Experiment and Simulation on a Refrigeration Ventilation System for Deep Metal Mines

被引:0
作者
Shao, Wei [1 ,2 ]
Wang, Shuo [1 ]
Wang, Wenpu [1 ]
Shao, Kun [2 ]
Xiao, Qi [3 ,4 ]
Cui, Zheng [2 ]
机构
[1] Shandong Univ, Inst Thermal Sci & Technol, Jinan 250061, Peoples R China
[2] Shandong Inst Adv Technol, Jinan 250100, Peoples R China
[3] Wuhan 2nd Ship Design & Res Inst, Wuhan 430205, Peoples R China
[4] Sci & Technol Thermal Energy & Power Lab, Wuhan 430205, Peoples R China
基金
中国博士后科学基金;
关键词
refrigeration ventilation system; deep metal mine; simulation; heat current method; ARTIFICIAL NEURAL-NETWORK; HEAT-EXCHANGER NETWORKS; PERFORMANCE PREDICTION; OPTIMIZATION; DESIGN; MODEL; PUMPS; WATER;
D O I
10.3390/su15107818
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Significant harm from heat has become a key restriction for deep metal mining with increasing mining depth. This paper proposes a refrigeration ventilation system for deep metal mines combined with an existing air cycling system and builds an experimental platform with six stope simulation boxes. Using the heat current method and the driving-resistance balance relationship, the heat transfer and flow constraints of the system were constructed. An artificial neural network was used to establish models of heat exchangers and refrigerators with historical experimental data. Combining the models of the system and stope simulation box, an algorithm that iterates the water outlet temperature of the evaporator and condenser of the refrigerator was proposed to design the coupled simulation model. The heat balance analysis and comparison of the air outlet temperatures of the stope, as well as the heat transfer rates of the heat exchangers with the experimental data, validated the coupled simulation model. Additionally, the effects of cooling fans and the air inlet temperature of the cooling tower were discussed, which provided a powerful modelling method for the coupled model of a refrigeration ventilation system, helps to reduce energy consumption, and improves the sustainability of mining production.
引用
收藏
页数:20
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