本文主要探討硬焊型板式熱交換器以逆向流之流動方式，觀察入出埠口隨時間變化之物理現象，其中將會透過實驗與計算流體力學(CFD)軟體進行分析。首先由實驗數據得到隨時間相關之溫度流量關係，算出其總熱阻係數R，再利用CFD與實驗比對，並藉由CFD找到合適之R值進行研究與探討。
接著，運用類神經網路( Neural Network , NN )中R-NN之方式，將CFD算得之總熱阻係數與埠口質量流率進行訓練，且得到其關係式，方便未來進行使用與研究7層者，能夠直接拿來運用或當查表。
然而大部分文獻皆僅探討穩態之問題，對於控制結合熱流方面而言，時間軸的變化是非常重要與關注的，故本文最後藉由CFD進行暫態模擬分析，主要觀察3,5,7層各自達穩態時間之物理現象，以供未來進行此模組之運行有一定的參考依據。

This paper mainly discusses the physical phenomenon of the brazed plate heat exchanger in the reverse flow, and observes the physical phenomenon of the inlet and outlet changes with time, which will be analyzed by experimental and computational fluid dynamics (CFD) software. Firstly, the temperature-flow relationship related to time is obtained from the experimental data, and the total thermal resistance coefficient R is calculated. Then the CFD is compared with the experiment, and the appropriate R value is found by CFD.
Then, using the R-NN method in the Neural Network (NN), the total thermal resistance coefficient calculated by CFD and the mass flow rate of the mouth are trained, and the relationship is obtained, which is convenient for future use and research. The layer can be used directly or when looking up the table.
However, most of the literature only discusses the problem of steady state, the change of time axis is very important and concerned for controlling the combined heat flow. Therefore, the transient simulation analysis by CFD is mainly carried out in this paper. The main observations are 3, 5, 7 The physical phenomena of each layer reaching the steady-state time have certain reference for future operation of this module.

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