本研究運用類神經網路(Artificial Neural Network)建立一蒸發器動態模型。模型建立利用SolidWorks進行繪製並利用COMSOL Multiphysics軟體進行蒸發器之數值模擬，觀察其溫度場及速度場之變化。透過模擬所得之數據，利用類神經網路建立蒸發器動態模型。
在類神經網路中，影響蒸發器出口溫度的參數包含：蒸發器入口溫度、流場中速度及蒸發器鰭片溫度，經由不同的參數影響可得到不同的蒸發器出口溫度，以此關係建立蒸發器動態模型。
研究結果顯示，透過類神經網路所建立之蒸發器動態模型，在COMSOL數值模擬中將其取代原蒸發器，並與原模型進行比較，其誤差位於可接受範圍內，因此往後在蒸發器應用中之模擬，皆可用此模型替代蒸發器，減少模擬的困難度。

In this thesis, we uses an artificial neural network to establish an evaporator dynamic model. The models are drawn by SolidWorks and use the COMSOL Multiphysics software to simulate the evaporator and observe the changes in temperature and velocity fields. According to the simulation of the data, the neural network is used to establish the evaporator dynamic model.In the neural network, the parameters affecting the evaporator outlet temperature include: evaporator inlet temperature, velocity in the flow field, and evaporator fin temperature. These parameters are used to establish the evaporator dynamic model.We replace the original evaporator with the evaporator dynamic model which is established by the neural network in the COMSOL numerical simulation and compare it with the original model. The error is within the acceptable range. The results show that in the evaporator application simulation, the evaporator can be replaced by this model to reduce the difficulty of the simulation.

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