Engineering design search and optimisation is the process whereby existing engineering modeling and analysis capabilities are exploited to yield improved designs. Optimisation tools modify a design to increase, or reduce, some measure of merit (called the objective function) whilst satisfying various constraints. A plethora of optimisation methods are available to engineers, for example: classical gradient descent, evolutionary and stochastic searches, response surface models, data-fusion methods, multi-objective/Pareto approaches, and robust engineering design methods. However good quality design search requires a judicious choice and utilization of several optimisation methods.

In the next 2-5 years intelligent search tools will become a vital component of all engineering design systems. Such facilities will steer the user through the process of setting up, executing and post-processing design search and optimisation activities in a variety of disciplines. One of the leading figures in the US Grid initiative (and co-developer of Globus), Carl Kesselman, has frequently stated that ‘design optimisation is potentially a killer application for the grid^[1]. In the Geodise project we will address the challenge of delivering a grid-enabled optimisation and design search service and will focus, in the first instance, on the use of Computational Fluid Dynamics (CFD).

^[1] 1st EuroGlobus workshop, Lecce 16-23rd June 2001

Computational Fluid Dynamics