Giuseppe Degan Di Dieco, A. Barbosa, M. Pregnolato
{"title":"有洪水风险的河流道路桥梁的分类:对桥梁的分类和损坏模型","authors":"Giuseppe Degan Di Dieco, A. Barbosa, M. Pregnolato","doi":"10.1680/jbren.21.00065","DOIUrl":null,"url":null,"abstract":"Many communities around the world are facing increasing flood-induced damages to bridges due to climate change and rising urbanization. It is crucial to understand how different bridge types suffer from flooding and how this may affect the surrounding network. Despite the large body of literature for seismic and hurricane taxonomies, a few classifications exist for bridges at flood risk. This paper globally reviews existing bridge classifications to derive a bridge-flood taxonomy. The review found that existing studies mainly classify bridges according to the superstructure material, whereas subclasses consider superstructure and substructure components. This paper proposes a taxonomy of 20 attributes for riverine roadway bridges susceptible to flood hazards, and verifies its applicability for three bridge datasets in the UK. Results show that the considered datasets have data for 13 attributes, which can be used to derive regional bridge classes. In general, the taxonomy is functional for standardising different bridge datasets and applying/developing damage models for given bridge portfolios of flood-prone countries. Future works could apply the taxonomy to additional bridge datasets within a network for risk assessments; the proposed taxonomy could also be extended to allow integration with functionality and restoration models.","PeriodicalId":44437,"journal":{"name":"Proceedings of the Institution of Civil Engineers-Bridge Engineering","volume":"12 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A taxonomy of riverine roadway bridges at risk of flooding: towards bridge classes and damage models\",\"authors\":\"Giuseppe Degan Di Dieco, A. Barbosa, M. Pregnolato\",\"doi\":\"10.1680/jbren.21.00065\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Many communities around the world are facing increasing flood-induced damages to bridges due to climate change and rising urbanization. It is crucial to understand how different bridge types suffer from flooding and how this may affect the surrounding network. Despite the large body of literature for seismic and hurricane taxonomies, a few classifications exist for bridges at flood risk. This paper globally reviews existing bridge classifications to derive a bridge-flood taxonomy. The review found that existing studies mainly classify bridges according to the superstructure material, whereas subclasses consider superstructure and substructure components. This paper proposes a taxonomy of 20 attributes for riverine roadway bridges susceptible to flood hazards, and verifies its applicability for three bridge datasets in the UK. Results show that the considered datasets have data for 13 attributes, which can be used to derive regional bridge classes. In general, the taxonomy is functional for standardising different bridge datasets and applying/developing damage models for given bridge portfolios of flood-prone countries. Future works could apply the taxonomy to additional bridge datasets within a network for risk assessments; the proposed taxonomy could also be extended to allow integration with functionality and restoration models.\",\"PeriodicalId\":44437,\"journal\":{\"name\":\"Proceedings of the Institution of Civil Engineers-Bridge Engineering\",\"volume\":\"12 1\",\"pages\":\"\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2022-02-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Institution of Civil Engineers-Bridge Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1680/jbren.21.00065\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Institution of Civil Engineers-Bridge Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1680/jbren.21.00065","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
A taxonomy of riverine roadway bridges at risk of flooding: towards bridge classes and damage models
Many communities around the world are facing increasing flood-induced damages to bridges due to climate change and rising urbanization. It is crucial to understand how different bridge types suffer from flooding and how this may affect the surrounding network. Despite the large body of literature for seismic and hurricane taxonomies, a few classifications exist for bridges at flood risk. This paper globally reviews existing bridge classifications to derive a bridge-flood taxonomy. The review found that existing studies mainly classify bridges according to the superstructure material, whereas subclasses consider superstructure and substructure components. This paper proposes a taxonomy of 20 attributes for riverine roadway bridges susceptible to flood hazards, and verifies its applicability for three bridge datasets in the UK. Results show that the considered datasets have data for 13 attributes, which can be used to derive regional bridge classes. In general, the taxonomy is functional for standardising different bridge datasets and applying/developing damage models for given bridge portfolios of flood-prone countries. Future works could apply the taxonomy to additional bridge datasets within a network for risk assessments; the proposed taxonomy could also be extended to allow integration with functionality and restoration models.