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Proceedings of the 4th World Congress on Integrated Computational Materials Engineering (ICME 2017) pp 123–130Cite as

Integration of Experiments and Simulations to Build Material Big-Data

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Part of the book series: The Minerals, Metals & Materials Series ((MMMS))

Abstract

In this paper, a method for extracting stress-strain databases from material test measurements is introduced as one of the potential Integrated Computational Materials Engineering (ICME) tools. Measuring spatially heterogeneous stress and strain evolutionary data during material tests is a challenging and costly task. The proposed method can extract a large volume of spatially heterogeneous stress and strain evolutionary data from experimental boundary measurements such as tractions and displacements. For the purpose, nonlinear finite element models are intrusively implemented with artificial neural network (ANN)-based material constitutive models. Then a specialized algorithm that can auto-progressively train ANN material models guided by experimental measurements is executed. Any complex constitutive law is not presumed. From the algorithm, ANN gradually learns complex material constitutive behavior. The training databases are gradually accumulated with self-corrected stress and strain data predicted by the ANN. Finally, material databases are obtained. For an example, visco-elastoplastic material databases are obtained by the proposed method.

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Author information

Authors and Affiliations

  1. Department of Mechanical & Aerospace Engineering, Seoul National University, Building 301 Room 1308, Gwanak-ro 1, Gwanak-gu, Seoul, 08826, South Korea

    Gun Jin Yun

Authors
  1. Gun Jin Yun
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Corresponding author

Correspondence to Gun Jin Yun .

Editor information

Editors and Affiliations

  1. Thermo Calc Software Inc., McMurray, Pennsylvania, USA

    Paul Mason

  2. Naval Surface Warfare Center, Fairfax, Virginia, USA

    Charles R. Fisher

  3. Boeing, Seattle, Washington, USA

    Ryan Glamm

  4. University of Florida, Gainesville, Florida, USA

    Michele V. Manuel

  5. MICRESS Group at ACCESS e.V., Aachen, Germany

    Georg J. Schmitz

  6. Kanpur, India

    Amarendra K. Singh

  7. Purdue University, West Lafayette, Indiana, USA

    Alejandro Strachan

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© 2017 The Minerals, Metals & Materials Society

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Yun, G.J. (2017). Integration of Experiments and Simulations to Build Material Big-Data. In: Mason, P., et al. Proceedings of the 4th World Congress on Integrated Computational Materials Engineering (ICME 2017). The Minerals, Metals & Materials Series. Springer, Cham. https://doi.org/10.1007/978-3-319-57864-4_12

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