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An understanding of stiffness characteristics of different body regions, such as thorax, abdomen and pelvis of ES-2re and SID-IIs dummies under controlled laboratory test conditions is essential for development of both compatible performance targets for countermeasures and occupant protection strategies to meet the recently updated FMVSS214, LINCAP and IIHS Dynamic Side Impact Test requirements. The primary purpose of this study is to determine the transfer functions between the ES-2re and SID-IIs dummies for different body regions under identical test conditions using flat rigid wall sled tests. The experimental set-up consists of a flat rigid wall with five instrumented load-wall plates aligned with dummy’s shoulder, thorax, abdomen, pelvis and femur/knee impacting a stationary dummy seated on a rigid low friction seat at a pre-determined velocity.

The main purpose of this study was to determine the impact responses of the different body regions (shoulder, thorax, abdomen and pelvis/leg) of the ES-2re and SID-IIs dummies using rigid wall impacts under different initial test conditions. The experimental set-up consisted of a flat rigid wall with five instrumented load-wall plates aligned with dummy’s shoulder, thorax, abdomen, pelvis and knee impacting a stationary dummy seated on a rigid seat at a pre-determined velocity. The relative location and orientation of the load-wall plates was adjusted relative to the body regions of the ES-2re and SID-IIs dummies respectively.

The main purpose of this study was to determine the impact responses of the different body regions (shoulder, thorax, abdomen and pelvis/leg) of the ES-2re and SID-IIs dummies using rigid wall impacts under different initial test conditions. The experimental set-up consisted of a flat rigid wall with five instrumented load-wall plates aligned with dummy’s shoulder, thorax, abdomen, pelvis and knee impacting a stationary dummy seated on a rigid seat at a pre-determined velocity. The relative location and orientation of the load-wall plates was adjusted relative to the body regions of the ES-2re and SID-IIs dummies respectively.

Computational human body models, especially detailed finite element models are suitable for investigation of human body kinematic responses and injury mechanism. A real-world lateral vehicle-tree impact accident was reconstructed by using finite element method according to the accident description in the CIREN database. At first, a baseline vehicle FE model was modified and validated according to the NCAP lateral impact test. The interaction between the car and the tree in the accident was simulated using LS-Dyna software. Parameters that affect the simulation results, such as the initial pre-crash speed, impact direction, and the initial impact location on the vehicle, were analyzed. The parameters were determined by matching the simulated vehicle body deformations and kinematics to the accident reports.

Previously, a 10-year-old (YO) pediatric thorax finite element model (FEM) was developed and verified against child chest stiffness data measured from clinical cardiopulmonary resuscitation (CPR). However, the CPR experiments were performed at relatively low speeds, with a maximum loading rate of 250 mm/s. Studies showed that the biomechanical responses of human thorax exhibited rate sensitive characteristics. As such, the studies of dynamic responses of the pediatric thorax FEM are needed. Experimental pediatric cadaver data in frontal pendulum impacts and diagonal belt dynamic loading tests were used for dynamic validation. Thoracic force-deflection curves between test and simulation were compared. Strains predicted by the FEM and the injuries observed in the cadaver tests were also compared for injury assessment and analysis. This study helped to further improve the 10 YO pediatric thorax FEM.

As early as the 1950's, Gurdjian and colleagues (Gurdjian et al., 1955) observed that brain injuries could occur by direct pressure loading without any global head accelerations. This pressure-induced injury mechanism was "forgotten" for some time and is being rekindled due to the many mild traumatic brain injuries attributed to blast overpressure. The aim of the current study was to develop a finite element (FE) model to predict the biomechanical response of rat brain under a shock tube environment. The rat head model, including more than 530,000 hexahedral elements with a typical element size of 100 to 300 microns was developed based on a previous rat brain model for simulating a blunt controlled cortical impact. An FE model, which represents gas flow in a 0.305-m diameter shock tube, was formulated to provide input (incident) blast overpressures to the rat model. It used an Eulerian approach and the predicted pressures were verified with experimental data.

A total of eight low-speed, rear-end impact tests using two Post Mortem Human Subjects (PMHS) in a seated posture are reported. These tests were conducted using a HYGE-style mini-sled. Two test conditions were employed: 8 kph without a headrestraint or 16 kph with a headrestraint. Upper-body kinematics were captured for each test using a combination of transducers and high-speed video. A 3-2-2-2-accelerometer package was used to measure the generalized 3D kinematics of both the head and pelvis. An angular rate sensor and two single-axis linear accelerometers were used to measure angular speed, angular acceleration, and linear acceleration of T1 in the sagittal plane. Two high-speed video cameras were used to track targets rigidly attached to the head, T1, and pelvis. The cervical spine kinematics were captured with a high-speed, biplane x-ray system by tracking radiopaque markers implanted into each cervical vertebra.

The seatbelt system, originally designed for protecting occupants in frontal crashes, has been reported to be inadequate for preventing occupant head-to-roof contact during rollover crashes. To improve the effectiveness of seatbelt systems in rollovers, in this study, we reviewed previous literature and proposed vertical head excursion corridors during static inversion and dynamic rolling tests for human and Hybrid III dummy. Finite element models of a human and a dummy were integrated with restraint system models and validated against the proposed test corridors. Simulations were then conducted to investigate the effects of varying design factors for a three-point seatbelt on vertical head excursions of the occupant during rollovers. It was found that there were two contributing parts of vertical head excursions during dynamic rolling conditions.

Digital human modeling (DHM) progress worldwide will be much faster and cohesive if the diverse community now developing simulations has a global blueprint for DHM, and is able to work together efficiently. DHM developers and users can save time by building on each other's work. This paper highlights a panel discussion on DHM goals and strategic plans for the next decade to begin formulating the international blueprint. Four subjects are chosen as the starting points: (1) moving DHM into the public safety and internet arenas, (2) role of DHM in computer assisted surgery and automotive safety, (3) DHM in defense applications, and (4) DHM to improve workplace ergonomics.

Posture and external loads such as hand forces have a dominant effect on ergonomic analysis outcomes. Yet, current digital human modeling tools used for proactive ergonomics analysis lack validated models for predicting postures for standing hand-force exertions. To address this need, the effects of hand magnitude and direction on whole-body posture for standing static hand-force exertion tasks were quantified in a motion-capture study of 19 men and women with widely varying body size. The objective of this work was to identify postural behaviors that might be incorporated into a posture-prediction algorithm for standing hand-force tasks. Analysis of one-handed exertions indicates that, when possible, people tend to align their bodies with the direction of force application, converting potential cross-body exertions into sagittal plane exertions. With respect to the hand-force plane, pelvis position is consistent with a postural objective of reducing rotational trunk torques.

The pia-arachnoid complex (PAC) covering the brain plays an important role in the mechanical response of the brain due to impact or inertial loading. The mechanical properties of the bovine PAC under tensile loading have been characterized previously. However, the transverse properties of this structure, such as shear and normal traction which are equally important to understanding the skull/brain interaction under traumatic loading, have not been investigated. These material properties are essential information needed to adequately define the material model of the PAC in a finite element (FE) model of human brain. The purpose of this study was to determine, experimentally, the material properties of the PAC under normal traction loading. PAC specimens were obtained from freshly slaughtered bovine subjects from various locations.

High-speed biplane x-ray and neutral density targets were used to examine brain displacement and deformation during impact. Relative motion, maximum principal strain, maximum shear strain, and intracranial pressure were measured in thirty-five impacts using eight human cadaver head and neck specimens. The effect of a helmet was evaluated. During impact, local brain tissue tends to keep its position and shape with respect to the inertial frame, resulting in relative motion between the brain and skull and deformation of the brain. The local brain motions tend to follow looping patterns. Similar patterns are observed for impact in different planes, with some degree of posterior-anterior and right-left symmetry. Peak coup pressure and pressure rate increase with increasing linear acceleration, but coup pressure pulse duration decreases. Peak average maximum principal strain and maximum shear are on the order of 0.09 for CFC 60 Hz data for these tests.

Accurate representation of working postures is critical for ergonomic assessments with digital human models because posture has a dominant effect on analysis outcomes. Most current digital human modeling tools require manual manipulation of the digital human to simulate force-exertion postures or rely on optimization procedures that have not been validated. Automated posture prediction based on human data would improve the accuracy and repeatability of analyses. The effects of hand force location, magnitude, and direction on whole-body posture for standing tasks were quantified in a motion-capture study of 20 men and women with widely varying body size. A statistical analysis demonstrated that postural variables critical for the assessment of body loads can be predicted from the characteristics of the worker and task.

This study characterizes the response of the human cadaver abdomen to high-speed seatbelt loading using pyrotechnic pretensioners. A test apparatus was developed to deliver symmetric loading to the abdomen using a seatbelt equipped with two low-mass load cells. Eight subjects were tested under worst-case scenario, out-of-position (OOP) conditions. A seatbelt was placed at the level of mid-umbilicus and drawn back along the sides of the specimens, which were seated upright using a fixed-back configuration. Penetration was measured by a laser, which tracked the anterior aspect of the abdomen, and by high-speed video. Additionally, aortic pressure was monitored. Three different pretensioner designs were used, referred to as system A, system B and system C. The B and C systems employed single pretensioners. The A system consisted of two B system pretensioners. The vascular systems of the subjects were perfused.

The pia-arachnoid complex (PAC) covering the brain plays an important role in the mechanical response of the brain due to impact or inertial loading. However, the mechanical properties of the pia-arachnoid complex and its influence on the overall response of the brain have not been well characterized. Consequently, finite element (FE) brain models have tended to oversimplify the response of the pia-arachnoid complex, possibly resulting in a loss of accuracy in the model predictions. The aim of this study was to determine, experimentally, the material properties of the pia-arachnoid complex under quasi-static and dynamic loading conditions. Specimens of the pia-arachnoid complex were obtained from the parietal and temporal regions of freshly slaughtered bovine subjects with the specimen orientation recorded. Single-stroke, uniaxial quasi-static and dynamic tensile experiments were performed at strain-rates of 0.05, 0.5, 5 and 100 s-1 (n = 10 for each strain rate group).

Complete validation of any finite element (FE) model of the human brain is very difficult due to the lack of adequate experimental data. However, more animal brain injury data, especially rat data, obtained under well-defined mechanical loading conditions, are available to advance the understanding of the mechanisms of traumatic brain injury. Unfortunately, internal response of the brain in these experimental studies could not be measured. The aim of this study was to develop a detailed FE model of the rat brain for the prediction of intracranial responses due to different impact scenarios. Model results were used to elucidate possible brain injury mechanisms. An FE model, consisting of more than 250,000 hexahedral elements with a typical element size of 100 to 300 microns, was developed to represent the brain of a rat. The model was first validated locally against peak brain deformation data obtained from nine unique dynamic cortical deformation (vacuum) tests.

Numerical analyses frequently accompany experimental investigations that study injury biomechanics and improvements in automotive safety. Limited by computational speed, earlier mathematical models tended to simplify the system under study so that a set of differential equations could be written and solved. Advances in computing technology and analysis software have enabled the development of many sophisticated models that have the potential to provide a more comprehensive understanding of human impact response, injury mechanisms, and tolerance. In this article, 50 years of publications on numerical modeling published in the Stapp Car Crash Conference Proceedings and Journal were reviewed. These models were based on: (a) author-developed equations and software, (b) public and commercially available programs to solve rigid body dynamic models (such as MVMA2D, CAL3D or ATB, and MADYMO), and (c) finite element models.

The potential of digital human modeling to improve the design of products and workspaces has been limited by the time-consuming manual manipulation of figures that is required to perform simulations. Moreover, the inaccuracies in posture and motion that result from manual procedures compromise the fidelity of the resulting analyses. This paper presents a new approach to the control of human figure models and the analysis of simulated tasks. The new methods are embodied in an algorithmic framework developed in the Human Motion Simulation (HUMOSIM) laboratory at the University of Michigan. The framework consists of an interconnected, hierarchical set of posture and motion modules that control aspects of human behavior, such as gaze or upper-extremity motion. Analysis modules, addressing issues such as shoulder stress and balance, are integrated into the framework.

Cyclical stepping (gait) has been studied extensively. Some of these results are reflected in the straight and curved path step-following algorithms in commercial digital human modeling (DHM) implementations. With the aid of these algorithms, DHM users define start, intermediate, and end path points and the software generates a walking-like motion along the path. Most of these algorithms have substantial limitations, among them that the figures exhibit “foot skate,” meaning that the kinematic constraint of foot contact with the ground is not respected. Turning is accomplished by pivoting the entire figure, rather than through realistic lower-extremity motions. The simulation of the non-cyclical stepping motions accompanying manual material handling pickup and delivery tasks requires manual manikin manipulation. This paper proposes a paradigm for the simulation of stepping behavior in digital human models based on a model of foot placements and motions.

There has been much debate over “whiplash”-induced temporomandibular joint (TMJ) dysfunction following low-speed, rear-end automobile collisions. While several authors have reported TMJ injury based on case studies post collision, there has been little biomechanical evidence showing that rear-end impact was the primary cause of such injury. The purpose of this study was to measure the relative translation between the upper and lower incisors in cadavers subjected to low-speed, rear-end impacts. High-speed x-ray images used for this analysis were reported previously for the analysis of cadaveric cervical spine kinematics during low-speed, rear-end impacts. The cadavers were positioned at various seatback angles and body postures, producing an overall picture of various seating scenarios.