Theses and Dissertations
Issuing Body
Mississippi State University
Advisor
Thompson, David S.
Committee Member
Janus, J. Mark
Committee Member
Sescu, Adrian
Date of Degree
12-9-2016
Document Type
Graduate Thesis - Open Access
Major
Aerospace Engineering
Degree Name
Master of Science
College
James Worth Bagley College of Engineering
Department
Department of Aerospace Engineering
Abstract
Over the past few decades, visualization and application researchers have been investigating vortices and have developed several algorithms for detecting vortex-like structures in the flow. These techniques can adequately identify vortices in most computational datasets, each with its own degree of accuracy. However, despite these efforts, there still does not exist an entirely reliable vortex detection method that does not require significant user intervention. The objective of this research is to solve this problem by introducing a novel vortex analysis technique that provides more accurate results by optimizing the threshold for several computationally-efficient, local vortex detectors, before merging them using the Bayesian method into a more robust detector that assimilates global domain knowledge based on labeling performed by an expert. Results show that when choosing the threshold well, combining the methods does not improve accuracy; whereas, if the threshold is chosen poorly, combining the methods produces significant improvement.
URI
https://hdl.handle.net/11668/18862
Recommended Citation
Bassou, Randa, "Vortex Detection in CFD Datasets Using a Multi-Model Ensemble Approach" (2016). Theses and Dissertations. 4972.
https://scholarsjunction.msstate.edu/td/4972