煤自燃的发生严重威胁着自然环境、人类生存安全以及经济发展，被称为全球性的灾难。重力热管内部工质的两相流动可提取煤自燃产生的热量，降低煤堆温度，从而实现煤自燃的“绿色”治理。本文借助标准正交表设计关于工质种类(Al₂O₃-H₂O纳米流体，CuO-H₂O纳米流体及TiO₂-H₂O纳米流体)，充液率(15%，25%，35%)，长径比(16，11，8.5)的9根重力热管，探究重力热管应用于不同煤堆温度(70, 140, 210 °C)时煤堆温度场的变化规律及冷凝段温度分布情况；计算不同工况下重力热管的提热性能指标参数(降温幅度，降温率，有效影响半径，提热量)。结合层次分析法(AHP法)、熵权法以及逼近理想排序法(TOPSIS法)综合评价9根重力热管作用于不同工作温度时的提热性能，并使用极差法对实验结果进行分析，优选煤自燃不同温度阶段时重力热管最佳参数组合。最后基于VOF(volume of fluid)模型建立重力热管内部多相流过程，预测9根重力热管在高温下(350 °C)的提热性能，借助极差分析对重力热管进行优化，为重力热管应用于煤自燃热能提取方面的研究以及现场应用提供理论基础。主要研究结果如下：重力热管可有效降低煤堆温度，控制煤堆高温区域扩散，煤堆温度越高，降温效果越明显；其降温过程可分为大幅下降阶段以及平缓下降阶段，工作温度越高大幅下降阶段所占时间越长。此外，重力热管冷凝段测点温度随着工作时间的增加呈现出先急剧上升后缓慢下降并趋于平缓的变化趋势，冷凝段趋近于蒸发段的区域提热性高、稳定性好。另外，煤堆内测点的降温幅度和降温率与测点和重力热管之间的距离呈负相关。重力热管的提热量与工作温度呈正相关，而重力热管的有效影响半径随煤堆温度的增加并无规律性的变化。使用AHP法与熵权法确定表征重力热管提热性能的指标参数权重，结合TOPSIS法对正交实验结果进行综合评价，借助极差法对综合评价进行分析获得：在煤堆温度为70 °C时，实验最佳与综合优化所得重力热管皆为1^#重力热管；煤堆温度为140°C时，实验最佳与综合优化所得重力热管都为5^#重力热管；当煤堆温度升至210 °C时，实验最佳重力热管为3^#，而综合优化所得最佳参数组合：工质种类为Al₂O₃-H₂O纳米流体，充液率为15%，长径比为8.5。使用FLUENT数值模拟软件建立VOF模型，对工作温度为210 °C时综合优化所得重力热管最佳参数组合进行数值模拟，对比发现综合优化所得重力热管等效对流换热系数较实验最佳提升了12.94%。另外，预测及优化工作温度为350 °C的重力热管，获得各因素对重力热管提热性能的影响重要程度依次为：长径比>工质种类>充液率，最佳参数组合：工质种类为Al₂O₃-H₂O纳米流体，充液率为25%，长径比为8.5。

Coal spontaneous combustion (CSC) is called as a global disaster, which seriously threatens the natural, human healthy and economic growth. In order to realize the "green" control of CSC, there are lots of researchers have been applied Gravity Heat Pipe (GHP) on extracting the heat energy generated by CSC. In this study, 9 GHPs have been designed based on working fluid (Al₂O₃-H₂O nanofluids, CuO-H₂O nanofluids, and TiO₂-H₂O nanofluids), working fluid filling rates (15%, 25%, 35%), and length-diameter ratio (16, 11, 8.5) helped with orthogonal experiment. 9 GHPs had been applied on coal pile with different temperature to explore the influence of GHP on the temperature and temperature distribution of condensation section. Four index parameters (cooling range, cooling rate, effective radius, and extracting heat performance), which characteristic the heat transfer performance of GHP had been calculated. The weight of each index parameter is determined by the combination of analytic hierarchy process (AHP) and entropy weight method. And the method of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is used to evaluate the comprehensive extract heating performance of the 9 GHP under different temperature. And then, the range analysis was used to analyses the results of orthogonal experiment. Moreover, based on the VOF model, the multiphase flow process inside the GHP is established, and the total thermal resistance and equivalent convective heat transfer coefficient of 9 GHPs are calculated when the working temperature is 350 °C. The main research contents and results are as follows:

GHP can effectively reduce the temperature of coal pile. The cooling process of measuring points can be divided into two stages: large decline stage and gentle decline stage, and the high temperature coal pile have longer large decline stage. With the increase of working time, the temperature of condensation section increases sharply at first, then decreases slowly and tends to decrease. Besides, the closer the measuring point of condensation section is to evaporation section, the higher and more stable the temperature is. The cooling range and cooling rate of coal pile measuring points are positive correlation with the distance between measuring points and GHP. Furthermore, the extracting heat performance of GHP is positive with working temperature. However, the effective radius of GHP does not changed regularly with the temperature increased. According to range analysis, when the temperature is 70 °C, the best extracting heat performance of GHP by experiment and comprehensive optimization is 1^#. When the temperature rises to 140 °C, the best GHP by experiment and comprehensive optimization is 5^#. When the temperature is 210 °C, the GHP obtained by experiment is 3^#, and the optimal parameter combination obtained by comprehensive optimization：working fluid is Al₂O₃-H₂O nanofluids, working fluid filling rates is 15%, and length-diameter ratio is 8.5. The VOF model is established to simulate the optimal parameters combination of the GHP under 210 °C. The results show that the effective convective heat transfer coefficient is 12.94% higher than the experimental optimum. Moreover, combined with numerical simulation and orthogonal experiment, the equivalent convective heat transfer coefficient of 9 GHPs was been calculated. And the influence degree of each factor and best parameter combination was obtained: aspect ratio > working medium type > liquid filling rate, working fluid is Al₂O₃-H₂O nanofluids, working fluid filling rates is 25%, and length-diameter ratio is 8.5.

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