Status and Future of Geometry Modeling and Grid Generation for Design and Optimization

Abstract

Geometry modeling and grid generation (GMGG) have played, and will continue to play, an important role in computational aerosciences. During the last two decades, tremendous progress has occurred in GMGG; however, GMGG is still the biggest bottleneck to routine applications for complicated computational fluid dynamics and computational structures mechanics models for analysis, design, and optimization. We are still far from incorporating GMGG tools in a design and optimization environment for complicated configurations. It is still a challenging task to parameterize an existing model in today's computer-aided design systems, and the models created are not always good enough for automatic grid generation tools. Despite many advances in grid generation, the process is still the most labor-intensive and time-consuming part of the computational aerosciences for analysis, design, and optimization. In an ideal design environment, a design engineer would use a parametric model to evaluate alternative designs effortlessly and optimize an existing design for a new set of design objectives and constraints. For this ideal environment to be realized, the GMGG tools must have the following characteristics: 1) be automated, 2) provide consistent geometry across all disciplines, 3) be parametric, 4) provide sensitivity derivatives, and 5) fit in the product development cycle times. This paper reviews the status of GMGG for analysis, design, and optimization processes, and it focuses on some emerging ideas that will advance the GMGG toward the ideal design environment.