The Contribution of Pre-impact Posture on Restrained Occupant Finite Element Model Response in Frontal Impact

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.     

Experimental investigation of the effect of occupant characteristics on contemporary seat belt payout behavior in frontal impacts

Objective: The goal of this study was to investigate the influence of the occupant characteristics on seat belt force vs. payout behavior based on experiment data from different configurations in frontal impacts.

Methods: The data set reviewed consists of 58 frontal sled tests using several anthropomorphic test devices (ATDs) and postmortem human subjects (PMHS), restrained by different belt systems (standard belt, SB; force-limiting belt, FLB) at 2 impact severities (48 and 29 km/h). The seat belt behavior was characterized in terms of the shoulder belt force vs. belt payout behavior. A univariate linear regression was used to assess the factor significance of the occupant body mass or stature on the peak tension force and gross belt payout.

Results: With the SB, the seat belt behavior obtained by the ATDs exhibited similar force slopes regardless of the occupant size and impact severities, whereas those obtained by the PMHS were varied. Under the 48 km/h impact, the peak tension force and gross belt payout obtained by ATDs was highly correlated to the occupant stature (P =.03, P =.02) and body mass (P =.05, P =.04), though no statistical difference with the stature or body mass were noticed for the PMHS (peak force: P =.09, P =.42; gross payout: P =.40, P =.48). With the FLB under the 48 km/h impact, highly linear relationships were noticed between the occupant body mass and the peak tension force (R² = 0.9782) and between the gross payout and stature (R² = 0.9232) regardless of the occupant types.

Conclusions: The analysis indicated that the PMHS characteristics showed a significant influence on the belt response, whereas the belt response obtained with the ATDs was more reproducible. The potential cause included the occupant anthropometry, body mass distribution, and relative motion among body segments specific to the population variance. This study provided a primary data source to understand the biomechanical interaction of the occupant with the restraint system. Further research is necessary to consider these effects in the computational studies and optimized design of the restraint system in a more realistic manner.     

Measuring the environmental performance of IPPC industry: I. Devising a quantitative science-based and policy-weighted Environmental Emissions Index

This paper describes the derivation of an Environmental Emissions Index (EEI) intended to quantify the environmental performance of Integrated Pollution Prevention and Control (IPPC) installations and sectors. Characterisation and normalisation methods used in lifecycle analyses were applied to 20 routinely reported emissions parameters, pertaining to six environmental impact categories. Distance to policy targets for relevant emissions were used to weight impact categories, and link the EEI to policy priorities. Ireland and the EU15 were considered as scales of context. The European Pollutant Emission Register was a convenient source of normalisation data, but restricted the context of the EEI to industrial emissions, and distorted outputs. Using national and EU15 total loading estimates for normalisation resulted in an EEI that better reflected the relative contribution of reported emissions towards overall environmental pressures. Using Ireland's pharmaceutical sector as a case study indicated that weighting factors, and the toxicity range of NMVOC emissions, were the largest sources of EEI uncertainty. Through the integration of inventory data, scientific characterisation, and policy targets, the EEI translates reported emissions data from IPPC installations and sectors into a benchmark of environmental performance. It may be regarded as an evolving tool of potential utility to regulators and policy makers.