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Keywords: neural network
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Proceedings Papers

Proc. ASME. FEDSM2020, Volume 3: Computational Fluid Dynamics; Micro and Nano Fluid Dynamics, V003T05A055, July 13–15, 2020
Paper No: FEDSM2020-20184
...Abstract Abstract Investigation of applying physics informed neural networks on the test case involving flow past Converging-Diverging (CD) Nozzle has been investigated. Both Artificial Neural Network (ANN) and Physics Informed Neural Network (PINN) are used to do the training and prediction...
Proceedings Papers

Proc. ASME. FEDSM2020, Volume 3: Computational Fluid Dynamics; Micro and Nano Fluid Dynamics, V003T05A056, July 13–15, 2020
Paper No: FEDSM2020-20196
... Reynolds number of 30,000 for SD7003 airfoils using a genetic algorithm. Three artificial neural networks were coupled with the genetic algorithm to reduce the computational cost. The optimization process was used to find the optimum design parameters in order to maximize lift to drag ratio of airfoils...
Proceedings Papers

Proc. ASME. FEDSM2012, Volume 1: Symposia, Parts A and B, 783-788, July 8–12, 2012
Paper No: FEDSM2012-72468
... discrete information at given points; especially, for the cases of complex flows such as free vortex dump combustor swirling flows. For this type of flows, usual numerical interpolating schemes appear to be unsuitable. Recently, neural networks have emerged as viable means of expanding a finite data set...
Proceedings Papers

Proc. ASME. FEDSM2010, ASME 2010 3rd Joint US-European Fluids Engineering Summer Meeting: Volume 1, Symposia – Parts A, B, and C, 893-898, August 1–5, 2010
Paper No: FEDSM-ICNMM2010-30834
... Intensity in a Combustor Model Using Neural Network Analysis Saad A. Ahmed and Hany El Kadi College of Engineering, Mechanical Engineering Department, American University of Sharjah, Sharjah , PO Box 26666, UAE Phone: +9 71 6 5152468; Fax: +9 71 6 5152979 E-mail: sahmed@aus.edu ABSTRACT Predictions...