Book Chapter
Showing results 1 - 11 out of 11
Journal Articles
Showing results 81 - 100 out of 319
2023
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. 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, Article 116274. 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. 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, Article 103482. 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. 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, Article 109730. 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, Article 116068. 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, Article 102351. 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, Article 109775. 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, Article 105060. 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, Article 109896. 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
Grashorn, J., Urrea-Quintero, J.-H., Broggi, M., Chamoin, L., & Beer, M. (2023). Transport map Bayesian parameter estimation for dynamical systems. PAMM - Proceedings in Applied Mathematics and Mechanics, 23(1). https://doi.org/10.1002/pamm.202200136
Hong, F., Wei, P., Song, J., Valdebenito, M. A., Faes, M. G. R., & Beer, M. (2023). Collaborative and Adaptive Bayesian Optimization for bounding variances and probabilities under hybrid uncertainties. Computer Methods in Applied Mechanics and Engineering, 417, Article 116410. https://doi.org/10.1016/j.cma.2023.116410
Hong, F., Wei, P., Song, J., Faes, M. G. R., Valdebenito, M. A., & Beer, M. (2023). Combining data and physical models for probabilistic analysis: A Bayesian Augmented Space Learning perspective. Probabilistic Engineering Mechanics, 73, Article 103474. https://doi.org/10.1016/j.probengmech.2023.103474
Hong, X., Song, Y., Kong, F., & Beer, M. (2023). The Typhoon Wind Hazard Assessment Considering the Correlation among the Key Random Variables Using the Copula Method. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 9(2), Article 04023013. https://doi.org/10.1061/AJRUA6.RUENG-1018
Jiang, Y., Li, Z., Zhou, H., Wang, F., Beer, M., & Zheng, J. (2023). Reliability Evaluation of RC Columns with Wind-Dominated Combination Considering Random Biaxial Eccentricity. Journal of Structural Engineering (United States), 149(1), Article 06022007. https://doi.org/10.1061/(ASCE)ST.1943-541X.0003507
