Book Chapter
Showing results 1 - 11 out of 11
Journal Articles
Showing results 61 - 80 out of 313
2024
You, Z., Miao, H., Shi, Y., & Beer, M. (2024). Improving the performance of low-frequency magnetic energy harvesters using an internal magnetic-coupled mechanism. Journal of applied physics, 135(8), Article 084101. https://doi.org/10.1063/5.0195091
Yuan, P., Yuen, K. V., Beer, M., Cai, C. S., & Yan, W. (2024). A non-iterative partitioned computational method with the energy conservation property for time-variant dynamic systems. Mechanical Systems and Signal Processing, 209, Article 111105. https://doi.org/10.1016/j.ymssp.2024.111105
Zhang, Y., Dong, Y., & Beer, M. (2024). rLSTM-AE for dimension reduction and its application to active learning-based dynamic reliability analysis. Mechanical Systems and Signal Processing, 215, Article 111426. https://doi.org/10.1016/j.ymssp.2024.111426
Zhao, Y., Sun, B., Bi, S., Beer, M., & Moens, D. (2024). A sub-convex similarity-based model updating method considering multivariate uncertainties. Engineering structures, 318, Article 118752. https://doi.org/10.1016/j.engstruct.2024.118752
Zheng, Z., Beer, M., & Nackenhorst, U. (2024). Efficient stochastic modal decomposition methods for structural stochastic static and dynamic analyses. International Journal for Numerical Methods in Engineering, 125(12), Article e7469. https://doi.org/10.1002/nme.7469
Zhou, T., Guo, T., Dang, C., & Beer, M. (2024). Bayesian reinforcement learning reliability analysis. Computer Methods in Applied Mechanics and Engineering, 424, Article 116902. https://doi.org/10.1016/j.cma.2024.116902
Zhuang, J., Jia, M., Huang, C. G., Beer, M., & Feng, K. (2024). Health prognosis of bearings based on transferable autoregressive recurrent adaptation with few-shot learning. Mechanical Systems and Signal Processing, 211, Article 111186. https://doi.org/10.1016/j.ymssp.2024.111186
2023
Bai, Y., Li, X., Zhou, X., Li, P., & Beer, M. (2023). Soil-expended seismic metamaterial with ultralow and wide bandgap. Mechanics of materials, 180, Article 104601. https://doi.org/10.1016/j.mechmat.2023.104601
Bai, Y., Wang, S., Zhou, X., & Beer, M. (2023). Three-dimensional ori-kirigami metamaterials with multistability. Physical Review E, 107(3), Article 035004. https://doi.org/10.1103/PhysRevE.107.035004
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, Article 110072. 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), Article 04023022. 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, Article 110784. 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, Article 110873. 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, Article 102330. 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, 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
