本文以混合拉氏轉換法(Laplace transform technique)與有限差分法 (Finite difference method)的數值方法並配合最小平方法 (Least-squares scheme)及標準測試件之溫度量測值來預測CPU之散熱鰭片的散熱量與平均熱傳係數。由於標準測試件的厚度遠小於其長度與寬度，故本文以一維的數學模式來描述，並配合標準測試件之內部量測溫度來預估標準測試件表面溫度及表面熱通量。
結果顯示於自然對流(Free convection)與強迫對流(Forced convection)之環境下，鰭片間距與鰭片高度對本文預測值的影響不容忽視。自然對流環境下，平均熱傳係數會隨鰭片間距增大而增加，卻隨鰭片高度增高而減少。而本文之強迫對流(Forced convection)之平均熱傳係數的預測值將與相關文獻相比較，已驗証本文逆算法之準確性及合理性。

The present study applies the hybrid method of the Laplace transform technique and finite-difference method in conjunction with least-squares scheme and experimental temperature data to predict the heat dissipation and the average convection heat transfer coefficient on CPU heatsink. Due to the thickness of the standard test material is very smaller than its length and width, the one-dimension mathematical model is applied to perform the present inverse analysis. The effects of the fin spacing and fin height on the present estimates can not be negligible for free convection and forced convection. The free convection heat transfer coefficient is increased with increasing the fin spacing and is decreased with increasing the fin height. A comparison of the forced convection heat transfer coefficient between the present estimates and previous results is made in order to evidence the accuracy and reliability of the present inverse scheme.

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