Prediction of the Superficial Heat Source Parameters for TIG Heating Process Using FEM and ANN Modeling

Prediction of the Superficial Heat Source Parameters for TIG Heating Process Using FEM and ANN Modeling

The basic problem of the numerical model’s quenching process is establishing the characteristics of the boundary conditions. The existing descriptions of the boundary conditions, which represent the parameters of equipment used in heat treatment processes, do not accurately reflect the act...

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Main Authors: Joanna Wróbel, Adam Kulawik
Format: Article
Language:English
Published: MDPI AG 2019-09-01
Series:Entropy
Subjects:
artificial neural network
finite element method
tig welding
Online Access:https://www.mdpi.com/1099-4300/21/10/954
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spelling doaj-4f22b6a99495413d89c7ab840b2835c02020-11-25T01:50:57ZengMDPI AGEntropy1099-43002019-09-01211095410.3390/e21100954e21100954Prediction of the Superficial Heat Source Parameters for TIG Heating Process Using FEM and ANN ModelingJoanna Wróbel0Adam Kulawik1Institute of Computer and Information Sciences, The Faculty of Mechanical Engineering and Computer Science, Czestochowa University of Technology, Dabrowskiego 73, 42-201 Czestochowa, PolandInstitute of Computer and Information Sciences, The Faculty of Mechanical Engineering and Computer Science, Czestochowa University of Technology, Dabrowskiego 73, 42-201 Czestochowa, PolandThe basic problem of the numerical model’s quenching process is establishing the characteristics of the boundary conditions. The existing descriptions of the boundary conditions, which represent the parameters of equipment used in heat treatment processes, do not accurately reflect the actual process conditions. In the present study, the method of choice for superficial heat source parameters for TIG (tungsten inert gas) heating is modeled using artificial neural networks (ANN) and the finite element method (FEM). A comparison of the calculations obtained from the numerical model of non-steady state heat transfer with the results of the experimental studies is presented. The possibility of using ANN to compute the parameters of the boundary conditions for the heating treatment is analyzed. A multilayer feed-forward backpropagation network is developed and trained using value of temperature in the selected nodes obtained from numerical simulation.https://www.mdpi.com/1099-4300/21/10/954artificial neural networkfinite element methodtig welding
collection DOAJ
language English
format Article
sources DOAJ
author Joanna Wróbel
Adam Kulawik
spellingShingle Joanna Wróbel
Adam Kulawik
Prediction of the Superficial Heat Source Parameters for TIG Heating Process Using FEM and ANN Modeling
Entropy
artificial neural network
finite element method
tig welding
author_facet Joanna Wróbel
Adam Kulawik
author_sort Joanna Wróbel
title Prediction of the Superficial Heat Source Parameters for TIG Heating Process Using FEM and ANN Modeling
title_short Prediction of the Superficial Heat Source Parameters for TIG Heating Process Using FEM and ANN Modeling
title_full Prediction of the Superficial Heat Source Parameters for TIG Heating Process Using FEM and ANN Modeling
title_fullStr Prediction of the Superficial Heat Source Parameters for TIG Heating Process Using FEM and ANN Modeling
title_full_unstemmed Prediction of the Superficial Heat Source Parameters for TIG Heating Process Using FEM and ANN Modeling
title_sort prediction of the superficial heat source parameters for tig heating process using fem and ann modeling
publisher MDPI AG
series Entropy
issn 1099-4300
publishDate 2019-09-01
description The basic problem of the numerical model’s quenching process is establishing the characteristics of the boundary conditions. The existing descriptions of the boundary conditions, which represent the parameters of equipment used in heat treatment processes, do not accurately reflect the actual process conditions. In the present study, the method of choice for superficial heat source parameters for TIG (tungsten inert gas) heating is modeled using artificial neural networks (ANN) and the finite element method (FEM). A comparison of the calculations obtained from the numerical model of non-steady state heat transfer with the results of the experimental studies is presented. The possibility of using ANN to compute the parameters of the boundary conditions for the heating treatment is analyzed. A multilayer feed-forward backpropagation network is developed and trained using value of temperature in the selected nodes obtained from numerical simulation.
topic artificial neural network
finite element method
tig welding
url https://www.mdpi.com/1099-4300/21/10/954
work_keys_str_mv AT joannawrobel predictionofthesuperficialheatsourceparametersfortigheatingprocessusingfemandannmodeling
AT adamkulawik predictionofthesuperficialheatsourceparametersfortigheatingprocessusingfemandannmodeling
_version_ 1724999248677699584

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