Evidence map›Paper›PMID 37780097›Full record

ArticleExperimental mechanics2023

Estimation of the Deformation Gradient Tensor by Particle Tracking Near a Free Boundary with Quantified Error.

T Benkley, C Li, J Kolinski

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In one paragraph

Article in Experimental mechanics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

T Benkley *School of Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, 1015 Switzerland.
C Li *School of Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, 1015 Switzerland.
J KolinskiSchool of Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, 1015 Switzerland.ORCID 0000-0002-5960-0487

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Obtaining accurate displacement measurements for large material deformation and/or rotation presents a distinct challenge to digital image correlation (DIC) due to cumulative and decorrelation errors, particularly near material boundaries. Objective: We aim to accurately measure the deformation gradient tensor near boundary discontinuities in situations of large deformation and large deformation gradients. Methods: To achieve this goal, the locations of randomly distributed particles are tracked using an open-source particle-tracking software, Trackpy. A least-squares estimate of the deformation gradient tensor field uses nearest-neighbor material vectors and a first-order Finite Difference (FD) approximation, circumventing common errors in other methods. The error caused by FD approximation and that incurred by measurement are derived and tested with exhaustive numerical simulations. Furthermore, a uniaxial tensile test and mode-I fracture experiment are conducted with particle-embedded hydrogels to validate the method. Results: Numerical results corroborate a theoretical expression of measurement error. They show that the FD error increases while the measurement error decreases for a growing estimating radius. Moreover, measurement error is linearly correlated to displacement noise. A benchmark uniaxial tensile test validates the accuracy of the proposed estimator, and the near-crack-tip measurements in a tensile fracture experiment demonstrate the estimator's capabilities near a free surface, when a material undergoes large deformation and rotation. The results of the displacement and strain data are benchmarked against kinematic data obtained using an open-source DIC software, Ncorr. Computation time for both methods is compared. Conclusions: A deformation gradient tensor estimator is developed based on a particle tracking technique and a least squares routine. Theoretical error bounds on the estimator are verified by numerical simulations, and the method's capability is confirmed by physical experiments in evaluating large deformation and rotation near a free boundary. The proposed estimator is expected to open a door towards future material tests and experimental mechanics studies, especially in large deformation and large rotation scenarios.

Indexed as

Deformation gradient tensorError quantificationFracture mechanicsParticle tracking

Identifiers

PMID37780097
PMCPMC10541346

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.