Skip to main content
Log in

Identification of geo-material rheological constitutive model based on fast-convergent genetic algorithm

  • Published:
Journal of Central South University of Technology Aims and scope Submit manuscript

Abstract

To identify rheological constitutive model of geo-materials, one generalized constitutive law is applied. So, the problem of model identification is transformed to the problem of traditional parameters identification. According to the relationship of objective function and optimization methods, the global optimization method, such as evolutionary algorithm, is very suitable to solve parameter identification problems. A new fast-convergent genetic algorithm is applied in this study. In this new algorithm, there are only two individuals in one population. So, the whole computation efficiency of optimization back analysis will be very high. Using this new back analysis method, a real engineering example of one underground coal mine roadway is used to verify the computing ability of the algorithm to real problems. The results show that the efficiency of optimization back analysis can be improved greatly with this new algorithm.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. XU Ri-qing, GONG Xiao-nian, WANG Ming-yang, et al. Identification of visco-elastic models and deformation forecast[J]. Journal of Hydraulics Engineering, 1998(4): 75–80. (in Chinese)

  2. CHEN S H, CHEN S F, SHAHROUR I. The feedback analysis of excavated rock slope[J]. Rock Mechanics and Rock Engineering, 2001, 34(1): 39–56.

    Article  Google Scholar 

  3. KOWALCZYK T, FURUKAWA T, YOSHIMURA S, et al. An extensible evolutionary algorithm approach for inverse problems[C]//Tanaka M, Dulikravich G S. Int Sym on Inverse Problems in Engineering Mechanics. Amsterdam: Elsevier Science Publishers, 1998: 541–550.

    Chapter  Google Scholar 

  4. MILLAR D L. Automated back analysis of ground response in rocks and soils via evolutionary computing[C]//BARLA G. Proc of Eurock’96. Rotterdom: Balkema, 1996: 975–982.

    Google Scholar 

  5. GAO Wei, ZHENG Ying-ren. Back analysis of rock mass parameters based on evolutionary algorithm[J]. Journal of Hydraulics Engineering, 2000(8): 1–5. (in Chinese)

  6. XIONG Sheng-wu, LI Yuan-xiang, KANG Li-shan. Identification of spatially-varying parameters of parabolic partial differential equation by evolutionary algorithms[J]. Chinese Journal of Computers, 2000, 23(3): 261–265. (in Chinese)

    MathSciNet  Google Scholar 

  7. LIU Bao-guo. Identification of visco-elastic, visco-plastic model of rock mass and its engineering apllication[D]. Shanghai: Tongji University, 1997. (in Chinese)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Gao Wei  (高玮).

Additional information

Foundation item: Projects (90510019; 40648040) supported by the National Natural Science Foundation of China

Rights and permissions

Reprints and permissions

About this article

Cite this article

Gao, W. Identification of geo-material rheological constitutive model based on fast-convergent genetic algorithm. J Cent. South Univ. Technol. 14 (Suppl 1), 22–25 (2007). https://doi.org/10.1007/s11771-007-0206-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11771-007-0206-x

Key words

Navigation