A mechanized and integrated computational scheme is introduced to determine the human brain responses in an environment where the human head is exposed to explosions from trinitrotoluene (TNT), or other high-yield explosives, in military applications. The procedure is based on a three-dimensional (3-D) non-linear finite element method (FEM) that implements a simultaneous conduction of explosive detonation, shock wave propagation, blast-head interactions, and the confronting human head. The processes of blast propagation in the air and blast interaction with the head are modeled by an Arbitrary Lagrangian-Eulerian (ALE) multi-material FEM formulation, together with a penalty-based fluid/structure interaction (FSI) algorithm. Such a model has already been successfully validated against experimental data regarding air-free blast and plate-blast interactions. The human head model is a 3-D geometrically realistic configuration that has been previously validated against the brain intracranial pressure (ICP), as well as shear and principal strains under different impact loadings of cadaveric experimental tests of Hardy et al. [Hardy W. N., C. Foster, M. Mason, S. Chirag, J. Bishop, M. Bey, W. Anderst, and S. Tashman. A study of the response of the human cadaver head to impact. Proc. 51 ( st ) Stapp. Car Crash J. 17-80, 2007]. Different scenarios have been assumed to capture an appropriate picture of the brain response at a constant stand-off distance of nearly 80 cm from the core of the explosion, but exposed to different amounts of a highly explosive (HE) material such as TNT. The over-pressures at the vicinity of the head are in the range of about 2.4-8.7 atmosphere (atm), considering the reflected pressure from the head. The methodology provides brain ICP, maximum shear stresses and maximum principal strain within the milli-scale time frame of this highly dynamic phenomenon. While focusing on the two mechanical parameters of pressure, and also on the maximum shear stress and maximum principal strain to predict the brain injury, the research provides an assessment of the brain responses to different amounts of over-pressure. The research also demonstrates the ability to predict the ICP, as well as the stress and strain within the brain, due to such an event. The research cannot identify, however, the specific levels of ICP, stress and strain that necessarily lead to traumatic brain injury (TBI) because there is no access to experimental data regarding head-blast interactions.

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In this paper, a micromechanical model of a composite lamina material with fiber waviness is described. Results are presented and discussed with regard to stiffness and strength predictions for composite lamina. A micromechanical model of a unit cell from periodically distributed unidirectional waved cylindrical fibers embedded within matrix is proposed to withdraw the different material stiffness parameters. Finite element analysis of the periodic unit cell characterizing the structural stiffness of the composite material is carried out to determine the average stress and strain components. The composite stress-strain relations are then employed to determine the stiffness parameters. Numerical results for a typical composite constituted of polymer matrix and carbon fibers in the form of periodically hexagonal packing and initially sinusoidal waviness are presented for different amplitude to wavelength ratios and a range of fiber volume fractions. The results reveal the presence of local periodic-antisymmetric stresses that are usually unaccounted for in conventional structural analysis. The potential influence of these stresses on failure prediction is discussed.

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This paper proposes a micromechanics algorithm utilising the finite element method (FEM) for the analysis of heterogeneous matter. The characterisation procedure takes the material properties of the constituents, axons and extracellular matrix (ECM) as input data. The material properties of both the axons and the matrix are assumed to have linear viscoelastic behaviour with a perfect bonding between them. The results of the modelling have been validated with experimental data with material white input from brainstem by considering the morphology of brainstem in which most axons are oriented in longitudinal direction in the form of a uniaxial fibrous composite material. The method is then employed to examine the undulations of axons within different subregions of white matter and to study the impact due to axon/matrix volume fractions. For such purposes, different unit cells composed of wavy geometries and with various volume factions have been exposed to the six possible loading scenarios. The results will clearly demonstrate the undulation and axon volume fraction impacts. In this respect, undulation affects the material stiffness heavily in the axon longitudinal direction, whereas the axons' volume fraction has a much greater impact on the mechanical properties of the white matter in general. Also the results show that the created stresses and strains in the axons and matrix under loading will be impacted by undulation change. With increase in undulation the matrix suffers higher stresses when subjected to tension, whereas axons suffer higher stresses in shear. The axons always exhibit higher stresses whereas the matrix exhibits higher strains. The evaluated time-dependent local stress and strain concentrations within a repeating unit cell of the material model are indicative of the mechanical behaviour of the white tissue under different loading scenarios.