Views from Intelligent Light
Earl Duque

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

Turbo image/animation from AIAA Aviation 2015

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:

Earl Duque

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. “

Roger Rintala

Reduce Data Three Orders of Magnitude while Retaining Full Fidelity

WindFarmClose

Work presented at the AHS 70th Annual Forum demonstrates that extracts are invaluable for both data reduction and quantitative analysis.

 

In their paper, “Turbulence Transport Phenomena in the Wakes of Wind Turbines”, Jha et al, show that data reduced by three orders of magnitude still retains full fidelity enabling quantitative analysis not possible before.

 

See the movie created for this project

Review the paper

 

 

Earl Duque

PAR CFD 2015 Meeting – Reporting on the push toward extreme scale CFD

Movie Still

The image shows volume rendering of AVF-LESLIE results for a turbulent planar flame front.
Click to view animation

 

Last month at the PAR CFD 2015 meeting in Montreal, Canada, I presented a paper entitled “The Impact of In Situ Data Processing and Analytics upon Scaling of CFD Solvers and Workflows“.

 

This work is based on research under our Department of Energy Phase II grant (Award Number DE-SC0007548) and also work under a DOE grant, through the Office of Advanced Scientific Computing Research (Award number DE-SC0012449).

 

The latter grant is an effort led by Wes Bethel at Lawrence Berkeley National Laboratory in collaboration with Argonne National Laboratory, Georgia Tech and Kitware. In this work we used the AVF-LESLIE code from Prof. Suresh Menon’s lab at Georgia Tech, instrumenting it with VisIt/Libsim.

 

The goal is to determine the overhead associated with in situ processing in comparison to conventional file based volumetric post-processing at scale. For this paper, ‘at scale’ means on the order of 60,000 cores.

 

Next year we plan to be at 120,000 cores. To date, AVF-LESLIE has been instrumented with VisIt/Libsim and is now able to directly output FieldView XDB files using 40,000 cores and we’re working on new in situ data analysis pipelines that can only be performed in situ.

 

I enjoyed the meeting and learned a lot about the challenges as we all work toward exa-scale CFD simulations.

 

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