Publications of Prof. Dr.-Ing. Michael Beer

Book Chapter

  • Beer, M. (2023): Fuzzy Probability TheoryLin, 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 EngineeringLiu, 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 LearningRabczuk, 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 TreatmentIn: 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
  • Julian Salomon, Jasper Behrensdorf, Michael Beer (2022): Resilienz baulicher Infrastruktur - sicher und wirtschaftlicher durch Dick und Dünn26. Dresdner Baustatik - Seminar – „Realität-Modellierung-Tragwerksplanung“, Institut für Statik und Dynamik der Tragwerke, TU Dresden
    ISSN: 1615-9705
  • Beer, M. (2021): Fuzzy Probability TheoryIn: 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 SystemsIn: 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: ChallengesIn: 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

Journal Articles

  • Behrendt, M.; Dang, C.; Beer, M. (2024): Data-driven and physics-based interval modelling of power spectral density functions from limited dataMechanical Systems and Signal Processing, 208, Article 111078
    DOI: 10.1016/j.ymssp.2023.111078
  • 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 samplingProbabilistic 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 FunctionsASCE-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 signalsMechanical Systems and Signal Processing, 211, Article 111210
    DOI: 10.1016/j.ymssp.2024.111210
  • Brandt, J.; Iversen, T.; Eckert, C.; Peterssen, F.; Bensmann, B.; Bensmann, A.; Beer, M.; Weyer, H.; Hanke-Rauschenbach, R. (2024) (2024): Cost and competitiveness of green hydrogen and the effects of the European Union regulatory frameworkNature Energy, in press
  • Dang, C.; Beer, M. (2024): Semi-Bayesian active learning quadrature for estimating extremely low failure probabilitiesReliability 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 methodProbabilistic 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 probabilitiesComputer 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 estimationReliability 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 transformASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, in press.
    DOI: 10.1061/AJRUA6/RUENG-1169
  • 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 ReviewASCE Open: Multidisciplinary Journal of Civil Engineering, in press.
  • Grashorn, J.; Broggi, M.; Ludovic, C.; Beer, M. (2024): Efficiency comparison of MCMC and Transport Map Bayesian posterior estimation for structural health monitoringMechanical Systems and Signal Processing, in press.
  • Hong, F.Q.; Wei, P.F.; Beer, M. (2024): Parallelization of Adaptive Bayesian Cubature Using Multimodal Optimization AlgorithmsEngineering Computations, in press.
  • Hong, F.Q; Wei, P.F.; Fu, J.F.; Beer, M. (2024): A sequential sampling-based Bayesian numerical method for reliability-based design optimizationReliability 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 probabilitiesStructural 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 loadsProbabilistic 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 loadsMechanical 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 frameworkReliability Engineering and System Safety, 242, Article 109771
    DOI: 10.1016/j.ress.2023.109771
  • 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 normReliability 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 modelInternational 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 modelFatigue & Fracture of Engineering Materials & Structures, in press.
  • 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 FaultsMechanical Systems and Signal Processing, 210, Article 111142
  • 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 strengthInternational Journal of Geomechanics, in press.
  • Liu, J.X.; Shi, Y.; Chen, D.; Beer, M. (2024): Hybrid uncertainty propagation based on multi-fidelity surrogate modelComputers 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-PDEMEarthquake Engineering & Structural Dynamics, 53(5), 1677-1929
    DOI: 10.1002/eqe.4093
  • 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 surveyInternational 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 ExpertsArchitectural Engineering and Design Management TAEM, 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 TechniquesReliability Engineering and System Safety, 242, Article 109806
    DOI: 10.1016/j.ress.2023.109806
  • Wang, C.; Beer, M.; Faes. M.G.R.; Feng, D.C. (2024): Resilience assessment under imprecise probabilityASCE-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 probabilitiesReliability Engineering and System Safety, 244, Article 109953
  • 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 uncertaintyComputers 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 loadingEarthquake 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 MonitoringJournal of Wind Engineering & Industrial Aerodynamics, 247, Article 105679
    DOI: 10.1016/j.jweia.2024.105679
  • 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 mechanismJournal 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 systemsMechanical Systems and Signal Processing, 209, Article 111105
    DOI: 10.1016/j.ymssp.2024.111105
  • Zheng, Z.B.; Beer, M.; Nackenhorst, U. (2024): Efficient stochastic modal decomposition methods for structural stochastic static and dynamic analysesInternational Journal for Numerical Methods in Engineering, in press
  • Zhou, T.; Guo, T.; Dang, C.; Beer, M. (2024): Bayesian reinforcement learning reliability analysisComputer 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 LearningMechanical 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 bandgapMechanics 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 multistabilityPhysical 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 transformASCE-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 quantificationMechanical 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 TutorialMechanical 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 excitationMechanical 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 methodStructural 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 motionApplied 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 tunnelEngineering 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 measureEarthquake 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 motionEarthquake 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 dataEarthquake 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 processesMechanical 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 modelProbabilistic 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 systemsJournal 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 observationsMechanical 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 treatmentStructural 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 algorithmComputer 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 approachMechanical 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 uncertaintiesComputers 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 momentsJournal 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 degradationMechanical 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 engineJournal 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 systemsProceedings 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 PerspectiveProbabilistic 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 UncertaintiesComputer 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 MethodASCE-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 processesMechanical 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 ParametersJournal 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 NGBNEngineering 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 MethodASCE-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 analysisActa 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 MachinesReliability 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 CorrelationMechanical 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 ApproximationMechanical 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 excitationMechanical 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 samplingStructural 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 SurveyInternational 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 optimizationStructural 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 uncertaintiesMechanical 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 informationMechanical 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 ClimateASCE 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 MonitoringComputers 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 algorithmProbabilistic 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 OptimizationDisaster 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 systemsMechanical Systems and Signal Processing, 200, Article 110609.
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    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 StatesInternational 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 samplingStructural 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 AnalysisMechanical 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 samplingComputer 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 VariablesStructural 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 analysisASCE-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 UncertaintyMechanical 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 IntegrationComputer 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 FunctionsMechanical 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 spaceStructural 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 AnalysisMathematical Structures and Modeling, 3(51), 97–104.
  • Behrensdorf, J.; Broggi, M.; Beer, M. (2019): Reliability analysis of networks interconnected with copulasASCE-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 analysisMechanical 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 buildingsMechanical 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 parametersMechanical 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 dataMechanical 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 modelsASCE-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 excitationNonlinear 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 FailuresProceedings 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 NetworksPeriodica 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 approachesUnderground 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 SignatureASCE-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 systemsMechanical 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 SystemsASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 6(2), Article 020901. | File |
    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’ OverviewAdministrative 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 variablesMechanical 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 SpectrumASCE 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 FunctionASCE'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 analysisMechanical 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 estimationMechanical 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 approachSoils 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 examplesReliability 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 modelJournal 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 updatingMechanical 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 uncertaintiesComputer 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 assessmentEuropean 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 measurementsInternational 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 spectraStructural 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 NetworksAdvances 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 informationComputers 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 ExampleSafety Science, 106: 230-243.
  • Zhang, Y.; Kim, C.-W.; Beer, M.; Dai, H.L.; Soares, C.G. (2018): Modeling multivariate ocean data using asymmetric copulasCoastal 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 dataMechanical 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 farmsMechanical 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 projectsConstruction 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 ProjectsASCE-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 ParametersInternational 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 dataComputers 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 InspectionsASCE-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 fittingStructural 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 loadASCE 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 communicationSafety 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 studiesSafety 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 loadsRussian 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 ChangeASCE-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 hazardsStochastic 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 loadASCE 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 corrosionStructural 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 dataASCE-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 representationsMechanical 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 parametersInternational 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 signatureReliability 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 eccentricityASCE'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 ExplanationJournal 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 designStructural 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 excitationJournal 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 designSafety 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 variablesComputers 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 dataProbabilistic 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 dataStructural Safety; 52: 150-160.
  • Comerford, L.; Kougioumtzoglou, I. a.; Beer, M. (2015): Uncertainty Quantification in Power Spectrum Estimation of Stochastic Processes Subject to Missing DataInternational Journal of Sustainable Materials and Structural Systems (IJSMSS).
  • de Angelis, M.; Patelli, E.; Beer, M. (2015): Advanced Line Sampling for efficient robust reliability analysisStructural 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 failureEngineering Structures; 98: 74-80.
  • Kougioumtzoglou, I. A.; Zhang, Y.; Beer, M. (2015): Softening Duffing Oscillator Reliability Assessment Subject to Evolutionary Stochastic ExcitationASCE-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 InformationASCE-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 structuresComputers & 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 spacesProbabilistic Engineering Mechanics; 38: 42—53.
  • Beer, M.; Ferson, S.; Kreinovich, V. (2013): Imprecise probabilities in engineering analysesMechanical 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 contextStructural 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 deviationSoft Computing; 17(8): 1415—1423.
  • Stein, M.; Beer, M.; Kreinovich, V. (2013): Bayesian approach for inconsistent informationInformation 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 methodMechanical Systems and Signal Processing; 37(1): 137—151.
  • Beer, M.; Graf, W.; Kaliske, M. (2012): Safety and robustness assessment of structures with generalized data uncertaintyGACM 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 ErrorsJournal of engineering mechanics; 138(11): 1326—1338.
  • Beer, M.; Liebscher, M. (2010): Detection of branching points in noisy processesComputational Mechanics; 45(4): 363—374.
  • Jensen, H. A.; Beer, M. (2010): Discrete-continuous variable structural optimization of systems under stochastic loadingStructural 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 corrosionStructural Safety; 32(6): 425—432.
  • Beer, M. (2009): Engineering quantification of inconsistent informationInternational Journal of Reliability and Safety; 3(1-3): 174—200.
  • Beer, M.; Spanos, P. D. (2009): A neural network approach for simulating stationary stochastic processesStructural Engineering and Mechanics; 32(1): 71—94.
  • Freitag, S.; Beer, M.; Graf, W.; Kaliske, M. (2009): Lifetime prediction using accelerated test data and neural networksComputers & Structures; 87(19): 1187—1194.
  • Beer, M.; Liebscher, M. (2008): Designing robust structures - A nonlinear simulation based approachComputers and Structures; 86(10): 1102—1122.
  • Möller, B.; Beer, M. (2008): Engineering computation under uncertainty - Capabilities of non-traditional modelsComputers and Structures; 86(10): 1024—1041.
  • Beer, M. (2007): Model-free samplingStructural 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 KernelJournal of Engineering Mechanics; 133(7): 773—779.
  • Graf, W.; Möller, B.; Beer, M. (2006): Zum Einfluss der Datenbasis auf Tragwerkssicherheit und VersagensrisikoWissenschaftliche 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 randomnessComputers and Structures; 84(8-9): 585—603.
  • Beer, M. (2004): Uncertain structural design based on nonlinear fuzzy analysisZAMM - 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 randomnessComputers and Structures; 81(15): 1567—1582.
  • Möller, B.; Beer, M.; Graf, W.; Hoffmann, A.; Sickert, J. (2000): Modellierung von Unschärfe im IngenieurbauBauinformatik; 3: 21—25.
  • Möller, B.; Graf, W.; Beer, M. (2000): Fuzzy-Tragwerksanalyse - Tragwerksanalyse mit unscharfen ParameternBauingenieur; 75(11): 697—708.
  • Möller, B.; Graf, W.; Beer, M. (2000): Fuzzy structural analysis using α-level optimizationComputational Mechanics; 26(6): 547—565.
  • Beer, M.; Graf, W.; Hoffmann, A. (1999): Possibility Theory Based Safety AssessmentComputer-Aided Civil and Infrastructure Engineering; 14(2): 81—91.