Impact coal internal block size effect on physical and mechanical parameters’ similarity criteria validity: Numerical simulation and adjustment

Abstract

Physical analog modeling is an effective approach for studying the hazards of coal bursts in coal similarity criteria for physical and mechanical parameters of the actual and similar materials are crucial to yield realistic results. The derivation of similarity criteria is predominantly based on dimensional analysis, while a systematic methodology has yet to be developed. This paper attempts to fill this gap by combining the equation transformation method with similarity theory to conduct an in-depth study on the similarity criteria of physical parameters of impact coal with various internal block sizes. On this basis, the influence of internal block size of impact coal on similarity criteria was studied. Block size can provide a selection basis for similar materials, and the influence of block size on model physical parameters and similarity criteria under different geometric similarity ratios was explored. The variation laws between geometric similarity ratio, block size, and physical properties were clarified, and the similarity criteria of impact coal under the influence of block size were adjusted. New insights into material selection for physical analog modeling were proposed. The established similarity criteria for impact coal under the influence of different block sizes can provide a theoretical basis for determining various parameters in the physical analog modeling of coal bursts, when building a physical model of impact coal, material selection and size selection can be based on similarity criteria to more accurately reproduce coal explosion disasters in the laboratory.

Keywords

Physical analog modeling / Coal burst / Impact coal / Similarity criteria / Block size / Similar materials

Acknowledgements

This research is supported by the Fundamental Research Funds for the Central Universities (No. 2024-10941); China University of Mining and Technology 2024 Graduate Innovation Program Projects (No. 2024WLKXJ011); Jiangsu Graduate Student Research and Innovation Program (No. KYCX24_2846); and the National Natural Science Foundation of China (Nos. 52227901 and 51934007).

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