In-Situ Feature Tracking and Visualization of a Temporal Mixing Layer

Abstract

The flow field for a temporal mixing layer was analyzed by solving the Navier-Stokes equations via a Large Eddy Simulation method, LESLIE3D, and then visualizing and post-processing the resulting flow features by utilizing the prototype visualization and CFD data analysis software system Intelligent In-Situ Feature Detection, Tracking and Visualization for Turbulent Flow Simulations (IFDT). The system utilizes volume rendering with an Intelligent Adaptive Transfer Function that allows the user to train the visualization system to highlight flow features such as turbulent vortices. A feature extractor based upon a Prediction-Correction method then tracks and extracts the flow features and determines the statistics of features over time. The method executes In-Situ with the flow solver via a Python Interface Framework to avoid the overhead of saving data to file. The movie submitted for this visualization showcase highlights the visualization of the flow such as the formation of vortex features, vortex breakdown, the onset of turbulence and then fully mixed conditions.