Formability Studies on Magnesium Based AZ31B Alloy Sheet in LS Dyna Program Code

Magnesium alloys has potential applications in aerospace and automotive industries as they are having good formability. Material properties like yield strength, ductility, have direct influence on material’s formability and product quality. At high temperature applications like aeroengine and steam...

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Main Authors: B. Viswanadhapalli, V.K. Bupesh Raja, K. Chaitanya, S. Kannan
Format: Article
Language:English
Published: Polish Academy of Sciences 2025-03-01
Series:Archives of Metallurgy and Materials
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Online Access:https://journals.pan.pl/Content/134510/AMM-2025-1-20-Bupesh%20Raja.pdf
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author B. Viswanadhapalli
V.K. Bupesh Raja
K. Chaitanya
S. Kannan
author_facet B. Viswanadhapalli
V.K. Bupesh Raja
K. Chaitanya
S. Kannan
author_sort B. Viswanadhapalli
collection DOAJ
description Magnesium alloys has potential applications in aerospace and automotive industries as they are having good formability. Material properties like yield strength, ductility, have direct influence on material’s formability and product quality. At high temperature applications like aeroengine and steam engine, finding these properties are very crucial. For this purpose, uni-axial tension tests are performed at high temperatures on AZ31B magnesium alloy sheet to evaluate material formability properties. Finite element-based simulations have also been carried in LS Dyna program code. The output of the simulation is to find effective stresses and effective plastic strains. For this purpose, Tresca and Von Mises yielding conditions are utilized. These stresses are crucial in predicting and evaluating the forming limits of the material before necking. The results obtained from simulation code are consistent with experimental observations. An attempt has been made to predict formability by machine learning models. Random Forest shows the better model in predicting the formability. It has been concluded that the machine learning and Dyna code predictions has greatly minimises the physical experimentation.
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institution Kabale University
issn 2300-1909
language English
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publisher Polish Academy of Sciences
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series Archives of Metallurgy and Materials
spelling doaj-art-cf49535d36ae4e8698f825a95fff78db2025-08-20T03:44:10ZengPolish Academy of SciencesArchives of Metallurgy and Materials2300-19092025-03-01vol. 70No 1183192https://doi.org/10.24425/amm.2025.152532Formability Studies on Magnesium Based AZ31B Alloy Sheet in LS Dyna Program CodeB. Viswanadhapalli0https://orcid.org/0000-0003-4949-7321V.K. Bupesh Raja1https://orcid.org/0000-0002-8929-1814K. Chaitanya2https://orcid.org/0000-0001-5991-2600S. Kannan3https://orcid.org/0000-0003-4897-1319School of Mechanical Engineering, Sathyabama Institute of Science and Technology, Chennai IndiaSchool of Mechanical Engineering, Sathyabama Institute of Science and Technology, Chennai IndiaDepartment of Computer Science Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, IndiaDean – Engineering, Architecture and Interior Design Amity University, Dubai, UAEMagnesium alloys has potential applications in aerospace and automotive industries as they are having good formability. Material properties like yield strength, ductility, have direct influence on material’s formability and product quality. At high temperature applications like aeroengine and steam engine, finding these properties are very crucial. For this purpose, uni-axial tension tests are performed at high temperatures on AZ31B magnesium alloy sheet to evaluate material formability properties. Finite element-based simulations have also been carried in LS Dyna program code. The output of the simulation is to find effective stresses and effective plastic strains. For this purpose, Tresca and Von Mises yielding conditions are utilized. These stresses are crucial in predicting and evaluating the forming limits of the material before necking. The results obtained from simulation code are consistent with experimental observations. An attempt has been made to predict formability by machine learning models. Random Forest shows the better model in predicting the formability. It has been concluded that the machine learning and Dyna code predictions has greatly minimises the physical experimentation.https://journals.pan.pl/Content/134510/AMM-2025-1-20-Bupesh%20Raja.pdfmagnesium alloy sheetuni-axial tension testls dyna program codemachine learning model
spellingShingle B. Viswanadhapalli
V.K. Bupesh Raja
K. Chaitanya
S. Kannan
Formability Studies on Magnesium Based AZ31B Alloy Sheet in LS Dyna Program Code
Archives of Metallurgy and Materials
magnesium alloy sheet
uni-axial tension test
ls dyna program code
machine learning model
title Formability Studies on Magnesium Based AZ31B Alloy Sheet in LS Dyna Program Code
title_full Formability Studies on Magnesium Based AZ31B Alloy Sheet in LS Dyna Program Code
title_fullStr Formability Studies on Magnesium Based AZ31B Alloy Sheet in LS Dyna Program Code
title_full_unstemmed Formability Studies on Magnesium Based AZ31B Alloy Sheet in LS Dyna Program Code
title_short Formability Studies on Magnesium Based AZ31B Alloy Sheet in LS Dyna Program Code
title_sort formability studies on magnesium based az31b alloy sheet in ls dyna program code
topic magnesium alloy sheet
uni-axial tension test
ls dyna program code
machine learning model
url https://journals.pan.pl/Content/134510/AMM-2025-1-20-Bupesh%20Raja.pdf
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AT vkbupeshraja formabilitystudiesonmagnesiumbasedaz31balloysheetinlsdynaprogramcode
AT kchaitanya formabilitystudiesonmagnesiumbasedaz31balloysheetinlsdynaprogramcode
AT skannan formabilitystudiesonmagnesiumbasedaz31balloysheetinlsdynaprogramcode