Author: Sean Javad Kamkar

Publisher: Stanford University

Published: 2011

Total Pages: 218

ISBN-13:

A new adaptive mesh refinement strategy that is based on a coupled feature-detection and error-estimation approach is developed. The overall goal is to apply the proper degree of refinement to key vortical features in aircraft and rotorcraft wakes. The refinement paradigm is based on a two-stage process wherein the vortical regions are initially identified for refinement using feature-detection, and then the appropriate resolution is determined by the local solution error. The feature-detection scheme uses a local normalization procedure that allows it to automatically identify regions for refinement with threshold values that are not dependent upon the convective scales of the problem. An error estimator, based on the Richardson Extrapolation method, then supplies the identified features with appropriate levels of refinement. The estimator is shown to be well-behaved for steady-state and time-accurate aerodynamic flows. The above strategy is implemented within the Helios code, which features a dual-mesh paradigm of unstructured grids in the near-body domain, and adaptive Cartesian grids in the off-body domain. A main objective of this work is to control the adaption process so that high fidelity wake resolution is obtained in the off-body domain. The approach is tested on several theoretical and practical vortex-dominated flow-fields in an attempt to resolve wingtip vortices and rotor wakes. Accuracy improvements to rotorcraft performance metrics and increased wake resolution are simultaneously documented.