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題名：類神經網路應用於雙相氣泡流相傳遞特性之即時決定
書刊名：大葉學報
作者：楊安石／林柏宏
作者(外文)：Yang, An-shik／Lin, Po-hung
出版日期：2002
卷期：11:1
頁次：頁51-57
主題關鍵詞：類神經網路；倒傳遞；雙相氣泡流；相分佈；Neural networks；Back propagation；Two-phase bubbly flow；Phase distribution
原始連結：連回原系統網址new window
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　　　　　雙相氣泡流的物理傳輸機制可經由廣泛地實驗量測與複雜的理論模擬等探討過程而了解；然而，在實際的工業應用中常需要快速地決定紊流氣泡流場動態特性，故而本研究運用類神經網路以即時掌握雙相氣泡流流域內相發展的機制。分析係基於Liu’s所量測實驗的數據資料分別建立三個倒傳遞類神經網路，以預測雙相氣泡紊流的空泡分率、液相速度和氣相速度等分佈。三個訓練完成後的倒傳遞類神經網路計算輸出與原量測數值比較後，驗證結果發現預測和目標向量之均方根誤差低於4.33%。本研究也完整調查了各種網路參數（包含了隱藏層數目、訓練對數目、轉換函數型式、學習增加率數目、學習減少率數目和動量項數目等）對於類神經網路訓練品質的影響。
　　　　　The physical transport mechanisms of gas-liquid flows are innately complex and generally entail a great effort to comprehend the nature of the flow field through either experimental measurements or theoretical simulations. Nevertheless, instant knowledge of bubbly-flow characteristics is needed practically for many industrial applications. In this study, an approach for using neural networks is implemented to demonstrate their effectiveness in the real-time determination of fully developed two-phase flow properties of upward bubbly-pipe flows. Three back-propagation neural networks are established via a training process with Liu’s experimental database to predict the distributions of a void fraction and axial liquid/gas velocities of upward two-phase turbulent bubbly flows. Comparisons of the predictions with the test target vectors indicate that the average root-mean-squared errors from three back-propagation neural networks are well within 4.33%. This study also examines the effects of various network parameters, including the number of hidden nodes, transfer function type, number of training pairs, learning rate-increasing ratio, learning rate-decreasing ratio, and momentum value on the performance of neural networks in detail.
期刊論文
1.Ackley, D. H.、Hinton, G. E.、Sejnowski, T. J.(1985)。A learning algorithm for Boltzmann machines。Cognitive Science，9，147-169。  new window
2.Alien, M. G.、Bulter, C. T.、Johnson, S. A.、Lo, E. Y.、Russo, F.(1993)。An imaging neural network combustion control system for utility boiler applications。Combustion and Flame，94，205-214。  new window
3.Andrew, J. M.、Lieberman, S. H.(1991)。Use of a neural network for the analysis of fluorescence spectra from mixtures of poly-cyclic aromatic hydrocarbons。SPIE, Chemical, Biochemical, and Environmental Fiber Sensor，3(2)，121-133。  new window
4.Bankoff, S. G.(1960)。A variable density single-fluid model for two-phase flow with particular reference to steam-water flow。Journal of Heat Transfer，82，265-271。  new window
5.Beatie, D. R. H.(1972)。Two-phase flow structure and mixing length theory。Nuclear Engineering Design，21，46-64。  new window
6.Beyerlein, S. W.、Cossmann, R. K.、Richter, H. J.(1985)。Prediction of bubble concentration profiles in vertical turbulent two-phase flow。International Journal of Multiphase Flow，11，629-641。  new window
7.Carpenter, G. A.、Grossberg, S.、Reynolds, J. H.(1989)。ARTMAP: Supervised real-time learning and classification of nonstationary data by a self-organizing neural network。Neural Networks，4，303-314。  new window
8.Carpenter, G. A.(1989)。Neural network models for pattern recognition and associative memory。Neural Networks，2，243-257。  new window
9.Carpenter, G. A.、Grossberg, S.(1990)。ART 3: Hierarchical search using chemical transmitters in self-organizing pattern recognition architectures。Neural Networks，3，129-152。  new window
10.Chen, J. S.(1996)。Neural network based model and error compensation for thermally-induced spindle errors of a machining center。International Journal of Advanced Manufacturing Technology，12，303-308。  new window
11.Drew, D.、Lahey, R. T.(1982)。Phase distribution mechanisms in turbulent two-phase flow in a circular pipe。Journal Fluid Mechanics，117，91-106。  new window
12.Hsieh, W. H.、Chen , C. Y.(1998)。Inverse problem of specifying combustion parameters in the design of airbag inflators with neural networks。Combustion Science and Technology，136，171-197。  new window
13.Jacobs, R. A.(1988)。Increased rates of convergence through learning rates adoption。Neural Networks，1，295-307。  new window
14.Kuo, T. C.、Yang, A. S.、Pan, C. Pan、Chieng, C. C.(1997)。Eulerian-Lagrangian computations on phase distribution of two phase bubbly flow。International of Journal Multiphase Flow，24，1-15。  new window
15.Kuo, T. C.、Yang, A. S.、Pan, C. Pan、Chieng, C. C.(1999)。Effects of two phase turbulent structure interactions on phase distribution in bubbly pipe flows。Japanese Society of Mechanical Engineering Series B，42，419-428。  new window
16.Lahey, R. T.(1990)。The analysis of phase separation and phase distribution phenomena using two-fluid models。Nuclear Engineering Design，122，17-40。  new window
17.Levy, S.(1963)。Prediction of two-phase pressure drop and density distribution phenomena mixing length theory。Journal of Heat Transfer，85，137-152。  new window
18.Liu, T. J.(1993)。Bubble size and entrance length on void development in a vertical channel。International Journal of Multiphase Flow，19，99-113。  new window
19.Lopez de Bertodano, M.、Lahey, R. T.、Jones, D. C.(1994)。Development of a k-ε model for bubbly two-phase flow。Transaction American Society of Magazine Editors，116，128-134。  new window
20.Pokhama, H.、Mori, M.、Ransom, V. H.(1997)。The particle fluid model and using Lagrangian representation in two-phase flow modeling。Nuclear Engineering Design，175，59-69。  new window
21.Serizawa, A.、Kataoka, I.、Michiyoshi, I.(1975)。Turbulence structure of air-water bubbly flow。International Journal of Multiphase Flow，2，221-259。  new window
22.Shiraishi, H. I.、Susan, L.、Dongil, S. D.(1995)。CMAC neural network controller for fuel-injection system。IEEE Transaction on Control System Technology，3(1)，32-38。  new window
23.Whitaker, K. W.、Prasanth, Ravi K.、Markin, Robert E.(1993)。Specifying exhaust nozzle contours with a neural network。AIAA Journal，31，229-238。  new window
24.Carpenter, Gail A.、Grossberg, Stephen(1987)。A Massively Parallel Architecture for a Self-Organizing Neural Pattern Recognition Machine。Computer Vision, Graphics, and Image Processing，37，54-115。  new window
會議論文
1.Delhaye, J. M.(1969)。General equations of two-phase systems and their applications to air-water bubble flow and to steam-water flashing flow。11th Heat Transfer Conference。Minneapolis。  new window
2.Kuo, T. C.、Yang, A. S.、Pan, C. Pan、Chieng, C. C.(1997)。Prediction of the entrance region effect on turbulent bubbly flow in pipes。8th International Topical Meeting on Nuclear Reactor Thermal-Hydraulics。Kyoto。93-100。  new window
學位論文
1.Liu, T. J.(1989)。Experimental investigation of turbulence structure in two-phase bubbly flow(博士論文)。Northwestern University，Evanston, Illsnois, IL。  new window
圖書
1.Demuth, H.、Beale, M.(1993)。Neural Network Toolbox User's Guidance。Natick, Massachusetts：The Math Works Inc。  new window
2.Hertz, J.、Krogh, A.、Palmer, R. G.(1991)。Introduction to the Theory of Neural Computation。New York, NY：Addison-Wesley。  new window
圖書論文
1.Dumek, V.、Druckmuller, M.、Rauduensky, M.(1993)。Novel approaches to the IHCP: neural networks and expert systems。Inverse Problems in Engineering: Theory and Practice ASME。  new window
2.Matusi, G.(1992)。Characteristic structure of upward bubble flow。Dynamics of Two-Phase Flows。New York, NY：CRC Press。  new window
3.Rumelhart, D. E.、Hinton, G. E.、Williams, R. J.(1986)。Learning internal representation by error propagation。Parallel Distributed Processing。Cambridge, MA：MIT Press。  new window
 
 
 
 
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