Machine learning-based seismic assessment of framed structures with soil-structure interaction

作     者：Mohamed NOURELDIN Tabish ALI Jinkoo KIM Mohamed NOURELDIN;Tabish ALI;Jinkoo KIM

作者机构：Department of Global Smart CitySungkyunkwan UniversitySuwon 16419Korea 

出 版 物：《Frontiers of Structural and Civil Engineering》 (结构与土木工程前沿（英文版）)

年 卷 期：2023年第17卷第2期

页      面：205-223页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0818[工学-地质资源与地质工程] 0837[工学-安全科学与工程] 0903[农学-农业资源与环境] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by a National Research Foundation of Korea(NRF)grant funded by the Korean government(MSIT)(No.2021R1A2C2006631) 

主　　题：seismic hazard artificial neural network soil-structure interaction seismic analysis 

摘      要：The objective of the current study is to propose an expert system framework based on a supervised machine learning technique(MLT)to predict the seismic performance of low-to mid-rise frame structures considering soil-structure interaction(SSI).The methodology of the framework is based on examining different MLTs to obtain the highest possible accuracy for *** the MLT,a sensitivity analysis was conducted on the main SSI parameters to select the most effective input *** limit state criteria were used for the seismic evaluation within the process.A new global seismic assessment ratio was introduced that considers both serviceability and strength aspects by utilizing three different engineering demand parameters(EDPs).The proposed framework is novel because it enables the designer to seismically assess the structure,while simultaneously considering different EDPs and multiple limit ***,the framework provides recommendations for building component design based on the newly introduced global seismic assessment ratio,which considers different levels of seismic *** proposed framework was validated through comparison using non-linear time history(NLTH)*** results show that the proposed framework provides more accurate results than conventional ***,the generalization potential of the proposed framework was tested by investigating two different types of structural irregularities,namely,stiffness and mass *** results from the framework were in good agreement with the NLTH analysis results for the selected case studies,and peak ground acceleration(PGA)was found to be the most influential input parameter in the assessment process for the case study models *** proposed framework shows high generalization potential for low-to mid-rise structures.