Investigation of constitutive model of as-extruded spray-forming 7055 aluminum alloy based on BP artificial neural network

Gleeble physical simulation technique was employed to investigate the high-temperature flow stress characteristics of the studied spray forming 7055 aluminum alloy. Simultaneously, the Arrhenius constitutive model which couples the parameter of true strain and the BP artificial neural network consti...

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Main Authors: LUO Rui, CAO Yun, QIU Yu, CUI Shugang, ZHOU Haotian, ZHOU Yiming, YUAN Fei, ZHANG Xiaopeipei, CHENG Xiaonong
Format: Article
Language:zho
Published: Journal of Aeronautical Materials 2021-02-01
Series:Journal of Aeronautical Materials
Subjects:
Online Access:http://jam.biam.ac.cn/article/doi/10.11868/j.issn.1005-5053.2020.000089
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spelling doaj-b477e40eb2114329b928dba12d8a1f222021-04-15T08:30:42ZzhoJournal of Aeronautical MaterialsJournal of Aeronautical Materials1005-50531005-50532021-02-01411354410.11868/j.issn.1005-5053.2020.0000892020-0089Investigation of constitutive model of as-extruded spray-forming 7055 aluminum alloy based on BP artificial neural networkLUO Rui0CAO Yun1QIU Yu2CUI Shugang3ZHOU Haotian4ZHOU Yiming5YUAN Fei6ZHANG Xiaopeipei7CHENG Xiaonong8School of Materials Science and Engineering,Jiangsu University,Zhenjiang 212013,Jiangsu,ChinaSchool of Materials Science and Engineering,Jiangsu University,Zhenjiang 212013,Jiangsu,ChinaAVIC Manufacturing Technology Institute,Beijing 100024,ChinaSchool of Materials Science and Engineering,Jiangsu University,Zhenjiang 212013,Jiangsu,ChinaSchool of Materials Science and Engineering,Jiangsu University,Zhenjiang 212013,Jiangsu,ChinaSchool of Materials Science and Engineering,Jiangsu University,Zhenjiang 212013,Jiangsu,ChinaSchool of Materials Science and Engineering,Jiangsu University,Zhenjiang 212013,Jiangsu,ChinaSchool of Materials Science and Engineering,Jiangsu University,Zhenjiang 212013,Jiangsu,ChinaSchool of Materials Science and Engineering,Jiangsu University,Zhenjiang 212013,Jiangsu,ChinaGleeble physical simulation technique was employed to investigate the high-temperature flow stress characteristics of the studied spray forming 7055 aluminum alloy. Simultaneously, the Arrhenius constitutive model which couples the parameter of true strain and the BP artificial neural network constitutive model were contrastingly utilized to predict the flow stress behavior of the experimental alloy. The result shows that the flow stress of spray forming 7075 aluminum alloy is significantly affected by deformation parameter, which is negative correlated with deformation temperature and positively correlated with strain rate. Through the comparison of the two models, the average relative error of the Arrhenius constitutive model lies over 2%. And the error of the model tends to increase with the rising temperature. Moreover, the average absolute error and the average relative error reach the maximum at hot processing temperature (around 450 ℃). It is difficult to precisely predict the flow stress characteristics of the alloy. However, BP artificial neural network constitutive model has higher prediction accuracy, the average relative error δ value is only 0.813% and has higher temperature stability.http://jam.biam.ac.cn/article/doi/10.11868/j.issn.1005-5053.2020.000089spray forming7055 aluminum alloyconstitutive modelneural networkhot deformation
collection DOAJ
language zho
format Article
sources DOAJ
author LUO Rui
CAO Yun
QIU Yu
CUI Shugang
ZHOU Haotian
ZHOU Yiming
YUAN Fei
ZHANG Xiaopeipei
CHENG Xiaonong
spellingShingle LUO Rui
CAO Yun
QIU Yu
CUI Shugang
ZHOU Haotian
ZHOU Yiming
YUAN Fei
ZHANG Xiaopeipei
CHENG Xiaonong
Investigation of constitutive model of as-extruded spray-forming 7055 aluminum alloy based on BP artificial neural network
Journal of Aeronautical Materials
spray forming
7055 aluminum alloy
constitutive model
neural network
hot deformation
author_facet LUO Rui
CAO Yun
QIU Yu
CUI Shugang
ZHOU Haotian
ZHOU Yiming
YUAN Fei
ZHANG Xiaopeipei
CHENG Xiaonong
author_sort LUO Rui
title Investigation of constitutive model of as-extruded spray-forming 7055 aluminum alloy based on BP artificial neural network
title_short Investigation of constitutive model of as-extruded spray-forming 7055 aluminum alloy based on BP artificial neural network
title_full Investigation of constitutive model of as-extruded spray-forming 7055 aluminum alloy based on BP artificial neural network
title_fullStr Investigation of constitutive model of as-extruded spray-forming 7055 aluminum alloy based on BP artificial neural network
title_full_unstemmed Investigation of constitutive model of as-extruded spray-forming 7055 aluminum alloy based on BP artificial neural network
title_sort investigation of constitutive model of as-extruded spray-forming 7055 aluminum alloy based on bp artificial neural network
publisher Journal of Aeronautical Materials
series Journal of Aeronautical Materials
issn 1005-5053
1005-5053
publishDate 2021-02-01
description Gleeble physical simulation technique was employed to investigate the high-temperature flow stress characteristics of the studied spray forming 7055 aluminum alloy. Simultaneously, the Arrhenius constitutive model which couples the parameter of true strain and the BP artificial neural network constitutive model were contrastingly utilized to predict the flow stress behavior of the experimental alloy. The result shows that the flow stress of spray forming 7075 aluminum alloy is significantly affected by deformation parameter, which is negative correlated with deformation temperature and positively correlated with strain rate. Through the comparison of the two models, the average relative error of the Arrhenius constitutive model lies over 2%. And the error of the model tends to increase with the rising temperature. Moreover, the average absolute error and the average relative error reach the maximum at hot processing temperature (around 450 ℃). It is difficult to precisely predict the flow stress characteristics of the alloy. However, BP artificial neural network constitutive model has higher prediction accuracy, the average relative error δ value is only 0.813% and has higher temperature stability.
topic spray forming
7055 aluminum alloy
constitutive model
neural network
hot deformation
url http://jam.biam.ac.cn/article/doi/10.11868/j.issn.1005-5053.2020.000089
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AT caoyun investigationofconstitutivemodelofasextrudedsprayforming7055aluminumalloybasedonbpartificialneuralnetwork
AT qiuyu investigationofconstitutivemodelofasextrudedsprayforming7055aluminumalloybasedonbpartificialneuralnetwork
AT cuishugang investigationofconstitutivemodelofasextrudedsprayforming7055aluminumalloybasedonbpartificialneuralnetwork
AT zhouhaotian investigationofconstitutivemodelofasextrudedsprayforming7055aluminumalloybasedonbpartificialneuralnetwork
AT zhouyiming investigationofconstitutivemodelofasextrudedsprayforming7055aluminumalloybasedonbpartificialneuralnetwork
AT yuanfei investigationofconstitutivemodelofasextrudedsprayforming7055aluminumalloybasedonbpartificialneuralnetwork
AT zhangxiaopeipei investigationofconstitutivemodelofasextrudedsprayforming7055aluminumalloybasedonbpartificialneuralnetwork
AT chengxiaonong investigationofconstitutivemodelofasextrudedsprayforming7055aluminumalloybasedonbpartificialneuralnetwork
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