Coupling between topology optimization and digital image correlation for the design of specimen dedicated to selected material parameters identification

Chamoin, Ludovic; Jailin, Clément; Diaz, Matthieu; Quesada, Lucas

doi:10.1016/j.ijsolstr.2020.02.032

Cited by 18 publications

(30 citation statements)

References 58 publications

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“…It was concluded in [1,6,16] that parameter identification from heterogeneous specimens outperforms the one using classical homogeneous tests, such as uniaxial tensile test. Experimental procedures performed in [2,11,[17][18][19] on this type of specimens also demonstrated its reliability. Furthermore, it was proved that heterogeneous mechanical tests can reduce the number of the required experimental classical tests for the material parameter identification [9].…”

Section: Intr Introduction Oductionmentioning

confidence: 69%

“…Regarding the biaxial loading, it was intensively studied the cruciform shaped sample with differences on some geometrical parameters [6,7] as well as introducing perforations [8,9]. Concerning the optimization approaches, interesting studies have been made using shape optimization of the specimen outer boundaries in [10] and topology optimization in [11,12].…”

Section: Intr Introduction Oductionmentioning

confidence: 99%

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Design of heterogeneous interior notched specimens for material mechanical characterization

Conde¹,

Andrade‐Campos²,

Oliveira³

et al. 2021

Esaform 2021

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Nowadays, virtual predictions are essential in the design and development of new engineering parts. A critical aspect for virtual predictions is the accuracy of the constitutive model to simulate the material behavior. A state-of-the-art constitutive model generally involves a large number of parameters, and according to classical procedures, this requires many mechanical experiments for its accurate identification. Fortunately, this large number of mechanical experiments can be reduced using heterogeneous mechanical tests, which provide richer mechanical information than classical homogeneous tests. However, the test’s richness is much dependent on the specimen's geometry and can be improved with the development of new specimens. Therefore, this work aims to design a uniaxial tensile load test that presents heterogeneous strain fields using a shape optimization methodology, by controlling the specimen's interior notch shape. The optimization problem is driven by a cost function composed by several indicators of the heterogeneity present in the specimen. Results show that the specimen's heterogeneity is increased with a non-circular interior notch. The achieved virtual mechanical test originates both uniaxial tension and shear strain states in the plastic region, being the uniaxial tension strain state predominant.

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Section: Intr Introduction Oductionmentioning

confidence: 69%

Section: Intr Introduction Oductionmentioning

confidence: 99%

Design of heterogeneous interior notched specimens for material mechanical characterization

Conde¹,

Andrade‐Campos²,

Oliveira³

et al. 2021

Esaform 2021

View full text Add to dashboard Cite

show abstract

“…The work presented in Chamoin et al [117] considers a more advanced shape optimization methodology, SIMP, but still based on FE sensitivities. It was proposed to use IDIC [24] to identify the shear modulus of linear elastic orthotropic materials.…”

Section: Design By Identification Qualitymentioning

confidence: 99%

Towards Material Testing 2.0. A review of test design for identification of constitutive parameters from full‐field measurements

Pierron

Grédiac

2020

Strain

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Full‐field optical measurements like digital image correlation or the grid method have brought a paradigm shift in the experimental mechanics community. While inverse identification techniques like finite element model updating or the virtual fields method have been the object of significant developments, current test methods, inherited from the age of strain gauges or linear variable displacement transducers, are generally not well adapted to the rich information provided by these new measurement tools. This paper provides a review of the research dealing with the design and optimization of heterogeneous mechanical tests for the identification of material parameters from full‐field measurements, christened here Material Testing 2.0 (MT2.0).

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“…However, this is reduced to very limited variations of the geometry. At the opposite extreme, very large design spaces were considered to explore completely generic designs in [22] where the authors developed a SIMP-type topology optimization algorithm. The method has the advantage of being able to evolve the topology and therefore to create holes or notches if necessary.…”

Section: Introductionmentioning

confidence: 99%

Spline-based specimen shape optimization for robust material model calibration

Chapelier

Bouclier

Passieux

2022

Preprint

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Identification from field measurements allows several parameters to be identified from a single test, provided that the measurements are sensitive enough to the parameters to be identified. To do this, authors use empirically defined geometries (with holes, notches...). The first attempts to optimize the specimen to maximize the sensitivity of the measurement are linked to a design space that is either very small (parametric optimization), which does not allow the exploration of very different designs, or, conversely, very large (topology optimization), which sometimes leads to designs that are not regular and cannot be manufactured. In this paper, we propose an intermediate approach based on a non-invasive CAD-inspired optimization strategy which relies on the definition of univariate spline Free-Form Deformation boxes to reduce the design space and thus regularize the problem. Then, from the modeling point of view, we propose a new objective function that takes into account the experimental setup and we add constraint functions that ensure that the gain is real and the shape physically sound. Several examples show that with this method and at low cost, one can significantly improve the identification of constitutive parameters without changing the experimental setup.

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Coupling between topology optimization and digital image correlation for the design of specimen dedicated to selected material parameters identification

Cited by 18 publications

References 58 publications

Design of heterogeneous interior notched specimens for material mechanical characterization

Design of heterogeneous interior notched specimens for material mechanical characterization

Towards Material Testing 2.0. A review of test design for identification of constitutive parameters from full‐field measurements

Spline-based specimen shape optimization for robust material model calibration

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