›› 2008, Vol. 29 ›› Issue (2): 370-374.

• Fundamental Theroy and Experimental Research • Previous Articles     Next Articles

Improvement study on response surface method for reliability analysis in geotechnical engineering

HUANG Liang1, YI Wei-jian1, WANG You2   

  1. 1. College of Civil Engineering, Hunan University, Changsha 410082, China； 2. School of Civil and Architectaral Engineering, Central South University, Changsha 410075, China
  • Received:2006-07-31 Online:2008-02-11 Published:2013-07-10

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Abstract: In order to enhance computational efficiency and precision of response surface methods, the global response surface method is improved. Using RBF neural network substitutes BP network as the approximation of implicit performance function, and the response surface is formed in the sphere of hyper-pyramid at iteration step. Compared with other response surface methods, numerical case studies show that the proposed method not only markedly reduces the times of iterations and finite element analysis to shorten the processing time, but also benefits to better accuracy. Moreover, the engineering examples of shallow foundation and retaining wall are analyzed on their structural reliability. The calculation results show that the proposed method may gain reliability index satisfyingly by quicker convergence rate and less machine time, and to be suitable for reliability analysis in geotechnical engineering.

Key words: reliability analysis, response surface, RBF neural network, implicit performance function, geotechnical engineering

CLC Number: 

  • TU 443
  • Please send e-mail to pingzhou3@126.com if you would like to read full paper in English for free. Parts of our published papers have English translations.
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