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...
Main Authors: | , , , , , , , , |
---|---|
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 |
id |
doaj-b477e40eb2114329b928dba12d8a1f22 |
---|---|
record_format |
Article |
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 |
work_keys_str_mv |
AT luorui investigationofconstitutivemodelofasextrudedsprayforming7055aluminumalloybasedonbpartificialneuralnetwork AT caoyun investigationofconstitutivemodelofasextrudedsprayforming7055aluminumalloybasedonbpartificialneuralnetwork AT qiuyu investigationofconstitutivemodelofasextrudedsprayforming7055aluminumalloybasedonbpartificialneuralnetwork AT cuishugang investigationofconstitutivemodelofasextrudedsprayforming7055aluminumalloybasedonbpartificialneuralnetwork AT zhouhaotian investigationofconstitutivemodelofasextrudedsprayforming7055aluminumalloybasedonbpartificialneuralnetwork AT zhouyiming investigationofconstitutivemodelofasextrudedsprayforming7055aluminumalloybasedonbpartificialneuralnetwork AT yuanfei investigationofconstitutivemodelofasextrudedsprayforming7055aluminumalloybasedonbpartificialneuralnetwork AT zhangxiaopeipei investigationofconstitutivemodelofasextrudedsprayforming7055aluminumalloybasedonbpartificialneuralnetwork AT chengxiaonong investigationofconstitutivemodelofasextrudedsprayforming7055aluminumalloybasedonbpartificialneuralnetwork |
_version_ |
1721526464906526720 |