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Identifying crack tip position and stress intensity factors from displacement data

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Abstract

Fracture prognosis and characterization efforts require knowledge of crack tip position and the Stress Intensity Factors (SIFs) acting in the vicinity of the crack. Here, we present an efficient numerical approach to infer both of these characteristics under a consistent theoretical framework from noisy, unstructured displacement data. The novel approach utilizes the separability of the asymptotic linear elastic fracture mechanics fields to expedite the search for crack tip position and is particularly useful for noisy displacement data. The manuscript begins with an assessment of the importance of accurately locating crack tip position when quantifying the SIFs from displacement data. Next, the proposed separability approach for quickly inferring crack tip position is introduced. Comparing to the widely used displacement correlation approach, the performance of the separability approach is assessed. Cases involving both noisy data and systematic deviation from the asymptotic linear elastic fracture mechanics model are considered, e.g. inelastic material behavior and finite geometries. An open source python implementation of the proposed approach is available for use by those doing field and laboratory work involving digital image correlation and simulations, e.g. finite element, discrete element, molecular dynamics and peridynamics, where the crack tip position is not explicitly defined.

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Acknowledgements

The authors thank J. Carroll for providing displacement and DIC analysis data. The authors thank E. David Reedy for reviewing a draft of the manuscript and providing valuable technical insight. This work was supported in part by the Advanced Simulation and Computing (ASC) program at Sandia National Laboratories for the U.S. Department of Energy’s National Nuclear Security Administration. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. Department of Energy or the United States Government. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for U.S. Government purposes. DHW gratefully acknowledges support from the Office of Naval Research #N000142012484 and the National Science Foundation #1922081.

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Author notes

  1. Swati Gupta and Grant West have contributed equally.

Authors and Affiliations

  1. Cornell Fracture Group, School of Civil and Environmental Engineering, Cornell University, Ithaca, NY, 14853, USA

    Swati Gupta, Grant West & Derek H. Warner

  2. Sandia National Laboratories, Computational Materials and Data Science, Albuquerque, NM, 87123, USA

    Mark A. Wilson

  3. Sandia National Laboratories, Materials and Failure Modeling, Albuquerque, NM, 87123, USA

    Scott J. Grutzik

Authors
  1. Swati Gupta
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  2. Grant West
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  3. Mark A. Wilson
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  4. Scott J. Grutzik
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  5. Derek H. Warner
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Contributions

The study was conceptualized and designed by DHW, SJG and MAW The first draft of the manuscript was prepared by SG and GW. The final implementation of the methodology and the analysis was performed by SG. All authors contributed to the paper and approved the final manuscript.

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Correspondence to Derek H. Warner.

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Gupta, S., West, G., Wilson, M.A. et al. Identifying crack tip position and stress intensity factors from displacement data. Int J Fract 243, 47–63 (2023). https://doi.org/10.1007/s10704-023-00729-4

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