While over 30% of US occupant fatalities occur in rollover crashes, no dummy has been developed for such a condition. Currently, an efficient, cost-effective methodology is being implemented to develop a biofidelic rollover dummy. Instead of designing a rollover dummy from scratch, this methodology identifies a baseline dummy and modifies it to improve its response in a rollover crash. Using computational models of the baseline dummy, including both multibody (MB) and finite element (FE) models, the dummy's structure is continually modified until its response is aligned (using BioRank/CORA metric) with biofidelity targets. A previous study (Part I) identified the THOR dummy as a suitable baseline dummy by comparing the kinematic responses of six existing dummies with PMHS response corridors through laboratory rollover testing. In this study (Part II), the whole-body kinematic responses of the THOR MB and FE models were validated with responses of the physical THOR dummy in experiments that simulated rollover conditions. This step is necessary to ensure accuracy of the computer-aidedengine
ering dummy design, thereafter improving confidence in the proposed rollover dummy design modifications. In addition, to ensure the robustness of the model validation, the sensitivities of the THOR dummy computational model responses to parameters with uncertainty in the experiment were assessed, including seatbelt pretension, friction, and dummy seating posture. In summary, both the THOR MB and FE model responses matched well with its physical counterpart. Future studies (Part III) will focus on using these validated dummy models for rollover dummy design modification and evaluation.
While over 30% of US occupant fatalities occur in rollover crashes, no dummy has been developed for such a condition. Currently, an efficient, cost-effective methodology is being implemented to develop a biofidelic rollover dummy. Instead of designing a rollover dummy from scratch, this methodology identifies a baseline dummy and modifies it to improve its response in a rollover crash. Using computational models of the baseline dummy, including both multibody (MB) and finite element (FE) models, the dummy's structure is continually modified until its response is aligned (using BioRank/CORA metric) with biofidelity targets. A previous study (Part I) identified the THOR dummy as a suitable baseline dummy by comparing the kinematic responses of six existing dummies with PMHS response corridors through laboratory rollover testing. In this study (Part II), the whole-body kinematic responses of the THOR MB and FE models were validated with responses of the physical THOR dummy in experiments that simulated rollover conditions. This step is necessary to ensure accuracy of the computer-aidedengineering dummy design, thereafter improving confidence in the proposed rollover dummy design modifications. In addition, to ensure the robustness of the model validation, the sensitivities of the THOR dummy computational model responses to parameters with uncertainty in the experiment were assessed, including seatbelt pretension, friction, and dummy seating posture. In summary, both the THOR MB and FE model responses matched well with its physical counterpart. Future studies (Part III) will focus on using these validated dummy models for rollover dummy design modification and evaluation.
