Buchbeiträge
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Journal-Artikel
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2023
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, Artikel 110072. Vorabveröffentlichung online. https://doi.org/10.1016/j.ymssp.2022.110072
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), Artikel 04023022. Vorabveröffentlichung online. https://doi.org/10.1061/AJRUA6.RUENG-1048
Bi, S., Beer, M., Cogan, S., & Mottershead, J. (2023). Stochastic Model Updating with Uncertainty Quantification: An Overview and Tutorial. Mechanical Systems and Signal Processing, 204, Artikel 110784. Vorabveröffentlichung online. https://doi.org/10.1016/j.ymssp.2023.110784
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, Artikel 110873. Vorabveröffentlichung online. https://doi.org/10.1016/j.ymssp.2023.110873
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, Artikel 102330. Vorabveröffentlichung online. https://doi.org/10.1016/j.strusafe.2023.102330
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, Artikel 110573. Vorabveröffentlichung online. https://doi.org/10.1016/j.ymssp.2023.110573
Chen, G., Yang, J., 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. https://doi.org/10.1002/eqe.3752
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(7), 2179-2195. https://doi.org/10.1002/eqe.3877
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, Artikel 116274. Vorabveröffentlichung online. https://doi.org/10.1016/j.engstruct.2023.116274
Chen, G., Liu, Y., & Beer, M. (2023). Identification of near-fault multi-pulse ground motion. Applied mathematical modelling, 117, 609-624. Vorabveröffentlichung online. https://doi.org/10.1016/j.apm.2023.01.002
Chen, G., Yang, J., Wang, R., Li, K., Liu, Y., & Beer, M. (2023). Seismic damage analysis due to near-fault multipulse ground motion. Earthquake Engineering and Structural Dynamics, 52(15), 5099-5116. https://doi.org/10.1002/eqe.4003
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, Artikel 103482. Vorabveröffentlichung online. https://doi.org/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, 15(12), 3291-3304. Vorabveröffentlichung online. https://doi.org/10.1016/j.jrmge.2023.05.009
Dai, H., Zhang, R., & Beer, M. (2023). A new method for stochastic analysis of structures under limited observations. Mechanical Systems and Signal Processing, 185, Artikel 109730. Vorabveröffentlichung online. https://doi.org/10.1016/j.ymssp.2022.109730
Dang, C., Valdebenito, M. A., Song, J., Wei, P., & Beer, M. (2023). Estimation of small failure probabilities by partially Bayesian active learning line sampling: Theory and algorithm. Computer Methods in Applied Mechanics and Engineering, 412, Artikel 116068. Vorabveröffentlichung online. https://doi.org/10.1016/j.cma.2023.116068
Dang, C., Valdebenito, M. A., Faes, M. G. R., Song, J., Wei, P., & Beer, M. (2023). Structural reliability analysis by line sampling: A Bayesian active learning treatment. Structural safety, 104, Artikel 102351. Vorabveröffentlichung online. https://doi.org/10.1016/j.strusafe.2023.102351
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, Artikel 109775. Vorabveröffentlichung online. https://doi.org/10.15488/12761, https://doi.org/10.1016/j.ymssp.2022.109775
Feng, C., Faes, M., Broggi, M., Dang, C., Yang, J., Zheng, Z., & Beer, M. (2023). Application of interval field method to the stability analysis of slopes in presence of uncertainties. Computers and geotechnics, 153, Artikel 105060. Vorabveröffentlichung online. https://doi.org/10.1016/j.compgeo.2022.105060
Feng, K., Ji, J. C., Zhang, Y., Ni, Q., Liu, Z., & Beer, M. (2023). Digital twin-driven intelligent assessment of gear surface degradation. Mechanical Systems and Signal Processing, 186, Artikel 109896. Vorabveröffentlichung online. https://doi.org/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. https://doi.org/10.33737/jgpps/160055
