Accelerating the Post‐Processing of Large Scale Unsteady CFD Applications via In SituData Reduction and Extracts
Dr. Earl P.N. Duque
Manager of Applied Research, Intelligent Light
Tuesday, April 14th, 2015
Lehman Building Room 272
Writing, storing, moving and post‐processing vast unsteady datasets can interfere with an engineer’s interpretation and reporting of results. This seminar will present ongoing research to develop new methods designed to extract and reduce large unsteady CFD derived volumetric data. In‐Situ data extraction whereby sub‐setting and segmenting the volume data using data extraction and analysis libraries directly integrated within the solver codes themselves is the first step. To further reduce the amount of unsteady CFD extract data written to disk, methods such as Proper Orthogonal Decomposition may be used to reconstructed the solution data within a given error band. This seminar will present preliminary research and how the CFD could use these techniques to analyze their large‐scale CFD solutions.
BIO: Dr. Duque manages the Applied Research Group at Intelligent Light, the makers of the leading CFD post‐processing software FieldView. Previous to Intelligent Light, he was a tenured Professor of Mechanical Engineering at Northern Arizona University. Prior to his time at the university, he was a Research Scientist for the Army’s Rotorcraft CFD Applications Group located at the Numerical Aerodynamic Simulation Facility at NASA Ames Research Center. His current research focuses upon the development of large scale data management techniques for multi‐physics simulations. He has been awarded the Lichten Medal from the American Helicopter Society for his pioneering CFD studies on the BERP helicopter rotors, the Army Superior Civilian Service Medal for his lead role in the use of CFD to study and alleviate vibratory load problems on the Apache‐Longbow and Comanche Helicopters and is an Associate Fellow of the AIAA.
I had the honor and pleasure to participate in the Atmosphere to Electrons Workshop hosted by the Department of Energy, Office of Energy Efficiency and Renewable Energy. The focus of the initiative is on the use of computational simulation to improve understanding and performance predictions from the microscale to the mesoscale.
FieldView image published in paper: “Turbulence Transport Phenomena in the Wakes of Wind Turbines”, Earl Duque, Intelligent Light; Pankaj Jha and Jessica Bashioum and Sven Schmitz, The Pennsylvania State University
The event brought together leaders from the wind energy community including National Labs, Universities and Industry. The purpose was to map out the direction for simulating the performance of a wind turbine farm; capturing the temporal and spatial scales from meso-scale (kilometer and hours) down to the airfoil boundary layer scales (micron and milliseconds). Morning and afternoon sessions began with a topical plenary talk followed by working groups focused on the computation and modeling needs at different scales such as Park Scale, Turbine Scale and Airfoil Scale.
Wind Farm – FieldView image as published in “Wind Farm Simulations Using a Full Rotor Model for Wind Turbines”, J. Sitaraman, D. Mavriplis, E. Duque AIAA Paper 2014-1086
For me, it was clear that it will be essential to include in-situ data analysis methods and file I/O standards in order to work with the tremendous volumes of data that will be created and processed. This was recognized by many at the meeting. The use of in-situ methods with FieldView and VisIt offers solutions to those grappling with the current data analysis bottlenecks.
With the high-caliber people from government, academia, and industry converging on this challenging problem, the A2E initiative is making progress toward vast improvements in the understanding of the complex physics of wind flowing into and through wind farms. DOE sees the potential to improve wind farm efficiency by 20% while drastically reducing operating costs for wind energy producers.