Epistemic Uncertainty Treatment Using Group Method of Data Handling Algorithm in Seismic Collapse Fragility

Abstract

Developing fragility functions is the essential step in incorporating important uncertainties in next-generation performance-based earthquake engineering (PBEE) methodology. The present paper is aimed to involve record-to-record variability as well as modelling uncertainty sources in developing the fragility curves at the collapse limit state. In this article, in order to reduce the dispersion of uncertainties, Group Method of Data Handling (GMDH) in combination with Monte Carlo Simulation (MCS) is used to develop structural collapse fragility curve, considering effects of epistemic and aleatory uncertainties. A Steel Moment Resisting Frame (SMRF) is chosen as the tested structure. The fragility curves obtained by the proposed method which belongs to GMDH approaches are compared with those resulted from simple and well-known available methods such as First-Order Second-Moment (FOSM), Approximate Second-Order Second-Moment (ASOSM) and Monte Carlo (MC)/Response Surface Method (RSM), somehow, as an accurate method. The results of the application of the proposed approach indicate increasing accuracy and precision of the outputs as well as power with the same computational time compared to aforementioned methods. The GMDH method introduced here can be applied to the other performance levels.

A Comprehensive Evaluation of Tuned Vertical Isolation System for Seismic Risk Mitigation

“…In the realm of seismic behavior and risk assessment, providing second layer of control to the system also leads to a significant stride in addressing uncertainties inherent in seismic events (Karimi Ghaleh Jough & Ghasemzadeh, 2023). The dynamic and unpredictable nature of seismic behavior necessitates a nuanced understanding of uncertainties, a focal point explored in many researches (Babaei & Zarfam, 2019;Karimi Ghaleh Jough & Beheshti Aval, 2018;Karimi Ghaleh Jough & Şensoy, 2020;Karimi Ghaleh Jough et al, 2021;Dithurson et al 2023).…”