Solution adaptive grid strategies based on the redistribution of a ®xed number of points are described in this paper. The redistribution is performed using weight functions that vary based on signi®cant¯ow features. The weight functions are evaluated using an equidistribution principle. In this paper, emphasis is placed on the development of weight functions applicable to compressible¯ows exhibiting large scale separated vortical¯ows, vortex±vortex and vortex±surface interactions, separated shear layers and multiple shocks of dierent intensities. Algebraic, elliptic and parabolic methods of grid generation have been utilized for structured grid redistribution. Additionally, a point movement scheme is presented for generalized (structured/unstructured/hybrid) grid adaptation. Computer Aided Geometry Design (CAGD) techniques are combined with redistribution schemes to maintain the ®delity of solid boundaries. In particular, solid boundaries are represented using Non-Uniform Rational B-Splines (NURBS). A grid generation software system ± Parallel Multiblock Adaptive Grid generation (PMAG) ± using an elliptic redistribution scheme is also described with emphasis placed on the parallel implementation for multiblock structured grids with unstructured blocking topologies and on interpolation issues. Computational examples demonstrating the in¯uence of dierent weight functions and grid redistribution strategies are presented. Ó
Current and emerging trends in High Performance Computing (HPC) are providing transformational capabilities for simulation-based research and development and simulation-based design. Numerous efforts are underway to provide exascale systems in the next decades. HPC architectures are rapidly evolving and the tools and methods need to keep pace with both the scale and the evolving hardware architecture. Emerging HPC capabilities provide potential for simulation of increasingly complex, multi-scale and multidisciplinary applications for discovery, design and evaluation of aerospace systems. The computational mesh, along with the geometry that it represents, has a considerable impact on the quality, stability, and amount of resources required to complete numerical simulations. Extreme-scale environments require increased levels of process automation and reliability not currently available in state-of-the-art mesh generation tools. These shortcomings make geometry modeling and mesh generation a pacing bottleneck for the future. The paper will summarize the panel discussion that was held at AIAA's 2015 SciTech Conference in which the path for geometry and mesh generation as a supporting element of the NASA CFD 2030 Vision was discussed.
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