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Articles 1 - 2 of 2
Full-Text Articles in Structural Engineering
Machine Learning-Based Data And Model Driven Bayesian Uncertanity Quantification Of Inverse Problems For Suspended Non-Structural System, Zhiyuan Qin
All Dissertations
Inverse problems involve extracting the internal structure of a physical system from noisy measurement data. In many fields, the Bayesian inference is used to address the ill-conditioned nature of the inverse problem by incorporating prior information through an initial distribution. In the nonparametric Bayesian framework, surrogate models such as Gaussian Processes or Deep Neural Networks are used as flexible and effective probabilistic modeling tools to overcome the high-dimensional curse and reduce computational costs. In practical systems and computer models, uncertainties can be addressed through parameter calibration, sensitivity analysis, and uncertainty quantification, leading to improved reliability and robustness of decision and …
Seismic Performance Assessment Of Building Contents: Monetary Losses And Injuries, Sereen Majdalaweyh
Seismic Performance Assessment Of Building Contents: Monetary Losses And Injuries, Sereen Majdalaweyh
All Dissertations
Building contents include all the components that are not attached to the building which the owners place after the construction phase, such as furniture, electrical equipment, glassware, and other personal items. Loss and damage assessment of building contents proved to be challenging in performance-based earthquake engineering frameworks because of the data sparsity. Damages to building contents during an earthquake not only cause monetary losses; tumbling and over-toppling of heavy building contents could result in injuries and even deaths of occupants. While major advancements have been made in performance-based earthquake engineering; however, the focus is mainly on damages and collapse risk …