Buchbeiträge
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Zeige Ergebnisse 1 - 11 von 11
Journal-Artikel
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2025
Liu, J., Shi, Y., Ding, C., & Beer, M. (2025). Efficient global sensitivity analysis framework and approach for structures with hybrid uncertainties. Computer Methods in Applied Mechanics and Engineering, 436, Artikel 117726. https://doi.org/10.1016/j.cma.2024.117726
Luo, Y., Dang, C., Broggi, M., & Beer, M. (2025). Stochastic dynamic response analysis via dimension-reduced probability density evolution equation (DR-PDEE) with enhanced tail-accuracy. Probabilistic Engineering Mechanics, 79, Artikel 103735. https://doi.org/10.1016/j.probengmech.2025.103735
Mei, L. F., Yan, W. J., Yuen, K. V., & Beer, M. (2025). Streaming variational inference-empowered Bayesian nonparametric clustering for online structural damage detection with transmissibility function. Mechanical Systems and Signal Processing, 222, Artikel 111767. https://doi.org/10.1016/j.ymssp.2024.111767
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, 433(Part A), Artikel 117490. https://doi.org/10.1016/j.cma.2024.117490
Mo, J., Yan, W. J., Yuen, K. V., & Beer, M. (2025). Enhancing high-dimensional probabilistic model updating: A generic generative model-inspired framework with GAN-embedded implementation. Computer Methods in Applied Mechanics and Engineering, 445, Artikel 118190. https://doi.org/10.1016/j.cma.2025.118190
Moghtaderi, S. H., Thamburaja, P., Jedi, M. A. M., Beer, M., Abdullah, S., & Ariffin, A. K. (2025). Recent Advances of Machine Learning in Fracture Mechanics of Quasi-Brittle Materials: A Review. Jurnal Kejuruteraan, 37(7), 3151-3172. https://doi.org/10.17576/jkukm-2025-37(7)-06
Shi, Y., Liu, C., Beer, M., Huang, H. Z., & Liu, Y. (2025). Response flow graph neural network for capacitated network reliability analysis. Reliability Engineering and System Safety, 262, Artikel 111198. https://doi.org/10.1016/j.ress.2025.111198
Singh, M. J., Yao, K., Lei, T., Liu, S., Zhang, Y., Yao, Z., & Beer, M. (2025). Load-bearing performance and failure behavior of multi-flange deep cement mixing columns. Marine Georesources and Geotechnology. Vorabveröffentlichung online. https://doi.org/10.1080/1064119X.2025.2538816
Song, L. K., Tao, F., Li, X. Q., Yang, L. C., Wei, Y. P., & Beer, M. (2025). Physics-embedding multi-response regressor for time-variant system reliability assessment. Reliability Engineering and System Safety, 263, Artikel 111262. https://doi.org/10.1016/j.ress.2025.111262
Song, J., Liang, Z., Wei, P., & Beer, M. (2025). Sampling-based adaptive Bayesian quadrature for probabilistic model updating. Computer Methods in Applied Mechanics and Engineering, 433(Part A), Artikel 117467. https://doi.org/10.1016/j.cma.2024.117467
Wang, Z., Zhou, X., Bai, Y., Xie, C., Tan, Y., & Beer, M. (2025). Ori-kirigami modules for constructing multistable systems and deployable engineering structures. Physical Review B, 112(10), Artikel 104109. https://doi.org/10.1103/9w8d-mwgt
Wang, R., Chen, G., Liu, Y., & Beer, M. (2025). Seismic Reliability Assessment Framework for Unsaturated Soil Slope under Near-Fault Pulse-Like Ground Motion. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 11(2), Artikel 04025005. https://doi.org/10.1061/AJRUA6.RUENG-1227
Zhang, Y., Dang, C., Xu, J., & Beer, M. (2025). Output probability distribution estimation of stochastic static and dynamic systems using Laplace transform and maximum entropy. Computer Methods in Applied Mechanics and Engineering, 439, Artikel 117887. https://doi.org/10.1016/j.cma.2025.117887
Zhang, K., Chen, N., Liu, J., & Beer, M. (2025). Uncertainty characterization and propagation analysis for pneumatic soft acoustic metamaterial system. Mechanical Systems and Signal Processing, 232, Artikel 112722. https://doi.org/10.1016/j.ymssp.2025.112722
Zheng, Z., Dai, H., Beer, M., & Nackenhorst, U. (2025). Simulation of parameterized random fields, Part I: Gaussian cases. Mechanical Systems and Signal Processing, 238, Artikel 113215. https://doi.org/10.1016/j.ymssp.2025.113215
Zheng, Z., Dai, H., Beer, M., & Nackenhorst, U. (2025). Simulation of parameterized random fields, Part II: Non-Gaussian cases. Mechanical Systems and Signal Processing, 240, Artikel 113386. https://doi.org/10.1016/j.ymssp.2025.113386
Zhou, T., Zhu, X., Guo, T., Dong, Y., & Beer, M. (2025). Multi-point Bayesian active learning reliability analysis. Structural safety, 114, Artikel 102557. https://doi.org/10.1016/j.strusafe.2024.102557
2024
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, Artikel 111078. https://doi.org/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 sampling. Probabilistic Engineering Mechanics, 75, Artikel 103592. https://doi.org/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, 10(3), Artikel 04024034. https://doi.org/10.1061/AJRUA6.RUENG-1219
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