Function Field Analysis for the Visualization of Flow Similarity in Time-Varying Vector Fields

  title={Function Field Analysis for the Visualization of Flow Similarity in Time-Varying Vector Fields},
  author={Harald Obermaier and Kenneth I. Joy},
Modern time-varying flow visualization techniques that rely on advection are able to convey fluid transport, but cannot provide an accurate insight into local flow behavior over time or locally corresponding patterns in unsteady vector fields. We overcome these limitations of purely Lagrangian approaches by generalizing the concept of function fields to time-varying flows. This representation of unsteady vector-fields as stationary function fields, where every position in space is a vector… 
Comparative Visual Analysis of Lagrangian Transport in CFD Ensembles
This work develops a Lagrangian framework for the comparison of flow fields in an ensemble and introduces a classification space that facilitates incorporation of these properties into a common ensemble visualization.


Over Two Decades of Integration-Based, Geometric Flow Visualization
This survey reviews and classify geometric flow visualization literature according to the most important challenges when considering such a visualization, a central theme being the seeding object upon which they are based.
A Phase Field Model for Continuous Clustering on Vector Fields
A new method for the simplification of flow fields is presented, based on continuous clustering, which introduces specific physical quantities in the simulation to control the shape, orientation and distribution of the clusters as a function of the underlying flow field.
Overview of Flow Visualization
Path Line Attributes - an Information Visualization Approach to Analyzing the Dynamic Behavior of 3D Time-Dependent Flow Fields
An approach to visually analyzing the dynamic behavior of 3D time-dependent flow fields by considering the behavior of the path lines and how path line attributes are used for describing characteristic features of these flows is described.
Flow Radar Glyphs—Static Visualization of Unsteady Flow with Uncertainty
A new type of glyph is introduced to visualize unsteady flow with static images, allowing easier analysis of time-dependent phenomena compared to animated visualization, and examples from CFD and the field of stochastic hydrogeology show that it is easy to discriminate areas of different spatiotemporal flow behavior and regions of different uncertainty variations in space and time.
Flow Visualization Overview
This chapter presents an overview of important and widely used approaches to flow visualization, along with references to more detailed descriptions in the original scientific publications.
Interactive Exploration and Analysis of Pathlines in Flow Data
Three new concepts in pathline analysis are presented which further improve the abilities of analysis: a multi-step analysis which helps to save time and space needed for computation, direct pathline brushing, and the use of pre-configured view arrangements.
A continuous clustering method for vector fields
A new method for the simplification of flow fields is presented, based on continuous clustering, which discusses the applicability of this new type of approach mainly for flow fields, where the cluster energy penalizes cross streamline boundaries, but the method also carries provisions in other fields as well.
Interactive cross-detector analysis of vortical flow data
This paper discusses the application of multiple linked views for advanced vortex investigation in flow data and demonstrates how linking and brushing of derived feature information can lead to increased performance in interactive feature analysis.
Interactive Visualization of Function Fields by Range‐Space Segmentation
This work presents a dimension reduction and feature extraction method for the visualization and analysis of function field data that focuses upon the creation of high‐dimensional range‐space segmentations from which to generate meaningful visualizations and extract separating surfaces between features.