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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 2014-08-21, 08:49 authored by Luqman K. Abidoye, Diganta DasDiganta 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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