Pub Date : 2023-03-01DOI: 10.1061/ajrua6.rueng-967
Ketan Kumar Sengar, S. Saha, Maheshreddy Gade
{"title":"Vector-Valued Intensity Measures for Seismic Risk Assessment of Base-Isolated Liquid Storage Tanks","authors":"Ketan Kumar Sengar, S. Saha, Maheshreddy Gade","doi":"10.1061/ajrua6.rueng-967","DOIUrl":"https://doi.org/10.1061/ajrua6.rueng-967","url":null,"abstract":"","PeriodicalId":48571,"journal":{"name":"Asce-Asme Journal of Risk and Uncertainty in Engineering Systems Part A-Civil Engineering","volume":"16 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84346111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1061/ajrua6.rueng-976
Mahdi Shadabfar, M. Mahsuli, Ya-dong Xue, Yi Zhang, Chenglong Wu
{"title":"Time-Variant System Reliability Analysis of Concrete Sewer Pipes under Corrosion Considering Multiple Failure Modes","authors":"Mahdi Shadabfar, M. Mahsuli, Ya-dong Xue, Yi Zhang, Chenglong Wu","doi":"10.1061/ajrua6.rueng-976","DOIUrl":"https://doi.org/10.1061/ajrua6.rueng-976","url":null,"abstract":"","PeriodicalId":48571,"journal":{"name":"Asce-Asme Journal of Risk and Uncertainty in Engineering Systems Part A-Civil Engineering","volume":"8 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77409236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1061/ajrua6.rueng-960
Jiarui Xu, Fengshan Jiang, Zhiqiang Xie, Guofang Wang
The safe operation of natural gas long-distance pipeline stations is the critical link for its sustainable transmission. Therefore, station operation risk assessment and space-time expression in high consequence areas have become a critical problem that must be urgently addressed. The conventional way to assess the probability of gas pipeline failure cannot meet the requirements of the natural gas operating companies for the safety assessment of natural gas stations. Taking the example of the China–Myanmar natural gas pipeline branch station, based on the fuzzy fault tree model (FFT), a comprehensive pipeline safety evaluation method (CPSE-FFT) has been introduced, which evaluates the risk factor of pipeline operation in the station area and the social security risk brought by it. In this case study, the method is applied to a branch station of the China–Myanmar long-distance pipeline. In the results, the probability of pipeline accidents in the area of the station is 5.79×10−4 times/year, and six buildings with higher risk levels among the 37 buildings are also exposed on the risk distribution map. The overall social risk level is also expressed. CPSE-FFT is a practical, reasonable, and accurate assessment method that can quantitatively reflect the risks posed by the safe operation of natural gas stations. This method is suitable for most natural gas station risk assessments. The results of the risk assessment provide a reference for managers and decision-makers to reduce the risk of natural gas stations.
{"title":"Risk Assessment Method for the Safe Operation of Long-Distance Pipeline Stations in High-Consequence Areas Based on Fault Tree Construction: Case Study of China–Myanmar Natural Gas Pipeline Branch Station","authors":"Jiarui Xu, Fengshan Jiang, Zhiqiang Xie, Guofang Wang","doi":"10.1061/ajrua6.rueng-960","DOIUrl":"https://doi.org/10.1061/ajrua6.rueng-960","url":null,"abstract":"The safe operation of natural gas long-distance pipeline stations is the critical link for its sustainable transmission. Therefore, station operation risk assessment and space-time expression in high consequence areas have become a critical problem that must be urgently addressed. The conventional way to assess the probability of gas pipeline failure cannot meet the requirements of the natural gas operating companies for the safety assessment of natural gas stations. Taking the example of the China–Myanmar natural gas pipeline branch station, based on the fuzzy fault tree model (FFT), a comprehensive pipeline safety evaluation method (CPSE-FFT) has been introduced, which evaluates the risk factor of pipeline operation in the station area and the social security risk brought by it. In this case study, the method is applied to a branch station of the China–Myanmar long-distance pipeline. In the results, the probability of pipeline accidents in the area of the station is 5.79×10−4 times/year, and six buildings with higher risk levels among the 37 buildings are also exposed on the risk distribution map. The overall social risk level is also expressed. CPSE-FFT is a practical, reasonable, and accurate assessment method that can quantitatively reflect the risks posed by the safe operation of natural gas stations. This method is suitable for most natural gas station risk assessments. The results of the risk assessment provide a reference for managers and decision-makers to reduce the risk of natural gas stations.","PeriodicalId":48571,"journal":{"name":"Asce-Asme Journal of Risk and Uncertainty in Engineering Systems Part A-Civil Engineering","volume":"719 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136156907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1061/ajrua6.rueng-953
Reza Filizadeh, E. Hernández, D. Rosowsky
{"title":"Time-Dependent Damage Evolution of Reinforced Concrete Bridge Piers: Implications for Multihazard Analysis","authors":"Reza Filizadeh, E. Hernández, D. Rosowsky","doi":"10.1061/ajrua6.rueng-953","DOIUrl":"https://doi.org/10.1061/ajrua6.rueng-953","url":null,"abstract":"","PeriodicalId":48571,"journal":{"name":"Asce-Asme Journal of Risk and Uncertainty in Engineering Systems Part A-Civil Engineering","volume":"5 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84939496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1061/ajrua6.rueng-927
M. Rahimi, A. Shafieezadeh
{"title":"Multistate Overflow Fragility Models for Homogenous Inland Levees with Noncohesive Sediments","authors":"M. Rahimi, A. Shafieezadeh","doi":"10.1061/ajrua6.rueng-927","DOIUrl":"https://doi.org/10.1061/ajrua6.rueng-927","url":null,"abstract":"","PeriodicalId":48571,"journal":{"name":"Asce-Asme Journal of Risk and Uncertainty in Engineering Systems Part A-Civil Engineering","volume":"45 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88274389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-03-01DOI: 10.1061/ajrua6.rueng-962
Hua-Ming Qian, Hong-Zhong Huang, Jing Wei
The active-learning Kriging (ALK)–based time-variant system reliability analysis has been widely concentrated. Unfortunately, the current time-variant system reliability methods are mostly focused on the series system, parallel system, or series-parallel system; thus, they cannot efficiently deal with the time-variant reliability problem of a complex system such as bridge system, network system, and so on. In view of this issue, the paper proposes an efficient time-variant reliability method for a complex system by introducing the structure function into the ALK-based time-variant reliability analysis. Firstly, similar to the ALK-based time-variant system reliability method, some extreme values corresponding to the initial input samples are optimized, and thus the initial extremum response surface is constructed based on the Kriging model. Then, considering the epistemic uncertainty of the Kriging predictions, the predicted response of system structure function under a particular input sample is viewed as a random variable, and its mean and variance are computed based on the minimal cut sets of a complex system. Lastly, considering the aleatory uncertainty between the different candidate samples, the point corresponding to the maximum prediction variance is selected, the most important component is decided by introducing the structure importance, and its extreme value is correspondingly optimized to update the initial extremum response surface. The stopping criterion is also provided in this paper and the effectiveness of the proposed method is illustrated by several examples.
{"title":"Time-Variant Reliability Analysis for a Complex System Based on Active-Learning Kriging Model","authors":"Hua-Ming Qian, Hong-Zhong Huang, Jing Wei","doi":"10.1061/ajrua6.rueng-962","DOIUrl":"https://doi.org/10.1061/ajrua6.rueng-962","url":null,"abstract":"The active-learning Kriging (ALK)–based time-variant system reliability analysis has been widely concentrated. Unfortunately, the current time-variant system reliability methods are mostly focused on the series system, parallel system, or series-parallel system; thus, they cannot efficiently deal with the time-variant reliability problem of a complex system such as bridge system, network system, and so on. In view of this issue, the paper proposes an efficient time-variant reliability method for a complex system by introducing the structure function into the ALK-based time-variant reliability analysis. Firstly, similar to the ALK-based time-variant system reliability method, some extreme values corresponding to the initial input samples are optimized, and thus the initial extremum response surface is constructed based on the Kriging model. Then, considering the epistemic uncertainty of the Kriging predictions, the predicted response of system structure function under a particular input sample is viewed as a random variable, and its mean and variance are computed based on the minimal cut sets of a complex system. Lastly, considering the aleatory uncertainty between the different candidate samples, the point corresponding to the maximum prediction variance is selected, the most important component is decided by introducing the structure importance, and its extreme value is correspondingly optimized to update the initial extremum response surface. The stopping criterion is also provided in this paper and the effectiveness of the proposed method is illustrated by several examples.","PeriodicalId":48571,"journal":{"name":"Asce-Asme Journal of Risk and Uncertainty in Engineering Systems Part A-Civil Engineering","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135594069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1061/ajrua6.rueng-990
M. Stewart
{"title":"Climate Adaptation Engineering: An Optimist’s View","authors":"M. Stewart","doi":"10.1061/ajrua6.rueng-990","DOIUrl":"https://doi.org/10.1061/ajrua6.rueng-990","url":null,"abstract":"","PeriodicalId":48571,"journal":{"name":"Asce-Asme Journal of Risk and Uncertainty in Engineering Systems Part A-Civil Engineering","volume":"244 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85524476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1061/ajrua6.rueng-994
Yan Li
{"title":"Evolutionary Game Analysis for the Behaviors of Risk Allocation Participants in Public–Private Partnerships","authors":"Yan Li","doi":"10.1061/ajrua6.rueng-994","DOIUrl":"https://doi.org/10.1061/ajrua6.rueng-994","url":null,"abstract":"","PeriodicalId":48571,"journal":{"name":"Asce-Asme Journal of Risk and Uncertainty in Engineering Systems Part A-Civil Engineering","volume":"31 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85627305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1061/ajrua6.rueng-943
D. Feng, Xinhe Sun, Yue Li, Gang Wu
{"title":"Two-Parameter–Based Damage Measure for Probabilistic Seismic Analysis of Concrete Structures","authors":"D. Feng, Xinhe Sun, Yue Li, Gang Wu","doi":"10.1061/ajrua6.rueng-943","DOIUrl":"https://doi.org/10.1061/ajrua6.rueng-943","url":null,"abstract":"","PeriodicalId":48571,"journal":{"name":"Asce-Asme Journal of Risk and Uncertainty in Engineering Systems Part A-Civil Engineering","volume":"10 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84738412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1061/ajrua6.rueng-941
Ning-Xiang Yang, Xing Jin, Qingke Nie, X. Guan, Wenjun Zhang, Huifeng Liu
{"title":"Driving Parameter Trends and a Safety Evaluation Method Based on the Composite Ratio for Shield Tunneling in Complex Strata","authors":"Ning-Xiang Yang, Xing Jin, Qingke Nie, X. Guan, Wenjun Zhang, Huifeng Liu","doi":"10.1061/ajrua6.rueng-941","DOIUrl":"https://doi.org/10.1061/ajrua6.rueng-941","url":null,"abstract":"","PeriodicalId":48571,"journal":{"name":"Asce-Asme Journal of Risk and Uncertainty in Engineering Systems Part A-Civil Engineering","volume":"1 1","pages":""},"PeriodicalIF":2.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88944610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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