A Study on the Effects of Strain Rates on Characteristics of Brain Tissue

Abstract

Traumatic brain injury (TBI) often happens when the brain tissue undergoes a high rate mechanical load. Although numerous research works have been carried out to study the mechanical characterization of brain matter under quasi-static (strain rate ≤ 100 S−1) loading but a limited amount of experimental studies are available for brain tissue behavior under dynamic strain rates (strain rate ≥ 100 S−1). In this paper, the results of a study on mechanical properties of ovine brain tissue under unconfined compression tests are to be presented. The samples were compressed under uniaxial strain rates of 0.0667, 3.33, 6.667, 33.33, 66.667 and 200 S−1. The brain tissue presents a stiffer response with increasing strain rate, showing a time-dependent behavior. So the hyperelastic-only models are not adequate to exhibit the brain viscoelasticity. Therefore, two hyper-viscoelastic constitutive equations based on power function model and Mooney-Rivlin energy function are applied to the results with quasi-static strain rate (≤ 100 S−1). Good agreement of experimental and theoretical has been achieved for results of the low strain rates. It is concluded that the obtained material parameters from quasi-static tests are not appropriate enough to fit the result with the high strain rate of 200 S−1. The study will further provide new insight into a better understanding of the rate-dependency behavior of the brain tissue under dynamic conditions. This is essential in the development of constitutive material characteristics for an efficient human brain finite element models to predict TBI under impact condition or high motion.

Ex-vivo quantification of ovine pia arachnoid complex biomechanical properties under uniaxial tension

“…Similar to previous studies investigating CNS tissue biomechanics [29][30][31] a Mooney-Rivlin model was applied to estimate material constants that were based on experimentally generated stress-strain curves. The present study found the Ovine PAC Mooney-Rivlin material parameters C10, C01, and C20 (Eq.1) to be 1, -1.004 and 0.629 MPa, respectively.…”

Making a point: shared mechanics underlying the diversity of biological puncture

“…Most biological tissues are viscoelastic, meaning that their response to applied stresses is dependent on the rate of application (strain rate; see Glossary) (Burstein and Frankel, 1968;Kunzek et al, 1999;Vogel, 2013). Most of what we know about rate dependency in biological tissues has come from an interest in human injury as a result of impact trauma (Champion et al, 2003;Chatelin et al, 2010;Karunaratne, 2016;Zhu et al, 2017), with most of the experimental work performed on various bovine and porcine tissues (McElhaney, 1966;Van Sligtenhorst et al, 2006;Shergold et al, 2006;Song et al, 2007;Cheng et al, 2009;Nie et al, 2011;Comley and Fleck, 2012;Rashid et al, 2013;Farid et al, 2017). This is just a small sample of the literature; however, little empirical data exist for strain rate effects on biological tissues outside of mammalian model taxa.…”

A Mesoscale Finite Element Modelling Approach for Understanding Brain Morphology and Material Heterogeneity Effects in Chronic Traumatic Encephalopathy

“…Computational head models (Horgan & Gilchrist 2003;Takhounts et al 2008;McAllister et al 2012;Yang et al 2014;Ghajari et al 2017;Ganpule et al 2017;Fernandes et al 2018) informed from material constitutive models (Mendis et al 1995;Donnelly et al 1997;Arbogast & Margulies 1999;el Sayed et al 2008;Hosseini Farid et al 2017;Hosseini-Farid et al 2019) with various injury criteria (Newman 1986;Newman & Shewchenko 2000;Kimpara & Iwamoto 2012;Takhounts et al 2013) are used to predict injury under various boundary conditions with some frameworks developed to specifically target injury ). Some of these injury criteria implemented on macroscale head models included significant uncertainty when compared to neurological injury in real-world injury scenarios (Marjoux et al 2008).…”