Abstract:One of the primary factors affecting safe and effective mining in fully mechanized mining faces with large mining heights is coal wall sloughing. This paper establishes the mechanical model of the coal wall and uses the deflection theory for the mechanics of materials to find the maximum point of the deflection of the coal wall, which is the most easily deformed and damaged during the mining process, based on the mining production conditions of the 12-2up108 working face in the Jinjitan Coal Mine. In order to … Show more
“…From a failure perspective, stress concentration becomes more obvious at the end face of the sample as the L/D ratio decreases (Lundborg N, 1967), and the energy storage process is accelerated, leading to the ejection of rock fragments at a faster speed. These two results illustrate the significant influence of rock size on the energy storage process (Li et al, 2023). To provide a reliable reference for predicting rock burst, these findings emphasize the importance of considering the strain rate and size effects when evaluating rock burst proneness.…”
Section: Effect Of Strain Rate and L/d Ratio On Linear Energy Charact...mentioning
In deep rock engineering, evaluating the likelihood of rock burst is imperative to ensure safety. This study proposes a new metric, the post-peak dissipated energy index, which accounts for strain rate and size effects in assessment of the rock burst proneness of a rock mass. To investigate rock burst proneness, conventional compression tests were conducted on limestone and slate samples with different length to diameter (L/D) ratios (ranging from 0.3 to 1.5) at four different strain rates (0.005, 0.01, 0.5, and 1.0 s−1). Based on the testing observations, the actual rock burst proneness was classified into three categories (no risk, low risk, and high risk). A new criterion was also established using the post-peak dissipated energy index, which is the ratio of elastic energy to total dissipated energy. The impact of the strain rate and L/D ratio on rock burst proneness was analyzed. The results indicated that increased strain rates cause a strong hardening effect, leading to staged growth of rock burst proneness. However, the rock burst proneness decreases non-linearly with the increasing L/D ratio. The accuracy of the proposed criterion was validated by comparison with existing criteria, demonstrating that the energy-based index ensures a reliable evaluation of the rock burst proneness of a rock mass. The proposed method has excellent potential for practical application in deep rock engineering.
“…From a failure perspective, stress concentration becomes more obvious at the end face of the sample as the L/D ratio decreases (Lundborg N, 1967), and the energy storage process is accelerated, leading to the ejection of rock fragments at a faster speed. These two results illustrate the significant influence of rock size on the energy storage process (Li et al, 2023). To provide a reliable reference for predicting rock burst, these findings emphasize the importance of considering the strain rate and size effects when evaluating rock burst proneness.…”
Section: Effect Of Strain Rate and L/d Ratio On Linear Energy Charact...mentioning
In deep rock engineering, evaluating the likelihood of rock burst is imperative to ensure safety. This study proposes a new metric, the post-peak dissipated energy index, which accounts for strain rate and size effects in assessment of the rock burst proneness of a rock mass. To investigate rock burst proneness, conventional compression tests were conducted on limestone and slate samples with different length to diameter (L/D) ratios (ranging from 0.3 to 1.5) at four different strain rates (0.005, 0.01, 0.5, and 1.0 s−1). Based on the testing observations, the actual rock burst proneness was classified into three categories (no risk, low risk, and high risk). A new criterion was also established using the post-peak dissipated energy index, which is the ratio of elastic energy to total dissipated energy. The impact of the strain rate and L/D ratio on rock burst proneness was analyzed. The results indicated that increased strain rates cause a strong hardening effect, leading to staged growth of rock burst proneness. However, the rock burst proneness decreases non-linearly with the increasing L/D ratio. The accuracy of the proposed criterion was validated by comparison with existing criteria, demonstrating that the energy-based index ensures a reliable evaluation of the rock burst proneness of a rock mass. The proposed method has excellent potential for practical application in deep rock engineering.
“…The actual power consumption can be measured by a clamp-type electric power meter and a three-phase power analyzer. The conversion rate of electric energy and primary energy is taken as 0.404 (Li et al, 2023).…”
This paper takes a groundwater source heat pump in the region as the research object and based on field research, experimental tests combined with comparative analysis, the data on its operation is monitored and analyzed in terms of operation, energy saving, and environment. The results show that the cooling temperatures of the test rooms were all below 26°C, the average coefficient of performance of the units was 4.61–4.93 and the average coefficient of performance of the system was 3.08–3.27. In addition, compared to conventional water-cooled chillers, 466 tons of standard coal could be saved in one cooling season, resulting in a reduction of 1,150.8 tons of carbon dioxide emissions, 9.3 tons of sulfur dioxide emissions and 4.7 tons of dust emissions The savings in operating costs are 793,000 RMB. This shows that the groundwater source heat pump has good energy efficiency and economy. The research results obtained in this paper provide a reference for improving energy efficiency and optimizing the operation of the groundwater source heat pump system. It is of great significance to the application of groundwater source heat pump systems in areas with complex geological environments.
“…The above models are also beneficial exploration for slope displacement prediction of open pit mine (Mahmoodzaden, et al, 2022), but they also have problems in generalization ability, robustness and prediction accuracy. Therefore, it is necessary to establish a displacement prediction model with high prediction accuracy and strong generalization ability to ensure the safety production of the open pit slope (Liu et al, 2022;Li et al, 2023). The extreme learning machine (ELM) is a new method of single-layer feed forward neural network that has emerged in recent years.…”
Mine geological disaster is a complex non-linear system. The traditional prediction model has the disadvantages of low prediction accuracy and poor reliability. In order to solve this problem, the open-pit mine slope displacement is taken as the research object. Based on a new algorithm extreme learning machine (ELM), the new intelligent algorithm sparrow search algorithm (SSA) are introduced to determine the weights and thresholds of the input layer and hidden layer of ELM. The open-pit mine slope displacement prediction model of improved ELM is constructed and applied to an engineering example. The results show that the root mean square error of SSA-ELM model is only a quarter of that of BP model, which is 50% higher than that of GM (1,1) and ELM models. The correlation coefficient of the prediction results of the SSA-ELM model is 0.983, and the accuracy is better than that of the traditional model. The single ELM model and the PSO-ELM model show that the SSA algorithm has better improvement effect. The SSA model has good comprehensive performance and high prediction accuracy. It is feasible to apply it to the prediction of slope displacement in open-pit mines.
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