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ASME Press Select Proceedings
Intelligent Engineering Systems through Artificial Neural Networks Volume 18
Editor
ISBN-10:
0791802823
ISBN:
9780791802823
No. of Pages:
700
Publisher:
ASME Press
Publication date:
2008
eBook Chapter
21 Neural Network and Genetic Programming in Pressure Loss Estimation in Eccentric Pipe Flow
By
A. Murat Ozbayoglu
,
A. Murat Ozbayoglu
TOBB University of Economics and Technology
Department of Computer Engineering Ankara
, Turkey
; mozbayoglu@etu.edu.tr
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Cosku Kasnakoglu
,
Cosku Kasnakoglu
TOBB University of Economics and Technology
Department of Electrical Engineering Ankara
, Turkey
; kasnakoglu@etu.edu.tr
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Zeynep Aydiner
,
Zeynep Aydiner
TOBB University of Economics and Technology
Department of Computer Engineering Ankara
, Turkey
; zaydiner@etu.edu.tr
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M. Evren Ozbayoglu
M. Evren Ozbayoglu
Middle East Technical University
Department of Petroleum and Natural Gas Engineering Ankara
, Turkey
; ozevren@metu.edu.tr
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Page Count:
8
-
Published:2008
Citation
Ozbayoglu, AM, Kasnakoglu, C, Aydiner, Z, & Ozbayoglu, ME. "Neural Network and Genetic Programming in Pressure Loss Estimation in Eccentric Pipe Flow." Intelligent Engineering Systems through Artificial Neural Networks Volume 18. Ed. Dagli, CH. ASME Press, 2008.
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Studies of fluid flow in annular pipes have been popular in the petroleum engineering research. Most of the work has concentrated on CFD (Computational Fluid Dynamics) simulations, analytical and empirical models. In this study a neural network and evolutionary programming approach is developed to model the behavior of fluid flow in eccentric pipes. The model uses the fluid rheological parameters, density, mass flow rate, eccentricity, inner and outer pipe diameters, and predicts the pressure drop (ΔP) in the pipe in the flow direction. The evolutionary programming model uses basic mathematical operators, logarithm and sine functions. The results are compared with...
Abstract
Fluid Flow in Annular Pipes
Flow Control Problem
Tests
Results and Conclusions
Nomenclature
References
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