Search

Objectives: The objective of this study was to determine the potential chest injury benefits and influence on occupant kinematics of a belt system with independent control of the shoulder and lap portions.Methods: This article investigates the kinematics and dynamics of human surrogates in 35 km/h impacts with 2 different restraints: a pretensioning (PT), force-limiting (FL) seat belt, a reference belt system, and a concept design with a split buckle consisting (SB) of 2 separate shoulder and lap belt bands. The study combines mathematical simulations with the THOR dummy and THUMS human body model, and mechanical tests with the THOR dummy and 2 postmortem human surrogate (PMHS) tests of similar age (39 and 42 years) and anthropometry (62 kg, 181 cm vs. 60 kg, 171.5 cm). The test setup consisted of a rigid metallic frame representing a standard seating position of a right front passenger. The THOR dummy model predictions were compared to the mechanical THOR dummy test results. The THUMS-predicted number of fractured ribs were compared to the number of fractured ribs in the PMHS.Results: THOR sled tests showed that the SB seat belt system decreased chest deflection significantly without increasing the forward displacement of the head. The THOR model and the THOR physical dummy predicted a 13- and 7-mm reduction in peak chest deflection, respectively. Peak diagonal belt force in the mechanical test with the reference belt was 5,582 N and the predicted force was 4,770 N. The THOR model also predicted lower belt forces with the SB system than observed in the tests (5,606 vs. 6,085 N). THUMS predicted somewhat increased head displacement for the SB system compared to the reference system. Peak diagonal force with the reference belt was 4,000 N and for the SB system it was 5,200 N. The PMHS test with the SB belt resulted in improved kinematics and a smaller number of rib fractures (2 vs. 5 fractures) compared to the reference belt.Conclusion: Concepts for a belt system that can reduce the load on the chest of the occupant in a crash and thereby reduce the number of injured occupants, in particular the elderly, was proposed. [ABSTRACT FROM AUTHOR]

Objective: The objective of the current study was to perform a parametric study with different impact objects, impact locations, and impact speeds by analyzing occupant kinematics and injury estimations using a whole-vehicle and whole-body finite element-human body model (FE-HBM). To confirm the HBM responses, the biofidelity of the model was validated using data from postmortem human surrogate (PMHS) sled tests.Methods: The biofidelity of the model was validated using data from sled experiments and correlational analysis (CORA). Full-scale simulations were performed using a restrained Global Human Body Model Consortium (GHBMC) model seated on a 2001 Ford Taurus model using a far-side lateral impact condition. The driver seat was placed in the center position to represent a nominal initial impact condition. A 3-point seat belt with pretensioner and retractor was used to restrain the GHBMC model. A parametric study was performed using 12 simulations by varying impact locations, impacting object, and impact speed using the full-scale models. In all 12 simulations, the principal direction of force (PDOF) was selected as 90°. The impacting objects were a 10-in.-diameter rigid vertical pole and a movable deformable barrier. The impact location of the pole was at the C-pillar in the first case, at the B-pillar in the second case, and, finally, at the A-pillar in the third case. The vehicle and the GHBMC models were defined an initial velocity of 35 km/h (high speed) and 15 km/h (low speed). Excursion of the head center of gravity (CG), T6, and pelvis were measured from the simulations. In addition, injury risk estimations were performed on head, rib cage, lungs, kidneys, liver, spleen, and pelvis.Results: The average CORA rating was 0.7. The shoulder belt slipped in B- and C-pillar impacts but somewhat engaged in the A-pillar case. In the B-pillar case, the head contacted the intruding struck-side structures, indicating higher risk of injury. Occupant kinematics depended on interaction with restraints and internal structures-especially the passenger seat. Risk analysis indicated that the head had the highest risk of sustaining an injury in the B-pillar case compared to the other 2 cases. Higher lap belt load (3.4 kN) may correspond to the Abbreviated Injury Scale (AIS) 2 pelvic injury observed in the B-pillar case. Risk of injury to other soft anatomical structures varied with impact configuration and restraint interaction.Conclusion: The average CORA rating was 0.7. In general, the results indicated that the high-speed impacts against the pole resulted in severe injuries, higher excursions followed by low-speed pole, high-speed moving deformable barrier (MDB), and low-speed MDB impacts. The vehicle and occupant kinematics varied with different impact setups and the latter kinematics were likely influenced by restraint effectiveness. Increased restraint engagement increased the injury risk to the corresponding anatomic structure, whereas ineffective restraint engagement increased the occupant excursion, resulting in a direct impact to the struck-side interior structures. [ABSTRACT FROM AUTHOR]

Objective: The objective of the current study was to evaluate the whole-body kinematic response of the Total Human Model for Safety (THUMS) occupant model in controlled laboratory rollover tests by comparing the model response to postmortem human surrogate (PMHS) kinematic response targets published in 2014.Methods: A computational model of the parametric vehicle buck environment was developed and the AM50 THUMS occupant model (Ver 4.01) was subjected to a pure dynamic roll at 360°/s in trailing-side front-row seating position. A baseline configuration was defined by a baseline posture representing the average of all PMHS postures, with a friction coefficient of 0.4 for the belt and 0.6 for the seat. To encompass challenges in controlling boundary conditions from the PMHS tests and ensure the robustness of the model evaluation, a total of 12 simulations were performed to investigate the following: 1. The effect of initial posture by adding 3 additional postures representing PMHS extremes. 2. The effect of belt tension by varying tension from the nominal vehicle retractor belt tension of 5 N to the 35 N belt tension used in the PMHS tests. 3. The effect of friction between the environment (belt, seat) and THUMS. Trajectories (head, T1, T4, T10, L1, and sacrum), spinal segment rotations (head-to-T1, T1-to-T4, T4-to-T10, T10-to-L1, and L1-to-sacrum) relative to the rollover buck and spinal segment elongation/compression calculated from the simulations were compared to PMHS corridors using a correlation method (CORA).Results: THUMS baseline response showed lower correlation (overall CORA score = 0.63) with the PMHS response in rollover compared to other crash modes. THUMS and PMHS demonstrated similar kinematic responses in the longitudinal axis and vertical axis but significantly different lateral excursion relative to the seat. In addition, no spinal elongation was observed for THUMS compared to the PMHS. The posture, pretension, and belt frictions were found to alter model kinematics, especially on THUMS lateral axis motion. The posture was judged to be the most sensitive parameter evaluated because a change of 30 mm in the lateral axis results in up to an 80 mm of change in observed displacement.Conclusions: Though the model response in the lateral axis is significantly different than that of the PMHS, it is unclear whether this difference is the result of extrinsic factors (posture, pretension, and friction), where exact values in experiment are unknown or by model intrinsic factors (e.g., spine stiffness). These differences in occupant kinematics could potentially subject the PMHS and THUMS to very different loading conditions under roof impact in rollover crashes: different occupant posture and different roof impact location. Therefore, different injury mechanisms and severity might be predicted by the current model relative to the PMHS. Consequently, though the information provided in the current study could be useful for improving model biofidelity for rollover crashes, additional studies are required to properly solve this issue. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study was to compare and evaluate the difference in head kinematics between the TNO and THUMS models in pedestrian accident situations.Methods: The TNO pedestrian model (version 7.4.2) and the THUMS pedestrian model (version 1.4) were compared in one experiment setup and 14 different accident scenarios where the vehicle velocity, leg posture, pedestrian velocity, and pedestrian's initial orientation were altered. In all simulations, the pedestrian model was impacted by a sedan. The head trajectory, head rotation, and head impact velocity were compared, as was the trend when various different parameters were altered.Results: The multibody model had a larger head wrap-around distance for all accident scenarios. The maximum differences of the head's center of gravity between the models in the global x-, y-, and z-directions at impact were 13.9, 5.8, and 5.6 cm, respectively. The maximum difference between the models in head rotation around the head's inferior-superior axis at head impact was 36°. The head impact velocity differed up to 2.4 m/s between the models. The 2 models showed similar trends for the head trajectory when the various parameters were altered.Conclusions: There are differences in kinematics between the THUMS and TNO pedestrian models. However, these model differences are of the same magnitude as those induced by other uncertainties in the accident reconstructions, such as initial leg posture and pedestrian velocity. [ABSTRACT FROM AUTHOR]

Objective: Driver monitoring systems (DMS) are the next generation of vehicle safety technology. Broadly, these refer to the embedded, aftermarket wearable or vehicle-mounted devices that collect observable information about the operator to make real-time assessment of their capacity to perform the driving task. Integrating biobehavioral monitoring (primarily ocular metrics) with driving performance assessments, these systems function to infer driver state in real time to identify operator conditions that negatively affect driving (such as fatigue, inattention, or distraction).Method: We review available methods used to infer driver state, as referenced against accepted models for optimal performance. Modeling our observations on deviation from predetermined performance thresholds used to trigger graded safety alerts, we suggest that many psychoactive substances produce alterations to biobehavioral processes including attentional and motor control, which affect performance indices in a manner already arguably captured by these technologies.Results: Using these existing frameworks, there is considerable potential to similarly catalogue the effect of many common intoxicants known to negatively affect driving ability. This will provide safety-relevant and practical biological models for the development of next-generation multimodal DMS that integrate ocular and physiological variables sensitive to the effects of common and emergent psychoactive substances.Conclusion: These devices have tangible potential application across all areas of transportation, including aviation, rail, and all commercial and private vehicle systems. [ABSTRACT FROM AUTHOR]

Objective: Analyses of crash data have shown that older, obese, and/or female occupants have a higher risk of injury in frontal crashes compared to the rest of the population. The objective of this study was to use parametric finite element (FE) human models to assess the increased injury risks and identify safety concerns for these vulnerable populations. Methods: We sampled 100 occupants based on age, sex, stature, and body mass index (BMI) to span a wide range of the U.S. adult population. The target anatomical geometry for each of the 100 models was predicted by the statistical geometry models for the rib cage, pelvis, femur, tibia, and external body surface developed previously. A regional landmark-based mesh morphing method was used to morph the Global Human Body Models Consortium (GHBMC) M50-OS model into the target geometries. The morphed human models were then positioned in a validated generic vehicle driver compartment model using a statistical driving posture model. Frontal crash simulations based on U.S. New Car Assessment Program (U.S. NCAP) were conducted. Body region injury risks were calculated based on the risk curves used in the US NCAP, except that scaling was used for the neck, chest, and knee-thigh-hip injury risk curves based on the sizes of the bony structures in the corresponding body regions. Age effects were also considered for predicting chest injury risk. Results: The simulations demonstrated that driver stature and body shape affect occupant interactions with the restraints and consequently affect occupant kinematics and injury risks in severe frontal crashes. U-shaped relations between occupant stature/weight and head injury risk were observed. Chest injury risk was strongly affected by age and sex, with older female occupants having the highest risk. A strong correlation was also observed between BMI and knee-thigh-hip injury risk, whereas none of the occupant parameters meaningfully affected neck injury risks. Conclusions: This study is the first to use a large set of diverse FE human models to investigate the combined effects of age, sex, stature, and BMI on injury risks in frontal crashes. The study demonstrated that parametric human models can effectively predict the injury trends for the population and may now be used to optimize restraint systems for people who are not similar in size and shape to the available anthropomorphic test devices (ATDs). New restraints that adapt to occupant age, sex, stature, and body shape may improve crash safety for all occupants. [ABSTRACT FROM AUTHOR]

Objective: Evaluating the biofidelity of pedestrian finite element models (PFEM) using postmortem human subjects (PMHS) is a challenge because differences in anthropometry between PMHS and PFEM could limit a model's capability to accurately capture cadaveric responses. Geometrical personalization via morphing can modify the PFEM geometry to match the specific PMHS anthropometry, which could alleviate this issue. In this study, the Total Human Model for Safety (THUMS) PFEM (Ver 4.01) was compared to the cadaveric response in vehicle-pedestrian impacts using geometrically personalized models.Methods: The AM50 THUMS PFEM was used as the baseline model, and 2 morphed PFEM were created to the anthropometric specifications of 2 obese PMHS used in a previous pedestrian impact study with a mid-size sedan. The same measurements as those obtained during the PMHS tests were calculated from the simulations (kinematics, accelerations, strains), and biofidelity metrics based on signals correlation (correlation and analysis, CORA) were established to compare the response of the models to the experiments. Injury outcomes were predicted deterministically (through strain-based threshold) and probabilistically (with injury risk functions) and compared with the injuries reported in the necropsy.Results: The baseline model could not accurately capture all aspects of the PMHS kinematics, strain, and injury risks, whereas the morphed models reproduced biofidelic response in terms of trajectory (CORA score = 0.927 ± 0.092), velocities (0.975 ± 0.027), accelerations (0.862 ± 0.072), and strains (0.707 ± 0.143). The personalized THUMS models also generally predicted injuries consistent with those identified during posttest autopsy.Conclusions: The study highlights the need to control for pedestrian anthropometry when validating pedestrian human body models against PMHS data. The information provided in the current study could be useful for improving model biofidelity for vehicle-pedestrian impact scenarios. [ABSTRACT FROM AUTHOR]

Objective: A novel anthropomorphic test device (ATD) representative of the 50th percentile male soldier is being developed to predict injuries to a vehicle occupant during an underbody blast (UBB). The main objective of this study was to develop and validate a finite element (FE) model of the ATD lower limb outfitted with a military combat boot and to insert the validated lower limb into a model of the full ATD and simulate vertical loading experiments.Methods: A Belleville desert combat boot model was assigned contacts and material properties based on previous experiments. The boot model was fit to a previously developed model of the barefoot ATD. Validation was performed through 6 matched pair component tests conducted on the Vertically Accelerated Loads Transfer System (VALTS). The load transfer capabilities of the FE model were assessed along with the force-mitigating properties of the boot. The booted lower limb subassembly was then incorporated into a whole-body model of the ATD. Two whole-body VALTS experiments were simulated to evaluate lower limb performance in the whole body.Results: The lower limb model accurately predicted axial loads measured at heel, tibia, and knee load cells during matched pair component tests. Forces in booted simulations were compared to unbooted simulations and an amount of mitigation similar to that of experiments was observed. In a whole-body loading environment, the model kinematics match those recorded in experiments. The shape and magnitude of experimental force-time curves were accurately predicted by the model. Correlation between the experiments and simulations was backed up by high objective rating scores for all experiments.Conclusion: The booted lower limb model is accurate in its ability to articulate and transfer loads similar to the physical dummy in simulated underbody loading experiments. The performance of the model leads to the recommendation to use it appropriately as an alternative to costly ATD experiments. [ABSTRACT FROM AUTHOR]

Objective: The goal of this study was to evaluate the biofidelity of the Total Human Model for Safety (THUMS; Ver. 4.01) pedestrian finite element models (PFEM) in a whole-body pedestrian impact condition using a well-characterized generic pedestrian buck model.Methods: The biofidelity of THUMS PFEM was evaluated with respect to data from 3 full-scale postmortem human subject (PMHS) pedestrian impact tests, in which a pedestrian buck laterally struck the subjects using a pedestrian buck at 40 km/h. The pedestrian model was scaled to match the anthropometry of the target subjects and then positioned to match the pre-impact postures of the target subjects based on the 3-dimensional motion tracking data obtained during the experiments. An objective rating method was employed to quantitatively evaluate the correlation between the responses of the models and the PMHS. Injuries in the models were predicted both probabilistically and deterministically using empirical injury risk functions and strain measures, respectively, and compared with those of the target PMHS.Results: In general, the model exhibited biofidelic kinematic responses (in the Y-Z plane) regarding trajectories (International Organization for Standardization [ISO] ratings: Y = 0.90 ± 0.11, Z = 0.89 ± 0.09), linear resultant velocities (ISO ratings: 0.83 ± 0.07), accelerations (ISO ratings: Y = 0.58 ± 0.11, Z = 0.52 ± 0.12), and angular velocities (ISO ratings: X = 0.48 ± 0.13) but exhibited stiffer leg responses and delayed head responses compared to those of the PMHS. This indicates potential biofidelity issues with the PFEM for regions below the knee and in the neck. The model also demonstrated comparable reaction forces at the buck front-end regions to those from the PMHS tests. The PFEM generally predicted the injuries that the PMHS sustained but overestimated injuries in the ankle and leg regions.Conclusions: Based on the data considered, the THUMS PFEM was considered to be biofidelic for this pedestrian impact condition and vehicle. Given the capability of the model to reproduce biomechanical responses, it shows potential as a valuable tool for developing novel pedestrian safety systems. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study is to use a validated finite element model of the human body and a certified model of an anthropomorphic test dummy (ATD) to evaluate the effect of simulated precrash braking on driver kinematics, restraint loads, body loads, and computed injury criteria in 4 commonly injured body regions.Methods: The Global Human Body Models Consortium (GHBMC) 50th percentile male occupant (M50-O) and the Humanetics Hybrid III 50th percentile models were gravity settled in the driver position of a generic interior equipped with an advanced 3-point belt and driver airbag. Fifteen simulations per model (30 total) were conducted, including 4 scenarios at 3 severity levels: median, severe, and the U.S. New Car Assessment Program (U.S.-NCAP) and 3 extra per model with high-intensity braking. The 4 scenarios were no precollision system (no PCS), forward collision warning (FCW), FCW with prebraking assist (FCW+PBA), and FCW and PBA with autonomous precrash braking (FCW + PBA + PB). The baseline ΔV was 17, 34, and 56.4 kph for median, severe, and U.S.-NCAP scenarios, respectively, and were based on crash reconstructions from NASS/CDS. Pulses were then developed based on the assumed precrash systems equipped. Restraint properties and the generic pulse used were based on literature.Results: In median crash severity cases, little to no risk (<10% risk for Abbreviated injury Scale [AIS] 3+) was found for all injury measures for both models. In the severe set of cases, little to no risk for AIS 3+ injury was also found for all injury measures. In NCAP cases, highest risk was typically found with No PCS and lowest with FCW + PBA + PB. In the higher intensity braking cases (1.0-1.4 g), head injury criterion (HIC), brain injury criterion (BrIC), and chest deflection injury measures increased with increased braking intensity. All other measures for these cases tended to decrease. The ATD also predicted and trended similar to the human body models predictions for both the median, severe, and NCAP cases. Forward excursion for both models decreased across median, severe, and NCAP cases and diverged from each other in cases above 1.0 g of braking intensity.Conclusions: The addition of precrash systems simulated through reduced precrash speeds caused reductions in some injury criteria, whereas others (chest deflection, HIC, and BrIC) increased due to a modified occupant position. The human model and ATD models trended similarly in nearly all cases with greater risk indicated in the human model. These results suggest the need for integrated safety systems that have restraints that optimize the occupant's position during precrash braking and prior to impact. [ABSTRACT FROM AUTHOR]

Objectives: Due to limitations of classic imaging approaches, the internal response of abdominal organs is difficult to observe during an impact. Within the context of impact biomechanics for the protection of the occupant of transports, this could be an issue for human model validation and injury prediction.Methods: In the current study, a previously developed technique (ultrafast ultrasound imaging) was used as the basis to develop a protocol to observe the internal response of abdominal organs in situ at high imaging rates. The protocol was applied to 3 postmortem human surrogates to observe the liver and the colon during impacts delivered to the abdomen.Results: The results show the sensitivity of the liver motion to the impact location. Compression of the colon was also quantified and compared to the abdominal compression.Conclusions: These results illustrate the feasibility of the approach. Further tests and comparisons with simulations are under preparation. [ABSTRACT FROM AUTHOR]

Introduction: The objective of this study was to reconstruct 4 real-world motor vehicle crashes (MVCs), 2 with lumbar vertebral fractures and 2 without vertebral fractures in order to elucidate the MVC and/or restraint variables that increase this injury risk.Methods: A finite element (FE) simplified vehicle model (SVM) was used in conjunction with a previously developed semi-automated tuning method to arrive at 4 SVMs that were tuned to mimic frontal crash responses of a 2006 Chevrolet Cobalt, 2012 Ford Escape, 2007 Hummer H3, and 2002 Chevrolet Cavalier. Real-world crashes in the first 2 vehicles resulted in lumbar vertebrae fractures, whereas the latter 2 did not. Once each SVM was tuned to its corresponding vehicle, the Total HUman Model for Safety (THUMS) v4.01 was positioned in 120 precrash configurations in each SVM by varying 5 parameters using a Latin hypercube design (LHD) of experiments: seat track position, seatback angle, steering column angle, steering column telescoping position, and d-ring height. For each case, the event data recorder (EDR) crash pulse was used to apply kinematic boundary conditions to the model. By analyzing cross-sectional vertebral loads, vertebral bending moments, and maximum principal strain and stress in both cortical and trabecular bone, injury metric response as a function of posture and restraint parameters was computed.Results: Tuning the SVM to specific vehicle models produced close matches between the simulated and experimental crash test responses for head, T6, and pelvis resultant acceleration; left and right femur loads; and shoulder and lap belt loads. Though vertebral load in the THUMS simulations was highly similar between injury cases and noninjury cases, the amount of bending moment was much higher for the injury cases. Seatback angle had a large effect on the maximum compressive load and bending moment in the lumbar spine, indicating the upward tilt of the seat pan in conjunction with precrash positioning may increase the likelihood of suffering lumbar injury even in frontal, planar MVCs.Conclusion: In conclusion, precrash positioning has a large effect on lumbar injury metrics. The lack of lumbar injury criteria in regulatory crash tests may have led to inadvertent design of seat pans that work to apply axial force to the spinal column during frontal crashes. [ABSTRACT FROM AUTHOR]

Objective: The significant computational resources required to execute detailed human body finite-element models has motivated the development of faster running, simplified models (e.g., GHBMC M50-OS). Previous studies have demonstrated the ability to modularly incorporate the validated GHBMC M50-O brain model into the simplified model (GHBMC M50-OS+B), which allows for localized analysis of the brain in a fraction of the computation time required for the detailed model. The objective of this study is to validate the head and neck kinematics of the GHBMC M50-O and M50-OS (detailed and simplified versions of the same model) against human volunteer test data in frontal and lateral loading. Furthermore, the effect of modular insertion of the detailed brain model into the M50-OS is quantified.Methods: Data from the Navy Biodynamics Laboratory (NBDL) human volunteer studies, including a 15g frontal, 8g frontal, and 7g lateral impact, were reconstructed and simulated using LS-DYNA. A five-point restraint system was used for all simulations, and initial positions of the models were matched with volunteer data using settling and positioning techniques. Both the frontal and lateral simulations were run with the M50-O, M50-OS, and M50-OS+B with active musculature for a total of nine runs.Results: Normalized run times for the various models used in this study were 8.4 min/ms for the M50-O, 0.26 min/ms for the M50-OS, and 0.97 min/ms for the M50-OS+B, a 32- and 9-fold reduction in run time, respectively. Corridors were reanalyzed for head and T1 kinematics from the NBDL studies. Qualitative evaluation of head rotational accelerations and linear resultant acceleration, as well as linear resultant T1 acceleration, showed reasonable results between all models and the experimental data. Objective evaluation of the results for head center of gravity (CG) accelerations was completed via ISO TS 18571, and indicated scores of 0.673 (M50-O), 0.638 (M50-OS), and 0.656 (M50-OS+B) for the 15g frontal impact. Scores at lower g levels yielded similar results, 0.667 (M50-O), 0.675 (M50-OS), and 0.710 (M50-OS+B) for the 8g frontal impact. The 7g lateral simulations also compared fairly with an average ISO score of 0.565 for the M50-O, 0.634 for the M50-OS, and 0.606 for the M50-OS+B. The three HBMs experienced similar head and neck motion in the frontal simulations, but the M50-O predicted significantly greater head rotation in the lateral simulation.Conclusion: The greatest departure from the detailed occupant models were noted in lateral flexion, potentially indicating the need for further study. Precise modeling of the belt system however was limited by available data. A sensitivity study of these parameters in the frontal condition showed that belt slack and muscle activation have a modest effect on the ISO score. The reduction in computation time of the M50-OS+B reduces the burden of high computational requirements when handling detailed HBMs. Future work will focus on harmonizing the lateral head response of the models and studying localized injury criteria within the brain from the M50-O and M50-OS+B. [ABSTRACT FROM AUTHOR]

Objective: Human body models have the potential to better describe the human anatomy and variability than dummies. However, data sets available to verify the human response to impact are typically limited in numbers, and they are not size or gender specific. The objective of this study was to investigate the use of model morphing methodologies within that context.Methods: In this study, a simple human model scaling methodology was developed to morph two detailed human models (Global Human Body Model Consortium models 50th male, M50, and 5th female, F05) to the dimensions of post mortem human surrogates (PMHS) used in published literature. The methodology was then successfully applied to 52 PMHS tested in 14 impact conditions loading the abdomen. The corresponding 104 simulations were compared to the responses of the PMHS and to the responses of the baseline models without scaling (28 simulations). The responses were analysed using the CORA method and peak values.Results: The results suggest that model scaling leads to an improvement of the predicted force and deflection but has more marginal effects on the predicted abdominal compressions. M50 and F05 models scaled to the same PMHS were also found to have similar external responses, but large differences were found between the two sets of models for the strain energy densities in the liver and the spleen for mid-abdomen impact simulations. These differences, which were attributed to the anatomical differences in the abdomen of the baseline models, highlight the importance of the selection of the impact condition for simulation studies, especially if the organ location is not known in the test.Conclusions: While the methodology could be further improved, it shows the feasibility of using model scaling methodologies to compare human models of different sizes and to evaluate scaling approaches within the context of human model validation. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study was to discuss the influence of the pre-impact posture to the response of a finite element human body model (HBM) in frontal impacts.Methods: This study uses previously published cadaveric tests (PMHS), which measured six realistic pre-impact postures. Seven postured models were created from the THUMS occupant model (v4.0): one matching the standard UMTRI driving posture as it was the target posture in the experiments, and six matching the measured pre-impact postures. The same measurements as those obtained during the cadaveric tests were calculated from the simulations, and biofidelity metrics based on signals correlation (CORA) were established to compare the response of the seven models to the experiments.Results: The HBM responses showed good agreement with the PMHS responses for the reaction forces (CORA = 0.80 ± 0.05) and the kinematics of the lower part of the torso but only fair correlation was found with the head, the upper spine, rib strains (CORA= 0.50 ± 0.05) and chest deflections (CORA = 0.67 ± 0.08). All models sustained rib fractures, sternal fracture and clavicle fracture. The average number of rib fractures for all the models was 5.3 ± 1.0, lower than in the experiments (10.8 ± 9.0). Variation in pre-impact posture greatly altered the time histories of the reaction forces, deflections and the rib strains, mainly in terms of time delay, but no definite improvement in HBM response or injury prediction was observed. By modifying only the posture of the HBM, the variability in the impact response was found to be equivalent to that observed in the experiments. The postured HBM sustained from 4 to 8 rib fractures, confirming that the pre-impact posture influenced the injury outcome predicted by the simulation.Conclusions: This study tries to answer an important question: what is the effect of occupant posture on kinematics and kinetics. Significant differences in kinematics observed between HBM and PMHS suggesting more coupling between the pelvis and the spine for the models which makes the model response very sensitive to any variation in the spine posture. Consequently, the findings observed for the HBM cannot be extended to PMHS. Besides, pre-impact posture should be carefully quantified during experiments and the evaluation of HBM should take into account the variation in the predicted impact response due to the variation in the model posture. [ABSTRACT FROM AUTHOR]