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Modeling the relationship between macro- and meso-parameters of coal using a combined optimization method

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Abstract

From a mesoscopic perspective, coal is a complicated net-shaped force-bearing system. It is reasonable to simulate this complicated system by particles and parallel bonds among the particles. Based on this cognition, Particle Flow Code (PFC) has been developed. The model calibration is fundamental for effective simulation of crack behaviors using PFC. Only partial meso-parameters have been considered so far, and the calibration process is not effectively arranged. In this paper, a combination optimization method, termed as GT–RSM–MD, was proposed. Based on this method, the calibration was effectively conducted. The main controlling parameters of elasticity modulus, Poisson’s ratio, and uniaxial compressive strength were obtained by the grey relational analysis and factorial screening. Subsequently, the response surface models between three macro-parameters and their main controlling meso-parameters were established via the experimental design and model verification. Based on these models, fast match between meso-parameters and macro-parameters was realized. The PFC model calibration provides a crucial reference for selection of the meso-parameters set in the simulation.

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Acknowledgements

This work is financially supported by the State Key Research Development Program of China (Grant No. 2017YFC0804206), Fundamental Research Funds for the Central Universities (Grant No. 106112017CDJXY240001), and the National Natural Science Foundation of China (51674050), which are gratefully acknowledged.

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Authors and Affiliations

  1. State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University, Chongqing, 400044, China

    Quanle Zou

  2. School of Safety Engineering, China University of Mining and Technology, Xuzhou, 221116, China

    Baiquan Lin

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  1. Quanle Zou
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  2. Baiquan Lin
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Correspondence to Quanle Zou.

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Zou, Q., Lin, B. Modeling the relationship between macro- and meso-parameters of coal using a combined optimization method. Environ Earth Sci 76, 479 (2017). https://doi.org/10.1007/s12665-017-6816-1

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  • DOI: https://doi.org/10.1007/s12665-017-6816-1

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