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    Quantifying the Uncertainty of Structural Parameters Using Machine Learning–Based Surrogate Models 

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2025:;Volume ( 011 ):;issue: 002:;page 04025023-1
    Author(s): Jiawei Gao; Ke Du; Jing Qi
    Publisher: American Society of Civil Engineers
    Abstract: Uncertainty quantification is crucial for accurately assessing the seismic vulnerability of structures in performance-based earthquake engineering (PBEE). Traditional methods, such as the first order second moment (FOSM) ...
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    Comparative Seismic Performance Assessment of Reinforced Concrete Frame Structures with and without Structural Enhancements Using the FEMA P-58 Methodology 

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2021:;Volume ( 007 ):;issue: 004:;page 04021047-1
    Author(s): Ke Du; Wen Bai; Jiulin Bai; Deng Yan; Maosheng Gong; Jingjiang Sun
    Publisher: ASCE
    Abstract: Adding energy dissipation devices to reinforced concrete (RC) frame structures is a commonly adopted structural enhancement in seismically active regions. In this paper, a state-of-the-art seismic performance assessment ...
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