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TECHNICAL BRIEFS

Prediction of Turbulence Statistics Behind a Square Cylinder Using Neural Networks and Fuzzy Logic

[+] Author and Article Information
P. K. Panigrahi, Manish Dwivedi, Vinay Khandelwal

Department of Mechanical Engineering, Indian Institute of Technology, Kanpur, UP 208016, India

Mihir Sen

Department of Aerospace Engineering, University of Notre Dame, Notre Dame, IN 46556

J. Fluids Eng 125(2), 385-387 (Mar 27, 2003) (3 pages) doi:10.1115/1.1537251 History: Received March 19, 2002; Revised August 28, 2002; Online March 27, 2003
Copyright © 2003 by ASME
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References

Sen, M., and Goodwine, J. W., 2001, “Soft Computing in Control,” The MEMS Handbook, M. Gad-el-Hak, ed., CRC Press, Boca Raton, FL, Chap. 14, pp. 1–37.
Dutta, S., Muralidhar, K., and Panigrahi, P. K., 2002, “Influence of the Orientation of a Square Cylinder on the Wake Properties,” Exp. Fluids, in press.
Panigrahi, P. K., Khandelwal, V., and Sen, M., 2002, “Prediction of Turbulent Statistics Behind a Rib Using Artificial Neural Network,” Proceedings of the Fifth ISHMT/ASME Heat & Mass Transfer Conference & Sixteenth National Heat & Mass Transfer Conference, Calcutta, Jan. 3–5, Tata McGraw-Hill, pp. 676–681.
Xie,  H., Mahajan,  R. L., and Lee,  Y., 1995, “Fuzzy Logic Models for Thermally Based Microelectronic Manufacturing Processes,” IEEE Trans. Semicond. Manuf., 8(3), pp. 219–226.
Rediniotis,  O. K., and Chrysanthakopoulos,  G., 1988, “Application of Neural Networks and Fuzzy Logic to the Calibration of the Seven-Hole Probe,” ASME J. Fluids Eng., 120, pp. 95–101.

Figures

Grahic Jump Location
Comparison of u,v,urms,vrms, and uv data at various X/h-locations with ANN and FLM predictions. Symbols correspond to experimental data, solid line to FLM and dotted line to ANN. Different data are used for training and testing.

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