Towards rapid and automated vulnerability classification of concrete buildings

作     者：Lissette Iturburu Jean Kwannandar Shirley J.Dyke Xiaoyu Liu Xin Zhang Julio Ramirez Lissette Iturburu;Jean Kwannandar;Shirley J.Dyke;Xiaoyu Liu;Xin Zhang;Julio Ramirez

作者机构：Lyles School of Civil EngineeringPurdue UniversityWest LafayetteIN 47907United States School of Mechanical EngineeringPurdue UniversityWest LafayetteIN 47907United States 

出 版 物：《Earthquake Engineering and Engineering Vibration》 (地震工程与工程振动（英文刊）)

年 卷 期：2023年第22卷第2期

页      面：309-332页

核心收录：

学科分类：07[理学] 08[工学] 081402[工学-结构工程] 070503[理学-地图学与地理信息系统] 0708[理学-地球物理学] 0705[理学-地理学] 0814[工学-土木工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：US National Science Foundation under Grant No.NSF-OAC-1835473。 

主　　题：object detection segmentation U-Net vulnerability hazards earthquakes reinforced concrete building inventories and databases 

摘      要：With the overwhelming number of older reinforced concrete buildings that need to be assessed for seismic vulnerability in a city,local governments face the question of how to assess their building inventory.By leveraging engineering drawings that are stored in a digital format,a well-established method for classification reinforced concrete buildings with respect to seismic vulnerability,and machine learning techniques,we have developed a technique to automatically extract quantitative information from the drawings to classify vulnerability.Using this technique,stakeholders will be able to rapidly classify buildings according to their seismic vulnerability and have access to information they need to prioritize a large building inventory.The approach has the potential to have significant impact on our ability to rapidly make decisions related to retrofit and improvements in our communities.In the Los Angeles County alone it is estimated that several thousand buildings of this type exist.The Hassan index is adopted here as the method for automation due to its simple application during the classification of the vulnerable reinforced concrete buildings.This paper will present the technique used for automating information extraction to compute the Hassan index for a large building inventory.