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研究生:屈鴻均
論文名稱:應用基因遺傳演算法及模擬退火演算法優化電路板晶片之佈局
論文名稱(外文):Application of Genetic Algorithms and Simulated Annealing to the optimal microchip layout on a printed wiring board
指導教授:陳冠
指導教授(外文):Kuan Chen
學位類別:碩士
校院名稱:國立臺灣科技大學
系所名稱:機械工程系
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:1999
畢業學年度:87
語文別:中文
論文頁數:108
中文關鍵詞:遺傳演算法模擬退火演算法佈局晶片
外文關鍵詞:Genetic AlgorithmsSimulated Annealinglayoutmicrochip
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摘要
微小晶片在印刷電路板上的佈局,在電子元件散熱的問題上,佔有很重要的席位。一組好的晶片佈局,可以使晶片表面的最高溫降低,因此延長晶片的壽命,減少成本的浪費。
在精密度不設限的情況下,晶片的佈局有無限多組解。用窮舉法來找,不僅沒有效率,更不見得能找到最佳解。本文以人工智慧的“基因遺傳演算法”以及“模擬退火演算法”作平面熱傳問題的最佳化。以“解析解方法”取代CFD的繁雜設定及費時計算,藉這兩種演算法之優越的搜尋及學習能力,得到不錯的結果,也證明這兩種方法的可靠性。
最後再將平面熱傳問題的最佳、次等、最差佈局所算出之溫度分佈,與同樣佈局但凸起1mm及5mm的CFD套裝軟體算出之晶片表面溫度作比較。結果顯示,晶片發熱量迥異之平面熱傳問題裡的較差佈局與次等佈局在晶片凸起的情形下,呈現混沌不明的局面。原因是迴流區加上尾流區的效應,打亂了原有的優劣次序。然而慶幸的是,在最佳佈局裡,因其獨有佈局特質的明確性,使其雖受迴流區及尾流效應的影響,卻不至於影響到其最佳佈局的優越性;也就是說,當晶片發熱量迥異時,平面熱傳問題之最佳佈局的確能為凸起晶片之佈局所採用,這正符合我們的期待。
晶片發熱量相近的平面熱傳問題之佈局與凸起晶片之佈局,呈現優劣互換的遺憾結果。據研究及文獻說法,晶片間迴流及尾端迴流的效應,成為優劣互換的關鍵。迴流效應越強烈,流場的散熱效果越好,所以凸起晶片較佳的佈局,理應順勢而為。然而這佈局法卻不受平面熱傳問題之較佳佈局的青睞。在平面熱傳的較佳佈局表現上,因前面幾個晶片無間距的確是較好的佈局策略,卻不巧是凸起晶片須避免之無迴流效應的夢魘,況且連帶讓晶片間的熱量產生連續囤積,比比都是導致凸起晶片散熱不良的致命傷。但撥亂反正的是,雖然無法直接套用平面熱傳所找出之最佳佈局方法,但若能洞悉這兩者中間差異性的奧妙及源由,便也能大膽的在凸起晶片之較佳佈局預測上,窺知一二。
在相關文獻的研究議題上,多人是使用實驗的方法來研究較佳佈局。然而在佈局的精度考量上,明顯不足且粗糙。因為其只能約略的講述大方向,無法作個通盤考量。然而本文可補其不足,應用人工智慧所找到的全域最佳解,作更明確的佈局指示。

ABSTRACT
The layout of microchips on a printed wiring board plays an important role in electronics cooling problems. Optimizing the chip layout has the potential to considerably reduce the maximum chip temperature, resulting in longer service time and lower replacement costs of microchips.
Theoretically there are infinite ways to arrange a set of microchips on a printed wiring boards if no restriction is placed on the spatial resolution of chip locations and spacing. Thus the use of exhaustive search to determine the optimal chip locations and spacing. Thus the use of exhaustive search to determine the optimal chip layout is inefficient and may not be able to find the best result. In the present study two AI techniques: GA and SA were employed for optimizing the heat transfer from a set of microchips of different sizes
And power rates flush-mounted on a circuit board. The analytical solution of laminar flow over a flat plate with spatially varying heat flux was used in place of CFD computation to save the time and effort require for the optimization of chip layout. Both methods demonstrated superb learning capability and search speed.
Also included in the present investigation are comparisons between the
Heat transfer results of flush-mounted chips and microchips sticking out of the circuit board surface. The height of the microchips in the latter case ranged from 1 to 5mm and a commercial CFD code PHOENICS was used for heat transfer calculations. The surface temperature distribution of flush-mounted chips differed slightly from that of chips of finite height. However the optimal chip layout determined from the analytical solution of flush-mounted chips was found to be still applicable to the layout of chips of finite height.
Previous studies of the optimization of microchip layouts were mainly experimental work and were low in accuracy. Only the pattern of optical chip layouts were determined in these experiments. The present investigation applied AI to the search of the best solution among all valid chip layouts. As a result the optimal chip layouts can be definitely determined.

目錄
摘要………………………………………………………………. I
英文摘要…………………………………………………………. III
誌謝……………………………………………………………… V
目錄……………………………………………………………… VI
圖表目錄………………………………………………………… IX
符號索引………………………………………………………… XIV
第一章 緒論
1.1 前言…………………………………………………. 1
1.2 研究目的……………………………………………. 2
1.3 研究範圍……………………………………………. 2
1.4 文獻回顧……………………………………………. 3
1.5 本文內容綱要………………………………………. 11
第二章 問題架構及研究模式
2.1 問題說明…………………………………………... 13
2.2平面熱傳問題之說明……………………………….. 14
2.2.1 解析解之理論模式…………………………… 14
2.2.2 本文平面熱傳之物理模式設定……………… 15
2.3 基因遺傳演算法(GA)之工作原理………………… 16
2.4 GA應用於本文研究之設定………………………. 21
2.5 模擬退火演算法(SA)之工作原理………………… 26
2.6 SA應用於本文研究之設定……………………….. 29
2.7 PHOENICS應用於本文研究之設定……………… 32
2.7.1 基本假設………………………………………. 32
2.7.2 邊界條件………………………………………. 32
2.7.3 數值分析………………………………………. 33
第三章 結果分析與討論
3.1 遺傳演算法結果分析與討論……………………... 37
3.1.1 晶片發熱量迥異之情況……………………… 37
3.1.2 晶片發熱量相近之情況……………………… 40
3.2 模擬退火演算法結果分析與討論………………... 42
3.2.1 晶片發熱量迥異之情況……………………… 42
3.2.2 晶片發熱量相近之情況……………………… 43
3.3 平面熱傳與凸起晶片之差異性…………………... 44
3.3.1 PHOENICS格點疏密度及疊代次數之測試.. 44
3.3.2 晶片發熱量迥異之情況……………………… 48
3.3.3 晶片發熱量相近之情況……………………… 51
第四章 結論與建議
……………………………………………………………………… 56
參考文獻…………………………………………………………… 57
作者簡介…………………………………………………………… 58

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