Abstract:

A multidisciplinary design optimization (MDO) methodology is developed to link the aerodynamic shape design to the system costs for magnetically levitated (MAGLEV) vehicles. These railed vehicles can cruise at speeds approaching that of short haul aircraft and travel just inches from a guideway. They are slated for high speed intercity service of up to 500 miles in length and would compete with air shuttle services. The realization of this technology hinges upon economic viability which is the impetus for the design methodology presented here. This methodology involves models for the aerodynamics, structural weight, direct operating cost, acquisition cost, and life cycle cost and utilizes the DOT optimization software. Optimizations are performed using sequential quadratic programming for a 5 design variable problem. This problem is reformulated using 7 design variables to overcome problems due to non-smooth design space. The reformulation of the problem provides a smoother design space which is navigable by calculus based optimizers. The MDO methodology proves to be a useful tool for the design of MAGLEV vehicles. The optimizations show significant and sensible differences between designing for minimum life cycle cost and other figures of merit. The optimizations also show a need for a more sensitive acquisition cost model which is not based simply on weight engineering. As a part of the design methodology, a low-order aerodynamics model is developed for the prediction of 2-D, ground effect flow over bluff bodies. The model employs a continuous vortex sheet to model the solid surface, discrete vortices to model the shed wake, the Stratford Criterion to determine the location of the turbulent separation, and the vorticity conservation condition to determine the strength of the shed vorticity. The continuous vortex sheet better matches the mechanics of the flow than discrete singularities and therefore better predicts the ground effect flow. The predictions compare well with higher-order computational methods and experimental data. A 3-D extension to this model is investigated, although no 3-D design optimizations are performed.

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