ABSTRACT

An exploratory design and analysis code for underwater vehicles with ducted, 
multi-stage propulsion systems is developed from an existing version. Boundary 
layer modeling is added and used to predict flow separation as well as to 
estimate the effect of wake fraction on propulsive efficiency. Force balance 
(i.e., convergence to a self-propelled condition) is achieved by automatic 
variation of advance coefficient.  The force and boundary layer calculations 
of the revised code are validated using published experimental data.

A slightly modified version of the code is then used as the evaluator for 
an original Pareto genetic algorithm.  The algorithm seeks the code's Pareto
(non-dominated) frontier in terms of usable hull volume and propulsive 
efficiency, with the intention of investigating the feasibility of so-called 
``full stern'' submarines.  Three different methods of Pareto selection, drawn 
from the current literature, are installed in the algorithm and compared in 
terms of their ability to locate and define the frontier.

A new concept in evolutionary computation---non-interbreeding competitive 
species---is introduced, allowing simultaneous optimization of four 
incompatible propulsor configurations. This produces a feasibility frontier 
with  optimal propulsor configuration as a function of stern fullness. The 
ability of the algorithm to define a three-objective Pareto surface  is  
demonstrated, by including minimal cavitation as a third objective.   

The results provide evidence for the viability of full stern submarines, 
demonstrate the utility of genetic algorithms in obtaining Pareto design 
frontiers, and show that Pareto optimization is preferred to scalarized 
multi-objective optimization in general decision-making.