Mathematical modeling of AZ30 magnesium alloys at high temperature using the ring compression test and genetic algorithm method

In the present investigation, a new method is proposed to study the AZ30 flow curve at elevated temperatures and various strain rate. Experiments were carried out with the goal of obtaining flow curve of AZ30 at three different temperature and strain rates by using the ring test method. The presente...

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Autores principales:	Barati Farzan, Esfandiari Mona, Babaei Sajjad, Hoseini-Tabar Zahra, Atarod Aida
Formato:	article
Lenguaje:	EN
Publicado:	De Gruyter 2021
Materias:	az30 mg alloy compressive strength high temperature genetic algorithm Mechanical engineering and machinery TJ1-1570
Acceso en línea:	https://doaj.org/article/cc3a3490fb4044c7be32cda47cd266d4
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spelling	oai:doaj.org-article:cc3a3490fb4044c7be32cda47cd266d42021-12-05T14:10:52ZMathematical modeling of AZ30 magnesium alloys at high temperature using the ring compression test and genetic algorithm method0334-89382191-024310.1515/jmbm-2021-0011https://doaj.org/article/cc3a3490fb4044c7be32cda47cd266d42021-09-01T00:00:00Zhttps://doi.org/10.1515/jmbm-2021-0011https://doaj.org/toc/0334-8938https://doaj.org/toc/2191-0243In the present investigation, a new method is proposed to study the AZ30 flow curve at elevated temperatures and various strain rate. Experiments were carried out with the goal of obtaining flow curve of AZ30 at three different temperature and strain rates by using the ring test method. The presented work aims to develop a model using genetic algorithm for AZ30 flow stress prediction during different test conditions. The Santam machine was implicated that was able to perform experiments by controlling both the position and load modes. At each temperature and strain rate the isothermal test was performed respectively. In the present investigation for three varios temperatures and strain rates, 54 ring compression tests were carried out with different levels of reduction in height. Then each specimen was water cooled quickly to investigate the microstructure of AZ30 magnesium alloy by using optical microscope. The model used in the present study was able to predict the flow curve with an 2.3% accuracy. This model has excellent potential to be employed in various industry applications.Barati FarzanEsfandiari MonaBabaei SajjadHoseini-Tabar ZahraAtarod AidaDe Gruyterarticleaz30 mg alloycompressive strengthhigh temperaturegenetic algorithmMechanical engineering and machineryTJ1-1570ENJournal of the Mechanical Behavior of Materials, Vol 30, Iss 1, Pp 103-109 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	az30 mg alloy compressive strength high temperature genetic algorithm Mechanical engineering and machinery TJ1-1570
spellingShingle	az30 mg alloy compressive strength high temperature genetic algorithm Mechanical engineering and machinery TJ1-1570 Barati Farzan Esfandiari Mona Babaei Sajjad Hoseini-Tabar Zahra Atarod Aida Mathematical modeling of AZ30 magnesium alloys at high temperature using the ring compression test and genetic algorithm method
description	In the present investigation, a new method is proposed to study the AZ30 flow curve at elevated temperatures and various strain rate. Experiments were carried out with the goal of obtaining flow curve of AZ30 at three different temperature and strain rates by using the ring test method. The presented work aims to develop a model using genetic algorithm for AZ30 flow stress prediction during different test conditions. The Santam machine was implicated that was able to perform experiments by controlling both the position and load modes. At each temperature and strain rate the isothermal test was performed respectively. In the present investigation for three varios temperatures and strain rates, 54 ring compression tests were carried out with different levels of reduction in height. Then each specimen was water cooled quickly to investigate the microstructure of AZ30 magnesium alloy by using optical microscope. The model used in the present study was able to predict the flow curve with an 2.3% accuracy. This model has excellent potential to be employed in various industry applications.
format	article
author	Barati Farzan Esfandiari Mona Babaei Sajjad Hoseini-Tabar Zahra Atarod Aida
author_facet	Barati Farzan Esfandiari Mona Babaei Sajjad Hoseini-Tabar Zahra Atarod Aida
author_sort	Barati Farzan
title	Mathematical modeling of AZ30 magnesium alloys at high temperature using the ring compression test and genetic algorithm method
title_short	Mathematical modeling of AZ30 magnesium alloys at high temperature using the ring compression test and genetic algorithm method
title_full	Mathematical modeling of AZ30 magnesium alloys at high temperature using the ring compression test and genetic algorithm method
title_fullStr	Mathematical modeling of AZ30 magnesium alloys at high temperature using the ring compression test and genetic algorithm method
title_full_unstemmed	Mathematical modeling of AZ30 magnesium alloys at high temperature using the ring compression test and genetic algorithm method
title_sort	mathematical modeling of az30 magnesium alloys at high temperature using the ring compression test and genetic algorithm method
publisher	De Gruyter
publishDate	2021
url	https://doaj.org/article/cc3a3490fb4044c7be32cda47cd266d4
work_keys_str_mv	AT baratifarzan mathematicalmodelingofaz30magnesiumalloysathightemperatureusingtheringcompressiontestandgeneticalgorithmmethod AT esfandiarimona mathematicalmodelingofaz30magnesiumalloysathightemperatureusingtheringcompressiontestandgeneticalgorithmmethod AT babaeisajjad mathematicalmodelingofaz30magnesiumalloysathightemperatureusingtheringcompressiontestandgeneticalgorithmmethod AT hoseinitabarzahra mathematicalmodelingofaz30magnesiumalloysathightemperatureusingtheringcompressiontestandgeneticalgorithmmethod AT atarodaida mathematicalmodelingofaz30magnesiumalloysathightemperatureusingtheringcompressiontestandgeneticalgorithmmethod
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Mathematical modeling of AZ30 magnesium alloys at high temperature using the ring compression test and genetic algorithm method

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