D. Di Francesco, M. Chryssanthopoulos, Michael Havbro Faber, U. Bharadwaj
{"title":"使用信息分析值对包括暴露风险在内的检验特征进行评价","authors":"D. Di Francesco, M. Chryssanthopoulos, Michael Havbro Faber, U. Bharadwaj","doi":"10.1080/10286608.2021.1887154","DOIUrl":null,"url":null,"abstract":"ABSTRACT All engineering structures degrade or become damaged in service to some extent. Information collection activities, such as inspection or structural health monitoring can reduce uncertainty in probabilistic models of structural condition. By linking the information that they provide to the improved integrity management strategies that they facilitate, their expected value can be quantified. This value of information can be obtained using Bayesian decision analysis. In this work an extended value of information model is presented that accounts for the risk associated with exposure to a hazardous environment. By evaluating this risk on the same scale as the risk of structural failure, the relationship between the expected quality of information and the number of staff-hours in a hazardous environment (such as an offshore oil and gas platform) is investigated. An example case study identifies the requirements regarding the precision, bias, and reliability of information from autonomous or remote inspection methods, for them to be considered as an optimal risk management strategy.","PeriodicalId":50689,"journal":{"name":"Civil Engineering and Environmental Systems","volume":"48 1","pages":"36 - 58"},"PeriodicalIF":1.7000,"publicationDate":"2021-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Evaluation of inspection features including exposure risk using a value of information analysis\",\"authors\":\"D. Di Francesco, M. Chryssanthopoulos, Michael Havbro Faber, U. Bharadwaj\",\"doi\":\"10.1080/10286608.2021.1887154\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT All engineering structures degrade or become damaged in service to some extent. Information collection activities, such as inspection or structural health monitoring can reduce uncertainty in probabilistic models of structural condition. By linking the information that they provide to the improved integrity management strategies that they facilitate, their expected value can be quantified. This value of information can be obtained using Bayesian decision analysis. In this work an extended value of information model is presented that accounts for the risk associated with exposure to a hazardous environment. By evaluating this risk on the same scale as the risk of structural failure, the relationship between the expected quality of information and the number of staff-hours in a hazardous environment (such as an offshore oil and gas platform) is investigated. An example case study identifies the requirements regarding the precision, bias, and reliability of information from autonomous or remote inspection methods, for them to be considered as an optimal risk management strategy.\",\"PeriodicalId\":50689,\"journal\":{\"name\":\"Civil Engineering and Environmental Systems\",\"volume\":\"48 1\",\"pages\":\"36 - 58\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2021-01-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Civil Engineering and Environmental Systems\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1080/10286608.2021.1887154\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Civil Engineering and Environmental Systems","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/10286608.2021.1887154","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
Evaluation of inspection features including exposure risk using a value of information analysis
ABSTRACT All engineering structures degrade or become damaged in service to some extent. Information collection activities, such as inspection or structural health monitoring can reduce uncertainty in probabilistic models of structural condition. By linking the information that they provide to the improved integrity management strategies that they facilitate, their expected value can be quantified. This value of information can be obtained using Bayesian decision analysis. In this work an extended value of information model is presented that accounts for the risk associated with exposure to a hazardous environment. By evaluating this risk on the same scale as the risk of structural failure, the relationship between the expected quality of information and the number of staff-hours in a hazardous environment (such as an offshore oil and gas platform) is investigated. An example case study identifies the requirements regarding the precision, bias, and reliability of information from autonomous or remote inspection methods, for them to be considered as an optimal risk management strategy.
期刊介绍:
Civil Engineering and Environmental Systems is devoted to the advancement of systems thinking and systems techniques throughout systems engineering, environmental engineering decision-making, and engineering management. We do this by publishing the practical applications and developments of "hard" and "soft" systems techniques and thinking.
Submissions that allow for better analysis of civil engineering and environmental systems might look at:
-Civil Engineering optimization
-Risk assessment in engineering
-Civil engineering decision analysis
-System identification in engineering
-Civil engineering numerical simulation
-Uncertainty modelling in engineering
-Qualitative modelling of complex engineering systems