Scalable Knowledge Capture is Essential to Avoid CFD Bottlenecks
Image produced by Intelligent Light via XDB’s from an Air Force Research Laboratory (AFRL) sponsored Phase II SBIR, Contract FA8650-14-C-2439.
NASA’s CFD Vision 2030 Study details the many challenges that remain to routinely obtain accurate physics-based predictions of complex turbulent flows, including how to streamline and automate analysis to gain knowledge. Evolving HPC architectures will produce huge amounts of data, and future CFD technologies must be built to both realize the promise and avoid the pitfalls of this uncertain landscape. At Aviation 2015 this summer, Intelligent Light’s Dr. Earl Duque participated in an expert panel that discussed visions for post-processing and knowledge capture to meet the NASA 2030 CFD goals. Dr. Duque will be the lead author on the summary paper targeted for SciTech 2016.
Reduced Order Modeling Identified in the Study as an Enabling Technology
Reduced Order Modeling (ROM) can both compress and summarize, in a physics-oriented way, large unsteady CFD results and experimental data. Dr. Duque’s Applied Research Group at Intelligent Light has been successfully collaborating with BYU in an Air Force Research Laboratory-funded research effort to apply ROMs and Self-Organizing Maps (SOMs) to turbomachinery CFD. This is one example of how a partnership of government, industry and university researchers is working to make NASA’s 2030 CFD vision a reality.
Considered by many to be the critical element in preparing students to succeed in the modern economy, STEM education is important to you and your children.
Fueling knowledge development and creativity – Using FieldView XDBview, Darrin Stephens of Applied CCM, introduces students to basic aerodynamics concepts.
When his daughter and her classmates wanted to understand aerodynamics, Dr. Darrin Stephens of Applied CCM knew he could bring examples from his work to help. Dr. Stephens is a FieldView user and is accustomed to showing clients and colleagues characteristics of fluid flows he’s been studying using computational fluid dynamics (CFD). Using CFD simulation and FieldView gave him a powerful way to help students see what they can’t directly observe, a problem engineers face all the time.
The students are participating in a human powered vehicle competition. They recognized that as their vehicle moved faster, the affects of airflow could limit the speed they could attain and maintain. They asked Dr. Stephens to help them understand some basic aerodynamic concepts. He responded by bringing real-life CFD solutions to the classroom and sharing those results with XDBview.
“As part of my lesson I used FieldView XDBview (latest version is fantastic by the way!) with the result from my previous V8 super car simulations to help explain & demonstrate drag, induced drag, streamlines etc.” – Darrin Stephens, Applied CCM
Air is a unseen force acting on objects in motion. CFD allows students and engineers alike to see airflows and effects they cannot directly observe.
XDBview allowed Dr. Stephens to show moving airflow and explain the impact on a racecar, effects that are similar to what the students would need to consider. Having used FieldView to post-process his unsteady OpenFOAM simulation solutions, he created lightweight XDB files and used XDBview to interactively explore the flow solution and explain aerodynamics to the students. Because the XDBview session was fully interactive, they were free to ask questions and see new representations of the flow field.
Fluid flows and aerodynamics surround us but students need some training to look for them and to consider them when pursuing projects like their human powered vehicles. Demonstrations such as Dr. Stephens’ shared help students see what they normally can’t, understand new phenomena and send them out of class better prepared to become skilled observers of fluid mechanics when they can see its effects during their daily lives.
After the demonstration, the students asked for videos they could continue to watch and share with their parents. The videos on this page show the CFD simulation results from a flow study of a Holden VE Commodore V8 supercar.
Darrin Stephens is a founder and managing director of Applied CCM, an engineering software development company with offices in Australia and Canada.
Recently posted videos created by Dr. Darrin Stephens of Applied CCM provide an example of how FieldView is used in the day to day work of engineers. Applied CCM is an engineering software development company with deep expertise in applying OpenFOAM to study fluid mechanics for its clients. Dr. Stephens uses FieldView to ensure productivity and to clearly present results to his clients.
The vehicle’s surface has been colored by the local pressure results (−3000 to 0 m2/s−2) while streamlines show airflow characteristics. FieldView image courtesy of Applied CCM Pty Ltd.
A good video sequence can be a powerful way to show key flow characteristics and patterns but the views and content are fixed when a movie is made. Applied CCM went a step further and used XDBview to interactively explore datasets. XDBview users freely change views, look at different scalar values, apply thresholds or add/remove display elements like streamlines. Having this capability in a free viewer using compact datasets allows Dr. Stephens to share insights with clients or give individuals the ability to freely explore and interact with complex data on their own.
In this image, displayed vectors show the direction the vehicle surface needs to be moved to increase the lift. The vectors are colored by the absolute value of the z component of the shape sensitivity limited to a maximum value of 5. FieldView image courtesy of Applied CCM Pty Ltd.
The case studies quantified the sensitivity of designs to pronounced features such as areas of large curvature, sudden changes and sharp edges.
New equations were developed to preserve time symmetry for turbulent flows. First published in the SAE paper, the new computational approach was implemented using the OpenFOAM library.
Work presented at the AHS 70th Annual Forum demonstrates that extracts are invaluable for both data reduction and quantitative analysis.
In their paper, “Turbulence Transport Phenomena in the Wakes of Wind Turbines”, Jha et al, show that data reduced by three orders of magnitude still retains full fidelity enabling quantitative analysis not possible before.