Abstract
Most of the coal mining in China is underground, which will inevitably cause surface deformation and trigger a series of geological disasters. Therefore, it is essential to find a suitable method to forecast the ground sinking caused by underground mining. The most commonly used prediction model in China is the probability integral model (PIM). But when this model is used in the geological condition of mining under thick loose layers, the predicted edge of the sinking basin will converge faster than the actual measured sinking situation. A geometric model (GM) with a similar model shape as the PIM but with a larger boundary value was established in this paper to solve this problem. Then an improved cuckoo search algorithm (ICSA) was proposed in this paper to calculate the GM parameters. The stability and reliability of the ICSA were verified through a simulated working face. At last, the ICSA, in combination with the GM and the PIM, was used to fit 6 working faces with the geological mining condition of thick loose layers in the Huainan mining area. The results prove that GM can solve the above-mentioned PIM problem when it is used in geological mining conditions of thick loose layers. And it was obtained through comparative analysis that the GM and the PIM parameters can take the same value except for the main influence radius.
Highlights
The continuous mining of the coal resources provides a strong guarantee for the rapid development of China’s economy
Due to the limitation of the shape of the model curve, the problem of small boundary value is much more obvious while the probability integral model (PIM) is applied to predict surface subsidence caused by mining under thick loose layers, and this problem cannot be solved by adjusting the model parameters
By comparing the fitting effects of the geometric model (GM) and the PIM in 6 working faces, it can be concluded that the GM is more suitable than the PIM in predicting surface subsidence caused by mining under thick loose layers. and the relationship between the GM parameters and the PIM parameters is drawn
Summary
The continuous mining of the coal resources provides a strong guarantee for the rapid development of China’s economy. Xu et al (2020) studied the movement laws of the overlying bedrock while mining shallow buried coal seams under thick loose layers. Due to the limitation of the shape of the model curve, the problem of small boundary value is much more obvious while the PIM is applied to predict surface subsidence caused by mining under thick loose layers, and this problem cannot be solved by adjusting the model parameters. It is necessary to establish a model with simple parameters and suitable for surface subsidence prediction caused by mining under thick loose layers. By comparing the fitting effects of the GM and the PIM in 6 working faces, it can be concluded that the GM is more suitable than the PIM in predicting surface subsidence caused by mining under thick loose layers. By comparing the fitting effects of the GM and the PIM in 6 working faces, it can be concluded that the GM is more suitable than the PIM in predicting surface subsidence caused by mining under thick loose layers. and the relationship between the GM parameters and the PIM parameters is drawn
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