Experimental, modelling and simulation of an approach for optimizing the superplastic forming of Ti-6%Al-4%V titanium alloy

A.O Mosleh, A.V Mikhaylovskaya, A.D Kotov, J.S. Kwame

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

The study presents an integrated approach for superplastic forming of Ti-6%Al-4%V titanium alloy. The flow behavior of the studied alloy was investigated using uniaxial constant strain rate tensile tests in a temperature range of 800–900 °C and a strain rate range of 3 × 10−4–3 × 10-3s-1. The obtained flow behavior was modeled using the simple Johnson-Cook (S J-C), modified Johnson-Cook (M J-C) and artificial neural network (ANN) models. An assessment study between the constructed models was performed in order to evaluate the predictability of each model. Standard statistical comparative quantities such as correlation coefficient (R), mean absolute relative error (AARE) and the root mean square error (RMSE) were used to ascertain the model viability. The S J-C model proved ineffectual in predicting the flow behavior of Ti-6%Al-4%V alloy. The M J-C and ANN models are able to successfully describe the flow behavior of the alloy. The validity of the model used for the simulation was ascertained by testing the predicted data with the constructed models at a temperature of 875 °C and a strain rate of 2 × 10-3s-1 using DEFORM 3D finite element simulation (FES). The obtained results from the FES were verified with the experimental results after superplastic forming process. The FES results show the possibility of using uniaxial tensile test data to simulate superplastic forming process of the Ti-6%Al-4%V titanium sheets.
LanguageEnglish
Pages262-272
Number of pages11
JournalJournal of Manufacturing Processes
Volume45
Early online date13 Jul 2019
DOIs
Publication statusPublished - 30 Sep 2019

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Titanium alloys
Strain rate
Titanium sheet
Neural networks
Modeling and simulation
Mean square error
Simulation
Temperature
Finite element
Testing

Keywords

  • titanium alloys
  • constitutive modeling
  • Johnson-Cook (J-C) models
  • artificial neural network
  • superplastic forming
  • finite elements analysis

Cite this

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title = "Experimental, modelling and simulation of an approach for optimizing the superplastic forming of Ti-6{\%}Al-4{\%}V titanium alloy",
abstract = "The study presents an integrated approach for superplastic forming of Ti-6{\%}Al-4{\%}V titanium alloy. The flow behavior of the studied alloy was investigated using uniaxial constant strain rate tensile tests in a temperature range of 800–900 °C and a strain rate range of 3 × 10−4–3 × 10-3s-1. The obtained flow behavior was modeled using the simple Johnson-Cook (S J-C), modified Johnson-Cook (M J-C) and artificial neural network (ANN) models. An assessment study between the constructed models was performed in order to evaluate the predictability of each model. Standard statistical comparative quantities such as correlation coefficient (R), mean absolute relative error (AARE) and the root mean square error (RMSE) were used to ascertain the model viability. The S J-C model proved ineffectual in predicting the flow behavior of Ti-6{\%}Al-4{\%}V alloy. The M J-C and ANN models are able to successfully describe the flow behavior of the alloy. The validity of the model used for the simulation was ascertained by testing the predicted data with the constructed models at a temperature of 875 °C and a strain rate of 2 × 10-3s-1 using DEFORM 3D finite element simulation (FES). The obtained results from the FES were verified with the experimental results after superplastic forming process. The FES results show the possibility of using uniaxial tensile test data to simulate superplastic forming process of the Ti-6{\%}Al-4{\%}V titanium sheets.",
keywords = "titanium alloys, constitutive modeling, Johnson-Cook (J-C) models, artificial neural network, superplastic forming, finite elements analysis",
author = "A.O Mosleh and A.V Mikhaylovskaya and A.D Kotov and J.S. Kwame",
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Experimental, modelling and simulation of an approach for optimizing the superplastic forming of Ti-6%Al-4%V titanium alloy. / Mosleh, A.O; Mikhaylovskaya, A.V; Kotov, A.D; Kwame, J.S.

In: Journal of Manufacturing Processes, Vol. 45, 30.09.2019, p. 262-272.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Experimental, modelling and simulation of an approach for optimizing the superplastic forming of Ti-6%Al-4%V titanium alloy

AU - Mosleh, A.O

AU - Mikhaylovskaya, A.V

AU - Kotov, A.D

AU - Kwame, J.S.

PY - 2019/9/30

Y1 - 2019/9/30

N2 - The study presents an integrated approach for superplastic forming of Ti-6%Al-4%V titanium alloy. The flow behavior of the studied alloy was investigated using uniaxial constant strain rate tensile tests in a temperature range of 800–900 °C and a strain rate range of 3 × 10−4–3 × 10-3s-1. The obtained flow behavior was modeled using the simple Johnson-Cook (S J-C), modified Johnson-Cook (M J-C) and artificial neural network (ANN) models. An assessment study between the constructed models was performed in order to evaluate the predictability of each model. Standard statistical comparative quantities such as correlation coefficient (R), mean absolute relative error (AARE) and the root mean square error (RMSE) were used to ascertain the model viability. The S J-C model proved ineffectual in predicting the flow behavior of Ti-6%Al-4%V alloy. The M J-C and ANN models are able to successfully describe the flow behavior of the alloy. The validity of the model used for the simulation was ascertained by testing the predicted data with the constructed models at a temperature of 875 °C and a strain rate of 2 × 10-3s-1 using DEFORM 3D finite element simulation (FES). The obtained results from the FES were verified with the experimental results after superplastic forming process. The FES results show the possibility of using uniaxial tensile test data to simulate superplastic forming process of the Ti-6%Al-4%V titanium sheets.

AB - The study presents an integrated approach for superplastic forming of Ti-6%Al-4%V titanium alloy. The flow behavior of the studied alloy was investigated using uniaxial constant strain rate tensile tests in a temperature range of 800–900 °C and a strain rate range of 3 × 10−4–3 × 10-3s-1. The obtained flow behavior was modeled using the simple Johnson-Cook (S J-C), modified Johnson-Cook (M J-C) and artificial neural network (ANN) models. An assessment study between the constructed models was performed in order to evaluate the predictability of each model. Standard statistical comparative quantities such as correlation coefficient (R), mean absolute relative error (AARE) and the root mean square error (RMSE) were used to ascertain the model viability. The S J-C model proved ineffectual in predicting the flow behavior of Ti-6%Al-4%V alloy. The M J-C and ANN models are able to successfully describe the flow behavior of the alloy. The validity of the model used for the simulation was ascertained by testing the predicted data with the constructed models at a temperature of 875 °C and a strain rate of 2 × 10-3s-1 using DEFORM 3D finite element simulation (FES). The obtained results from the FES were verified with the experimental results after superplastic forming process. The FES results show the possibility of using uniaxial tensile test data to simulate superplastic forming process of the Ti-6%Al-4%V titanium sheets.

KW - titanium alloys

KW - constitutive modeling

KW - Johnson-Cook (J-C) models

KW - artificial neural network

KW - superplastic forming

KW - finite elements analysis

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SP - 262

EP - 272

JO - Journal of Manufacturing Processes

T2 - Journal of Manufacturing Processes

JF - Journal of Manufacturing Processes

SN - 1526-6125

ER -