Hasil Pencarian - L. Capolungo

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  1. 1
    How can machine learning be used for accurate representations and predictions of fracture nucleation in zirconium alloys with hydride populations?

    How can machine learning be used for accurate representations and predictions of fracture nucleation in zirconium alloys with hydride populations? oleh T. Hasan, L. Capolungo, M. A. Zikry

    Diterbitkan 2023-07-01
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  2. 2
    A Multiphysics Thermoelastoviscoplastic Damage Internal State Variable Constitutive Model including Magnetism

    A Multiphysics Thermoelastoviscoplastic Damage Internal State Variable Constitutive Model including Magnetism oleh M. Malki, M. F. Horstemeyer, H. E. Cho, L. A. Peterson, D. Dickel, L. Capolungo, M. I. Baskes

    Diterbitkan 2024-05-01
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  3. 3
    Automated characterization and classification of 3D microstructures: an application to 3D deformation twin networks in titanium

    Automated characterization and classification of 3D microstructures: an application to 3D deformation twin networks in titanium oleh H.T. Vo, P. Pinney, M.M. Schneider, M. Arul Kumar, R.J. McCabe, C.N. Tomé, L. Capolungo

    Diterbitkan 2023-12-01
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  4. 4
    Deformation twinning and grain partitioning in a hexagonal close-packed magnesium alloy

    Deformation twinning and grain partitioning in a hexagonal close-packed magnesium alloy oleh M. Arul Kumar, B. Clausen, L. Capolungo, R. J. McCabe, W. Liu, J. Z. Tischler, C. N. Tomé

    Diterbitkan 2018-11-01
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  5. 5
    Deformation twinning versus slip in Ni-based alloys, containing Pt2Mo-structured, Ni2Cr-typed precipitates

    Deformation twinning versus slip in Ni-based alloys, containing Pt2Mo-structured, Ni2Cr-typed precipitates oleh H.T. Vo, K. Dang, F. Teng, M. Schneider, B.P. Eftink, S.A. Maloy, J.D. Tucker, L. Capolungo, P. Hosemann

    Diterbitkan 2021-09-01
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