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Application of artificial neural network in the prediction of scale dependency of dynamic effects in two-phase flow system

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conference contribution
posted on 21.08.2014, 08:49 by Luqman K. Abidoye, Diganta Das
Application of artificial neural network in the prediction of scale dependency of dynamic effects in two-phase flow system

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Chemical Engineering

Published in

XX. International Conference on Computational Methods in Water Resources (CMWR 2014)

Pages

00 - ?

Citation

ABIDOYE, L.K. and DAS, D.B., 2014. Application of artificial neural network in the prediction of scale dependency of dynamic effects in two-phase flow system. IN: XX. International Conference on Computational Methods in Water Resources Book of Abstracts and List of Participants. Stuttgart, Computational Methods in Water Resources (CMWR 2014).

Publisher

University of Stuttgart

Version

AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2014

Notes

This is a conference abstract accepted for the Computational Methods in Water Resources (CMWR2014) conference, University of Stuttgart, Germany on 9th -13th June, 2014. The complete abstract booklet is available at: http://www.cmwr14.de/images/bookofabstracts/CMWR14BookofAbstracts.pdf

Language

en

Location

Stuttgart, Germany

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