Research on Dust Migration and Dust Deposition Rules of Breathing Zone in Fully Mechanized Mining Face.

The dust in the breathing zone of the fully mechanized mining face poses a serious threat to the lives and health of the workers, and clarifying the distribution and settlement pattern of the dust in the breathing zone is an important foundation for reducing dust concentrations in the breathing zone and improving the workers' working environment. The dust concentration distribution at the mining face and the settlement results of different dust particle sizes along the breathing zone were analyzed in detail using a combination of computational fluid dynamics simulation and downhole measurements by establishing a highly simulated 3D solid model of the 2302 fully mechanized mining face at the Xinqiao coal mine. The study's findings reveal that dust from advanced support and coal-cutting processes converge within 20-60 m of the coal mining region, generating a high-concentration pollution zone at the height of the sidewalk breathing zone. The particle size of dust in the breathing zone is primarily concentrated between 1 and 40 µm, and the fully mechanized mining face is split into a rapid settling area, a medium settling area, and a slow settling area based on particle size settling speed. Eddy currents in the return airway lead to an increase in dust particles of 20-40 µm in the breathing zone area. The results of the study can provide a theoretical basis for dust management at the fully mechanized mining face for the breathing zone area.

Erratum: Corection to "Multiple Sequence Long and Short Memory Network Model for Corner Gas Concentration Prediction on Coal Mine Workings".

[This corrects the article DOI: 10.1021/acsomega.2c05188.].

Multiple Sequence Long and Short Memory Network Model for Corner Gas Concentration Prediction on Coal Mine Workings.

To further improve the accuracy of recurrent neural network in predicting the gas concentration in the upper corner of the mine tunnel, this paper proposes a method to construct a gas concentration prediction model based on multiple sequence long and short memory network, considering the spatial correlation between the gas concentration in the return airway and upper corner. The reliability of the model construction is improved by using the white noise test and smoothness test to verify the interpretability of the data in this paper and constructing supervised learning type data for gas concentration prediction model training and testing by means of data set division and data windowing. Through experimental comparison, grid search, and time series decomposition, the model algorithm, training parameters, and experimental results were combined to make an in-depth analysis of the influence of each parameter on the model training and the prediction. A training model of the spatially fused gas concentration prediction model with a network layer of 1 and a number of neurons of 32 as the model structure, Adam as the optimization algorithm, and a learning rate of 0.001 and a batch size of 32 as the training parameters was finally determined. The gas concentration prediction model trained in this paper performed well in the test set with a mean square error (MSE) of 0.0013, and its superiority was verified by comparing it with other models to provide some experience and basis for subsequent studies on gas concentration prediction in the upper corner.

Infrared Radiation Characterization of Damaged Coal Rupture Based on Stress Distribution and Energy.

As coal mine production enters the deep mining stage, the impact of coal and rock dynamic hazards is becoming more and more significant. And the coal and rock containing initial damage such as fractures are more susceptible to destabilization damage by disturbance. So, this paper takes coal containing macro-crack with different inclination angles as the research object and uses the RMT-150B rock mechanics system to carry out uniaxial loading rupture tests on the specimens. On this basis, the changes in infrared radiation on the surface are observed using an infrared thermal imaging camera, and it is analyzed and studied according to the stress distribution and energy change of the specimens. The results show that the strain ratio at crack closure after bearing the coal gradually increases with the increase in the macro-crack inclination. When the inclination angle is 0° < α < 90°, there are obvious low-temperature bands on the upper and lower sides after macro-crack closure. The variance of the infrared thermal image of the specimen can reflect its infrared radiation information more effectively and has a good correspondence with the stress-strain curve. With the increase in the specimen macro-crack inclination angle, the linear change of VIRT is more obvious, the rate of change gradually increases, and the inclination angle is the maximum at 90°. The accumulated elastic strain energy U e is the main source of energy for the sudden change in infrared radiation generated during the bursting process that occurs when the specimen is damaged, and U e is linearly and positively correlated with the change in infrared radiation in front of the specimen peak. These will provide some experimental basis and theoretical guidance for the use of infrared radiation precursor characteristics to warn the damaged coal-rock dynamic disaster.