Designed especially for neurobiologists, FluoRender is an interactive tool for multi-channel fluorescence microscopy data visualization and analysis.
Deep brain stimulation
BrainStimulator is a set of networks that are used in SCIRun to perform simulations of brain stimulation such as transcranial direct current stimulation (tDCS) and magnetic transcranial stimulation (TMS).
Developing software tools for science has always been a central vision of the SCI Institute.

Events on December 1, 2021

Guoning Chen, Associate Professor at University of Houston Presents:

Bridge the Geometric Representation and Physical Relevance in Flow Visualization

December 1, 2021 at 12:00pm for 1hr Password: sci_vis


Effective visualization is of paramount importance in helping domain scientists gain knowledge about the complex physical processes of various vector fields (especially flow) stemming from
many scientific and engineering applications and research. Over several decades of efforts, the visualization community has developed a wide range of techniques for the effective visual representation and analysis of various flow data. In this talk, I will provide a brief review on some recent advances in flow visualization. I will classify the techniques into two groups, i.e., (1) methods that focus on the extraction and visualization of certain geometric features/patterns of the flow and (2) approaches that aim to highlight physical characteristics of interest in the
flow. Each group of techniques has its advantages and disadvantages. Although most attention is given to the geometric aspect of the flow in the flow visualization community due to its intuitive representation, I will show that purely concentrating on the geometric behavior of the flow is not always sufficient for revealing the physical properties of the flow. To partially address that, we developed a few techniques that aim to connect the geometric representation of the flow with the relevant physical properties of the flow. The initial results of these techniques show that they may select or construct geometric representations (e.g., pathlines or iso-surfaces) that effectively highlight important physical characteristics of the flow. However, more work needs to be done to achieve a physics-aware visualization framework that supports the effective processing and interpretation of turbulent flows generated by modern CFD models.

Posted by: Nathan Galli