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This paper describes the development of a three-dimensional lumped-mass structure and dummy model to study barrier-to-car side impacts. The test procedures utilized to develop model input data are also described. The model results are compared to crash test results from a series of six barrier-to-car crash tests. Sensitivity analysis using the validated model show the necessity to account for dynamic structural rate effects when using quasi-statically measured vehicle crush data.

Macroscopic constitutive behaviors of aluminum 5052-H38 honeycombs under dynamic inclined loads with respect to the out-of-plane direction are investigated by experiments. The results of the dynamic crush tests indicate that as the impact velocity increases, the normal crush strength increases and the shear strength remains nearly the same for a fixed ratio of the normal to shear displacement rate. The experimental results suggest that the macroscopic yield surface of the honeycomb specimens as a function of the impact velocity under the given dynamic inclined loads is not governed by the isotropic hardening rule of the classical plasticity theory. As the impact velocity increases, the shape of the macroscopic yield surface changes, or more specifically, the curvature of the yield surface increases near the pure compression state.

An age-dependent, serious-to-fatal (AIS3+), thoracic risk curve was derived and evaluated for frontal impacts. The study consisted of four parts. In Part 1, two datasets of post mortem human subjects (PMHS) were generated for statistical and sensitivity analyses. In Part 2, logistic regression analyses were conducted. For each dataset, two statistical methods were applied: (1) a conventional maximum likelihood method, and (2) a modified maximum likelihood method. Therefore, four statistical models were derived — one for each dataset/statistical method combination. For all of the resulting statistical models (risk curves), the linear combination of maximum normalized sternum deflection and age of the PMHS was identified as a feasible predictor of AIS3+ thoracic injury probability. In Part 3, the PMHS-based risk curves were transformed into test-dummy-based risk curves. In Part 4, validation studies were conducted for each risk curve.

This paper compares and contrasts the modeling features present in the MVMA2D and the MADYM02D occupant simulation models. Simulations of a series of sled tests with a Hybrid II test dummy restrained with a 3-point belt system have been conducted using the MADYM02D model. The simulation results agree with the test results.

Lower-body injury data for adults in real-world frontal impacts in the National Automotive Sampling System (NASS) were collected, analyzed, and modeled via statistical methods. Two levels of lower-body injury were considered: maximum serious-to-fatal (MAIS3+) and moderate-to-fatal (MAIS2+). In the analysis, we observed that a substantial fraction of all lower-body injured occupants had no recorded floor/toe pan intrusion: 47% of all MAIS3+ injured occupants; 69% of all MAIS2+ injured occupants. In the statistical modeling, we developed binary logistic regression models to fit the MAIS3+ and MAIS 2+ injury data. The statistically significant variables (p ≤ 0.05) were the speed change of the crash, postcrash floor/toe pan intrusion, level of restraint, occupant age, and occupant gender.

Numerical analyses frequently accompany experimental investigations that study injury biomechanics and improvements in automotive safety. Limited by computational speed, earlier mathematical models tended to simplify the system under study so that a set of differential equations could be written and solved. Advances in computing technology and analysis software have enabled the development of many sophisticated models that have the potential to provide a more comprehensive understanding of human impact response, injury mechanisms, and tolerance. In this article, 50 years of publications on numerical modeling published in the Stapp Car Crash Conference Proceedings and Journal were reviewed. These models were based on: (a) author-developed equations and software, (b) public and commercially available programs to solve rigid body dynamic models (such as MVMA2D, CAL3D or ATB, and MADYMO), and (c) finite element models.