Urban vulnerability under various blast loading scenarios: Analysis using GIS-based multi-criteria decision analysis techniques

《Urban vulnerability under various blast loading scenarios: Analysis using GIS-based multi-criteria decision analysis techniques》

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关键字: Physical vulnerability; Multi-criteria evaluation; Geospatial Information Systems; Blast loading; Ordered Weighted Averaging; SYSTEMS; RISK; RESILIENCE; EARTHQUAKE; OPERATORS; CITIES; CITY; TOOL

作者单位: [Ghajari, Yasser Ebrahimian; Modiri, Mandi; Hosnavi, Reza; Abbasi, Morteza] Malek Ashtar Univ Technol, Tehran 158751774, Iran. [Alesheikh, Ali Asghar] KN Toosi Univ Technol, GIS Dept, Tehran, Iran. [Sharifi, Ayyoob] Natl Inst Environm Studies, Global Carbon Project Tsukuba Int Off, Tsukuba, Ibaraki, Japan. [Ghajari, Yasser Ebrahimian] Babol Noshirvani Univ Technol, Fac Civil Engn, Babol Sar, Iran. Ghajari, YE (reprint author), Malek Ashtar Univ Technol, Tehran 158751774, Iran.; Ghajari, YE (reprint author), Babol Noshirvani Univ Technol, Fac Civil Engn, Babol Sar, Iran. E-Mail: y.ebrahimian@nit.ac.ir; alesheikh@kntu.ac.ir; mmodiri@ut.ac.ir; hosnavi@mut.ac.ir; mabbasi@mut.ac.ir; sharifi.ayyoob@nies.go.jp

摘要: This paper examines physical vulnerability of District No. 6 of Tehran to blast damages and blast loads. The main objectives are to enhance planners and decision makers' awareness of the extent of vulnerability of buildings in the study area (under different risk scenarios) and to provide guidance on how to enhance preparedness against potential risks. Physical vulnerability of District No. 6 of Tehran was evaluated under three different blast loading scenarios. An expert survey, involving specialists with expertise in urban development, passive defense, construction, and architecture was carried out to extract fourteen vulnerability criteria. Fuzzy criteria maps corresponding to each of these criteria were produced in Geospatial Information Systems (GIS) environment. Fuzzy analytic hierarchy processing was used to weigh the criteria. Criterion maps were combined using the fuzzy weighted linear combination operator. Finally, Ordered Weighted Averaging (OWA) operator was applied to generate final vulnerability maps. Results show that, for all scenarios, almost 70% of the buildings in the district are of high vulnerability. Sensitivity analysis confirms the reliability of the model.