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Whitepaper: Massive CFD Data Handled Quickly Without Compromise – Maximize Your CFD Investment

IL-ARG-CaseStudy-13-01_HighLiftMassive CFD Data Handled Quickly Without Compromise – Maximize Your CFD Investment
Real World Example Case: Analysis From High Lift Drag Prediction Workshop Simulations.


The 2013 AIAA High Lift Production Workshop asked participants to develop and run multiple high-lift prediction simulations and compare results.  Intelligent Light used an engineered CFD workflow to complete the full set of simulations and produce the comparisons using a single part-time researcher.  The engineered workflow enabled IL to be the only participant who ran the entire simulation set rather than scoping down the project to  limit case and data volume at the front end. An example of CFD without compromise!

 “Cray systems provide central computational resources at commercial, academic and government centers around the world; often serving distributed user communities.  Efficient tools to analyze CFD simulation results and enable the remote user community are essential.   Management, automation, and remote visualization capabilities in FieldView are a proven technology for post processing whether the data is across the room or across the country. Cray is pleased to work with Intelligent Light to ensure this is a robust and efficient solution.

Per Nyberg, Director of Cray Business Development

This whitepaper provides both a case study and tutorial for working with large CFD data.  The author presents how the CFD flow solver, OVERFLOW2, and Intelligent Light’s CFD post-processor, FieldView, was used in a remote solving and remote post-processing environment to analyze solutions for the AIAA High Lift Drag Prediction Workshop.  Using the OVERFLOW2 solver from NASA, over 63 solutions were obtained on a remotely located Cray XE6 system.  The large volumes of data were stored on the remote system where FieldView Parallel was used in batch and interactive modes to interrogate the data.  An extract workflow was applied to create FieldView surface extract databases (XDBs), line extracts, and streamlines, reducing the data by a factor of 275,  The extracts were transferred to local laptop where FieldView FVX scripts, together with GNUplot, were used to automatically generate comparisons between the cases and against experimental data. This paper summarizes the work and provides examples for using FieldView, FVX and XDB workflows to automate the post-processing of large scale simulations.

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