Using the simple compression test to determine Young’s modulus, Poisson’s ratio and the Coulomb friction coefficient

Williams, J. G.; Gamonpilas, Chaiwut

doi:10.1016/j.ijsolstr.2008.03.023

Cited by 49 publications

(37 citation statements)

References 13 publications

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“…As a result the rubber is compressed and it expands laterally; this is called the "barrelling effect". Previous works have determined the analytical solution of this deformation for an elastic material [8], [28], [29]. However, the solution for more complicated material models (such as viscoelastic and hyperelastic) is not trivial.…”

Section: Bonded Compression Testmentioning

confidence: 99%

Inverse-FEM Characterization of a Brain Tissue Phantom to Simulate Compression and Indentation

et al. 2012

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The realistic simulation of tool-tissue interactions is necessary for the development of surgical simulators and one of the key element for it realism is accurate bio-mechanical tissue models. In this paper, we determined the mechanical properties of soft tissue by minimizing the difference between experimental measurements and the analytical or simulated solution of the deformation. Then, we selected the best model parameters that fit the experimental data to simulate a bonded compression and a needle indentation with a flat-tip. We show that the inverse FEM allows accurate material property estimation. We also validated our results using multiple tool-tissue interactions over the same specimen. Caracterización de tejido cerebral artificial utilizando Inverse-FEM para simular indentación y comprensión ResumenUna simulación realista de la interacción tejido-herramienta es necesaria para desarrollar simuldores quirúrgicos, y la presición en modelos biomecánicos de tejidos es determinante para cumplir tal fin. Los trabajos previos han caracterizado las propiedades de tejidos blandos; sin embargo, ha faltado una validación apropiada de los resultados. En este trabajo se determinaron las propiedades mecánicas de un tejido blando minimizando la diferencia entre las mediciones experimentales y la solución analítica o simulada del problema. Luego, fueron seleccionados los parámetros que mejor se ajustaron a los datos experimentales para simular una compresión con fricción y la indentación de una aguja con punta plana. Se concluye que el inverse-FEM permite la precisa estimación de las propiedades del material. Además, estos resultados fueron validados con varias interacciones tejido-herramienta sobre el mismo espécimen.

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Section: Bonded Compression Testmentioning

confidence: 99%

Inverse-FEM Characterization of a Brain Tissue Phantom to Simulate Compression and Indentation

et al. 2012

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“…However, the generation of undesirable friction at the specimen/platen interface is unavoidable during compression tests at quasistatic and dynamic loading conditions. Williams and Gamonpilas (2008) derived analytical solutions for the compression of cylinders with bonded surfaces and with Coulomb friction conditions at the interfaces. It was shown that the apparent moduli were strong functions of Poisson's ratio and of the Coulomb friction coefficients.…”

Section: Introductionmentioning

confidence: 99%

Determination of friction coefficient in unconfined compression of brain tissue

Rashid

Destrade

Gilchrist

2012

Journal of the Mechanical Behavior of Biomedical Materials

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Unconfined compression tests are more convenient to perform on cylindrical samples of brain tissue than tensile tests in order to estimate mechanical properties of the brain tissue because they allow for homogeneous deformations. The reliability of these tests depends significantly on the amount of friction generated at the specimen/platen interface. Thus, there is a crucial need to find an approximate value of the friction coefficient in order to predict a possible overestimation of stresses during unconfined compression tests. In this study, a combined experimental -computational approach was adopted to estimate the dynamic friction coefficient µ of porcine brain matter against metal platens in compressive tests. Cylindrical samples of porcine brain tissue were tested up to 30% strain at variable strain rates, both under bonded and lubricated conditions in the same controlled environment. It was established that µ was equal to 0.09 ± 0.03, 0.18 ± 0.04, 0.18 ± 0.04 and 0.20 ± 0.02 at strain rates of 1, 30, 60 and 90/s, respectively. Additional tests were also performed to analyze brain tissue under lubricated and bonded conditions, with and without initial contact of the top platen with the brain tissue, with different specimen aspect ratios and with different lubricants (Phosphate Buffer Saline (PBS), Polytetrafluoroethylene (PTFE) and Silicon). The test conditions (lubricant used, biological tissue, loading velocity) adopted in this study were similar to the studies conducted by other research groups. This study will help to understand the amount of friction generated during unconfined compression of brain tissue for strain rates of up to 90/s.

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“…23 The elastic modulus (E) can be calculated from E a , the Poisson's ratio ν and the shape factor S, which is defined as the radius divided by the height in the case of cylindrical samples. 24 In the top, a clear variation in the length of A35 before and after compression is observed, while variations in the length of A90 were not evident at the naked eye. Small differences in the images for A90 before and after compression are caused by the different angle at which the photo was taken.…”

Section: Mechanical Propertiesmentioning

confidence: 94%

Tuning the structure and the mechanical properties of epoxy–silica sol–gel hybrid materials

2016

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Using the simple compression test to determine Young’s modulus, Poisson’s ratio and the Coulomb friction coefficient

Cited by 49 publications

References 13 publications

Inverse-FEM Characterization of a Brain Tissue Phantom to Simulate Compression and Indentation

Inverse-FEM Characterization of a Brain Tissue Phantom to Simulate Compression and Indentation

Determination of friction coefficient in unconfined compression of brain tissue

Tuning the structure and the mechanical properties of epoxy–silica sol–gel hybrid materials

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