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.

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