Constitutive modelling with a novel two-step optimization for an Al-Zn-Mg-Cu alloy and its application in FEA
The modified Johnson-Cook constitutive model was developed for describing the flow behavior of Al-7.8Zn-1.65Mg-2.0Cu (wt%) alloy based on the flow curves in the temperature range of 300 °C∼450 °C and strain rate range of 0.01 s ^−1 ∼ 10 s ^−1 which were obtained by isothermal compression tests cond...
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IOP Publishing
2021-01-01
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Online Access: | https://doi.org/10.1088/2053-1591/ac3793 |
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author | Daoxiang Wu Shuai Long Shuyan Wang Shi-Shan Li Yu-Ting Zhou |
author_facet | Daoxiang Wu Shuai Long Shuyan Wang Shi-Shan Li Yu-Ting Zhou |
author_sort | Daoxiang Wu |
collection | DOAJ |
description | The modified Johnson-Cook constitutive model was developed for describing the flow behavior of Al-7.8Zn-1.65Mg-2.0Cu (wt%) alloy based on the flow curves in the temperature range of 300 °C∼450 °C and strain rate range of 0.01 s ^−1 ∼ 10 s ^−1 which were obtained by isothermal compression tests conducted on a Gleeble-3500 isothermal simulator. A two-step optimization method was proposed to optimize the prediction precision according to the evaluation of average absolute relative error (AARE). By using a traversal procedure for calculating the model under different reference conditions, this evaluator was found varying in the range of 4.1837% ∼ 11.105%, revealing the great influence of reference condition on the precision, then the reference condition optimization (RCO) was conducted. Genetic algorithm (GA) was introduced as the second step of the two-step optimization (TSO) to optimize the material constants of the model, which furtherly improved the precision by reducing the AARE-value to 3.801%. The models before and after optimization were written into subroutines for the software DEFORM and the compression tests were investigated through finite element analysis (FEA). The simulated results (forming load and temperature rise) revealed that the model after TSO has the highest agreement with the experimental. |
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spelling | doaj.art-8098265ba8f946f59d9d8e253641d5862023-08-09T15:56:33ZengIOP PublishingMaterials Research Express2053-15912021-01-0181111651110.1088/2053-1591/ac3793Constitutive modelling with a novel two-step optimization for an Al-Zn-Mg-Cu alloy and its application in FEADaoxiang Wu0Shuai Long1https://orcid.org/0000-0003-3133-5666Shuyan Wang2Shi-Shan Li3Yu-Ting Zhou4Southwest Aluminum Group Co. Ltd, Chongqing 401326, People’s Republic of ChinaCollege of Metallurgy and Material Engineering, Chongqing University of Science and Technology , Chongqing 401331, People’s Republic of China; Chongqing Key Laboratory of Advanced Die and Mould Intelligent Manufacturing, Chongqing 400044, People’s Republic of ChinaSouthwest Aluminum Group Co. Ltd, Chongqing 401326, People’s Republic of ChinaCollege of Materials Science and Engineering, Chongqing University , Chongqing 400044, People’s Republic of China; Chongqing Key Laboratory of Advanced Die and Mould Intelligent Manufacturing, Chongqing 400044, People’s Republic of ChinaCollege of Materials Science and Engineering, Chongqing University , Chongqing 400044, People’s Republic of China; Chongqing Key Laboratory of Advanced Die and Mould Intelligent Manufacturing, Chongqing 400044, People’s Republic of ChinaThe modified Johnson-Cook constitutive model was developed for describing the flow behavior of Al-7.8Zn-1.65Mg-2.0Cu (wt%) alloy based on the flow curves in the temperature range of 300 °C∼450 °C and strain rate range of 0.01 s ^−1 ∼ 10 s ^−1 which were obtained by isothermal compression tests conducted on a Gleeble-3500 isothermal simulator. A two-step optimization method was proposed to optimize the prediction precision according to the evaluation of average absolute relative error (AARE). By using a traversal procedure for calculating the model under different reference conditions, this evaluator was found varying in the range of 4.1837% ∼ 11.105%, revealing the great influence of reference condition on the precision, then the reference condition optimization (RCO) was conducted. Genetic algorithm (GA) was introduced as the second step of the two-step optimization (TSO) to optimize the material constants of the model, which furtherly improved the precision by reducing the AARE-value to 3.801%. The models before and after optimization were written into subroutines for the software DEFORM and the compression tests were investigated through finite element analysis (FEA). The simulated results (forming load and temperature rise) revealed that the model after TSO has the highest agreement with the experimental.https://doi.org/10.1088/2053-1591/ac3793Al-7.8Zn-1.65Mg-2.0Cu (wt%) alloyconstitutive modelprediction precisiontwo-step optimizationfinite element analysis |
spellingShingle | Daoxiang Wu Shuai Long Shuyan Wang Shi-Shan Li Yu-Ting Zhou Constitutive modelling with a novel two-step optimization for an Al-Zn-Mg-Cu alloy and its application in FEA Materials Research Express Al-7.8Zn-1.65Mg-2.0Cu (wt%) alloy constitutive model prediction precision two-step optimization finite element analysis |
title | Constitutive modelling with a novel two-step optimization for an Al-Zn-Mg-Cu alloy and its application in FEA |
title_full | Constitutive modelling with a novel two-step optimization for an Al-Zn-Mg-Cu alloy and its application in FEA |
title_fullStr | Constitutive modelling with a novel two-step optimization for an Al-Zn-Mg-Cu alloy and its application in FEA |
title_full_unstemmed | Constitutive modelling with a novel two-step optimization for an Al-Zn-Mg-Cu alloy and its application in FEA |
title_short | Constitutive modelling with a novel two-step optimization for an Al-Zn-Mg-Cu alloy and its application in FEA |
title_sort | constitutive modelling with a novel two step optimization for an al zn mg cu alloy and its application in fea |
topic | Al-7.8Zn-1.65Mg-2.0Cu (wt%) alloy constitutive model prediction precision two-step optimization finite element analysis |
url | https://doi.org/10.1088/2053-1591/ac3793 |
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