Curvilinear Gridding and Connectivity Best Practices within the LAVA Framework

Speaker: James Koch, Computational Aerosciences Branch, NASA Ames Research Center
October 27, 2026

Presentation

Abstract

The Launch, Ascent, and Vehicle Aerodynamics (LAVA) CFD Framework's curvilinear capabilities include:

Steady and unsteady RANS
Hybrid-RANS LES
Wall-modeled and wall-resolved LES
Gradient-based design optimization utilizing the adjoint method
Sliding mesh and other rotory blade-specific features
Mesh morphing for aeroelastic analysis

All of which enable specialization in viscous analysis and design for aerospace vehicles, as well as rotating blade applications. A major hurdle when using curvilinear overset methods is best-practice grid generation and preprocessing. This includes the choice of grid topology, resolution, and aspect ratio, which all affect the complexity of mesh generation and solution accuracy.

This presentation will discuss best-practices in constructing grid topologies for the LAVA curvilinear solver, as well as the suite of tools available to alleviate and streamline user gridding and domain connectivity effort. Benefits of combining block-to-block meshing with traditional overset meshing are assessed, with emphasis on the setup for sliding mesh applications. The benefits and strategies for employing immersed methods are also overviewed and demonstrated, with a focus on replacing intersecting components with "almost body-fitted” immersed grids. Finally, employment of tools for off-body generation, panel weight generation, and refinement will also be discussed, which provide meshing workflow accelerators when combined with software like Chimera Grid Tools (CGT) and the associated suite of automated overset meshing tools known as EPOGS. By the end of this talk, attendees should understand what grid strategies are recommended to tackle problems of interest, and potential issues they may encounter during domain connectivity, and how to resolve them.

Biography

James Koch has been a research engineer in the Computational Aerosciences branch at the NASA Ames Research Center since 2020. His research focuses on overset geometry capture, preprocessing, and connectivity algorithmic strategies and implementation. James holds a MS and BS in Mechanical Engineering from Washington University in St. Louis, a BA in Physics from Grinnell College, and was a Marie Skłodowska-Curie research scholar for application and development of continuous adjoint methods in CFD.

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