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Reconstruction of Spatially Varying Random Material Properties by Self-Optimizing Inverse Method

  • Conference paper
Residual Stress, Thermomechanics & Infrared Imaging, Hybrid Techniques and Inverse Problems, Volume 9

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Abstract

In this paper, a new methodology for reconstructing spatially varying random material properties is presented by combining stochastic finite element (SFE) models with Self-Optimizing Inverse Method (Self-OPTIM). The Self-OPTIM can identify model parameters based on partial boundary force and displacement data from experimental tests. Statistical information (i.e. spatial mean, variance, correlation length and Gaussian normal random variables) of spatially varying random fields (RFs) are parameterized by Karhunen-Loève (KL) expansion method and integrated into SFE models. In addition, a new software framework is also presented that can simultaneously utilize any number of remote computers in a network domain for the Self-OPTIM simulation. This can result in a significant decrease of computational times required for the optimization task. Two important issues in the inverse reconstruction problem are addressed in this paper: (1) effects of the number of internal measurements and (2) non-uniform reaction forces along the boundary on the reconstruction accuracy. The proposed method is partially proven to offer new capabilities of reconstructing spatially inhomogeneous material properties and estimating their statistical parameters from incomplete experimental measurements.

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Authors and Affiliations

  1. Department of Civil Engineering, The University of Akron, 244 Sumner St. ASEC 210, Akron, OH, 44325-3905, USA

    Joshua M. Weaver & Gunjin J. Yun

Authors
  1. Joshua M. Weaver
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  2. Gunjin J. Yun
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Correspondence to Gunjin J. Yun .

Editor information

Editors and Affiliations

  1. Aalto University, Helsinki, Finland

    Sven Bossuyt

  2. Univ of British Columbia, Vancouver, British Columbia, Canada

    Gary Schajer

  3. Politecnico di Torino, Torino, Italy

    Alberto Carpinteri

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© 2016 The Society for Experimental Mechanics, Inc.

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Weaver, J.M., Yun, G.J. (2016). Reconstruction of Spatially Varying Random Material Properties by Self-Optimizing Inverse Method. In: Bossuyt, S., Schajer, G., Carpinteri, A. (eds) Residual Stress, Thermomechanics & Infrared Imaging, Hybrid Techniques and Inverse Problems, Volume 9. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-319-21765-9_1

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  • DOI: https://doi.org/10.1007/978-3-319-21765-9_1

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-21764-2

  • Online ISBN: 978-3-319-21765-9

  • eBook Packages: EngineeringEngineering (R0)

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