{"title":"Application of Particle Swarm Optimization Algorithm for Computing Critical Depth of Horseshoe Cross Section Tunnel","authors":"Ayoub Bahmanikashkooli , Majid Zare , Bahman Safarpour , Mostafa Safarpour","doi":"10.1016/j.apcbee.2014.01.037","DOIUrl":null,"url":null,"abstract":"<div><p>Critical depth is an important parameter in the design, operation and maintenance of open channels and analysis of gradually varied flow. For horseshoe cross section channels, the governing equations are highly nonlinear in the critical flow depth and thus solution of the implicit equations involves time consuming numerical methods. In current research, through conversion of critical depth equation to an objective function and then its minimization by using Particle Swarm Optimization algorithm, we calculate critical depth in horseshoe channels. The accuracy of the proposed model was also evaluated by comparing with existing equations. Furthermore this method can be used to deal with other optimization problems in hydraulic engineering.</p></div>","PeriodicalId":8107,"journal":{"name":"APCBEE Procedia","volume":"9 ","pages":"Pages 207-211"},"PeriodicalIF":0.0000,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.apcbee.2014.01.037","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"APCBEE Procedia","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2212670814000384","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Critical depth is an important parameter in the design, operation and maintenance of open channels and analysis of gradually varied flow. For horseshoe cross section channels, the governing equations are highly nonlinear in the critical flow depth and thus solution of the implicit equations involves time consuming numerical methods. In current research, through conversion of critical depth equation to an objective function and then its minimization by using Particle Swarm Optimization algorithm, we calculate critical depth in horseshoe channels. The accuracy of the proposed model was also evaluated by comparing with existing equations. Furthermore this method can be used to deal with other optimization problems in hydraulic engineering.