Researchers have conducted finite element (FE) analyses with human models to predict injuries due to traffic accidents or falling. In most of their analyses, cortical bone was simply modeled as a general isotropic elastoplastic material. In this study, a constitutive model of cortical bone considering anisotropic inelasticity and damage evolution was developed to predict injuries more accurately. The new model can satisfactorily represent mechanical properties of cortical bone including anisotropy of elastic modulus and yield stress with strain-rate dependency, and asymmetric stress-strain curves in tension and compression. Simultaneously the included damage-evolution equation enables to predict failure stress and strain with rate dependency in bone fracture simulations. The proposed model was verified using experimental data obtained from the literature. We applied the proposed model to a simple cylindrical FE model of the human femur, and performed simulations under loading conditions such as tension, compression, and torsion. The results showed some tendency of characteristic fracture patterns such as transverse fracture in tensile loading, oblique fracture in compression, and spiral fracture in torsion. The proposed constitutive model would have the potential for better injury prediction in the future.Key words : Cortical bone, Constitutive modeling, Anisotropy, Damage evolution, Fracture, Rate dependency IntroductionIn recent years, many researchers have conducted finite element (FE) analyses with human models to predict injuries due to traffic accident or falling (Tanaka et al., 2004;Watanabe et al., 2011). However, compared with the reproduction accuracy of the shapes of bones, the material model used in such analyses is simplified because mechanical properties of biomaterials have not been fully explained and satisfactory constitutive models do not exist. In most FE analyses, the option of isotropic elastoplastic material built in general-purpose FE-analysis software is selected as the mechanical property for cortical bone.Many researchers studied the actual mechanical properties of cortical bone. For example, Reilly and Burstein (1975) and Yoon and Katz (1976) conducted experiments that found transverse isotropy in elastic modulus of the femur. Moreover, at the point of strength and damage, anisotropy is observed along the circumferential and radial directions; hence, cortical bone could be considered as an orthotropic material (Currey, 2002). McElhaney (1966), Wood (1971), andCarter andHayes (1977) researched strain-rate dependency in the stress-strain curve of cortical bone; they found that the stiffness and brittleness were proportional to the strain rate. In addition, the strength of cortical bone decreases in the order of compressive, tensile, and torsional loading (Yamada, 1970). As explained previously, the mechanical properties of cortical bone considerably depend on the loading direction, differences in strain rates, and loading patterns such as tension and compression (Cowin et al., 19...

The optimized crash pulse has a concave shape and is dependent on the occupant restraint stiffness and maximum vehicle deformation. The shapes of the optimized crash pulse in the final phase were different for the objective functions of chest acceleration and chest deflection due to the inertial forces of the head and upper extremities. From the human FE model analysis it was found that the optimized crash pulse for the Hybrid III chest deflection can substantially reduce the risk of rib cage fractures. Supplemental materials are available for this article. Go to the publisher's online edition of Traffic Injury Prevention to view the supplemental file.

This simulation study indicates that mechanical loading promotes meandering and wave breaks of spiral reentry through MEF. Mechanical loading under pathological conditions may contribute to the maintenance of VF through these mechanisms.

Background Many biological soft tissues are hydrated porous hyperelastic materials, which consist of a complex solid skeleton with fine voids and fluid filling these voids. Mechanical interactions between the solid and the fluid in hydrated porous tissues have been analyzed by finite element methods (FEMs) in which the mixture theory was introduced in various ways. Although most of the tissues are surrounded by deformable membranes that control transmembrane flows, the boundaries of the tissues have been treated as rigid and/or freely permeable in these studies. The purpose of this study was to develop a method for the analysis of hydrated porous hyperelastic tissues surrounded by deformable membranes that control transmembrane flows. Results For this, we developed a new nonlinear finite element formulation of the mixture theory, where the nodal unknowns were the pore water pressure and solid displacement. This method allows the control of the fluid flow rate across the membrane using Neumann boundary condition. Using the method, we conducted a compression test of the hydrated porous hyperelastic tissue, which was surrounded by a flaccid impermeable membrane, and a part of the top surface of this tissue was pushed by a platen. The simulation results showed a stress relaxation phenomenon, resulting from the interaction between the elastic deformation of the tissue, pore water pressure gradient, and the movement of fluid. The results also showed that the fluid trapped by the impermeable membrane led to the swelling of the tissue around the platen. Conclusions These facts suggest that our new method can be effectively used for the analysis of a large deformation of hydrated porous hyperelastic material surrounded by a deformable membrane that controls transmembrane flow, and further investigations may allow more realistic analyses of the biological soft tissues, such as brain edema, brain trauma, the flow of blood and lymph in capillaries and pitting edema.

Although the generation mechanism of the low-frequency (LF) component of heart rate variability (HRV) is controversial, HRV is a potential candidate in designing objective measurement methodologies for emotions. These methodologies could be valuable for several biosignal applications. Here, we have conducted a simulation analysis using a novel mathematical model that integrates emotion, respiration, the nervous system, and the cardiovascular system. Our model has well reproduced experimental results, specifically concerning HRV with respiratory sinus arrhythmia and LF, the relation between HRV total power and the respiration frequency, and the homeostatic maintenance by the baroreflex. Our model indicates the following possibilities: (i) The delay in the heart rate control process of the parasympathetic activity works as a low-pass filter and the HRV total power decreases with a higher respiration frequency; (ii) the LF component of HRV and the Mayer wave are generated as transient responses of the baroreflex feedback control to perturbations induced by an emotional stimulus; and (iii) concentration on breathing to reduce the respiration frequency can reduce LF/HF and the reduction can be fed back to the emotional status.