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The aim of this study was to measure high-resolution strain fields in planar sections of brain tissue during translational acceleration to obtain validation data for numerical simulations. Slices were made from fresh, porcine brain tissue, and contained both grey and white matter as well as the complex folding structure of the cortex. The brain slices were immersed in artificial cerebrospinal fluid (aCSF) and were encapsulated in a rigid cavity representing the actual shape of the skull. The rigid cavity sustained an acceleration of about 900m/s(2) to a velocity of 4m/s followed by a deceleration of more than 2000m/s(2). During the experiment, images were taken using a high-speed video camera and Von Mises strains were calculated using a digital image correlation technique. The acceleration of the sampleholder was determined using the same digital image correlation technique. A rotational motion of the brain slice relative to the sampleholder was observed, which may have been caused by a thicker posterior part of the slice. Local variations in the displacement field were found, which were related to the sulci and the grey and white matter composition of the slice. Furthermore, higher Von Mises strains were seen in the areas around the sulci.

To understand brain injuries better, the mechanical properties of brain tissue have been studied for 50 years; however, no universally accepted data set exists. The variation in material properties reported may be caused by differences in testing methods and protocols used. An overview of studies on the mechanical properties of brain tissue is given, focusing on testing methods. Moreover, the influence of important test conditions, such as temperature, anisotropy, and precompression was experimentally determined for shear deformation. The results measured at room temperature show a stiffer response than those measured at body temperature. By applying the time-temperature superposition, a horizontal shift factor a(T)=8.5-11 was found, which is in agreement with the values found in literature. Anisotropy of samples from the corona radiata was investigated by measuring the shear resistance for different directions in the sagittal, the coronal, and the transverse plane. The results measured in the coronal and the transverse plane were 1.3 and 1.25 times stiffer than the results obtained from the sagittal plane. The variation caused by anisotropy within the same plane of individual samples was found to range from 25% to 54%. The effect of precompression on shear results was investigated and was found to stiffen the sample response. Combinations of these and other factors (postmortem time, donor age, donor type, etc.) lead to large differences among different studies, depending on the different test conditions.

No validated, generally accepted data set on the mechanical properties of brain tissue exists, not even for small strains. Most of the experimental and methodological issues have previously been addressed for linear shear loading. The objective of this work was to obtain a consistent data set for the mechanical response of brain tissue to either compression or shear. Results for these two deformation modes were obtained from the same samples to reduce the effect of inter-sample variation. Since compression tests are not very common, the influence of several experimental conditions for the compression measurements was analysed in detail. Results with and without initial contact of the sample with the loading plate were compared. The influence of a fluid layer surrounding the sample and the effect of friction were examined and were found to play an important role during compression measurements.To validate the non-linear viscoelastic constitutive model of brain tissue that was developed in Hrapko et al. (Biorheology 43 (2006), 623-636) and has shown to provide a good prediction of the shear response, the model has been implemented in the explicit Finite Element code MADYMO. The model predictions were compared to compression relaxation results up to 15% strain of porcine brain tissue samples. Model simulations with boundary conditions varying within the physical ranges of friction, initial contact and compression rate are used to interpret the compression results.

The non-linear mechanical behaviour of porcine brain tissue in large shear deformations is determined. An improved method for rotational shear experiments is used, producing an approximately homogeneous strain field and leading to an enhanced accuracy. Results from oscillatory shear experiments with a strain amplitude of 0.01 and frequencies ranging from 0.04 to 16 Hz are given. The immediate loss of structural integrity, due to large deformations, influencing the mechanical behaviour of brain tissue, at the time scale of loading, is investigated. No significant immediate mechanical damage is observed for these shear deformations up to strains of 0.45. Moreover, the material behaviour during complex loading histories (loading-unloading) is investigated. Stress relaxation experiments for strains up to 0.2 and constant strain rate experiments for shear rates from 0.01 to 1 s(-1) and strains up to 0.15 are presented. A new differential viscoelastic model is used to describe the mechanical response of brain tissue. The model is formulated in terms of a large strain viscoelastic framework and considers non-linear viscous deformations in combination with non-linear elastic behaviour. This constitutive model is readily applicable in three-dimensional head models in order to predict the mechanical response of the intra-cranial contents due to an impact.

The development of more comfortable seats is an important issue in the automotive industry. However, the development of new car seats is very time consuming and costly since it is typically based on experimental evaluation using prototypes. Computer models of the human-seat interaction could accelerate this process. The objective of this paper is to establish a protocol for the development of seat models using numerically efficient simulation techniques. The methodology is based on multi-body techniques: arbitrary surfaces, providing an accurate surface description, are attached to rigid bodies. The bodies are connected by kinematic joints, representing the seat back recliner and head restraint joint. Properties of the seat foam and frame have been lumped together. Further, experiments have been defined to characterise the mechanical properties required for the seat model for comfort applications. The protocol has been exemplified using a standard car seat. The seat model has been validated based on experiments with rigid loading devices with human-like shapes in terms of force-deflection characteristics. The response of the seat model agrees well with the experimental results. Therefore the presented method can be a useful tool in the seat development process, especially in early stages of the design process.

Seating comfort is becoming increasingly important for the automotive industry. Car manufacturers use seating comfort to distinguish their products from those of competitors. However, the development and design of a new, more comfortable seat is time consuming and costly. The introduction of computer models of human and seat will accelerate this process. The contact interaction between human and seat is an important factor in the comfort sensation of subjects. This paper presents a finite element (FE) model of the human buttocks, able to predict the pressure distribution between human and seating surface by its detailed and realistic geometric description. A validation study based on volunteer experiments shows reasonable correlation in pressure distributions between the buttocks model and the volunteers. Both for simulations on a rigid and a soft cushion, the model predicts realistic seat pressure distributions. A parameter study shows that a pressure distribution at the interface between human and seat strongly depends on variations in human flesh and seat cushion properties.

Objective: This paper describes the prediction of spinal forces in car occupants during vertical vibrations using a numerical multi-body occupant model., Background: An increasing part of the population is exposed to whole body vibrations in vehicles. In literature, vertical vibrations and low back pain are often related to each other. The cause of these low back pains is not well understood. A numerical human model, predicting intervertebral forces, can help to understand the mechanics of the human spine during vertical vibrations., Methods: Numerical human and seat models have been used. Human model responses have been validated for vertical vibrations (rigid and standard car seat condition): simulated and experimental seat-to-human frequency response functions have been compared. The spinal shear and compressive forces have been investigated with the model., Results: The human model seat-to-pelvis and seat-to-T1 frequency response functions in the rigid seat condition and all seat-to-human frequency response functions in the standard car seat condition approach the experimental results reasonably. The lumbar and the lower thoracic spine are subjected to the largest shear and compressive forces., Conclusions: The human model responses correlate reasonable with the volunteer responses. The predicted spinal forces could be used as a basis for derivation of hypothetical mechanisms and better understanding of low back pain disorders., Relevance: In order to solve the problem of whole body vibration related injuries, knowledge about the interaction between human spinal vertebrae in vertical vibrations is required. This interaction cannot be measured in volunteer experiments. This paper describes the application of a numerical human model for prediction of spinal forces, that could be used as a basis for derivation of hypotheses regarding low back pain disorders.

Pedestrian accidents are one of the main causes of traffic fatalities and injuries worldwide. New pedestrian safety regulations are being proposed in Europe and Japan to improve the protection afforded to pedestrians. Numerical simulations with biofidelic pedestrian models can be used to efficiently assess the risk to injury in pedestrian-vehicle impacts and to optimize the pedestrian protection in the early stages of the vehicle design process at relatively low costs. The goal of this study was to develop and validate a scaleable mid-size male pedestrian model. The model parameters were derived from published data and a large range of impactor tests. The biofidelity of the model has been verified using a range of full pedestrian-vehicle impact tests with a large range in body sizes (16 male, 2 female, height 160-192 cm, weight 53.5-90 kg). The simulation results were objectively correlated to the experimental data. Overall, the model predicted the measured response well. In particular the head kinematics were accurately predicted, indicated by global correlation scores over 90 %. The correlation score for the bumper forces and accelerations of various body parts was lower (47-64 %), which was largely attributed to the limited information available on the vehicle contact characteristics (stiffness, damping, deformation). Also, the effects of the large range in published leg fracture tolerances on the predicted risk to leg fracture by the pedestrian model were analyzed in detail. The validated mid-size male model was scaled to a range of body sizes, including children and females.

In current Finite Element (FE) head models, brain tissue is commonly assumed to display linear viscoelastic material behaviour. However, brain tissue behaves like a non-linear viscoelastic solid for shear strains above 1%. The main objective of this study was to study the effect of non-linear material behaviour on the predicted brain response. We used a non-linear viscoelastic constitutive model, developed on the basis of experimental shear data presented elsewere. First we tested the numerical implementation of the constitutive model by simulating the response of a silicone gel (Sylgard 572 A&B) filled cylindrical cup, subjected to a transient rotational acceleration. The experimental results could be reproduced within 9%. Subsequently, the effect of non-linear material modelling on computed brain response was investigated in an existing three-dimensional head model subjected to an eccentric rotation. At the applied external load strains in the brain were approximately ten times larger than was expected on the basis of published data. This is probably caused by the values of the shear moduli applied in the model. These are at least a factor of ten lower than the ones used in head models in literature but comparable to material data in recent literature. Non-linear material behaviour was found to influence the levels of predicted strains (+20%) and stresses (-11%) but not their temporal and spatial distribution. The pressure response was independent of non-linear material behaviour. In fact it could be predicted by the equilibrium of momentum, and thus it is independent of the choice of the brain constitutive model.

The large strain dynamic behaviour of brain tissue and silicone gel, a brain substitute material used in mechanical head models, was compared. The non-linear shear strain behaviour was characterised using stress relaxation experiments. Brain tissue showed significant shear softening for strains above 1% (approximately 30% softening for shear strains up to 20%) while the time relaxation behaviour was nearly strain independent. Silicone gel behaved as a linear viscoelastic solid for all strains tested (up to 50%) and frequencies up to 461 Hz. As a result, the large strain time dependent behaviour of both materials could be derived for frequencies up to 1000 Hz from small strain oscillatory experiments and application of Time Temperature Superpositioning. It was concluded that silicone gel material parameters are in the same range as those of brain tissue. Nevertheless the brain tissue response will not be captured exactly due to increased viscous damping at high frequencies and the absence of shear softening in the silicone gel. For trend studies and benchmarking of numerical models the gel can be a good model material.