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題名 | 田口法於銀奈米熱管之性能分析=Performance Analysis of Silver Heat Pipe Applications Using Taguchi Method |
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作者 | 陳育堂; 蔡聲鴻; 謝宏榮; | 書刊名 | 中華科技大學學報 |
卷期 | 58 2014.01[民103.01] |
頁次 | 頁29-42 |
分類號 | 440.137 |
關鍵詞 | 奈米流體熱管; 田口法; 變異數分析; 二階回歸方程; Nano-fluid heat pipe; Taguchi method; ANOVA; Second-order regression function; |
語文 | 中文(Chinese) |
中文摘要 | 奈米流體熱管的研究已進行許多年,由於影響其性能之控制變因有很多,因此常需耗費大量的時間實驗才能分析探討熱管的性能。此研究使用田口法進行實驗規劃,大量減少實驗次數,並對實驗結果進行變異數分析,找出每個因子在不同水準搭配下的最適化組合並探討各因子對奈米熱管性能表現的影響。本研究分別使用熱管長度180 mm、200 mm、220 mm,及傾斜角45°、60°、70°、90°,搭配加熱功率70 W、80 W、90 W、100 W,充填銀奈米流體濃度0 ppm、5 ppm、30 ppm、50 ppm交叉組合,以熱阻為品質進行L16直交表之田口方法分析其結果顯示最佳組合為60度的熱管傾斜角、80 W的加熱功率、5 ppm的奈米流體濃度與200 mm熱管長度,需另做實驗得知熱阻為0.016℃/W。最後利用二階回歸方程預測輸出品質,所得之預測熱阻值與實驗結果是相當符合,其準確度達99.94%。 |
英文摘要 | Nano-fluid heat pipe studies have been conducted for many years. Due to that the thermal performance of a heat pipe is affected by many variables, it requires a lot of time to experiment. In this study the Taguchi method was used to design experiments to reduce the experimental time. The ANOVA was used to find the optimal parameters and the influence of the individual factor on the performance of heat pipes. Parameters studied in this research were the length of heat pipe, the angle of inclination, the power of heating, and the concentration of the silver nano-fluid. The lengths of the heat pipe were 180 mm, 200 mm, and 220 mm; the angles of inclination were 45°, 60°, 70°, 90°; the heating powers were 70 W, 80 W, 90 W, 100 W; and the concentrations of the silver nano-fluid were 0 ppm, 5 ppm, 30 ppm, 50 ppm. Using the thermal resistance as the quality index, the Taguchi L16 orthogonal array method suggested that the best quality was achieved at the condition that the length of the heat pipe was 200 mm, the inclination angle was 60°, the heating power was 70 W, and the concentration of the nano-fluid was 5 ppm. Under this optimal condition, the thermal resistivity was 0.018℃/W. The analysis showed that the length of the heat pipe had the greatest impact of F=12.38 on the heat pipe performance. The second-order regression function was used to predicted the output quality. Comparing the predicted thermal resistances with the experimental results, it showed that the accuracy of predicted results was 99.94%. |
本系統之摘要資訊系依該期刊論文摘要之資訊為主。