Intelligent Light and FieldView

Come See Us at AIAA SciTech 2018!

We look forward to AIAA SciTech all year because it's a great place to meet with you, our clients and partners, to learn about what you are working on, find out about your needs and to share news and updates on our products and services.

Please join us in conference sessions, workshops and in our booth to learn how we are helping industry leaders like you to remove data bottlenecks and reduce costs with our FieldView products, engineered CFD workflows and advanced research initiatives.

Plus this is your first chance to get a demo of our new release: FieldView 17.

UPDATE: Join Steve at our In-booth presentation summarizing his presentation for the Future CFD Technologies Workshop
Tuesday, 9 January 2018 at 7:00 PM (booth #201)

Request a meeting

Conference Sessions and Workshops

 "Visualization and Data Analytics Challenges of Large-Scale High-Fidelity Numerical Simulations of Wind Energy Applications"
Andrew C. Kirby, Zhi Yang, Dimitri J. Mavriplis, Department of Mechanical Engineering, University of Wyoming, Earl P. N. Duque, Brad J. Whitlock, Intelligent Light.

Future CFD Technologies Workshop
Sat & Sun 6–7 January 2018 (agenda)
8:00 AM - 5:00 PM

Steve M. Legensky, Founder and General Manager, Intelligent Light

"The Tail Wags the Dog – How In-Situ Processing and Data Modeling Will Enable Knowledge Extraction at Scale to Address the 2030 CFD Vision" 

Sun - 7 January 2018
03:30 PM -04:00 PM

Typically, CFD data analysis and visualization is an afterthought and at the back end of "the dog"; in order to fully exploit the knowledge contained in simulations at exascale, the tail needs to wag the dog. Simply writing ever larger files containing mesh and results will not scale when it comes to extracting knowledge from simulations. Inspired by early NASA researchers and the Department of Energy's national labs, mechanisms for processing results directly via "in situ" or "in transit" techniques are adopted for large scale CFD workflows. This talk will review applications of those technologies and how they may impact our ability to achieve the 2030 goals in knowledge extraction and Uncertainty Quantification. In addition, data modeling and analysis may play a key role in directly extracting the knowledge buried in large unsteady CFD simulations and experiments. We will explore where further developments are needed to fully exploit techniques such as Dynamic Mode Decomposition, Machine Learning and other Reduced Order Model methodologies.

Earl Duque, PhD Manager of Applied Research, Intelligent Light

Visualization Session MVC-4
Wed - 10 January 2018
9:30 AM - 12:30 PM; Tampa 1

"Visualization and Data Analytics Challenges of Large-Scale High-Fidelity Numerical Simulations of Wind Energy Applications"
Andrew C. Kirby, Zhi Yang, Dimitri J. Mavriplis, Department of Mechanical Engineering, University of Wyoming, Earl P. N. Duque, Brad J. Whitlock, Intelligent Light.

Wed - 10 January 2018
10:00 AM - 10:30 AM

Visualization and data analysis techniques are explored to alleviate big-data problems found in simulations regarding wind energy applications including full wind farm simulations with blade-resolved geometries for wind turbines. Techniques for streamlining workflows for large-scale simulations are investigated and instrumented in the W2A2KE3D1 software framework. In-situ analysis through Libsim is instrumented and used to export data of high-density wind turbine simulations that is post-processed using FieldView and VisIt.

Special offer for users of CONVERGE