Inversion Analysis on Permeability Coefficient of Stratum in Engineering Area Based on RVM-CS

LI Ya-qi; YANG Jie; CHENG Lin; MA Chun-hui

doi:10.11988/ckyyb.20190825

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Journal of Changjiang River Scientific Research Institute ›› 2020, Vol. 37 ›› Issue (11) : 121-127. DOI: 10.11988/ckyyb.20190825

ROCK-SOIL ENGINEERING

Inversion Analysis on Permeability Coefficient of Stratum in Engineering Area Based on RVM-CS

LI Ya-qi^1,2, YANG Jie^1,2, CHENG Lin^1,2, MA Chun-hui^1,2

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Abstract

An inversion analysis model integrating relevance vector machine (RVM) and cuckoo search (CS) is established to accurately determine the permeability coefficients of strata in engineering area. Firstly, the uniform design method is employed to construct combinations of permeability coefficients, and the finite element method is used to calculate the water head values and generate RVM learning samples. In subsequence, the mapping relation between permeability coefficient and water head is constructed by RVM training which replaces the finite element method in calculating seepage. According to the measured water head values of drilling holes in the project area, the CS algorithm is adopted to search and determine the permeability coefficient of stratum. The seepage inversion model is applied to the inversion of initial seepage field of a large pumped storage power station project. Results demonstrate that the proposed model reflects the nonlinear relation between water head in borehole and permeability coefficient of multiple strata. RVM could replace the finite element method to determine quickly and accurately the permeability coefficient. The inversion results for the large pumped storage power station are reasonable and the accuracy of the proposed model meets engineering requirements.

Key words

permeability coefficient / inversion analysis / relevance vector machine / cuckoo search / uniform design method

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LI Ya-qi, YANG Jie, CHENG Lin, MA Chun-hui. Inversion Analysis on Permeability Coefficient of Stratum in Engineering Area Based on RVM-CS[J]. Journal of Changjiang River Scientific Research Institute. 2020, 37(11): 121-127 https://doi.org/10.11988/ckyyb.20190825

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