A step forward towards a comprehensive framework for assessing liquefaction land damage vulnerability:Exploration from historical data  

作　　者：Mahmood AHMAD Xiao-Wei TANG Jiang-Nan QIU Feezan AHMAD Wen-Jing GU 

机构地区：[1]State Key Laboratory of Coastal and Ofishore Engineering,Dalian University of Technology,Dalian 116024,China [2]Department of Civil Engineering,University of Engineering and Technology Peshawar(Bannu Campus),Bannu 28100,Pakistan [3]School of Economics&Management,Dalian University of Technology,Dalian 116024,China [4]Deparment of Civil Enginering,Abasyn Universit,Peshawar 25000,Pakistan

出　　处：《Frontiers of Structural and Civil Engineering》2020年第6期1476-1491,共16页结构与土木工程前沿（英文版）

基　　金：The research presented in this paper was part of the research sponsored by the National Key Research&Development Plan of China(Nos.2018YFC1505305 and 2016YFE0200100);Key Program of the National Natural Science Foundation of China(Grant No.51639002);Much gratitude is extended to the experts for their opinions on the BBN model building.

摘　　要：The unprecedented liquefaction-related land damage during earthquakes has highlighted the need to develop a model that better interprets the liquefaction land damage vulnerability(LLDV)when determining whether liquefaction is likely to cause damage at the ground's surface.This paper presents the development of a novel comprehensive framework based on select case history records of cone penetration tests using a Bayesian belief network(BBN)methodology to assess seismic soil liquefaction and liquefaction land damage potentials in one model.The BBN-based LLDV model is developed by integrating multi-related factors of seismic soil liquefaction and its induced hazards using a machine learming(ML)algorithm-K2 and domain knowledge(DK)data fusion methodology.Compared with the C4.5 decision tree-J48 model,naive Bayesian(NB)classifier,and BBN-K2 ML prediction methods in terms of overall accuracy and the Cohen's kappa coefficient,the proposed BBN K2 and DK model has a better performance and provides a substitutive novel LLDV framework for characterizing the vulnerability of land to liquefaction-induced damage.The proposed model not only predicts quantitatively the seismic soil liquefaction potential and its ground damage potential probability but can also identify the main reasons and fault-finding state combinations,and the results are likely to assist in decisions on seismic risk mitigation measures for sustainable development.The proposed model is simple to perform in practice and provides a step toward a more sophisticated liquefaction risk assessment modeling.This study also interprets the BBN model sensitivity analysis and most probable explanation of seismic soil liquefed sites based on an engineering point of view.

关 键 词：Bayesian belief network liquefaction-induced damage potential cone penetration test soil liquefaction structural leaming and domain knowledge 

分 类 号：P315[天文地球—地震学]