{"title":"从观测数据中识别和估计桥梁故障的因果效应","authors":"Aybike Özyüksel Çiftçioğlu , M.Z. Naser","doi":"10.1016/j.iintel.2023.100068","DOIUrl":null,"url":null,"abstract":"<div><p>This paper presents a causal analysis aimed at identifying and estimating causal effects with regard to bridge failures under extreme events. Observational data on about 299 bridge incidents were used to conduct this causal investigation and examine bridges’ performance. As causal investigations can also deliver counterfactual assessments of parallel worlds, a causal analysis can serve as a high-merit methodology to evaluate the performance of critical bridges. Our findings quantify the causal impacts of various factors spanning the characteristics of bridges, traffic demands, and incident type (i.e., fire, high wind, scour/flood, earthquake, and impact/collision). More specifically, our analysis reveals high causal effects related to the used structural system, construction materials, and demand served.</p></div>","PeriodicalId":100791,"journal":{"name":"Journal of Infrastructure Intelligence and Resilience","volume":"3 1","pages":"Article 100068"},"PeriodicalIF":0.0000,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772991523000439/pdfft?md5=99c0fa84cbc6713a8fe4c4d18727f3a6&pid=1-s2.0-S2772991523000439-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Identifying and estimating causal effects of bridge failures from observational data\",\"authors\":\"Aybike Özyüksel Çiftçioğlu , M.Z. Naser\",\"doi\":\"10.1016/j.iintel.2023.100068\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This paper presents a causal analysis aimed at identifying and estimating causal effects with regard to bridge failures under extreme events. Observational data on about 299 bridge incidents were used to conduct this causal investigation and examine bridges’ performance. As causal investigations can also deliver counterfactual assessments of parallel worlds, a causal analysis can serve as a high-merit methodology to evaluate the performance of critical bridges. Our findings quantify the causal impacts of various factors spanning the characteristics of bridges, traffic demands, and incident type (i.e., fire, high wind, scour/flood, earthquake, and impact/collision). More specifically, our analysis reveals high causal effects related to the used structural system, construction materials, and demand served.</p></div>\",\"PeriodicalId\":100791,\"journal\":{\"name\":\"Journal of Infrastructure Intelligence and Resilience\",\"volume\":\"3 1\",\"pages\":\"Article 100068\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2772991523000439/pdfft?md5=99c0fa84cbc6713a8fe4c4d18727f3a6&pid=1-s2.0-S2772991523000439-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Infrastructure Intelligence and Resilience\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2772991523000439\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Infrastructure Intelligence and Resilience","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772991523000439","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Identifying and estimating causal effects of bridge failures from observational data
This paper presents a causal analysis aimed at identifying and estimating causal effects with regard to bridge failures under extreme events. Observational data on about 299 bridge incidents were used to conduct this causal investigation and examine bridges’ performance. As causal investigations can also deliver counterfactual assessments of parallel worlds, a causal analysis can serve as a high-merit methodology to evaluate the performance of critical bridges. Our findings quantify the causal impacts of various factors spanning the characteristics of bridges, traffic demands, and incident type (i.e., fire, high wind, scour/flood, earthquake, and impact/collision). More specifically, our analysis reveals high causal effects related to the used structural system, construction materials, and demand served.