{"title":"Evolution Surfaces for Spatiotemporal Visualization of Vortex Features","authors":"Simon Ferrari, Yaoping Hu, R. Martinuzzi","doi":"10.1109/CJECE.2019.2917394","DOIUrl":null,"url":null,"abstract":"Turbulent fluid flow data are often 4-D, spatially and temporally complex, and require specific techniques for visualization. Common visualization techniques neglect the temporal aspect of this data, limiting the ability to convey feature motion, or offering the user a complicated visualization. To remedy this, we present an approach—evolution surfaces—focused on the spatiotemporal rendering of user-selected flow features (i.e., vortices). By abstracting the spatial representation of these features, the approach renders their spatiotemporal behavior with reduced visual complexity. The behavior of vortex features is presented as surfaces, with textures indicating properties of motion and evolution events (e.g., bifurcation and amalgamation) represented by the surface topology. We evaluated the approach on two data sets generated from empirical measurement and computational simulation (Re = 28 000 and Re = 1200, respectively). Our approach’s focus on handling evolution events makes it capable of visualizing higher Reynolds number (Re) flows than other surface-based techniques. This approach has been assessed by fluid dynamicists to assert the validity for flow analysis. Evolution surfaces offer a compact visualization of spatiotemporal vortex behaviors, opening potential avenues for exploration and analysis of fluid flows.","PeriodicalId":55287,"journal":{"name":"Canadian Journal of Electrical and Computer Engineering-Revue Canadienne De Genie Electrique et Informatique","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CJECE.2019.2917394","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Canadian Journal of Electrical and Computer Engineering-Revue Canadienne De Genie Electrique et Informatique","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CJECE.2019.2917394","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 3
Abstract
Turbulent fluid flow data are often 4-D, spatially and temporally complex, and require specific techniques for visualization. Common visualization techniques neglect the temporal aspect of this data, limiting the ability to convey feature motion, or offering the user a complicated visualization. To remedy this, we present an approach—evolution surfaces—focused on the spatiotemporal rendering of user-selected flow features (i.e., vortices). By abstracting the spatial representation of these features, the approach renders their spatiotemporal behavior with reduced visual complexity. The behavior of vortex features is presented as surfaces, with textures indicating properties of motion and evolution events (e.g., bifurcation and amalgamation) represented by the surface topology. We evaluated the approach on two data sets generated from empirical measurement and computational simulation (Re = 28 000 and Re = 1200, respectively). Our approach’s focus on handling evolution events makes it capable of visualizing higher Reynolds number (Re) flows than other surface-based techniques. This approach has been assessed by fluid dynamicists to assert the validity for flow analysis. Evolution surfaces offer a compact visualization of spatiotemporal vortex behaviors, opening potential avenues for exploration and analysis of fluid flows.
期刊介绍:
The Canadian Journal of Electrical and Computer Engineering (ISSN-0840-8688), issued quarterly, has been publishing high-quality refereed scientific papers in all areas of electrical and computer engineering since 1976