Chen, Guoning2021-08-062021-08-06December 22020-12December 2Portions of this document appear in: Nguyen, Duong B., Lei Zhang, Robert S. Laramee, David Thompson, Rodolfo Ostilla Monico, and Guoning Chen. "Physics‐based Pathline Clustering and Exploration." In Computer Graphics Forum, vol. 40, no. 1, pp. 22-37. 2021. And in: Nguyen, Duong B., Rodolfo Ostilla Monico, and Guoning Chen. "A Visualization Framework for Multi-scale Coherent Structures in Taylor-Couette Turbulence." IEEE Transactions on Visualization and Computer Graphics 27, no. 2 (2020): 902-912.https://hdl.handle.net/10657/8009Coherent structures are important features in fluid flows. A better understanding of the physics of coherent structures will help explain a diverse range of physical phenomena and help improve our capability of modeling complex turbulence flows, such as those often seen in combustion, chemical reaction, and heat transfer. However, due to their multi-scale nature and non-unified characterizations, extraction and separation of coherent structures remain a challenging task. This is further complicated by the overly complicated visual representation of these structures, significantly reducing the efficiency of the domain experts workflows for discovering the flow physics when they need to spend a considerable amount of time and effort to read the complex charts/graphs/geometries. In addition, the physical behaviors of flow that experts care about are not reliably conveyed in the visualizations due to the predominant focus on the geometric characteristics of the flow data. To address the above challenges and support domain experts to analyze various flow behaviors, especially coherent structures in the flow, this work proposes (1) a time-activity curve (TAC) based method to encode relevant physics into the geometric representation, (2) a novel pipeline to extract and visualize multi-scale coherent structures for the instantaneous (or time-independent) turbulent Taylor-Couette flow (TCF), and (3) a new framework to extract and visualize large-scale coherent structures in time-dependent shear flows using dynamic mode decomposition (DMD). The TAC-based framework enables us to select pathlines that can effectively represent the physical characteristics of interest and their temporal behavior in the fluid flow, which can be used to study the temporal behaviors of vortices, including their formation, merging, and breakdown. The novel visualization framework for TCF flows enables the separation of the large-scale and small-scale coherent structures in the instantaneous TCF flows for the first time in 3D, which supports the study of the formation of Taylor rolls -- a 3D coherent structures in TCFs, with different simulation parameters. The new DMD based framework for shear flows effectively extracts and visualizes the large-scale coherent structures over time, opening a new door for multi-scale coherent structure extraction and tracking over time for turbulence flow study.application/pdfengThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. UH Libraries has secured permission to reproduce any and all previously published materials contained in the work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).Flow Visualization, Coherent Structures, Time-Activity Curve, Turbulent Flow Analysis2021-08-06Thesisborn digital