MICS-ANN model: An artificial neural network model for fast computation of G-function in moving infinite cylindrical source model
MICS-ANN model: An artificial neural network model for fast computation of G-function in moving infinite cylindrical source model
复制标题
MICS-ANN模型：一种快速计算无限长圆柱源模型G函数的人工神经网络模型
DOI：
10.1016/j.geothermics.2021.102315
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发表时间：
2022-03
期刊：
影响因子：
3.9
通讯作者：
Y. Shoji;T. Katsura;K. Nagano
中科院分区：
文献类型：
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作者：
Y. Shoji;T. Katsura;K. Nagano
摘要地下换热器周围温度场模型是浅层地热系统模拟的关键部分。由于地下水流的存在或地下热交换器的复杂几何形状，一些模型尚未获得解析解。对于这样的模型，进行数值分析和计算成本是一个问题。在这里，我们展示了一种方法来重现有限体积法解的移动无限圆柱源模型快速，准确地使用人工神经网络。利用所得到的人工神经网络模型，仅需5.726s即可计算出移动无限圆柱源模型的逐时20年温度响应函数。有限体积法求解的人工神经网络模型的均方误差为2。158× 1 0− 6的无量纲温度，表明误差足够小。移动无限长圆柱热源模型的快速、准确计算，可望为具有地下水流场的浅层地热系统的优化设计提供参考。此外，这种用人工神经网络再现温度响应函数的方法不仅适用于无限长圆柱源模型，而且也适用于其它模型。
Abstract Model of the temperature field around the ground heat exchanger is a critical part of shallow geothermal system simulation. Some models have not yet obtained an analytical solution due to the presence of groundwater flow or the complex geometry of the ground heat exchanger. For such models, numerical analysis is performed and the computational cost is an issue. Here we show a method to reproduce the finite volume method solution of the moving infinite cylindrical source model quickly and accurately using an artificial neural network. Using the obtained artificial neural network model, the hourly 20-year temperature response function of the moving infinite cylindrical source model can be computed in only 5.726 s. The mean squared error of the artificial neural network model for the finite volume method solution was 2. 158× 1 0− 6 in dimensionless temperature, indicating a sufficiently small error. The fast and accurate calculation of the moving infinite cylindrical source model is expected to contribute to the optimal design of shallow geothermal systems with a groundwater flow field. In addition, this method of reproducing a temperature response function by artificial neural network may be applicable not only to the moving infinite cylindrical source model but also to other models.