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Crystal Plasticity Model Calibration for Ti-7Al Alloy with a Multi-fidelity Computational Scheme

  • Pınar Acar
Technical Article
  • 19 Downloads

Abstract

The present work addresses a Gaussian process-based multi-fidelity computational scheme to enable the crystal plasticity modeling of Ti-7Al alloy. The crystal plasticity simulations are performed by using computational techniques that lead to two different solution fidelities. The first technique involves the use of a one-point probability descriptor, orientation distribution function (ODF), which measures the volume fractions of crystals in different orientations. The ODF is posed as the low-fidelity method in the multi-fidelity scheme since it neglects the effects of the microstructural correlations and grain shapes to the macro-scale stress-strain response of the material. For the high-fidelity computational technique, crystal plasticity finite element method (CPFEM) is utilized. This is because the CPFEM resolves better in grain-level microstructural features. However, the CPFEM is a computationally expensive technique and it is not feasible to be utilized for computationally costly problems. Therefore, a multi-fidelity modeling scheme that improves the low-fidelity ODF simulation data with the high-fidelity CPFEM simulations is utilized to obtain the crystal plasticity parameters. The presented approach uses more samples from the computationally less expensive low-fidelity model and less samples from the computationally expensive high-fidelity model to build a numerical framework that satisfies both accuracy and computational time expectations. The results of the presented multi-fidelity scheme show a significant improvement on the accuracy of the crystal plasticity modeling of Ti-7Al compared to the results of the previous low-fidelity solution.

Keywords

Multi-fidelity modeling Gaussian process Calibration Crystal plasticity Titanium 

Notes

Acknowledgements

The author would like to acknowledge that the experimental data used in this work was provided by Dr. Anna Trump and Prof. John Allison (Materials Science and Engineering) at the University of Michigan.

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Copyright information

© The Minerals, Metals & Materials Society 2018

Authors and Affiliations

  1. 1.Mechanical EngineeringVirginia TechBlacksburgUSA

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