Automated Feature Extraction of Shear Layers

This thesis demonstrates a generalized method for extracting shear layers as features in viscous computational fluid dynamics flowfields. A source term indicative of shear in the flow combines with convective terms to constitute a conservation equation for a scalar shear layer detector variable. The source terms explored in this inves-tigation come from the viscous terms of the Navier-Stokes momentum equations as well as from a simple shear measure obtained from the velocity gradient tensor. A threshold value of the scalar detector variable indicates the boundary layer or wake edge, while the magnitude of the detector indicates the intensity of shear influence upon any particular point in the flow. Test cases validate the convective technique and demonstrate its rejection of false sources. Among the applications of shear layer feature extraction are solution improvement techniques like grid adaptation and tools for analysis and design such as visualization