本論文旨在探討反算法於三維不規則邊界形狀之預測。在實際工程中，考慮一三維物理模型其不規則的邊界形狀或是隨著時間而變動的不規則邊界形狀，可能無法由直接量測或是計算求得，這些不規則邊界幾何形狀將可由反算法中的函數預測法，又稱急遽遞減法(Steepest Descent Method)配合模擬紅外線溫度感測器所量測的溫度值來預測之。
本論文可分為兩個主題，均在探討反算法應用於不規則邊界形狀的預測，在第二章及第三章中，吾人皆以套裝軟體CFD-RC為基礎，利用急遽遞減法來研究三維任意幾何形狀的逆向熱傳導問題。在第二章中，乃利用急遽遞減法來進行三維未知穩態邊界形狀的預測，本問題的物理模型為一三維均勻材質，在上邊界Stop為一未知不規則幾何形狀，藉由已知邊界條件，以及量測面之溫度分佈來修正所預測的未知不規則邊界形狀。第三章中，則針對隨時間改變的未知不規則幾何形狀進行預測。
此外，吾人並考慮在不同起始猜值，以及不同量測誤差的情況下，討論上述方法對此兩個主題中所預測之邊界形狀的準確性。

A three-dimensional inverse geometry problem (shape identification problem), which is very limited in the literatures, in determining the unknown irregular surface configurations by utilizing the conjugate gradient method (CGM) and a general purpose commercial code CFD-RC is successfully developed and examined in this study based on the simulated measured temperature distributions on the bottom surface by infrared thermography. The advantage of calling CFD-RC as a subroutine in the present inverse calculation lies in that its auto mesh function enables the handling of this moving boundary problem.
Results obtained by using the technique of CGM to solve the inverse geometry problem are justified based on the numerical experiments. Three test cases are performed to test the validity of the present algorithm by using different types of surface shapes, initial guess and measurement errors. Results show that excellent estimations on the unknown surface geometry can be obtained with any arbitrary initial guesses.

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