Intelligent displacement back analysis for excavation of an underground powerhouse in China

W. M. Yang; S. C. Li; M. T. Li; X. J. Li; N. Liu

doi:10.1117/12.839228

24 August 2009 Intelligent displacement back analysis for excavation of an underground powerhouse in China

W. M. Yang, S. C. Li, M. T. Li, X. J. Li, N. Liu

Proceedings Volume 7375, ICEM 2008: International Conference on Experimental Mechanics 2008; 73752R (2009) https://doi.org/10.1117/12.839228
Event: International Conference on Experimental Mechanics 2008 and Seventh Asian Conference on Experimental Mechanics, 2008, Nanjing, China

Abstract

Back analysis is an effective method to obtain the rock mass mechanical parameters with measured displacements. But the traditional back analysis methods have some shortcomings, such as narrow scope of application and instability. The intelligent back analysis method which incorporates a neural network and a genetic algorithm can overcome the drawbacks mentioned above and give satisfactory results. In this paper, based on orthogonal design, neural network and genetic algorithms, the intelligent displacement back analysis was carried out for the excavation of an underground powerhouse of a pumped storage power station in China. First, a series of samples were selected to train the neural network so that the relations between displacement of rock mass and parameters were erected. Then the optimum values of parameters were gotten taking advantage of optimization of genetic algorithms. Substituting the obtained parameters into FDM software for forward computation, it was found that the calculated displacements agreed the measured data well. The intelligent back analysis method can be used as a powerful tool to find out the optimum mechanical parameters of rock mass.

Citation Download Citation

W. M. Yang, S. C. Li, M. T. Li, X. J. Li, and N. Liu "Intelligent displacement back analysis for excavation of an underground powerhouse in China", Proc. SPIE 7375, ICEM 2008: International Conference on Experimental Mechanics 2008, 73752R (24 August 2009); https://doi.org/10.1117/12.839228

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available