Takeshi Kitahara, email@example.com
Kanto Gakuin University
Yan-Gang Zhao, firstname.lastname@example.org
Siu-Kui Au, email@example.com
Nanyang Technological University
Yasutoshi Nomura, firstname.lastname@example.org
Model identification and structural reliability analysis considering damage and aging have become increasingly hot research topics. Despite many achievements in theoretical and computational techniques, the lack of accurate and reliable techniques for interpreting or measuring data remains a challenge in the structural dynamic problems under seismic excitations. In the process of data collection, modeling, and analysis, combined uncertainties, such as aleatory and epistemic uncertainty, arises due to sensing noise, modeling error, surrounding environment, and lack of knowledge. Therefore, quantifying the uncertainties leads to improving the robustness and accuracy for assessing the seismic performance of existing structures. In this MS, possible topics of interest include but are not limited to: probabilistic modeling, filtering techniques, stochastic techniques, Bayesian approach, imprecise probability, aleatory and/or epistemic uncertainty, model updating, structural health monitoring, etc.