Title of article
Applicationofneuralnetworkstopredictionofphasetransportcharacteristicsinhigh-pressuretwo-phaseturbulentbubblyflowsOriginalResearchArticle
Author/Authors
An-ShikYang، نويسنده , , Tien-ChuanKuo، نويسنده , , Pou-HongLing، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2003
Pages
19
From page
295
To page
313
Abstract
Thephasetransportphenomenonofthehigh-pressuretwo-phaseturbulentbubblyflowinvolvescomplicatedinterfacialinteractionsofthemass,momentum,andenergytransferprocessesbetweenphases,revealingthatanenormouseffortisrequiredincharacterizingtheliquid–gasflowbehavior.Nonetheless,theinstantaneousinformationofbubblyflowpropertiesisoftendesiredformanyindustrialapplications.Thisinvestigationaimstodemonstratethesuccessfuluseofneuralnetworksinthereal-timedeterminationoftwo-phaseflowpropertiesatelevatedpressures.Threeback-propagationneuralnetworks,trainedwiththesimulationresultsofacomprehensivetheoreticalmodel,areestablishedtopredictthetransportcharacteristics(specificallythedistributionsofvoid-fractionandaxialliquid–gasvelocities)ofupwardturbulentbubblypipeflowsatpressurescovering3.5–7.0MPa.Comparisonsofthepredictionswiththetesttargetvectorsindicatethattheaveragedroot-mean-squared(RMS)errorforeachoneofthreeback-propagationneuralnetworksiswithin4.59%.Inaddition,thisstudyappraisestheeffectsofdifferentnetworkparameters,includingthenumberofhiddennodes,thetypeoftransferfunction,thenumberoftrainingpairs,thelearningrate-increasingratio,thelearningrate-decreasingratio,andthemomentumvalue,onthetrainingqualityofneuralnetworks.
Journal title
Nuclear Engineering and Design Eslah
Serial Year
2003
Journal title
Nuclear Engineering and Design Eslah
Record number
894566
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