.
DOI: 10.1061/AJRUA6.0000925

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

Do, D.M. ; Gao, W.; Song, C.M.; Beer, M. (2016): Interval spectral stochastic finite element analysis of structures with aggregation of random field and bounded parameters,  International Journal of Numerical Methods in Engineering; Volume 108, Issue 10: 1198–1229.
DOI: 10.1002/nme.5251

Feng, G.; Patelli, E.; Beer, M.; Coolen, F. P. (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

Jiang, Y.B.; Zhou, H.; Beer, M.; Wang, L.; Zhang, J.R.; Zhao, L.J. (2016): Robustness of load and resistance design factors for RC columns with wind dominated combination considering random eccentricity,  ASCE's Journal of Structural Engineering: 04016221.
DOI: 10.1061/(ASCE)ST.1943-541X.0001720

Kosheleva, O.; Beer, M. (2016): Why Modified Exponential Covariance Kernel is Empirically Successful: A Theoretical Explanation,  Journal of Uncertain Systems; 10: 10—14.

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

Mitseas, I. P.; Kougioumtzoglou, I. A.; Spanos, P. D.; Beer, M. (2016): Nonlinear MDOF structural system survival probability determination subject to evolutionary stochastic excitation,  Journal of Mechanical Engineering, 62(7–8), 440–451.
DOI: 10.5545/sv-jme.2016.3752

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

Valdebenito, M. A.; Pérez, C. A.; Jensen, H. A.; Beer, M. (2016): Approximate fuzzy analysis of linear structural systems applying intervening variables,  Computers and Structures; 162: 116—129.
DOI: 10.1016/j.compstruc.2015.08.020

Comerford, L.; Kougioumtzoglou, I. A.; Beer, M. (2015): Compressive sensing based stochastic process power spectrum estimation subject to missing data,  Probabilistic Engineering Mechanics; 44: 66-76.

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.

Comerford, L.; Kougioumtzoglou, I. a.; Beer, M. (2015): Uncertainty Quantification in Power Spectrum Estimation of Stochastic Processes Subject to Missing Data,  International Journal of Sustainable Materials and Structural Systems (IJSMSS).

de Angelis, M.; Patelli, E.; Beer, M. (2015): Advanced Line Sampling for efficient robust reliability analysis,  Structural Safety; 52: 170-182.

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.

Kougioumtzoglou, I. A.; Zhang, Y.; Beer, M. (2015): Softening Duffing Oscillator Reliability Assessment Subject to Evolutionary Stochastic Excitation,  ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering: C4015001.

Zhang, M. Q.; Beer, M.; Koh, C. G.; Jensen, H. A. (2015): Nuanced Robustness Analysis with Limited Information,  ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering: B4015001.

Zhang, Y.; Beer, M.; Quek, S. T. (2015): Long-term performance assessment and design of offshore structures,  Computers & Structures; 154: 101-115.

Liu, Y.; Lee, F.; Quek, S.; Beer, M. (2014): A genetic algorithm approach for the calibration of a social force based model for shared spaces,  Probabilistic Engineering Mechanics; 38: 42—53.

Beer, M.; Ferson, S.; Kreinovich, V. (2013): Imprecise probabilities in engineering analyses,  Mechanical Systems and Signal Processing; 37(1-2): 4—29.

Beer, M.; Kreinovich, V. (2013): Interval or moments: Which carry more information?,  Soft Computing; 17(8): 1319—1327.

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

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.

Stein, M.; Beer, M.; Kreinovich, V. (2013): Bayesian approach for inconsistent information,  Information Sciences; 245: 96—111.

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): 137—151.

Beer, M.; Graf, W.; Kaliske, M. (2012): Safety and robustness assessment of structures with generalized data uncertainty,  GACM Report Summer 2012; 7: 23—28.

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.

Beer, M.; Liebscher, M. (2010): Detection of branching points in noisy processes,  Computational Mechanics; 45(4): 363—374.

Jensen, H. A.; Beer, M. (2010): Discrete-continuous variable structural optimization of systems under stochastic loading,  Structural Safety; 32(5): 293—304.

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.

Beer, M. (2009): Engineering quantification of inconsistent information,  International Journal of Reliability and Safety; 3(1-3): 174—200.

Beer, M.; Spanos, P. D. (2009): A neural network approach for simulating stationary stochastic processes,  Structural Engineering and Mechanics; 32(1): 71—94.

Freitag, S.; Beer, M.; Graf, W.; Kaliske, M. (2009): Lifetime prediction using accelerated test data and neural networks,  Computers & Structures; 87(19): 1187—1194.

Beer, M.; Liebscher, M. (2008): Designing robust structures - A nonlinear simulation based approach,  Computers and Structures; 86(10): 1102—1122.

Möller, B.; Beer, M. (2008): Engineering computation under uncertainty - Capabilities of non-traditional models,  Computers and Structures; 86(10): 1024—1041.

Beer, M. (2007): Model-free sampling,  Structural safety; 29(1): 49—65.

Spanos, P. D.; Beer, M.; Red-Horse, J. (2007): Karhunen–Loéve Expansion of Stochastic Processes with a Modified Exponential Covariance Kernel,  Journal of Engineering Mechanics; 133(7): 773—779.

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.

Möller, B.; Beer, M.; Graf, W.; Sickert, J. U. (2006): Time-dependent reliability of textile-strengthened RC structures under consideration of fuzzy randomness,  Computers and Structures; 84(8-9): 585—603.

Beer, M. (2004): Uncertain structural design based on nonlinear fuzzy analysis,  ZAMM - Zeitschrift fur Angewandte Mathematik und Mechanik; 84(10-11): 740—753.

Möller, B.; Graf, W.; Beer, M. (2004): Discussion on ''Structural reliability analysis through fuzzy number approach, with application to stability'',  Computers and Structures; 2(82): 325—327.

Möller, B.; Graf, W.; Beer, M. (2003): Safety assessment of structures in view of fuzzy randomness,  Computers and Structures; 81(15): 1567—1582.

Möller, B.; Beer, M.; Graf, W.; Hoffmann, A.; Sickert, J. (2000): Modellierung von Unschärfe im Ingenieurbau,  Bauinformatik; 3: 21—25.

Möller, B.; Graf, W.; Beer, M. (2000): Fuzzy-Tragwerksanalyse - Tragwerksanalyse mit unscharfen Parametern,  Bauingenieur; 75(11): 697—708.

Möller, B.; Graf, W.; Beer, M. (2000): Fuzzy structural analysis using α-level optimization,  Computational Mechanics; 26(6): 547—565.

Beer, M.; Graf, W.; Hoffmann, A. (1999): Possibility Theory Based Safety Assessment,  Computer-Aided Civil and Infrastructure Engineering; 14(2): 81—91.