Heat transfer analysis of surrounding rocks with thermal insulation layer in high geothermal roadway

Zhang, Yuan; Wan, Zhijun; Ma, Zhaoyang; Gu, Bin; Ma, Yangsheng

doi:10.2298/tsci161027178z

Cited by 3 publications

(2 citation statements)

References 7 publications

(7 reference statements)

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“…The dropout layer parameter, batch size, and optimizer learning rate were set as hyperparameters of the LSTM network model. The value ranges for optimization of hyperparameters were set as follows: [10,100] for the number of units in the LSTM layer, [0.1, 0.3] for the dropout layer parameter, [5,25] for the batch size, and [0.0001, 0.01] for the Adam optimizer learning rate.…”

Section: Modeling and Hyperparameter Tuningmentioning

confidence: 99%

“…In respect of heat exchange, the airflow temperature rise is mainly from the heat dissipated by the surrounding rocks [10], especially when the airflow is transported through a long distance from the pit bottom to the working face (Figure 1). The heat is exchanged between airflow and surrounding rock unsteadily, in a complex manner [11], and its theoretical calculation is based on the unstable heat exchange coefficient K τ derived from the concept of the temperature regulation sphere.…”

Section: Introductionmentioning

confidence: 99%

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Predicting Temperature and Humidity in Roadway with Water Trickling Using Principal Component Analysis-Long Short-Term Memory-Genetic Algorithm Method

Wu,

Jia,

Zhang

et al. 2023

Applied Sciences

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The heat dissipated from high geo-temperature underground surrounding rocks is the main heat source of working faces, while thermal water upwelling and trickling into the roadway will notably deteriorate the mine’s climate and thermal comfort. Predicting airflow temperature and relative humidity (RH) is conductive to intelligent control of air conditioning cooling and ventilation regulation. To accommodate this issue, an intelligent technique was proposed, integrating a genetic algorithm (GA) and long short-term memory (LSTM) based on rock temperature, inlet air temperature, water temperature, water flow rate, RH, and ventilation time. A total of 21 input features including over 200 pieces of data were collected from an independently developed modeling roadway to construct a dataset. Principal component analysis (PCA) was conducted to reduce features, and GA was used to tune the LSTM and PCA-LSTM architectures for best performance. The following research results were yielded. The proposed PCA-LSTM-GA model is more reliable and efficient than the single LSTM model or hybrid LSTM-GA model in predicting the air temperature Tfout and humidity RHout at the end of the water trickling roadway. The importance scores (ISs) indicate that Tfout is mainly influenced by the surrounding rock temperature (IS 0.661) and the inlet air temperature (IS 0.264). While RHout is primarily influenced by the rock temperature in the water trickling section (IS 0.577), the inlet air temperature (IS 0.187), and the trickling water temperature and flow rate (total IS 0.136), and it has an evident time effect. In addition, we developed relevant equipment and provided engineering practice methods to use the machine learning model. The proposed model, which can predict the mine microclimate, serves to facilitate coal and geothermal resource co-mining as well as thermal hazard control.

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Section: Modeling and Hyperparameter Tuningmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Predicting Temperature and Humidity in Roadway with Water Trickling Using Principal Component Analysis-Long Short-Term Memory-Genetic Algorithm Method

Wu,

Jia,

Zhang

et al. 2023

Applied Sciences

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Experimental Study on the Heat Transfer Mechanism of Temperature Field of High Geothermal Tunnels

Lu,

Yu,

Wang

et al. 2024

Preprint

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Influence of temperature on physical and mechanical properties of a sedimentary rock: Coal measure mudstone

et al. 2021

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Determining the physical and mechanical behavior of sedimentary rocks is one of the most common challenges in deep rock mass engineering. Experiments were conducted to study the physical and mechanical properties of coal measure mudstone with scanning electron microscope, xrays diffraction and uniaxial compression testing. The results show that temperature has a significant effect on the physical and mechanical properties of coal measure mudstone. The presence of clay minerals in the evaluated mudstone contributes to the unique characteristics seen at high temperature. The mudstone experiences obvious color changes on the surface as temperature rises. This is mostly attributed to the iron-bearing clay minerals. Internal color change is caused by thermal decomposition of kerogen associated with the clay minerals. As the major clay mineral in mudstone, kaolinite undergoes significant phase changes at high temperatures, which leads to changes in mechanical properties. From 25℃ to 200℃, due to the evaporation of absorbed water from the clay minerals, the strength of the mudstone increases significantly. As the temperature continues to rise beyond this, water evaporation continues and the rock strength increases gradually from 200℃ to 400℃. When the temperature reaches 400℃, this mudstone was strengthened as a result of decomposition of the kaolinite and thermal expansion of crystalline minerals. Above 600℃, dehydration of the clay minerals ends while thermal cracking initiates gradually, which results in decreasing strength.

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Heat transfer analysis of surrounding rocks with thermal insulation layer in high geothermal roadway

Cited by 3 publications

References 7 publications

Predicting Temperature and Humidity in Roadway with Water Trickling Using Principal Component Analysis-Long Short-Term Memory-Genetic Algorithm Method

Predicting Temperature and Humidity in Roadway with Water Trickling Using Principal Component Analysis-Long Short-Term Memory-Genetic Algorithm Method

Experimental Study on the Heat Transfer Mechanism of Temperature Field of High Geothermal Tunnels

Influence of temperature on physical and mechanical properties of a sedimentary rock: Coal measure mudstone

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