Fitted hyperelastic parameters for Human brain tissue from reported tension, compression, and shear tests

Morán, Richard; Smith, Joshua H.; García, José Jaime

doi:10.1016/j.jbiomech.2014.09.030

Cited by 63 publications

(42 citation statements)

References 28 publications

(50 reference statements)

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“…This is intended to investigate the uniformity of the product batches and to ensure that the product provides the representative test data Although the material performs different stress-strain curves under different loading condition, a unique and appropriate SEF for specific rubber can still be selected which is applicable under all loading condition. In order to select the appropriate SEF, a number of experimental tests must be carried out, or at least one of these simple tests, namely the uniaxial tensile, planar shear, or equibiaxial, must be conducted [39]. Generally, the SEF can be expressed in the following form [40].…”

Section: Methodsmentioning

confidence: 99%

FE Model of Low Grade Rubber for Modeling Housing’s Low-Cost Rubber Base Isolators

2018

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An accurate selection of strain energy function (SEF) plays a very important role for predicting the actual behavior of rubber material in the finite element analysis (FEA). The common method for selecting the SEF is by using the curve fitting procedure. However, the behavior of some typical rubbers, such as low grade rubbers (average hardness value of 47.2), cannot be predicted well by only using the curve fitting procedure. To accurately predict the actual behavior of such specifically nearly incompressible material, a series of FEA were carried out to simulate the actual behavior of four physical testing materials, namely the uniaxial, the planar shear, the equibiaxial, and the volumetric tests. This FEA is intended to examine the most suitable constitutive model in representing the rubber characteristics and behavior. From the comparisons, it can be concluded that the Ogden model provides a reasonably accurate prediction compared to the remaining investigated constitutive material models. Finally, the appropriate SEF, i.e. the Ogden model, was adopted for modeling a low-cost rubber base isolator (LCRBI) in the finite element analysis (FEA). The simple uniaxial compression test of the LCRBI is required for validating that the selected SEF works for predicting the actual behavior of LCRBI.

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Section: Methodsmentioning

confidence: 99%

FE Model of Low Grade Rubber for Modeling Housing’s Low-Cost Rubber Base Isolators

2018

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“…From the study conducted by Moran et al [18], it was found that the Hyperfoam, Ogden and polynomial functions have relatively good fit to the experimental data. The coefficient of determination for the Hyperfoam, Ogden and Polynomial were 0.97, 0.92 and 0.80 respectively.…”

Section: Materials Modelsmentioning

confidence: 97%

“…Hyperelastic materials can be considered to be isotropic, incompressible and strain rate independent. Due to the large deformations seen on tissues during surgeries, these models are used extensively for all kinds of tissues such as brain [13,18], liver tissue [14], skin [15], soft tissues [16] and for general laparoscopic simulation [17]. The relevant equations of the strain energy function can be explained as follows [18]:…”

Section: Materials Modelsmentioning

confidence: 99%

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Review on Finite Element Material Modelling Of Brain Tissue for Surgical Simulation

Tarlochan

Tangutooru

2016

MATEC Web Conf.

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Abstract. Surgical simulation is a growing field of interest as it serves as a good training for the medical practitioners as well as planning and preparing for surgery. For a reliable and a good outcome from the simulation, the challenge is to model the material properties of tissues as accurate as possible. For a real time surgical simulation the numerical model has to be simple and computationally inexpensive. One of the preferred numerical models is the finite element model. Hence, the objective of this paper is to review finite element modelling of the brain tissue. The human brain tissue is an interesting organ to be studied because of their use in understanding trauma related injuries and tissue injury mechanism during brain surgery.

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“…The stretch ratios can thus be calculated as

λ_{1} = λ, λ_{2} = λ_{3} = \frac{1}{\sqrt{λ}}

where λ is the stretch ratio in the uniaxial compression direction. The stretch ratio λ can be related to the engineering strain ε that is assumed to be positive in tension

λ = 1 + ε

…”

Section: Modified Constitutive Model For Sikaflex Adhesivesmentioning

confidence: 99%

Experimental Characterization and Modified Constitutive Modeling of the Strain Rate Dependent Compressive Behavior of Adhesives

Wang

2016

Macro Materials & Eng

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Predicting the impact performance of adhesively bonded structures requires the accurate characterization and constitutive formulation of the compressive behavior of the adhesive at dynamic strain rates. In this work, the stress–strain curves of Sikaflex adhesives are measured in uniaxial compression tests at quasi‐static and dynamic strain rates. The split‐Hopkinson pressure bar technique is modified with the hollow output bar to effectively characterize the dynamic response of the adhesive. It is found that the Sikaflex adhesive is incompressible and hyperelastic; the compressive behavior is significantly influenced by the strain rate. The strain rate sensitivity is not constant but varies as a function of the strain and the strain rate. The strain rate effect on compressive behavior is quantified and incorporated into the phenomenological hyperelastic constitutive model based on strain energy density. The modified constitutive equation accurately represents the strain rate dependent compressive behavior of Sikaflex adhesives.

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Fitted hyperelastic parameters for Human brain tissue from reported tension, compression, and shear tests

Cited by 63 publications

References 28 publications

FE Model of Low Grade Rubber for Modeling Housing’s Low-Cost Rubber Base Isolators

FE Model of Low Grade Rubber for Modeling Housing’s Low-Cost Rubber Base Isolators

Review on Finite Element Material Modelling Of Brain Tissue for Surgical Simulation

Experimental Characterization and Modified Constitutive Modeling of the Strain Rate Dependent Compressive Behavior of Adhesives

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