What do you see are the biggest challenges facing CFD in the next three years?

I see several bottlenecks in our ability to design, by computational means, the aerospace systems of the future:

1. Improved physical models including unsteadiness (turbulence, transition, acoustics, structures, combustion)
2. Seamless multi-disciplinary/multi-physics coupling at high fidelity
3. Harnessing the phenomenal computational power that will be available (in all steps of the analysis/design process, from mesh generation and adaptation, to solution and post-processing) and
4. Ensuring that both numerical errors and model-form uncertainties are appropriately quantified and handled.

John: Is that a prioritized list? If it is I’m glad to see turbulence modeling listed higher than meshing. Seriously, you include meshing from the standpoint of computational efficiency rather than issues of dealing with CAD or accuracy. How did you reach that conclusion?

Juan: They are not in any particular order: all of these challenges will need to be met (in the next 10-15 years) if we are to bring CFD to the next level. The issues in meshing and geometry interfaces will be fundamental, particularly for streamlining industrial processes. Ready-to-mesh CAD geometry, the ability to drive the design parametrically, and effective mesh adaptation procedures (to reduce numerical error) in highly-parallel environments must be available to accomplish significant improvements in efficiency.

What are you currently working on?

Our lab focuses on developing design methodologies for multi-disciplinary aerospace systems. We are currently working on uncertainty quantification of hypersonic air-breathing propulsion (at our PSAAP Center), low-boom supersonic aircraft, and high-speed re-entry vehicles, among other things. Over the past two years, a good portion of our lab, led by Dr. Francisco Palacios, has developed an open-source suite of tools for the analysis and design of problems governed by PDEs. The suite is named SU² (Stanford University Unstructured) and most of the applications so far can be found in the field of Computational Fluid Dynamics. SU² includes a flow solver, an adjoint solver to compute sensitivities, the ability to adapt the computational mesh, and both shape parameterization and optimization capabilities (all scripted using the Python language) so that users can analyze, optimize, and design out of the box. We have seen more than 4,000 downloads since the first release, and more than 40,000 visits to the SU² website (su2.stanford.edu). Our hope is that engineers and researchers around the world will contribute to developing additional capabilities in the source code so that design optimization capabilities can be accessed by anyone in the world.

SU2 solution for the DLR-F6. Mesh from Pointwise.

John: Tell me more about how you arrived at the decision to release SU² as open source. There are a lot of open source CFD codes out there, with OpenFOAM the most obvious example. How does SU2 fit into that universe, who is your target user, and where do commercial tools fit into that world?

Juan: That is an excellent question: why another open source solver? Why not just start with OpenFOAM and contribute to it? There are several reasons that I list below:

1. Our main area of interest requires the ability to (a) solve compressible flows over a very broad speed range, and (b) the ability to do design optimization using gradient-based algorithms. We could not find these capabilities in other open source solvers/frameworks.
2. Frankly, believe it or not, in a university laboratory we are also very concerned about the efficiency with which students pursue their own research projects,Must every student write his/her own solver from scratch? This is very inefficient. Can you leverage large portions of the infrastructure and develop the ones you need? Thus SU².
3. Our work involves complex configurations of industrial interest and the multi-block (face matched) mesh generation process in our previous solver, SUmb, was slowing our students down. A focus on unstructured meshes made sense.
4. We have been pursuing more multi-disciplinary problems that required additional equation sets (PDEs) to be solved. Leveraging the infrastructure that already existed was very helpful.

Overall, the effort to develop a new solver and optimization environment is beginning to pay off: several students in our group are sharing the development effort and the benefits of more rapid testing of research ideas.

Mach contours around a launch vehicle. CFD by SU2, mesh by Pointwise.

How did you get to be where you are today?

I would say it has been a combination of timing, luck, and hard work. I started my freshman year of college at the School of Aeronautical Engineering in Madrid, Spain. I then transferred to MIT, where I completed a bachelor’s degree. Then a master’s and Ph.D. degrees at Princeton University and, since 1997, I have been teaching at Stanford University (Department of Aeronautics & Astronautics). When I first left Spain for Cambridge, MA, I expected it to be for a period of one year. Twenty-five years later I am still around!

Who or what inspired you to get started in your career?

I am and have always been an aerospace nut. As a child, I wanted to be an astronaut. But at the sweet age of eight I realized that (a) I wore glasses, and (b) I lived in a country without a space program! I decided that the next best thing was to design the vehicles that flew in our atmosphere and that went into orbit. There were lots of people that inspired me to pursue my dreams: teachers in school, professors in college, fellow students, colleagues in industry, even a neighbor who built the most phenomenal R/C aircraft you have ever seen!

John: I find a lot of CFD people of a certain vintage were inspired by the space program. What effect do you think the current state of the U.S. space program has on tomorrow’s engineers? For example, I’ve listened to academic briefings that directly blame cancellation of the Space Shuttle for a drop in aerospace engineering enrollment.

Juan: Space and aeronautics programs in the U.S. (science and exploration, manned and robotic, space and aeronautics, government and private industry, applied and fundamental research) continue to inspire new generations of scientists and engineers. When you hear about the successful landing of the Mars Science Laboratory and the adventures of the Curiosity rover on the surface of Mars, you cannot help but feel proud of being a member of the human species! Why? Because these are wonders of science and engineering the sole existence for which is to improve knowledge and the quality of life for everyone on Earth. Though the end of the Space Shuttle era may have brought some sadness to many of us, the truth of the matter is that every week I hear of something new going on that can be as powerful a motivator as the Space Shuttle was in its time.

More CFD goodness from SU2.

What advice do you have for young people entering the field today?

Do not ever stop pursuing your dreams, and do not ever let anyone tell you cannot accomplish something. Think, plan, and try to do something. If it does not work, try again. And if it still does not work, keep trying until it does. Nothing is too difficult to be achieved.

John: Since you work daily with young people, I’ll ask you about something that’s become a pet peeve of mine and that’s the mystery surrounding younger generations: Gen X, Gen Y, Millennial, etc. I think that statements to the effect that younger generations are mysterious beings that need to be treated differently are categorically false. I think they’re more or less like every preceding generation and all that’s changed is the tools they use (e.g. mobile computing, social applications). Would you agree or disagree with that?

Juan: I am completely with you. I am tired of hearing that the latest generations have shorter attention spans, are not as focused/driven, or require more spoon-feeding in science and engineering. Nonsense! Every day I work with young people who are just as curious, driven, and hard working as you or I ever were. They learn differently, they communicate differently, and have slightly different team dynamics, but so did we!  I think the pace of knowledge is accelerating and the current generation is doing an admirable job of grasping all the opportunities. Aerospace has a bright future.

How do you know Pointwise?

I have been a Pointwise / Gridgen user since 1995. At that time, we were attempting to do aerodynamic shape optimization on complete aircraft configurations (both transonic and supersonic) and Pointwise was the company whose products we used. In our SU² development team, Pointwise is widely used for all types of applications. The ease of gridding lets us focus on what we do best: analysis and design optimization.

John: I was especially happy with how quickly your team at the ADL jumped on Pointwise and customized it with a plugin for compatibility with SU². That’s an example of why I like working with younger engineers: they have fewer bad habits to break.

Juan: Two things. Firstly, indeed, when students thought it was a pain to dump meshes from Pointwise in a given format (say CGNS) and then convert them to an SU² format, they just looked for a better way of doing it. It was obvious to them that adding to the way that Pointwise dumped meshes was the most efficient thing to do!  But, secondly, Pointwise responded admirably: within a week we had a capability in place. Thanks!

Can you share with us your favorite tools and resources that help you get your job done?

• For code development, there is hardly a better environment for OS X than Xcode (https://developer.apple.com/xcode/). It makes developing C++ code so much easier!
• I have to give a lot of kudos to the Python (http://www.python.org/) development team. What a simple and wonderful way to couple multiple high-fidelity solvers, even in a highly-parallel environment, with a few lines of code.
• For debugging, Totalview (http://www.roguewave.com/products/totalview.aspx) is amazing. I cannot believe the amount of printf() statements that I wasted in my life before I discovered Totalview.
• For visualization of results, I miss the capabilities of the IBM Data Explorer (which then became OpenDx). I enjoy using Ensight (from CEI http://www.ceisoftware.com/ensight10/) a lot these days.

John: I’m going to guess that your people at the ADL use Pointwise on the Mac. Is that working well for them?

Juan: Yes. Most of our students run on Mac OS X and Linux. Pointwise for the Mac has exceeded our expectations. We are very glad that you have decided to support the Mac as it is fairly pervasive in academic/research circles.

John: As you know, our Glyph scripting language is based on Tcl. Several people have recommended that we include Python bindings for Glyph. How do you think that would benefit script writers?

Juan: Python is one of the languages that we love in our lab. It allows us to prototype code very quickly and can interface with Fortran, C, and C++ for compute-intensive tasks. Having Python bindings for Glyph would be simply amazing. I will let you in on a little secret: the next generation loves Python. Why? I am convinced that Python’s popularity comes from the students’ familiarity with Matlab, which has become the tool of choice in the vast majority of undergraduate aerospace programs around the country.

If we were to come visit you where’s a good place to go out for dinner?

You would not be disappointed. The Bay Area is home to some of the most outstanding restaurants in the world. In Palo Alto, CA, I would recommend Tamarine (http://www.tamarinerestaurant.com/) if you like the flavors of the Far East, and in Menlo Park, CA, I enjoy Madera (http://www.maderasandhill.com/) for a true California cuisine experience.

John: Sounds great, Juan. Thanks for taking the time for this interview.