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Computer simulation was used as a complement to crash and injury field data analysis and physical sled and barrier tests to investigate and predict the spinal injuries of a rear impact in an IndyCar. The model was expected to relate the spinal loads to the observed injuries, thereby predicting the probability and location of spinal fractures. The final goal is to help reduce the fracture risk by optimizing the seat and restraint system design and the driver's position using computer modeling and sled testing. MADYMO Full FE Human Body Model (HBM) was selected for use because of its full spinal structural details and its compatibility with the vehicle and restraint system models. However, the IndyCar application imposed unique challenges to the HBM. First, the driver position in a race car is very different from that in a typical passenger car.

Since its invention in early 1990s, the side curtain airbag has become an important part of the occupant restraint system for side impact and rollover protection. Computer Aided Engineering (CAE) is often used to help side curtain airbag design. Because of the unique characteristics of side curtain airbag systems, the simulation of side curtain airbag systems faces different challenges in comparison to the simulation of driver and passenger airbag systems. The typical side curtain airbag CAE analysis includes, but is not limited to, cushion volume evaluation, cushion coverage review, cushion shrinkage and tension force review, deployment timing review and seam shape and location review. The commonly used uniform pressure airbag models serve the purpose in most cases.

Computer modeling and simulation have become one of the primary methods for development and design of automobile occupant protection systems (OPS). To ensure the accuracy and reliability of a math-based OPS design, the correlation quality assessment of mathematical models is essential for program success. In a typical industrial approach, correlation quality is assessed by comparing chart characteristics and scored based on an engineer's modeling experience and judgment. However, due to the complexity of the OPS models and their responses, a systematic approach is needed for accuracy and consistency. In this paper, a correlation grading methodology for the OPS models is presented. The grading system evaluates a wide spectrum of a computer model's performances, including kinematics, dynamic responses, and dummy injury measurements. Statistical analysis is utilized to compare the time histories of the tested and simulated dynamic responses.

A steering wheel is an indispensable component in an automobile. Although the steering wheel was invented about one hundred years ago and its structure has since become more and more complex with numerous innovations, documented analysis on steering wheel performance is very limited. Today, a steering wheel is not only a wheel that controls where your car goes; it also plays an important role in a vehicle occupant protection system. Therefore, many requirements have to be met before a steering wheel goes into production. With the development of computational mechanics and increasing computer capability, it has become much easier to evaluate the steering wheel performance in a totally different way. Instead of running prototype tests, steering wheel designs can be modeled virtually in various scenarios using finite element analysis, thus facilitating the development cycle.