本文針對具旋轉鰭片之套管式熱交換器進行數值熱流模擬，探討鰭片幾何參數對流場與熱場上的影響，並且在設計參數一定範圍內做單目標最佳化。利用幾何形狀參數包含鰭片占比、鰭片數量、鰭片高度、鰭片旋轉角度，組成不同構造的套管式熱交換器。在固定雷諾數、入口定溫的條件下模擬對向流動熱交換，數值模擬的結果以摩擦因子與紐賽數進行分析，並得出鰭片幾何對於管內熱傳及壓降的關係。由類神經網路建立熱交換器性能模型，並透過基因演算法做最佳化設計，以熱交換性能係數為指標搜尋設計參數內的最佳結果。最佳化搜尋之設計參數值與數值模擬進行驗證，並與建模使用的設計參數組相較，具有較佳的熱交換性能係數。顯示單目標最佳化的準確性以及數值模擬搭配類神經網路訓練的實用性。設計方法可用於各類熱交換器研究之參考。

This paper investigates the performance of a double pipe heat exchanger with twist fins by using numerical simulation and the single objective optimization method. The geometry variables of twist fins include fin proportion, number, height and rotation angle. The models simulate a counter flow in a heat exchanger under conditions of fixed Reynolds number and constant inlet temperature. The numerical results are analyzed by friction factor and Nusselt number for getting the relationship of fin geometry to heat transfer and pressure drop in the tube. These data can be used to build the performance model by the neural network method with the genetic algorithm for design optimization. The performance evaluation criteria (PEC) of the heat exchanger is the index of the design optimization. The design parameter of the optimal search is verified with numerical simulations and compared with other parameter. It has a better performance coefficient. The study shows the accuracy of the single-objective optimization method and the practicality of numerical modeling with neural network training. This design method can be used in different heat exchanger research and references.

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王啟川. 熱交換器設計. (五南圖書，民90)