Book Chapter
Showing results 1 - 11 out of 11
Journal Articles
Showing results 161 - 180 out of 313
2022
Yang, L., Bi, S., Faes, M. G. R., Broggi, M., & Beer, M. (2022). Bayesian inversion for imprecise probabilistic models using a novel entropy-based uncertainty quantification metric. Mechanical Systems and Signal Processing, 162, Article 107954. https://doi.org/10.1016/j.ymssp.2021.107954
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(391), Article 114516. https://doi.org/10.1016/j.cma.2021.114516
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. https://doi.org/10.1016/j.ress.2022.108794
Zhang, H., Bittner, M., & Beer, M. (2022). Method to generate artificial earthquake accelerations with time domain enhancement and attenuation characteristics. Ain Shams Engineering Journal, 13(3), Article 101606. https://doi.org/10.1016/j.asej.2021.09.031
Zhang, H., Bittner, M., & Beer, M. (2022). Seismic Response Meta-model of High-Rise Fame Structure Based on Time-Delay Neural Network. KSCE journal of civil engineering, 26(5), 2273-2294. https://doi.org/10.1007/s12205-022-0878-7
Zheng, Z., Beer, M., & Nackenhorst, U. (2022). An efficient reduced-order method for stochastic eigenvalue analysis. International Journal for Numerical Methods in Engineering, 123(23), 5884-5906. https://doi.org/10.1002/nme.7092
Zheng, Z., Beer, M., Dai, H., & 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. https://doi.org/10.1016/j.cma.2022.115360
2021
Bai, Y., Li, Y., Tang, Z., 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, 19(6), 2457-2482. https://doi.org/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 & system
safety, 216, Article 107935. https://doi.org/10.1016/j.ress.2021.107935
Bi, S., Beer, M., Zhang, J., 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. https://doi.org/10.1115/1.4050168
Dang, X. C., Wei, P., & Beer, M. (2021). An approach to evaluation of EVD and small failure probabilities of uncertain nonlinear structures under stochastic seismic excitations. Mechanical Systems and Signal Processing, 152, Article 107468. https://doi.org/10.1016/j.ymssp.2020.107468
Dang, C., Wei, P., Song, J., & 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. https://doi.org/10.1061/AJRUA6.0001179
Faes, M. G. R., Valdebenito, M. A., Yuan, X., Wei, P., & Beer, M. (2021). Augmented reliability analysis for estimating imprecise first excursion probabilities in stochastic linear dynamics. Advances in Engineering Software, 155, Article 102993. https://doi.org/10.1016/j.advengsoft.2021.102993
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. https://doi.org/10.1016/j.strusafe.2021.102092
Faes, M. G. R., 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. https://doi.org/10.1016/j.ymssp.2020.107482
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. https://doi.org/10.1615/Int.J.UncertaintyQuantification.2021033543
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. https://doi.org/10.1016/j.cma.2020.113487
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. https://doi.org/10.1016/j.ymssp.2021.107834
K C, S., Kumar, M., & Beer, M. (2021). Classical and Bayesian estimation of stress-strength reliability of a component having multiple states. International Journal of Quality and Reliability Management, 38(2), 528-535. https://doi.org/10.1108/IJQRM-01-2020-0009
Kitahara, M., Bi, S., 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 0001149. https://doi.org/10.1061/AJRUA6.0001149
