Dilaver Singh

Head and brain response to blast using sagittal and transverse finite element models

Mild traumatic brain injury caused by blast exposure from Improvised Explosive Devices has become increasingly prevalent in modern conflicts. To investigate head kinematics and brain tissue response in blast scenarios, two solid hexahedral blast-head models were developed in the sagittal and transverse planes. The models were coupled to an Arbitrary Lagrangian-Eulerian model of the surrounding air to model blast-head interaction, for three blast load cases (5 kg C4 at 3, 3.5 and 4 m). The models were validated using experimental kinematic data, where predicted accelerations were in good agreement with experimental tests, and intracranial pressure traces at four locations in the brain, where the models provided good predictions for frontal, temporal and parietal, but underpredicted pressures at the occipital location. Brain tissue response was investigated for the wide range of constitutive properties available. The models predicted relatively low peak principal brain tissue strains from 0.035 to 0.087; however, strain rates ranged from 225 to 571 s-1. Importantly, these models have allowed us to quantify expected strains and strain rates experienced in brain tissue, which can be used to guide future material characterization. These computationally efficient and predictive models can be used to evaluate protection and mitigation strategies in future analysis.

Modified Hopkinson Apparatus to Investigate Fluid Cavitation as a Potential Source of Injury

Mild Traumatic Brain Injury (mTBI) has been recognized as an important issue for persons exposed to blast. Specifically, this injury has been associated with exposure to blast overpressure and more recently relatively large negative pressures have been identified as occurring at the posterior regions of the brain in experimental and in numerical studies of frontal blast exposure. These negative pressures are caused by the reflection of the incident bar stress wave from the free surface of the skull, and may be intensified due to focusing effects from the curvature of the skull. Under certain circumstances, this negative pressure is hypothesized to cause cavitation of cerebrospinal fluid (CSF) surrounding the brain, potentially resulting in injury to the brain. Unfortunately the cavitation pressure of CSF has not been directly measured, so the consequence of negative pressures in numerical head models exposed to blast cannot be accurately predicted. The cavitation pressure of fluids is highly variable, depending on the presence of impurities in the fluid and the presence of dissolved gasses. In this study, a modified Compressive Split Hopkinson Pressure Bar (CSHPB) apparatus incorporating a sealed confinement chamber was used to generate negative pressures in distilled water to investigate the cavitation properties of water as a surrogate for CSF. The negative pressures in the fluid were measured using a pressure transducer designed for compression and validated in comparison to the input signal on the modified Hopkinson bar apparatus, as well as verified by a numerical model of the experiment. The CSHPB apparatus was used to generate initial compressive waves ranging from 1.85 to 7.85 MPa to produce cavitation in distilled water. The experimental tests were simulated with good agreement and used to obtain water peak negative pressures ranging from −1.32 to −5.64 MPa. Future tests will be undertaken to investigate cavitation properties of CSF.

Investigation of Cavitation Using a Modified Hopkinson Apparatus

Head injury, specifically mild Traumatic Brain Injury, has been identified as an increasingly common injury resulting from blast exposure. Advanced modeling has demonstrated the possibility of relatively high negative pressure at the posterior of the skull for frontal blast exposure, attributed to reflection and focusing of the stress waves due to curvature of the skull. It has been hypothesized that high negative pressures could lead to injury, possibly by cavitation of the cerebrospinal fluid (CSF). However, the cavitation pressure for CSF has not been measured directly in the literature, and thresholds are required for detailed numerical head models. Furthermore, the values for cavitation pressure of fluids in the literature vary widely, postulated to be due to varying levels of impurities and dissolved gases. In this study, a Split Hopkinson Pressure Bar apparatus was modified for tensile loading with a sealed confinement chamber and was used to investigate the cavitation properties of water. The modified apparatus was able to generate a tensile wave on the order of 3.4 MPa resulting in cavitation in the water sample. Future work will utilize this technique to investigate the cavitation pressure of CSF directly.

Experimental Testing and Computational Analysis of Viscoelastic Wave Propagation in Polymeric Split Hopkinson Pressure Bar

The use of polymeric bars in the traditional Kolsky or Split Hopkinson Pressure Bar (SHPB) has been suggested by several authors as a means of improving coupling to low impedance materials and to increase incident wave rise time to assist in achieving dynamic equilibrium when testing soft materials. However, one aspect that must be addressed in this application is viscoelastic wave propagation leading to wave attenuation and dispersion. The amount of dispersion and attenuation depends on the bar material selection and incident wave signal. Viscoelastic wave propagation has been successfully addressed in Polymeric SHPB through experimental determination of the wave propagation coefficients, and has been investigated through analytical techniques; however, there is no widely accepted method for computationally modeling these events, which would benefit test apparatus design and optimization.

An Investigation of Dimensional Scaling Using Cervical Spine Motion Segment Finite Element Models.

The paucity of experimental data for validating computational models of different statures underscores the need for appropriate scaling methods so that models can be verified and validated using experimental data. Scaling was investigated using 50th percentile male (M50) and 5th percentile female (F05) cervical spine motion segment (C4-C5) finite element models subject to tension, flexion, and extension loading. Two approaches were undertaken: geometric scaling of the models to investigate size effects (volumetric scaling) and scaling of the force-displacement or moment-angle model results (data scaling). Three sets of scale factors were considered: global (body mass), regional (neck dimensions), and local (segment tissue dimensions). Volumetric scaling of the segment models from M50 to F05, and vice versa, produced correlations that were good or excellent in both tension and flexion (0.825-0.991); however, less agreement was found in extension (0.550-0.569). The reduced correlation in extension was attributed to variations in shape between the models leading to nonlinear effects such as different time to contact for the facet joints and posterior processes. Data scaling of the responses between the M50 and F05 models produced similar trends to volumetric scaling, with marginally greater correlations. Overall, the local tissue level and neck region level scale factors produced better correlations than the traditional global scaling. The scaling methods work well for a given subject, but are limited in applicability between subjects with different morphology, where nonlinear effects may dominate the response.

Modeling the Neck for Impact Scenarios

Abstract This chapter presents a summary of computational modeling of the human neck for impact loading. The computational models require input parameters, including geometry or anatomy, boundary conditions, and material properties that correspond to the scale of the developed model. Computational neck models apply these inputs to predict kinetic and kinematic responses in impact scenarios, and ultimately predict the potential for injuries to the neck. 13.2 Anatomy of the Neck , 13.3 Neck Anthropometrics introduce the anatomy and anthropometrics of the neck, respectively. Injuries to the neck are discussed briefly in Section 13.4 , followed by a detailed discussion of the mechanical properties of structural tissues in the neck ( Section 13.5 ). A critical element for a computational model is the assessment of model performance relative to experimental data ( Section 13.6 ). Finally, a summary of historical and current computational neck models is presented in Section 13.7 .