Intelligent Light and FieldView

ScienceNode: Wind Farm CFD by University of Wyoming and Intelligent Light

In Situ processing enables full wind farm simulation by reducing file size from 234TB to under 1TB

Excerpted from an article originally published on ScienceNode. Read the complete article

Researchers at the University of Wyoming (UW) and Intelligent Light are working hard to improve the efficiency of wind energy. One aspect they're currently investigating is the use of computational fluid dynamics (CFD) to simulate, predict, and improve the performance of wind farms.

CFD uses supercomputers to model the behavior of fluids such as air or water over moving surfaces. In this instance, UW professor of mechanical engineering Dimitri Mavriplis and Earl Duque at Intelligent Light turned to CFD to study how wind currents transform after coming into contact with a moving turbine's blades in the context of a complete wind farm.

Using the Cheyenne supercomputer at the National Center for Atmospheric Research (NCAR)-Wyoming Supercomputer Alliance, Duque and UW researchers Mavriplis, Michael Brazell and Andrew Kirby were able to model wind farms in unique ways. 

What really makes their research unique is the use of in-situ processing. Unlike traditional visualizations produced from stored data, in-situ processing means that visualizations and analysis can be created as a simulation takes place, without writing to disk.

In-situ processing eliminates file transfer bottlenecks, allows increased fidelity, and faster turnaround. 

"In-situ has helped reduce the amount of 3D data that we need to store. Just the restart files take 10 TB on a 12-hour run. Automation has gone way up; we have scripts that go straight from simulation to animation. Also, in-situ has helped with debugging—I don't need to pull down 3D data, and I can just use slices, save those to a FieldView XDB file, and then view that on my local machine."

Michael Brazell, University of Wyoming

Excerpts trom an article was originally published on ScienceNode.org. Read the original article.

CFD images courtesy of Prof. Dimitry Mavripilis and Andrew Kirby, University of Wyoming, an Intelligent Light University Partner.
 
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Cranfield University - Teaching Fluid Dynamics with FieldView

Cranfield University has deployed FieldView in their Computational Fluid Dynamics (CFD) program for Master and PhD students. Dr. Antonis F. Antoniadis is the course director of the MSc in CFD at Cranfield University and also the curriculum designer:

The Masters program will provide a cohort of 50 students with access to and lessons in the use of FieldView for interpreting CFD.

MSc in CFD students at Cranfield University learn the fundamentals of CFD i.e. numerical methods fluid mechanics and heat transfer, programming and high performance computing (HPC) as well as data analysis. The course uses CFD codes like Fluent, STAR-CCM+, Pointwise, open-source and in-house solvers. Students develop their own solvers and use Fieldview to debug their codes and interpret results. The course is also focused on the applications of CFD for various industries including aerospace, automotive, energy and discrete manufacturing. The students are using state-of-the-art HPC facilities to solve industrial-scale problems and employ FieldView to visualize and post-process data.

"FieldView is another excellent addition to our CFD software envelope within our course. FieldView makes post-processing and visualisation tasks much easier than ever before. The intuitive interface also enables students to work with complex CFD data very quickly. We are thrilled by the support of AC&E and the quality of the FieldView workshop delivered by Anthony Mosquera"

Dr. Antonis F. Antoniadis
Director of MSc in Computational Fluid Dynamics at Cranfield University

Course info for: Computational Fluid Dynamics MSc

Support for the program is provided through the Intelligent Light University Partners Program and Applied Computing and Engineering (AC&E) who provides local training & support. 

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