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Study on the Improved Severity Coefficient Model of Dam Break Consequence Assessment

Authors :
Weiwei Sun
Zhifei Long
Qian Cai
Source :
American Journal of Civil Engineering. 9:84
Publication Year :
2021
Publisher :
Science Publishing Group, 2021.

Abstract

The assessment of the dam failure consequences is fundamental to the dam risk assessment, and the linear weight sum method is generally used. The comprehensive evaluation of dam failure consequences involves many evaluation factors, the dimensions of each factor are inconsistent. The key is to determine the coefficient of the severity degree of dam failure consequences. Based on the traditional methods, a new severity degree coefficient model of the loss of life, economic losses, environmental impact, and social impact is established after taking the current laws and regulations, the range of the severity of the impact, the establishment of normalized function, the introduction of piecewise function and other factors into comprehensive consideration, and use analysis hierarchy process to obtain weight. Apply the improved linear weighting method to the level assessment and rank of the dam failure consequences of Changlong reservoir, Xialan reservoir, Shibikeng reservoir, Longshan reservoir and Lingtan reservoir in Jiangxi Province, and then determine the grade and rank of dam failure consequences according to the calculation results, analyze the corresponding results accurately combined with expertise. The evaluation results and analysis show that if dam failure occurs, the consequences of the five dams are all very serious, it belongs to extraordinarily serious accidents. The severity degree coefficient of dam failure consequences model can reflect the severity degree of dam failure consequences more objectively and reasonably, and it has clear concept, simple calculation, and intuitive process.

Details

ISSN :
23308729
Volume :
9
Database :
OpenAIRE
Journal :
American Journal of Civil Engineering
Accession number :
edsair.doi...........950b90a762de457552a63c35125da5a9