Integrating Stochastic Engineering Models in a Distributed Environment

With the current tight monetary constraints placed on the US military there is a continuous need to reduce the cost of ownership of the Army ground vehicles. The consideration of uncertainty and design optimization is critical for designing high-performance, reliable, cost-effective Army combat vehicles. The proposed work develops an adequate computational tool for accurately performing military vehicle reliability-based design optimization (RBDO) using large-scale finite element models in distributed computing environments. To approach vigorously the RBDO problem for the Army vehicles, GP Technologies has teamed with University of Iowa CCAD and University of California at Berkeley. Under this project a new, powerful computational stochastic mechanics technology is developed and then is integrated with the RBDO software developed by University of Iowa CCAD. The proposed computational stochastic finite element technology includes two key components: (i) an accurate stochastic approximation of highly complex physical behavior using high-order stochastic field models and (ii) a fast physics-based stochastic simulation using a parallel multigrid solver for unstructured mesh problems. The new computational stochastic tools will be demonstrated on critical components of the Army High-Mobility Trailer and the Stryker. The resulted RBDO technologies will enable TACOM to design more cost-effective high-performance, durable & affordable military vehicles.