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

by Media | October 9, 2013 11:57 am

IL-ARG-CaseStudy-13-01_HighLift[1]Massive 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 [2]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.

Get the Whitepaper[3]

Endnotes:
  1. [Image]: http://blog.ilight.com/wp-content/uploads/2013/10/IL-ARG-CaseStudy-13-01_HighLift.pdf
  2. whitepaper : http://blog.ilight.com/wp-content/uploads/2013/10/IL-ARG-CaseStudy-13-01_HighLift.pdf
  3. Get the Whitepaper: http://blog.ilight.com/wp-content/uploads/2013/10/IL-ARG-CaseStudy-13-01_HighLift.pdf

Source URL: http://blog.ilight.com/whitepaper-using-fieldview-xdb-workflows-to-analyze-high-lift-drag-prediction-workshop-simulations/


Accelerating product engineering at smaller organizations

by Media | June 11, 2013 12:53 pm

Zipp Speed Weaponry[1]

Intelligent Light Case Study[2]:

A Lesson for Small Engineering and Manufacturing Companies[3]  –  How one small manufacturer leveraged high performance computing to increase revenues 100% and add 120 jobs to the Indiana economy.

SMMs need to innovate with limited resources. See how you can:

Learn how Intelligent Light delivered a combination of commercial CFD software and expert services to help Zipp Speed Weaponry harness the power of HPC enabled CFD.

Get the Case Study[4]

Related articles:

Technical details about the bicycle wheel study available from our CFD Visual Library[8]:

AIAA published papers on bicycle aerodynamics (Aerospace Sciences Meeting 2009-2011).  Available from our CFD Visual Library[8]:

 

Endnotes:
  1. [Image]: http://blog.ilight.com/wp-content/uploads/2013/06/zipp_corporate_logo.jpg
  2. Case Study: http://blog.ilight.com/wp-content/uploads/2013/06/CFDandHPC_SMM_Success.pdf
  3. A Lesson for Small Engineering and Manufacturing Companies: http://blog.ilight.com/wp-content/uploads/2013/06/CFDandHPC_SMM_Success.pdf
  4. Get the Case Study: http://blog.ilight.com/wp-content/uploads/2013/06/CFDandHPC_SMM_Success.pdf
  5. Intelligent Light receives prestigious HPC Innovation Excellence Award from IDC: http://blog.ilight.com/?p=479
  6. Cloud based HPC delivers for small organizations: http://www.ilight.com/images/visuallibrary/casestudies/2012-Dell_IL_Casestudy-10009914.pdf
  7. CFD Workflow Automation: http://blog.ilight.com/?p=504
  8. CFD Visual Library: http://www.ilight.com/en/component/visuallibrary

Source URL: http://blog.ilight.com/accelerating-product-engineering-at-smaller-organizations-2/


OVERFLOW Tips and Tricks

by Media | October 15, 2012 3:50 pm

Dr. Earl Duque, Intelligent Light’s manager or applied research and Overflow expert is presenting a tutorial at the Overset Grids Symposium.

[1]

Whitepaper: Tips and Tricks for Post-Processing OVERFLOW Results using FieldView 13

Synopsis: As an OVERFLOW and FieldView user for several years, I’d like to share with you several methods I’ve used for getting my work done in a more efficient manner. With the most recent version, FieldView 13, you’ll find new features and workflows that will benefit your work. From reading your data more completely using the new OVERFLOW direct reader to using our XDB technology to reduce your saved data, I’m sure you may find that at least one of the “Tips and Tricks” contained in this talk will be useful to your daily work.

Download our whitepaper  Tips and Tricks for Post-Processing OVERFLOW Results with FieldView 13[2].

Endnotes:
  1. [Image]: http://blog.ilight.com/wp-content/uploads/2012/10/IL-ARG-CaseStudy-12-01.pdf
  2. Tips and Tricks for Post-Processing OVERFLOW Results with FieldView 13: http://blog.ilight.com/wp-content/uploads/2012/10/IL-ARG-CaseStudy-12-01.pdf

Source URL: http://blog.ilight.com/overflow-tips-and-tricks/


Whitepaper: Slashing unsteady data size with XDB workflow results in huge productivity gains

by Media | January 6, 2012 12:00 am

Unsteady rotorcraft CFD analysis can generate mountains of grid and solution data, making transfer across networks time-consuming and often impractcal. Further the large data places a strain on available storage resources. XDB-based CFD workflow, made possible by FieldView 13, enables analysts to significantly reduce data size and better utilize remote HPC systems, achieving dramatic performance and productivity gains in the process. The means getting to answers faster and more cost-effectively than ever before.

This technical case study outlines XDB-based workflow approaches for an unsteady rotorcraft simulation. FieldView post-processed the transient data remotely, outputting XDB (eXtract database) files that reduced the size of the dataset from 36.4GB to 127.5MB – a reduction factor of 286. Transftering only these smaller files to a remote workstation for interactive review, high quality and extremely fast graphics allowed the analyst to view the time-dependent simulation results at more than 80 frames per second while sweeping through the data, rotating, panning and zooming.

 

Whitepaper: Slashing unsteady data size with XDB workflow results in huge productivity gains[1]

Endnotes:
  1. Whitepaper: Slashing unsteady data size with XDB workflow results in huge productivity gains: http://blog.ilight.com/wp-content/uploads/2012/01/IL-ARG-CaseStudy-11-01.pdf

Source URL: http://blog.ilight.com/slashing-unsteady-data-size-with-xdb-workflow-results-in-huge-productivity-gains-7/