CFD V&V Case Resources

This list is from a discussion on the CFD group on LinkedIn.

• CFDOnline Validation and Test Cases: wiki with problem descriptions and some calculation results but not case files / grids (on the handful that I checked)
  
• ERCOFTAC Classic Collection: "The database has undergone some re-structuring and expansion to include, amongst other things, more details of the test cases, computational results, and results and conclusions drawn from the ERCOFTAC Workshops on Refined Turbulence Modelling. At the moment, each case should contain at least a brief description, some data to download, and references to published work. Some cases contain significantly more information than this." Registration required.
  
• LaRC Turbulence Modeling Resource: " The objective is to provide a resource for CFD developers to obtain accurate and up-to-date information on widely-used RANS turbulence models, and verify that models are implemented correctly. This latter capability is made possible through "verification" cases. This site provides simple test cases and grids, along with sample results (including grid convergence studies) from one or more previously-verified codes for some of the turbulence models. Furthermore, by listing various published variants of models, this site establishes naming conventions in order to help avoid confusion when comparing results from different codes."
  
• CFD and Coffee: a list of resources focused on compressible RANS V&V.
  
• cfd-benchmarks: benchmarks focused on room air distribution
  
• Saturne Test Cases: a list of test cases for Code Saturne, which also links the Working Group 21 AGARD database among others
  
• NPARC Alliance Verification and Validation Archive: grids available, but not much grid convergence info
  
• Vassberg's NACA 0012 Grids: Hegedus Aero code-to-code calcs based on 2009 AIAA paper / grids for NACA 0012
  

I added the link to a Hegedus Aero page detailing his code-to-code and grid convergence results based on a previous AIAA paper and those same grids. The AIAA paper that page is based on is worth a read.

SU2 and OpenMDAO Joint Workshop

Here's an announcement for an exciting workshop combining the open source computational fluid dynamics code SU2 with the open source optimization framework OpenMDAO.

Dear Colleagues,

This is a friendly reminder about the OpenMDAO and SU2 joint workshop on Sept.30 - Oct.1 in Durand 450 (Stanford University). So far, we have had great interest for both in-person, and virtual attendance to the event and we are looking forward to a great workshop. There is still room for more participants and we encourage you to join us for as much workshop as you can. As a reminder, no experience with the software is necessary.

If you plan on attending in-person or virtually, all participants should register at the SU2 homepage:
http://su2.stanford.edu

For virtual attendance, you must additionally register for the online webinar at the following locations:
Day 1: https://attendee.gotowebinar.com/register/7114168239445654785
Day 2: https://attendee.gotowebinar.com/register/208563415407826177

OpenMDAO is an open-source framework for Multidisciplinary Design, Analysis and Optimization (MDAO). Written in Python, it functions to integrate analysis tools into a single design environment allowing for the investigation of engineering designs and optimization of designs subject to user requirements.

SU2 is an open-source numerical PDE solver that can be used to solve the equations of fluid motion. SU2 has been used to simulate a range of fluid including wind turbines, supersonic business jets, and hypersonic re-entry vehicles.

These powerful codes are suitable for general purpose applications. They have been downloaded more than ten-thousand times and have a continually growing footprint in a growing field of research. Because these codes are freely available and can be modified to suit specific needs, they can be used as part of countless research problems.

If you’re interested in multi-physics simulations applied to design, this is the workshop for you!

Each day will have a morning session to introduce the software packages and an afternoon session to give hands-on experience working with the codes. These sessions will focus on linking OpenMDAO and SU2 for specific multi-disciplinary problems. The best utilization of the two packages will be awarded an iPad!. The deadline for the competition (only on-site workshop attendees) will be on Thursday afternoon (October 3rd) and the winner will be announced on October 4th in the SU2 website.

The agenda for the workshop is attached. Food will be provided both days.

We hope you are able to join us for this exciting and engaging event!

Cheers,
The SU2 and OpenMDAO development teams

I wish I could spare the two days to participate virtually; looks like a really good event.

Update: Workshop Materials

• OpenMDAO Introduction, Installation, and Quick Start
  
• SU2 Introduction and Installation
  
• SU2 Advanced Analysis Topics (presentation)
  
• SU2 Advanced Analysis Topics (mesh and configuration example files)
  
• Shape optimization using SU2 (presentation)
  
• Shape optimization using SU2 (ONERA M6 files)
  

Update: videos and more from the workshop.

SCRAMSPACE: Launch Anomaly

Tough day at Andoya Rocket Range for University of Queensland SCRAMSPACE team. My heart goes out to these guys; they put a lot of good time, effort and smarts into their experiment.

Here's the official statement:

“The rocket carrying the scramjet launched at 3pm (Norwegian time, 11pm Brisbane time), however the payload failed to achieve the correct altitude to begin the scientific experiment as planned.

“The SCRAMSPACE payload, according to our data, was operating perfectly and performed extremely well before and during the launch, and we received telemetry data all the way into the water.

“Unfortunately the failed launch meant we could not carry out the experiment as planned.”

“The team is very disappointed. The project represents a lot of time, effort and money by a committed consortium of partners and sponsors.”
University of Queensland Hypersonics Chair Professor Russell Boyce

GE Jet Engine Bracket Challenge: Phase I Winners

I wrote previously about some neat entries in the GE Engine Bracket Challenge on GrabCAD that used topology optimization. As reported by GE, they have picked their winners from Phase I. Phase I consisted of simulating the submitted parts in several different load cases and ranking them by how much weight the designer was able to shave off.

Located around the world, finalists include:

• Ármin Fendrik, based in Hungary, is a third-year university student and this entry is among his first 3D printing designs.
• Thomas Johansson, Ph.D, based in Sweden, is a consultant for a Swedish hyper-car manufacturer and is a champion snowmobile drag racer.
• Nic Adams, based in Australia, supported the installation of a pathology lab automation system in a Sydney hospital, which includes a robotic handling system that helps analyze hundreds of test tubes each day.
• M Arie Kurniawan, based in Indonesia, is co-founder of an engineering firm that provides high quality mechanical engineering, design optimization and product design services.
• Sebastien Vavassori, based in the United Kingdom, is a stress engineer for a leading European space manufacturer and service provider.
• Piotr Mikulski, based in Poland, works as a rapid prototyping systems specialist for a Polish-Swiss joint-venture that provides industrial and machining services.
• Andreas Anedda, based in Italy, is a postgraduate university student and holds three patents.
• Alexis Costa is based in France.
• Mandli Peter is based in Hungary.
• Fidel Chirtes is based in Romania.

These winner from Phase I will have their designs "printed" in Titanium and then tested by GE to determine the winners for Phase II.

Falcon UAV Air Support in Colorado

Fellow AFIT-alum Chris Miser doing good stuff in the Civil UAV market. Airpower to the People!

In the wake of the recent floods in Colorado, Falcon UAV has spent the last three days providing volunteer aerial services to the Boulder County Emergency Operations Center (EOC) and the Incident Management Team (IMT). On Thursday afternoon while all National Guard aircraft were grounded due to weather Falcon UAV was proud to have been the only aircraft that was able to take flight to support the flood efforts in Lyons.

Falcon UAV Supports Colorado Flooding Until Grounded by FEMA

ProtoLabs Design Tips

Here are pdfs for 9 volumes of ProtoLabs Design tips. They do low volume injection molding and rapid three-axis CNC machining.

Volume 1 — Topics include: draft, radiused corners, material choices, shut-offs, texture...

Volume 2 — Topics include: side actions, naming files, text on parts, wall thickness...

Volume 3 — Topics include: hot tips on gates, parting lines, clips, shut-offs, materials matrix...

Volume 4 — Topics include: fun with cams, fillets, living hinges, ultrasonic welds, sink...

Volume 5 — Topics include: rotational draft, knit lines, square corners, prototyping...

Volume 6 — Topics include: bosses, prototyping processes, attachments, mold flow...

Volume 7 — Topics include: texture, pickouts, bump-offs, ejector pins, parting lines...

Volume 8 — Topics include: gates, living hinges, designing lenses, finishes, transparent parts, and more...

Volume 9 — Topics include: designing clips, elimination of unnecessary material, text, crush ribs, bridge tooling, injection molding gears…

SU2 Now on Git: Build and Install Latest on Fedora

As I wrote previously the Stanford University Unstructured (SU2) code is now available on git hub. Here's the steps to get the latest code, build and install it.

• Use the git client to clone the repo:
  
git clone https://github.com/su2code/SU2

  
• Follow the 'from source' install instructions for your system. It is should look something like:
  
./configure
make
make install

  This will give you (after a little help from the kindly devs) a plain-Jane version of SU2 for serial computations, without CGNS or Metis (graph partitioning) support.
  

Happy number crunching!

3-D Printing in DoD: Who's Dragging Their Feet?

I found this article, Why is the Pentagon Dragging Its Feet on 3D Printing, by way of Small Wars Journal. It has some interesting information. The Army is deploying mobile Fab Labs, which seems like a mini MIT FabLab in a shipping container. I think this is a really neat idea. How this can be characterized as feet dragging, I'm not sure. The feet dragging accusation is based on some hand-waving from an article on Disruptive Thinkers, and another article that seems to be worried that there is no Pentagon overlord in charge of an additive manufacturing strategy:

With possible dwindling budgets on the horizon, a clear strategy and cohesive approach is essential to create efficiencies in the area of research and development as well as eliminating duplicative efforts. In order for DoD to take advantage of what is anticipated to be an explosion in the commercial sector within the next ten years, the Department must take an active approach, partnering with the private sector to keep up with this relatively nascent technology and shaping/guiding it towards the desired end state the department has in mind.

One step towards a clear strategy and cohesive approach is for DoD to designate an AM Czar within the Department. They could serve as a single point for all things AM and not the myriad of technical advisory boards that currently exist. This office could then work with policy makers to execute and monitor a strategy which will allow DoD to take full advantage of this technology. Logically, this office would interface directly with the National Additive Manufacturing and Innovation Institute (NAMII) as DoD's representative
3-D Printing Revolution in Military Logistics

I think an "additive manufacturing Czar" sounds like a terrible idea (so I'm sure it will secure funding for some beltway bandits to do a study). I know my recent success with qualifying a particular additive manufacturing process and supplier for use in 3D printing wind tunnel models did not need a Pentagon king-pin to tell me about DoD's strategy for additive manufacturing. Using this technology just made sense as a way to solve my problem: get a complex wind-tunnel model rapidly, and at an affordable cost. I did not receive top-down direction or guidance to use AM, I simply took the initiative to solve my problem. After reading that article I'm left wondering, just how exactly is waiting on direction from the very heights of the bureaucracy supposed to lead to innovation?

UberCloud HPC Experiment

I think I originally saw a link for the UberCloud HPC Experiment on one of the "This week in CFD" posts on Another Fine Mesh. It is a market research exercise to see how people would use cloud computing (platform as a service, software as a service) for their high performance computing workloads. The focus of the experiment is on the difference between enterprise work-loads and high-performance or scientific computing work-loads. Here's some of the introduction describing the research:

We found that, in particular, small- and medium-sized enterprises in digital manufacturing would strongly benefit from HPC in the Cloud (or HPC as a Service). The major benefits they would realize by having access to additional remote compute resources are: the agility gained by speeding up product design cycles through shorter simulation run times; the superior quality achieved by simulating more sophisticated geometries or physics; and the discovery of the best product design by running many more iterations. These are benefits that increase a company’s competitiveness.

Tangible benefits like these make HPC, and more specifically HPC as a Service, quite attractive. But how far away are we from an ideal HPC cloud model? At this point, we don’t know. However, in the course of this experiment as we followed each team closely and monitored its challenges and progress, we gained an excellent insight into these roadblocks and how our teams have tackled them.
UberCloud HPC Experiment: Compendium of Cases

Each of their teams has an industry user, a resource provider, a software provider, and an HPC expert.

This part on applications is interesting:

By far, computational fluid dynamics (CFD) was the main application run in the cloud by the Round 1 and Round 2 teams – 11 of the 25 teams presented here concentrated their efforts in this area.

I think this really helps make the case for open source CFD codes:

In addition to unpredictable costs associated with pay-per-use billing, incompatible software licensing models are a major headache. Fortunately many of the software vendors, especially those participating in the Experiment, are working on creating more flexible, compatible licensing models, including on-demand licensing in the cloud.

Paying a per-core license makes no sense for these large jobs.

One of the interesting use cases was from Team 30 who used an open source stack (Elmer, CAELinux) on top of Amazon Web Services Elastic Compute Cloud.