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Some rollover testing methodologies require specification of vehicle kinematic parameters including travel speed, vertical velocity, roll rate, and pitch angle, etc. at the initiation of vehicle to ground contact, which have been referred to as touchdown conditions. The complexity of the vehicle, as well as environmental and driving input characteristics make prediction of realistic touchdown conditions for rollover crashes, and moreover, identification of parameter sensitivities of these characteristics, is difficult and expensive without simulation tools. The goal of this study was to study the sensitivity of driver input on touchdown parameters and the risk of rollover in cases of steering-induced soil-tripped rollovers, which are the most prevalent type of rollover crashes. Knowing the range and variation of touchdown parameters and their sensitivities would help in picking realistic parameters for simulating controlled rollover tests.

Multibody human models are widely used to investigate responses of human during an automotive crash. This study aimed to validate a commercially available multibody human body model against response corridors from volunteer tests conducted by Naval BioDynamics Laboratory (NBDL). The neck model consisted of seven vertebral bodies, and two adjacent bodies were connected by three orthogonal linear springs and dampers and three orthogonal rotational springs and dampers. The stiffness and damping characteristics were scaled up or down to improve the biofidelity of the neck model against NBDL volunteer test data because those characteristics were encrypted due to confidentiality. First, sensitivity analysis was performed to find influential scaling factors among the entire set using a design of experiment.

Some rollover test methods, which impose a touchdown condition on a test vehicle, have been developed to study vehicle crashworthiness and occupant protection in rollover crashes. In ground-tripped rollover crashes, speed, steering maneuver, braking, vehicle inertial and geometric properties, topographical and road design characteristics, and soil type can all affect vehicle touchdown conditions. It is presumed that while there may be numerous possible combinations of kinematic metrics (velocity components and orientation) at touchdown, there are also numerous combinations of metrics that are not likely to occur in rollover crashes. To determine a realistic set of touchdown conditions to be used in a vehicle rollover crash test, a lateral deceleration sled-based non-destructive rollover initiation test system (RITS) with a fully programmable deceleration pulse is in development.

The goal of this study was to evaluate the biofidelity of the three computational surrogates (GHBMC model, WorldSID model, and the FTSS ES-2re model) under the side impact rigid wall sled test condition. The responses of the three computational surrogates were compared to those of post mortem human surrogate (PMHS) and objectively evaluated using the correlation and analysis (CORA) rating method. Among the three computational surrogates, the GHBMC model showed the best biofidelity based on the CORA rating score (GHBMC =0.65, WorldSID =0.57, FTSS ES-2re =0.58). In general, the response of the pelvis of all the models showed a good correlation with the PMHS response, while the response of the shoulder and the lower extremity did not. In terms of fracture prediction, the GHBMC model overestimated bone fracture.

The objective of the study was to analyze independently the contribution of pre-impact spine posture on impact response by subjecting a finite element human body model (HBM) to whole-body, lateral impacts. Seven postured models were created from the original HBM: one matching the standard driving posture and six matching pre-impact posture measured for each of six subjects tested in previously published experiments. The same measurements as those obtained during the experiments were calculated from the simulations, and biofidelity metrics based on signals correlation were established to compare the response of HBM to that of the cadavers. HBM responses showed good correlation with the subject response for the reaction forces, the rib strain (correlation score=0.8) and the overall kinematics. The pre-impact posture was found to greatly alter the reaction forces, deflections and the strain time histories mainly in terms of time delay.