Intelligent Light and FieldView

Uncertainty Quantification (UQ) at ASME V&V Symposium

Uncertainty Quantification (UQ) of CFD data.

Earlier this month at the ASME V&V symposium, Seth Lawrence, a graduate student at our University Partner Northern Arizona University, presented his Master's thesis work on "Verification, Validation and Uncertainty Quantification of Turbulent Twin Jets". Seth was advised by our own Dr. Duque who maintains an adjunct Faculty position @ NAU. This event was Seth's first outing at a major international technical symposium. He did a great job of presenting (and defending) his work to the leaders in the field of V&V/UQ, such as Oberkampf, Roy, Celik and Eca. The work was a Challenge Problem sponsored by the ASME V&V 30 Committee.  GREAT JOB SETH!    

In Uncertainty Quantification (UQ), engineers utilize standardized procedures such as the ASME V&V 20 and V&V 30 guidelines to account for the effects of probabilistic inputs to a CFD simulation to arrive at a non-deterministic answer. Through UQ, an engineer could state with 95% certainty answers to their design question while justifying and documenting how they arrived at their answer.

This challenge problem was the only one at the symposium to focus on UQ. It is a key area of interest for those seeking to capitalize on information gleaned from verification & validation work in new design studies. 

To combine CFD and UQ analysis, Mr. Lawrence created an automated workflow using FieldView to post-process the results of Fluent solutions and pass data to Dakota (Sandia National Lab) and then pass data from Dakota as input to Fluent in an iterative process. FieldView was also used to visualize the CFD data to create images for the presentation and 3D PDF to share results.

"Seth did a great job presenting to the leaders in the VVUQ community. His work was well received and cited by other presenters later in the symposium.  It was gratifying to hear statements among veteran symposium participants including 'This is the first time I've seen error bars on a CFD result, very impressive.'"

Earl P. N. Duque, PhD Manager of Applied Research at Intelligent Light

Mr. Lawrence noted that he enjoyed the chance to see how the experts in this field approached the benchmark ASME turbulent twin jet numeric model validation problem.

Professor Tom L. Acker from NAU and Intelligent LIght's Earl P.N. Duque served as advisers on the project.

​Mr Lawrence used the 3D PDF export capability in FieldView throughout the development of the CFD model, allowing him to easily share results of his grid convergence study (CGI) and in the observed order of the solver (p-obs). 3D PDF files are downloadable below.

"Throughout the development of the CFD model, I made good use of the 3D PDF generator that is available in the new FieldView 16.1 package. This was very helpful in the presentation of model results, and provided the ability to easily send detailed model results of large CFD datasets in the form of a small file via email, and the recipient does not need any special software to view the 3D PDF results - fantastic!"

Seth Lawrence, Northern Arizona University
Download 3D PDF. Numerical uncertainty in y-velocity. Adobe Acrobat Reader recommended for viewing. 3D PDF content is not supported within web browswers.
Download 3D PDF. Observed y-velocity. Adobe Acrobat Reader recommended for viewing. 3D PDF content is not supported within web browsers.

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