Model-Based Intelligent Simulation of Underground Heat Ezchanger

摘要：

Referring to load aggregation scheme and superposition of pulses scheme, combining the conventional mathematical method with artificial neural network (ANN) is used to improve the modeling of the underground heat exchanger. In order to study computation time and calculation precision of the new model based on ANN, the improved model and the cylindrical source model are employed to simulate GSHPS operation under same simulation conditions. The simulation results show that new model-based intelligent simulation of ground heat exchanger has a good precision. Mean error of heat absorption capacity between the new model based intelligent and the cylindrical source model is 2.6％. Mean error of outlet flow temperature results between the new model based intelligent and the cylindrical source model is 1.28％. The computing time of new model is less than that of underground heat exchanger model based on superposition principle and cylindrical source theory. The computing time of improved model is lower than it of the no improved model about an order of magnitude under same simulation conditions.

关键词： Underground heat ezchanger The artificial neural network Simulation model

作者: Bo Fan Xinqiao Jin Zhimin Du Hua Dong Xuebin Yang

作者单位: School of Mechanical Engineering,Shanghai Jiao Tong University,Shanghai,China Institute of environment & municipal engineering,Qingdao Technology University,Qingdao,China

会议类型: 国际会议

会议名称: The 6th International Symposium on Heating,Ventilating and Air Conditioning(第六届国际暖通空调学术会议)

会议地点: 南京

会议语种:英文

页码: 1849-1856

在线出版日期: 2009-11-06（万方平台首次上网日期，不代表论文的发表时间）