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基于经典的Kelvin线热源模型和Kavanaugh圆柱源理论模型,运用负荷叠加、负荷阶跃、负荷累积的思想,结合人工神经网络建立了土壤源热泵系统地下埋管换热器仿真优化模型。与实验和理论已验证过的圆柱源理论模型的比较分析表明,地下埋管神经网络优化模型相对于传统的地下埋管解析解模型具有良好的计算精度和泛化能力,该模型应用于土壤源热泵系统的长期运行可以大大缩短计算时间,为土壤源热泵系统的优化及设计提供更有效率的模拟计算方法。
Based on the classic Kelvin linear heat source model and Kavanaugh cylindrical source theory model, the simulation model of underground heat exchangers for ground-source heat pump system is established with the idea of load superposition, load step and load accumulation combined with artificial neural network. Compared with the theoretical model of cylindrical source verified by experiment and theory, it shows that the neural network optimization model of underground buried pipe has good calculation accuracy and generalization ability compared with the traditional analytical model of underground pipe buried. This model is applied to soil source Long-term operation of the heat pump system can greatly shorten the calculation time, and provide a more efficient simulation calculation method for the optimization and design of the ground-source heat pump system.