Abstract

Optimal design of large engineering systems modeled as nonlinear programming problems remains a challenge because increased size reduces reliability and speed of numerical optimization algorithms. Decomposition of the original model into smaller coordinated submodels is desirable or even necessary. The article presents a methodology for optimal model-based decomposition of design problems, whether or not initially cast as optimization models. The overall model is represented by a hypergraph and is optimally partitioned into weakly-connected subgraphs that satisfy partitioning constraints. The formulation is robust enough to account for computational demands and resources, and the strength of interdependencies between the simulation modules contained in the model. This decomposition methodology is applied to a vehicle powertrain system design model comprising of engine, torque converter, transmission, and wheel-tire assembly, with 87 design relations and 119 design and state variables.

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