Finite Element (FE) modelling of spinal cord response to impact can provide unique insights into the neural tissue response and injury risk potential. Yet, contemporary human body models (HBMs) used to examine injury risk and prevention across a wide range of impact scenarios often lack detailed integration of the spinal cord and surrounding tissues. The integration of a spinal cord in contemporary HBMs has been limited by the need for a continuum-level model owing to the relatively large element size required to be compatible with HBM, and the requirement for model development based on published material properties and validation using relevant non-linear material data. The goals of this study were to develop and assess non-linear material model parameters for the spinal cord parenchyma and pia mater, and incorporate these models into a continuum-level model of the spinal cord with a mesh size conducive to integration in HBM. First, hyper-viscoelastic material properties based on tissue-level mechanical test data for the spinal cord and hyperelastic material properties for the pia mater were determined. Secondly, the constitutive models were integrated in a spinal cord segment FE model validated against independent experimental data representing transverse compression of the spinal cord-pia mater complex (SCP) under quasi-static indentation and dynamic impact loading. The constitutive model parameters were fit to a quasi-linear viscoelastic model with an Ogden hyperelastic function, and then verified using single element test cases corresponding to the experimental strain rates for the spinal cord (0.32–77.22 s−1) and pia mater (0.05 s−1). Validation of the spinal cord model was then performed by re-creating, in an explicit FE code, two independent ex-vivo experimental setups: 1) transverse indentation of a porcine spinal cord-pia mater complex and 2) dynamic transverse impact of a bovine SCP. The indentation model accurately matched the experimental results up to 60% compression of the SCP, while the impact model predicted the loading phase and the maximum deformation (within 7%) of the SCP experimental data. This study quantified the important biomechanical contribution of the pia mater tissue during spinal cord deformation. The validated material models established in this study can be implemented in computational HBM.
Spinal cord impacts can have devastating consequences. Computational models can investigate such impacts but require biofidelic numerical representations of the neural tissues and fluid–structure interaction with cerebrospinal fluid. Achieving this biofidelity is challenging, particularly for efficient implementation of the cerebrospinal fluid in full computational human body models. The goal of this study was to assess the biofidelity and computational efficiency of fluid–structure interaction methods representing the cerebrospinal fluid interacting with the spinal cord, dura, and pia mater using experimental pellet impact test data from bovine spinal cords. Building on an existing finite element model of the spinal cord and pia mater, an orthotropic hyperelastic constitutive model was proposed for the dura mater and fit to literature data. The dura mater and cerebrospinal fluid were integrated with the existing finite element model to assess four fluid–structure interaction methods under transverse impact: Lagrange, pressurized volume, smoothed particle hydrodynamics, and arbitrary Lagrangian–Eulerian. The Lagrange method resulted in an overly stiff mechanical response, whereas the pressurized volume method over‐predicted compression of the neural tissues. Both the smoothed particle hydrodynamics and arbitrary Lagrangian–Eulerian methods were able to effectively model the impact response of the pellet on the dura mater, outflow of the cerebrospinal fluid, and compression of the spinal cord; however, the arbitrary Lagrangian–Eulerian compute time was approximately five times higher than smoothed particle hydrodynamics. Crucial to implementation in human body models, the smoothed particle hydrodynamics method provided a computationally efficient and representative approach to model spinal cord fluid–structure interaction during transverse impact.
Quantifying the response of infill used to construct contemporary artificial turf is critical to the development of computational models and providing insights to reduce sports injury associated with artificial turf. In the current study, confined compression and direct shear tests were performed on typical infill materials (sand, SBR and two mixtures (33%: 67%) by-weight). The experimental tests exhibited a progression from high strength and stiffness (sand) to low strength and stiffness (SBR) with the mixtures having intermediate values. Increasing particle size, particularly sand, tended to increase the resistance of the infill to deformation. The experimental results were implemented into a soil constitutive material model and the experimental tests were simulated using a smoothed particle hydrodynamics (SPH) method to verify the implementation in a commercial explicit finite element solver. The SPH method successfully captured the initial loading up to yield, material flow and post-yield behavior, enabling large-scale particle flow that will be necessary to simulate artificial turf. The simulation results predicted the test force-displacement response well for SBR and mixture infills. The proposed methodology demonstrated the ability to measure properties of contemporary artificial turf infills in both compression and shear for pure sand, pure SBR and mixtures of the two, and use these properties to accurately represent the infill in a computational environment. The resulting model can be extended to large-scale turf models, to investigate athlete performance and injury risk when interacting with artificial turf.
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