Intelligent Light and FieldView

Manager of Applied Research

Join Our Team! Scientific Data Visualization Engineer

Intelligent Light's Applied Research Group is hiring.  We are seeking candidates for the position of Scientific Data Visualization Engineer.

Intelligent Light's Applied Research Group (ARG) seeks computer scientists, engineers, mathematicians, physicists, technically minded people of all types to join our team. By joining the ARG Crew you'll become part of the team developing the next generation of commercial scientific and engineering simulation data management, post‐processing and visualization tools for exascale.

To learn more about the position or to apply during AIAA SciTech, come see us at  our booth #304.  

Download the Position Announcement for a description of the position and requirements.

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File Name: Position-Announcement-Scientific-Data-Visualization-Engineer_160422.pdf
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Join Our Team! Scientific Data Visualization Engineer

Intelligent Light's Applied Research Group is hiring.  We are seeking candidates for the position of Scientific Data Visualization Engineer

To learn more about the position or to apply during SC16, come see us at the SC16 Job Fair on Wednesday, Nov. 16 from 10-3 or at our booth #4421.  

Download the Position Announcement for a description of the position and requirements.

pdf
File Name: Position-Announcement-Scientific-Data-Visualization-Engineer_160422.pdf
File Size: 173 kb
Download File

Rotor Heads Unite! - AIAA Hover Prediction Workshop

Isometric View Comparison of Iso-surfaces of Q-Criterion=0.001 colored by w-velocity

UPDATE Jan. 2017: The Hover Prediction Workshop continues and new work was presented at AIAA SciTech in January, 2017.  

This month at SciTech, I participated in the AIAA special session on Hover Prediction, also known as the Hover Prediction Workshop. This particular workshop has special meaning to me because I started my career in CFD when I was a Research Scientist at the US Army Aeroflightdynamics Directorate at NASA Ames Research Center. At that time, I was part of a group of engineers tasked with producing the first full helicopter CFD simulation. That goal was achieved, but the community is still working to define the best practices for predicting helicopter hover. It has been well over 10 years since I've presented to this community, so it was like a homecoming having this opportunity to present to them again.

The workshop brought together seven participants submitting data on the same sample cases but using different meshes, different solver codes and different methods. The goal was to be able to compare all the data to maximize the knowledge extracted.​

Intelligent Light supported this effort by contributing time and expertise to develop a standardized, automated, post-processing workflow that facilitated dataset comparison, report generation and knowledge extraction for a diverse set of CFD results. 

Our solution allowed the users to upload data that was then run through the automated routines to normalize the data, produce XDB extracts and publish comparison images. Participants are able to explore the XDB data extracts with their own licensed version of FieldView or by downloading the free viewer: XDBview. Generating images and compact XDB files allowed all users to explore their data interactively on their local systems.

Our team included Intelligent Light Application Engineers Atsushi Toyoda and Michael Burklund, and Intelligent Light Applied Research Group member Christopher P. Stone. We also brought in R-Systems, our on-demand HPC computing partner. R Systems provided an anonymous ftp server where the participants could upload their data and worked with our team to implement the workflow using PBS and parallel servers. It was easy to set up and run the post-processing tasks on the remote HPC systems. I'd like to thank R Systems for their help and support on this project.

In addition to the workflow engineering, Intelligent Light ran two unsteady OVERFLOW simulations for the workshop. These were executed by Intelligent Light on a remote Cray supercomputer that provided the HPC capability to run multiple full transient solutions for the project. We'd like to thank our partners at Cray for their support of this Workshop.

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AIAA AVIATION 2015 - Working with large data of today and tomorrow

 This turbine blade simulation result was awarded "Most Quantitatively Descriptive Flow Visualization Animation" in the Visualization Showcase at AIAA Aviation 2015. The achromatic colormap enhances the presentation of the numerical differences.
--click image for animation

I attended the AVIATION 2015 meeting in Dallas last month. I had a great time meeting with colleagues, listening in on great papers and presenting my own work. The week started with my presentation for the CFD Visualization Showcase session where I was awarded the "Most Quantitatively Descriptive Flow Visualization Animation" which highlighted the animations and images from my paper "EPIC – An Extract Plug-In Components Toolkit for In situ Data Extracts Architecture". The paper was presented at the "Post-Processing and Model Reduction" session.

In both the animations and the paper, I made use of FieldView's achromatic colormaps. I've found that the "Achromatic Vision 1" colormap, easily selected from the new colormap selector in the colormap tab (no more hunting around for user defined colormaps!!!) does a much better job at highlighting flow features that I didn't see using the default Spectrum colormaps. I use the Achromatic Vision 1 almost exclusively now for all my visualizations.

In addition, I took part in a panel discussion "The Path to CFD Visualization in 2030" where we discussed our ideas regarding "Facing the Knowledge Extraction and Visualization Challenges of the NASA CFD 2030 Vision".  During this panel, I described how CFD analysts require the ability to simultaneously compute both very large simulations and large numbers of simulations. Code verification/validation and uncertainty quantification studies also drive the need for unsteady solutions consisting of  billions of grid points and large ensembles of non-deterministic solutions. These types of studies are enabled by: In situ data processing where the solver directly outputs FieldView surface extracts,  FieldView XDB workflow and the use of XDBview.

In order to extract actionable knowledge and create visualizations of these extensive datasets, my Applied Research Group is developing new capabilities for CFDers through our DOE sponsored research with the VisIt code and the Air Force Research Lab EPISODE project (the paper I presented at AVIATION2015).  In the coming months, I will be working with the other panelists on a paper that we'll present at SciTech2016.

XDBs files and XDBview were critical to this work.

Learn more about in-situ post-processing with XDB workflows:

Unraveling the Mysteries of Turbulence Transport in a Wind Farm

A joint paper with Prof. Sven Schmitz was just issued in the "Wind Turbine 2015" special issue of the online journal Energies.

This paper entitled "Unraveling the Mysteries of Turbulence Transport in a Wind Farm" is co-authored with Pankaj K. Jha 1, Earl P. N. Duque 2, Jessica L. Bashioum 1 and Sven Schmitz 1,*

For this project, we used FieldView XDB workflows to enable the investigation of "mysteries involved in the recovery process of the wake momentum deficit, downstream of utility-scale wind turbines in the atmosphere."  The "High-resolution surface data extracts provide new insight into the complex recovery process of the wake momentum deficit governed by turbulence transport phenomena. "