基于遗传算法的岩土及填料热物性参数评估

发布时间：2018-03-03 21:59

  本文选题：填料热物性　切入点：遗传算法　出处：《湖南大学学报(自然科学版)》2017年03期 　论文类型：期刊论文

【摘要】：岩土及填料的热物性参数可直接影响地埋管换热器的性能设计.针对现场热响应测试中填料热物性参数需要预先测量,而无法通过计算直接评估的难题,在无限长线热源模型及管壁热阻修正复合介质线热源模型的基础上,应用遗传算法对岩土及填料的热物性参数同时进行评估,并结合热响应测试实验,验证了该方法的准确性.钻孔热阻、岩土导热系数和填料导热系数的评估值与实测值的相对误差分别为3.47%,1.42%和4.93%.2种模型计算所得流体平均温度与实测值的均方根误差分别为0.050 5℃和0.172℃.研究结果对地埋管换热器的设计具有重要参考价值.
[Abstract]:The thermal property parameters of rock, soil and fillers can directly affect the performance design of ground buried tube heat exchangers. In view of the difficult problem that the thermal physical parameters of fillers need to be measured in advance in the field thermal response test, they cannot be directly evaluated by calculation. On the basis of infinite line heat source model and tube wall heat resistance modified composite medium line heat source model, the thermal physical parameters of rock, soil and fillers are evaluated simultaneously by genetic algorithm, and the thermal response test experiment is carried out. The accuracy of the method is verified. The relative error between the evaluation value and the measured value of the thermal conductivity of rock soil and filler is 3.47% and 4.93.2%, respectively. The RMS error between the average temperature of fluid and the measured value is 0.050 鈩，

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