Multi-fidelity simulation modelling in optimization of a submarine propulsion system

An inherent trade-off exists in simulation model development and use: a trade-off between the level of detail simulated and the simulation model's computational cost. It is often desirable to simulate a high level of detail to a high degree of accuracy. However, due to the nature of design optimization, which requires a large number of design evaluations, the application of such simulation models can be prohibitively expensive. This paper presents an optimization framework consisting of a series hybrid optimization algorithm, in which a global search optimizes a submarine propulsion system using low-fidelity models and, in order to refine the results, a local search is used with high-fidelity models.