A Computational Framework for Human-centric Vehicular Crashworthiness Design and Decision-Making Under Uncertainty

Government agencies, globally, strive to minimize the likelihood and frequency of human death and severe injury on road transport systems. From an engineering design standpoint, the minimization of these road accident effects on occupants becomes a critical design goal. This necessitates the quantification and management of injury risks on the human body in response to several vehicular impact variables and their associated uncertainties for different crash scenarios. In this paper, we present a decision-based, robust design framework to quantify and manage the impact-based injury risks on occupants for different computational model-based car crash scenarios. The key functionality offered is the designer's capability to conduct robust concept exploration focused on managing the selected impact variables and associated uncertainties, such that injury risks are controlled within acceptable levels. The framework's efficacy is tested for near-side impact scenarios with impact velocity and angle of impact as the critical variables of interest. Two injury criteria, namely, Head Injury Criterion (HIC) and Lateral Neck Injury Criteria (Lateral Nij), are selected to quantitatively measure the head and neck injury risks in each crash simulation. Using the framework, a robust design problem is formulated to determine the combination of impact variables that best satisfice the injury goals defined. The framework and associated design constructs are generic and support the formulation and decision-based robust concept exploration of similar problems involving models under uncertainty. Our focus in this paper is on the framework rather than the results per se.

Assessment of Nanobag as a New Safety System in the Frontal Sled Test

Objective: The future mobility challenges leads to considering new safety systems to protect vehicle passengers in non-standard and complex seating configurations. The objective of this study is to assess the performance of a brand new safety system called nanobag and to compare it to the traditional airbag performance in the frontal sled test scenario. Methods: The nanobag technology is assessed in the frontal crash test scenario and compared with the standard airbag by numerical simulation. The previously identified material model is used to assemble the nanobag numerical model. The paper exploits an existing validated human body model to assess the performance of the nanobag safety system. Using both the new nanobag and the standard airbag, the sled test numerical simulations with the variation of human bodies are performed in 30 km/h and 50 km/h frontal impacts. Results: The sled test results for both the nanobag and the standard airbag based on injury criteria shows a good and acceptable performance of the nanobag safety system compared to the traditional airbag. Conclusion: The results show that the nanobag system has its performance compared to the standard airbag, which means that thanks to the design, the nanobag safety system has a high potential and extended application for multi-directional protection against impact.

Numerical Simulation of Airbag and Study on the Effect of Airbag Parameters on Head Injury Criteria

In the case of an accident, inflatable restraints system plays a critical role in ensuring the safety of vehicle occupants. Frontal airbags have saved 44,869 lives, according to research conducted by the National Highway Traffic Safety Administration (NHTSA).Finite element analysis is extremely important in the research and development of airbags in order to ensure optimum protection for occupant. In this work, we simulate a head impact test with a deploying airbag and investigate the airbag's parameters. The airbag's performance is directly influenced by the parameters of the cushion such as vent area and fabric elasticity. The FEM model is analysed to investigate the influence of airbag parameter, and the findings are utilised to determine an optimal value that may be employed in the construction of better occupant safety systems. Keywords: airbag, finite element method, occupant safety, frontal airbag, vent size, fabric elasticity, head injury criteria

Finite Element Analysis of the Motorcycle Helmet Material against Impact Velocity

A motorcycle helmet is the best protective headgear for the prevention of head injuries due to direct cranial impact. A finite element model based on realistic geometric features of a motorcycle helmet is established, and explicit finite element code is employed to simulate dynamic responses at different impact velocities. Peak acceleration and Head injury criterion values derived from the head form are used to assess the protective performance of the helmet. We have concluded that the dynamic responses of the helmet dramatically vary with impact velocity, as well as the mechanical properties of the outer shell and energy- absorbing liner. At low velocities e.g. 8.3 m/s, the shell stiffness and liner density should be relatively low to diminish head- contact force. At high velocity e.g. 11m/s, a stiffer shell and denser liner offer superior protection against head injuries. Different tests were performed in ansys explicit dynamics solver by taking different materials and calculating PLA, Head Injury Criteria, K.E, P.E, contact energy etc. The results obtained for different materials were then compared with easy other to draw the necessary conclusion’s. Keywords: Peak Linear Acceleration (PLA), Head Injury Criteria.

Evaluation of Head Injury Criteria for Injury Prediction Effectiveness: Computational Reconstruction of Real-World Vulnerable Road User Impact Accidents

This study evaluates the effectiveness of various widely used head injury criteria (HICs) in predicting vulnerable road user (VRU) head injuries due to road traffic accidents. Thirty-one real-world car-to-VRU impact accident cases with detailed head injury records were collected and replicated through the computational biomechanics method; head injuries observed in the analyzed accidents were reconstructed by using a finite element (FE)-multibody (MB) coupled pedestrian model [including the Total Human Model for Safety (THUMS) head–neck FE model and the remaining body segments of TNO MB pedestrian model], which was developed and validated in our previous study. Various typical HICs were used to predict head injuries in all accident cases. Pearson’s correlation coefficient analysis method was adopted to investigate the correlation between head kinematics-based injury criteria and the actual head injury of VRU; the effectiveness of brain deformation-based injury criteria in predicting typical brain injuries [such as diffuse axonal injury diffuse axonal injury (DAI) and contusion] was assessed by using head injury risk curves reported in the literature. Results showed that for head kinematics-based injury criteria, the most widely used HICs and head impact power (HIP) can accurately and effectively predict head injury, whereas for brain deformation-based injury criteria, the maximum principal strain (MPS) behaves better than cumulative strain damage measure (CSDM0.15 and CSDM0.25) in predicting the possibility of DAI. In comparison with the dilatation damage measure (DDM), MPS seems to better predict the risk of brain contusion.

The Head AIS 4+ Injury Thresholds for the Elderly Vulnerable Road User Based on Detailed Accident Reconstructions

Compared with the young, the elderly (age greater than or equal to 60 years old) vulnerable road users (VRUs) face a greater risk of injury or death in a traffic accident. A contributing vulnerability is the aging processes that affect their brain structure. The purpose of this study was to investigate the injury mechanisms and establish head AIS 4+ injury tolerances for the elderly VRUs based on various head injury criteria. A total of 30 elderly VRUs accidents with detailed injury records and video information were selected and the VRUs’ kinematics and head injuries were reconstructed by combining a multi-body system model (PC-Crash and MADYMO) and the THUMS (Ver. 4.0.2) FE models. Four head kinematic-based injury predictors (linear acceleration, angular velocity, angular acceleration, and head injury criteria) and three brain tissue injury criteria (coup pressure, maximum principal strain, and cumulative strain damage measure) were studied. The correlation between injury predictors and injury risk was developed using logistical regression models for each criterion. The results show that the calculated thresholds for head injury for the kinematic criteria were lower than those reported in previous literature studies. For the brain tissue level criteria, the thresholds calculated in this study were generally similar to those of previous studies except for the coup pressure. The models had higher (>0.8) area under curve values for receiver operator characteristics, indicating good predictive power. This study could provide additional support for understanding brain injury thresholds in elderly people.

Dynamic Responses of Female Volunteers in Rear Impact Sled Tests at Two Head Restraint Distances

The objective of this study was to assess the biomechanical and kinematic responses of female volunteers with two different head restraint (HR) configurations when exposed to a low-speed rear loading environment. A series of rear impact sled tests comprising eight belted, near 50th percentile female volunteers, seated on a simplified laboratory seat, was performed with a mean sled acceleration of 2.1 g and a velocity change of 6.8 km/h. Each volunteer underwent two tests; the first test configuration, HR10, was performed at the initial HR distance ∼10 cm and the second test configuration, HR15, was performed at ∼15 cm. Time histories, peak values and their timing were derived from accelerometer data and video analysis, and response corridors were also generated. The results were separated into three different categories, HR10C (N = 8), HR15C (N = 6), and HR15NC (N = 2), based on: (1) the targeted initial HR distance [10 cm or 15 cm] and (2) whether the volunteers’ head had made contact with the HR [Contact (C) or No Contact (NC)] during the test event. The results in the three categories deviated significantly. The greatest differences were found for the average peak head angular displacements, ranging from 10° to 64°. Furthermore, the average neck injury criteria (NIC) value was 22% lower in HR10C (3.9 m2/s2), and 49% greater in HR15NC (7.4 m2/s2) in comparison to HR15C (5.0 m2/s2). This study supplies new data suitable for validation of mechanical or mathematical models of a 50th percentile female. A model of a 50th percentile female remains to be developed and is urgently required to complement the average male models to enhance equality in safety assessments. Hence, it is important that future protection systems are developed and evaluated with female properties taken into consideration too. It is likely that the HR15 test configuration is close to the limit for avoiding HR contact for this specific seat setup. Using both datasets (HR15C and HR15NC), each with its corresponding HR contact condition, will be possible in future dummy or model evaluation.