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Back analysis for rock model surrounding underground roadways in coal mine based on black hole algorithm

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Abstract

The huge plastic deformation is the characteristic of the underground roadways in coal mine. Therefore, to compute the stability of underground roadways, a elastic–plastic constitutive model of surrounding rock must be obtained. Many elastic–plastic constitutive models for rock mass have been proposed. In this study, a generalized constitutive law for an elastic–plastic constitutive model is applied. Using this generalized constitutive law, the problem of model identification is transformed to a problem of parameter back analysis, which is a typical and complicated optimization. To improve the efficiency of the traditional optimization method, a black hole algorithm is applied in this study. Combining the generalized constitutive law for an elastic–plastic constitutive model and black hole algorithm, a new back analysis method for model identification of rocks surrounding underground roadways in coal mine is proposed. Using this new method, the elastic–plastic constitutive models for two underground roadways in Huainan coal mine has been back-calculated. The results are compared with those of traditional genetic algorithm, fast genetic algorithm and immune continuous ant colony algorithm, that proposed in previous studies. The results show that the new model back analysis algorithm can significantly improve the computation efficiency and the computation effect, and is a very good method for back analysis the rock model surrounding underground roadways in coal mine.

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Acknowledgments

The financial supports from The Fundamental Research Funds for the Central Universities under Grant Nos. 2014B17814, 2014B07014 and 2014B04914 are all gratefully acknowledged.

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Correspondence to Wei Gao.

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Gao, W., Ge, M., Chen, D. et al. Back analysis for rock model surrounding underground roadways in coal mine based on black hole algorithm. Engineering with Computers 32, 675–689 (2016). https://doi.org/10.1007/s00366-016-0445-2

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  • DOI: https://doi.org/10.1007/s00366-016-0445-2

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