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A multi-body dynamics model of the U.S. Army3s High Mobility Multi-purpose Wheeled Vehicle (HMMWV) has been created using commercial software (ADAMS) to simulate and analyze the vehicle3s rollover behavior. However, manual operation of such simulation and analysis for design purposes is prohibitively expensive and time consuming, limiting the engineers3 ability to utilize the model fully and extract from it useful design information in a timely, cost-effective manner. To address this challenge, a commercial system integration and optimization software (OPTIMUS) is utilized in order to automate the simulation processes and to enable the more complex uncertainty-based analysis of the HMMWV rollover behavior under a variety of external conditions. Challenges involved in integrating the software are highlighted and remedies are discussed. Rollover analysis results from using the integrated model and automated simulation are also presented.

This paper proposes an approach for optimal design of multilevel systems under uncertainty. The approach utilizes the stochastic extension of the analytical target cascading formulation. The reliability of satisfying the probabilistic constraints is computed by means of the most probable point method using the hybrid mean value algorithm. A linearization technique is employed for estimating the propagation of uncertainties throughout the problem hierarchy. The proposed methodology is applied to a piston-ring/cylinder-liner engine subassembly design problem. Specifically, we assess the impact of variations in manufacturing-related properties such as surface roughness on engine attributes such as brake-specific fuel consumption. Results are compared to the ones obtained using Monte Carlo simulation.