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This research paper addresses the ground vehicle reliability prediction process based on a new integrated reliability prediction framework. The integrated stochastic framework combines the computational physics-based predictions with experimental testing information for assessing vehicle reliability. The integrated reliability prediction approach incorporates the following computational steps: i) simulation of stochastic operational environment, ii) vehicle multi-body dynamics analysis, iii) stress prediction in subsystems and components, iv) stochastic progressive damage analysis, and v) component life prediction, including the effects of maintenance and, finally, iv) reliability prediction at component and system level. To solve efficiently and accurately the challenges coming from large-size computational mechanics models and high-dimensional stochastic spaces, a HPC simulation-based approach to the reliability problem was implemented.

This contribution demonstrates the use of high performance computing, specifically Graphics Processing Unit (GPU) based computing, for the simulation of tracked ground vehicles. The work closes a gap in physics based simulation related to the inability to accurately characterize the 3D mobility of tracked vehicles on granular terrains (sand and/or gravel). The problem of tracked vehicle mobility on granular material is approached using a discrete element method that accounts for the interaction between the track and each discrete particle in the terrain. This continuum approach captures the dynamics of systems with more than 1,000,000 bodies interacting simultaneously. Two factors render the approach feasible. First, the frictional contact problem between the terrain and the vehicle draws on a convex optimization methodology in which the solution becomes the first order optimality condition of a cone complementarity problem.

This paper addresses some aspects of an on-going multiyear research project for US Army TARDEC. The focus of the research project has been the enhancement of the overall vehicle reliability prediction process. This paper describes briefly few selected aspects of the new integrated reliability prediction approach. The integrated approach uses both computational mechanics predictions and experimental test databases for assessing vehicle system reliability. The integrated reliability prediction approach incorporates the following computational steps: i) simulation of stochastic operational environment, ii) vehicle multi-body dynamics analysis, iii) stress prediction in subsystems and components, iv) stochastic progressive damage analysis, and v) component life prediction, including the effects of maintenance and, finally, iv) reliability prediction at component and system level.

In the context of off-road vehicle simulations, deformable terrain models mostly fall into three categories: simple visualization of the deformed terrain only, use of empirical relationships for the deformation, or finite/discrete element approaches for the terrain. A real-time vehicle dynamics simulation with a physics-based tire model (brush, ring or beam-based models) requires a terrain model that accurately reflects the deformation and response of the soil to all possible inputs of the tire in order to correctly simulate the response of the vehicle. The real-time requirement makes complex finite/discrete element approaches unfeasible, and the use of a ring or beam -based tire model excludes purely empirical terrain models. We present the development of a three-dimensional vehicle/terrain interaction model which is comprised of a tire and deformable terrain model to be used with a real-time vehicle dynamics simulator.

1 This paper describes a modeling, simulation, and visualization framework aimed at enabling physics-based analysis of ground vehicle mobility. This framework, called Chrono, has been built to leverage parallel computing both on distributed and shared memory architectures. Chrono is both modular and extensible. Modularity stems from the design decision to build vertical applications whose goal is to reduce the end-to-end time from vision-to-model-to-solution-to-visualization for a targeted application field. The extensibility is a consequence of the design of the foundation modules, which can be enhanced with new features that benefit all the vertical applications. Two factors motivated the development of Chrono. First, there is a manifest need of modeling approaches and simulation tools to support mobility analysis on deformable terrain.