DocumentCode :
496272
Title :
A New Intelligent Back-Analysis Method Based on Differential Evolution Algorithm
Author :
Su, Guoshao
Author_Institution :
Dept. of Civil & Archit. Eng., Guangxi Univ., Nanning, China
Volume :
1
fYear :
2009
fDate :
24-26 April 2009
Firstpage :
212
Lastpage :
214
Abstract :
In light of the fact that it is very hard to determine mechanics parameters of rock mass using the traditional method in geotechnical engineering, a new method based on Differential Evolution algorithm (DE) combined with Fast Lagrangian Analysis of Continua in 3 Dimension (FLAC3D) numerical calculation code is proposed for identification of the mechanics parameters of rock mass. At first, stochastic mechanics parameters are initialized. Then, the difference in displacement between the numerical value and in-situ measurements is regarded as fitness value to evaluate quality of the trial mechanics parameters. Furthermore, mechanics parameters of rock mass are updated continually according to differential evolution rule until the optimum mechanic parameters are found. The results of case study and application in tunnel engineering both show that the method is feasible and efficient for identifying mechanics parameters of rock mass.
Keywords :
geotechnical engineering; numerical analysis; rocks; statistical mechanics; stochastic processes; tunnels; differential evolution algorithm; differential evolution rule; fast Lagrangian analysis of continua; geotechnical engineering; intelligent back-analysis method; rock mass mechanics parameters; stochastic mechanics; tunnel engineering; Algorithm design and analysis; Chromium; Computational intelligence; Computer architecture; Genetic mutations; Lagrangian functions; Mechanical variables measurement; Numerical models; Optimization methods; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on
Conference_Location :
Sanya, Hainan
Print_ISBN :
978-0-7695-3605-7
Type :
conf
DOI :
10.1109/CSO.2009.262
Filename :
5193677
Link To Document :
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