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2020
- Stopka K.S. and McDowell, D.L., “Microstructure-sensitive computational estimates of driving forces for surface vs. subsurface fatigue crack formation in duplex Ti-6Al-4V and Al 7075-T6,” JOM, Vol. 72, No. 1, 2020, pp. 28-38.
- Stopka, K.S. and McDowell, D.L., “Microstructure-Sensitive Computational Multiaxial Fatigue of Al 7075-T6 and Duplex Ti-6Al-4V,” International Journal of Fatigue, Vol. 133, 2020, p. 105460.
- Gu, T., Stopka, K.S., Xu, C., and McDowell, D.L., “Prediction of maximum Fatigue Indicator Parameters for duplex Ti-6Al-4V using extreme value theory,” Acta Materialia, Vol. 188, 2020, pp. 504-516.
- Zhang, Y., Chen, W., McDowell, D.L., Wang, Y.M., and Zhu, T., “Lattice Strains and Diffraction Elastic Constants of Cubic Polycrystals,” Journal of the Mechanics and Physics of Solids, Vol. 138, 2020, p. 103899.
- Tallman, A.E., Swiler, L.P., Wang, Y., and McDowell, D.L., “Uncertainty Propagation in Reduced Order Models based on Crystal Plasticity,” Computer Methods in Applied Mechanics and Engineering, Vol. 365, 2020, p. 113009.
- Stopka, K.S., Gu, T., and McDowell, D.L., “Effects of Algorithmic Simulation Parameters on the Prediction of Extreme Value Fatigue Indicator Parameters in Duplex Ti-6Al-4V,” Int. J. Fatigue, Vol. 141, 2020, p. 105865.
- Gupta, A., Gruber, J., Rajaram, S.R., Thompson, G.B., McDowell, D.L., and Tucker, G.J., “On the Mechanistic Origins of Maximum Strength in Nanocrystalline Metals: Attaining Gridlock at the Nanoscale,” npj Computational Materials, 6, 2020, 153; https://doi.org/10.1038/s41524-020-00425-0.
- Chu, K., Foster, M.E., Sills, R.B., Zhou, X., Zhu, T., and McDowell, D.L., “Temperature and Composition Dependent Mobility of Screw Dislocations in Fe0.7NixCr0.3-x Austenitic Stainless Steels from Large Scale Molecular Dynamics Simulationa,” npj Computational Materials 6, 2020, 179; https://doi.org/10.1038/s41524-020-00452-x.
- McDowell, D.L., “Gaps and Barriers to the Successful Integration and Adoption of Practical Materials Informatics Tools and Workflows,“ JOM, Vol. 73, 2020, pp. 138-148.
- Whelan, G. and McDowell, D.L., “Machine Learning Enabled Uncertainty Quantification for Modeling Fatigue Critical Engineering Alloys Using an ICME Workflow,” Integr Mater Manuf Innov, TMS, Vol. 9, 2020, pp. 376-393.