Assessment of fuzzy global seismic vulnerability for RC structures. (1st October 2022) - Guo, Mengxue; Huang, Hua; Xue, Chunliang; Huang, Min
Abstract : This paper proposed a fuzzy global seismic vulnerability analysis framework to investigate the effect of stochastic uncertainty and epistemic uncertainty for RC structures simulated by Monte Carlo simulation (MCS) and OpenSeesPy. The classical probability model was used to describe the stochastic uncertainty in fuzzy-random variables (model design parameters). The epistemic uncertainties in the probability model parameters and performance level threshold values were portrayed by incorporating triangle fuzzy numbers. Meanwhile, the vine copula-based global vulnerability curves were obtained by R-Packages to reflect that the dependence configuration between each component-level seismic response. The results showed that the global vulnerability can be accurately simulated by the selected d -vine structure and situated between the upper and lower bounds. The third floor can be regarded as the least fragile component under all performance levels in the case of perfectly independence, and the pair-copula model C34 consisted of the third and fourth floors showed a sensitive seismic response. Moreover, epistemic uncertainties showed different effects on the global vulnerability for RC structures under four limit states. The vulnerability curves considering fuzzy performance level and distribution parameters included a wider interval. The framework provided a practical approach for engineers and researchers to be informed of how stochastic, epistemic uncertainties, and dependence configuration affect global seismic vulnerability, facilitating the structure design, decision-making, and post-earthquake rehabilitation. Highlights: A novel fuzzy global seismic vulnerability analysis framework was proposed to study the uncertainty effect for RC frame. Stochastic uncertainty in the ground motion and structure model was describe by IDA analysis and the probability model. Epistemic uncertainty in the probability model parameter and limit state were portrayed by the triangle fuzzy number. The global vulnerability of RC structures can be accurately simulated by the selected D-vine structure and parameters.