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研究生: 黃威程
Wei-Cheng Huang
論文名稱: 軸流式風扇多目標最佳化的數值模擬研究
A numerical simulation study of multi-objective optimization for axial fans
指導教授: 林顯群
Sheam-Chyun Lin
口試委員: 林顯群
Sheam-Chyun Lin
楊旭光
陳呈芳
學位類別: 碩士
Master
系所名稱: 工程學院 - 機械工程系
Department of Mechanical Engineering
論文出版年: 2023
畢業學年度: 112
語文別: 中文
論文頁數: 143
中文關鍵詞: 軸流風扇多目標最佳化流場數值模擬氣動力與聲響性能反應曲面法田口灰關聯法
外文關鍵詞: Axial-flow fan, The multiple-objective optimization, Numerical simulation, Aerodynamic and acoustic performances, Taguchi based gray relational analysis, Response surface method
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  • 由於風扇的發展歷史上已經非常悠久,隨著科技的發展,軸流式風扇的氣動力性能不斷提高,但也已經到達瓶頸,因此風扇的多目標性能最佳化成為研究重點,本文以常見的十四公分軸流風扇作為研究目標。建立一套具有可信度的最大風量、噪音分析模擬方法,接著列出有可能對於此兩項目標有影響的參數做田口法分析,並且利用此次田口法作為研究基礎。接著,縮小參數範圍並建立兩套最佳化方式,分別為田口灰關聯法與反應曲面法,以比較兩套最佳化方法的優劣;模擬研究結果顯示,以110 CFM、34 dBA當作最佳化目標,田口灰關聯法的最佳化結果為105.34 CFM、34.34dBA,誤差為4.23%、1%,而反應曲面法的最佳化結果為108.66 CFM、34.11dBA,誤差為1.1%、0.32%。綜合以上研究成果顯示,田口法能夠有效挑出貢獻度較大之控制因子,而不論是田口灰關聯分析及反應曲面法都能夠有效地為軸流式風扇進行性能優化,其中又以反應曲面法之效果更佳,但是需多耗時約60%時間,而本研究完成之系統化的多目標最佳化設計流程可應用於各式風扇之性能提升,如離心式、軸流式、斜流式風扇等。


    This research establishes an optimizing scheme under the multi-objective constraint for a 14cm-in-diameter axial-flow fan, which is used extensively in the electronic thermal designs. Firstly, an 8-design-variable parametric study is executed comprehensively with the aids of CFD simulation results to realize their influences on the maximum flow rate and the acoustic noise. Next, these numerical data are analyzed via Taguchi method to find the corresponding performance contribution for each parameter by comparing their signal-to-noise (S/N) ratios. The outcomes indicate that the dominant variables in order are the twist angles on mid-section and tip-end of the blade, the forward-inclined angle, and the deviated distance of blade, which can be used to decrease the number and narrow the variation range of parameters considered in the 2nd optimum phase.
    Thereafter, Taguchi-based gray correlation and response surface method are selected for conducting the in-depth optimization aiming at the design goal (110 CFM and 34 dBA). Subsequently, the response-surface method results in the aerodynamic and acoustic performances of 108.66 CFM and 34.11 dBA, which are deviated from the target by 1.1% and 0.32%, respectively. Also, Taguchi-based gray correlation analysis generates the slightly down-grade characteristics at 105.34 CFM (4.23%) and 34.34 dBA (1.1%) with a lesser analysis effort, which is roughly 60% of what needed in the response-surface method. In summary, this thesis demonstrates that Taguchi method can identify key parameters and their contributions. Also, both Taguchi based gray-correlation analysis and the response-surface method are capable to optimize the performance of an axial-flow fans near the design goal. Moreover, the multi-objective optimizing scheme established here can be utilized on the performance enhancement for other fan types under various design conditions.

    摘要 I Abstract II 誌謝 IV 目錄 V 圖目錄 IX 表目錄 XI 符號索引 XIII 第一章 緒論 1 1.1 前言 1 1.2 文獻回顧 2 1.2.1風扇設計 3 1.2.2風扇性能改善 4 1.2.3數值方法 8 1.3 研究動機與方法 10 第二章 風扇設計 17 2.1 軸流式風扇之參數定義與設計 17 2.1.1翼型 20 2.1.2 葉片之基本角度 23 2.1.3 葉片之偏移 26 2.2 風扇之性能曲線與噪音特性 32 第三章 數值方法 36 3.1 統御方程式 38 3.2 紊流模組 40 3.2.1 k-ɛ model 41 3.2.2 SST k-ω model 42 3.2.3 大尺度渦旋模擬法 46 3.3 聲學模式理論 47 3.4 數值計算和邊界條件 51 3.4.1離散化方程式 52 3.4.2流場數值計算之主要方法 55 3.4.3 邊界條件 56 第四章 原型風扇之流場模擬與田口法分析 59 4.1 原型風扇模型之模擬分析 59 4.1.1 風扇之計算區域建立與網格劃分 60 4.1.2 邊界條件 64 4.1.3 網格獨立性和時間獨立性之驗證 69 4.2 田口法分析 71 4.2.1 品質特性與目標值 72 4.2.2 控制因子與直交表選用 72 4.2.3 訊噪比分析 74 4.2.4 因子反應與變異數分析(ANOVA) 80 第五章 多目標之最佳化方法 89 5.1 田口灰關聯分析 91 5.1.1 田口法分析 93 5.1.2 灰關聯分析(Grey Relational Analysis,GRA) 99 5.2 反應曲面分析 112 5.2.1 中央合成設計 116 5.2.2 D-optimal最佳設計 117 5.2.3變異數分析(ANOVA) 123 5.2.4 預測最佳模型與建立反應曲面 127 第六章 結論與建議 135 6.1 結論 136 6.2 建議 138 參考文獻 141

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