Utilizing Artificial Neural Network for Load Prediction Caused by Fluid Sloshing in Tanks

In this research, neural network models were used to predict the action of sloshing phenomena in a tank containing fluid under harmonic excitation. A new methodology is proposed in this analysis to test and simulate fluid sloshing behavior in the tank. The sloshing behavior was first modeled using t...

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Main Authors: Hossein Goudarzvand Chegini, Gholamreza Zarepour
Format: Article
Language:English
Published: Wiley 2021-01-01
Series:Geofluids
Online Access:http://dx.doi.org/10.1155/2021/3537542
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author Hossein Goudarzvand Chegini
Gholamreza Zarepour
author_facet Hossein Goudarzvand Chegini
Gholamreza Zarepour
author_sort Hossein Goudarzvand Chegini
collection DOAJ
description In this research, neural network models were used to predict the action of sloshing phenomena in a tank containing fluid under harmonic excitation. A new methodology is proposed in this analysis to test and simulate fluid sloshing behavior in the tank. The sloshing behavior was first modeled using the smooth particle hydrodynamics (SPH) method. The backpropagation of the error algorithm was then used to apply the two multilayer feed-forward neural networks and the recurrent neural network. The findings of the SPH process are employed in the training and testing of neural networks. Input neural network data include the tank position, velocity, and acceleration, neural output data, and fluid sloshing curve wave position. The findings of the neural networks were correlated with the experimental evidence provided in the literature. The findings revealed that neural networks can be used to predict fluid sloshing.
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language English
publishDate 2021-01-01
publisher Wiley
record_format Article
series Geofluids
spelling doaj-art-7a425f44ee9e434fb9f8c0904f40dd4b2025-02-03T06:11:58ZengWileyGeofluids1468-81151468-81232021-01-01202110.1155/2021/35375423537542Utilizing Artificial Neural Network for Load Prediction Caused by Fluid Sloshing in TanksHossein Goudarzvand Chegini0Gholamreza Zarepour1Department of Mechanical Engineering, University Campus 2, University of Guilan, Rasht 41447-84475, IranDepartment of Mechanical Engineering, University of Guilan, Rasht 51665-315, IranIn this research, neural network models were used to predict the action of sloshing phenomena in a tank containing fluid under harmonic excitation. A new methodology is proposed in this analysis to test and simulate fluid sloshing behavior in the tank. The sloshing behavior was first modeled using the smooth particle hydrodynamics (SPH) method. The backpropagation of the error algorithm was then used to apply the two multilayer feed-forward neural networks and the recurrent neural network. The findings of the SPH process are employed in the training and testing of neural networks. Input neural network data include the tank position, velocity, and acceleration, neural output data, and fluid sloshing curve wave position. The findings of the neural networks were correlated with the experimental evidence provided in the literature. The findings revealed that neural networks can be used to predict fluid sloshing.http://dx.doi.org/10.1155/2021/3537542
spellingShingle Hossein Goudarzvand Chegini
Gholamreza Zarepour
Utilizing Artificial Neural Network for Load Prediction Caused by Fluid Sloshing in Tanks
Geofluids
title Utilizing Artificial Neural Network for Load Prediction Caused by Fluid Sloshing in Tanks
title_full Utilizing Artificial Neural Network for Load Prediction Caused by Fluid Sloshing in Tanks
title_fullStr Utilizing Artificial Neural Network for Load Prediction Caused by Fluid Sloshing in Tanks
title_full_unstemmed Utilizing Artificial Neural Network for Load Prediction Caused by Fluid Sloshing in Tanks
title_short Utilizing Artificial Neural Network for Load Prediction Caused by Fluid Sloshing in Tanks
title_sort utilizing artificial neural network for load prediction caused by fluid sloshing in tanks
url http://dx.doi.org/10.1155/2021/3537542
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