Extraction of Mechanical Properties of Shape Memory Alloys From Instrumented Spherical Indentation

Abstract An approach to infer mechanical properties of shape memory alloys (SMAs) from instrumented spherical indentation records of indenter tip loading force, P, versus the resultant indentation depth, h, during indentation loading and unloading is proposed. The approach is based on (i) a finite element (FE) model for describing the forward problem of determining the indentation response, i.e., the P−h curve, for a given set of SMA mechanical properties, (ii) a computationally efficient Gaussian process surrogate model to replace the costly FE one, and (iii) an iterative solution strategy, which approximates the unknown model parameters from an experimentally determined P−h record and their corresponding probability densities via a Bayesian inference framework and a Markov Chain Monte Carlo sampling strategy. The efficacy of the proposed approach is demonstrated using numerical experiments, i.e., indentation curves generated by evaluating the FE model at points in the parameter space.

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Publication Details

Journal
Journal of Applied Mechanics
Published
2024-11-21
DOI
https://doi.org/10.1115/1.4067206
Citations
1
Primary Topic
Shape Memory Alloy Transformations
Type
article
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article

Extraction of Mechanical Properties of Shape Memory Alloys From Instrumented Spherical Indentation

Santiago El Awad, Theocharis Baxevanis, Tian Chen, Emmanuel Sansusthy Tardío
1 citations
Journal of Applied Mechanics
Shape Memory Alloy Transformations
0.12
article

Extraction of Mechanical Properties of Shape Memory Alloys From Instrumented Spherical Indentation

Santiago El Awad, Theocharis Baxevanis, Tian Chen, Emmanuel Sansusthy Tardío
article en
1 citations

Abstract

Abstract An approach to infer mechanical properties of shape memory alloys (SMAs) from instrumented spherical indentation records of indenter tip loading force, P, versus the resultant indentation depth, h, during indentation loading and unloading is proposed. The approach is based on (i) a finite element (FE) model for describing the forward problem of determining the indentation response, i.e., the P−h curve, for a given set of SMA mechanical properties, (ii) a computationally efficient Gaussian process surrogate model to replace the costly FE one, and (iii) an iterative solution strategy, which approximates the unknown model parameters from an experimentally determined P−h record and their corresponding probability densities via a Bayesian inference framework and a Markov Chain Monte Carlo sampling strategy. The efficacy of the proposed approach is demonstrated using numerical experiments, i.e., indentation curves generated by evaluating the FE model at points in the parameter space.

Journal of Applied MechanicsVol. 92(2)
Martin Luther King, Jr. Multi-Service Ambulatory Care Center (US)
Openalex Percentile: Top 58%
Shape Memory Alloy Transformations
0.12
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