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Meet: David Saunders

Numerical Software Engineer
Ames Research Center, Moffett Field, CA

My Journals

Who I Am and What I Do
Spending the past 24 years at NASA Ames Research Center with one company providing software services could mean either (a) I'm in a dreadful rut or (b) I really enjoy the work. Happily, the answer is (b), and I hope very much for many more years yet. Maybe I can explain why.

Most of my 24 years have been in support of the Aerodynamics Division at Ames. Applied aerodynamics basically involves two main activities: (1) using computers to predict and improve the performance of airfoils, wings, and (more recently) whole aircraft, and (2) using wind tunnels--and more computers--to test those predictions on scale models. Often the results agree, but sometimes they differ, while results from the actual aircraft may differ again. Narrowing these differences through the use of more and more sophisticated computational and experimental techniques is one of the aerodynamicist's goals. As a software engineer trained in numerical methods, I am not an aerodynamicist, but I have been able to provide some of the programming help needed to further this basic goal.

More specifically, much of this support has involved combining two very complex types of calculation into a form that allows an aerodynamicist to modify or refine a given shape to have better performance. The two types of calculation linked together are (1) the ability to compute the airflow about a given aerodynamic shape, and (2) the ability to optimize that shape by means of a general purpose minimization method. Optimization refers to automating the calculation of good values of some problem-dependent parameters, called variables, in order to reduce some other quantity such as cost, energy consumption, or--in our case, as one possibility--aerodynamic drag for a given lift (that is, minimize air resistance for a given aircraft weight). Usually, the minimization is performed in the presence of practical considerations termed constraints, although simpler unconstrained optimization methods have been used to good effect.

Please note that while it takes highly knowledgeable specialists to produce good flow solvers and other highly skilled professionals to implement good optimization packages, combining the two and applying the combination as an aerodynamic design-by-optimization tool is much more within the domain of mere mortals. It might help to compare this with conducting an orchestra: the conductor probably couldn't come close to writing what the composer wrote, and he or she cannot play most of the instruments the way the musicians can. Nevertheless, the conductor manages to bring the two sets of talent together and produce (usually) happy results. If you've ever wondered what synergistic effects are, you've just read about two examples.

A little more specifically, my work has included helping develop and apply an airfoil design-by-optimization program (two-dimensional flow), a similar three-dimensional program for treating a rotor blade or a yawed wing (more on which below), and an even more elaborate wing/body design code with an option to include under-the-wing engine effects for supersonic transport applications. Most recently, such methods have been generalized to treat any complex configuration by decomposing the shape about the aircraft into numerous blocks, which in turn leads to a natural way of parallelizing the calculations: different blocks can be treated by different processors of a multiple-processor computer at the same time.

Another advance as crucial as parallelizing the design process has emerged in recent years which enables the optimization to be performed vastly more efficiently than was long believed possible, but this introduction is already too lengthy, so I will not describe that breakthrough until later. I hasten to emphasize that this work is a team effort, completely dependent upon the dramatic progress achieved by the theoreticians, the implementers of the corresponding software, and the manufacturers of more and more powerful computer systems. In combination, these software and hardware tools are now automating design refinement of more efficient aircraft. Over the life of an airplane, such refinements can save vast amounts of fuel, so NASA and the airframe manufacturers will be striving to improve the accuracy and efficiency of these methods for a long time to come. I hope to remain a part of it, and maybe some of you readers will get to join similar worthy and challenging efforts, too.

My Career Journey
It would be nice to believe that a childhood fascination with all things to do with aviation, particularly jet airplanes, was responsible for my eventual participation in aircraft design, but I am very much aware that it was much more luck than good management. First, I had a twin brother to share that hobby with and to help me much later. As children we each subscribed to different aviation magazines (I to Flight International, he to The Aeroplane each week, plus numerous monthlies) and we devoured them all during what was, in retrospect, the most dramatic of eras as the jet engine enabled a remarkable proliferation of more and more advanced aircraft. (The pace of development of new designs has slowed drastically in the past couple of decades, presumably because the costs and complexities have mushroomed greatly. All the more reason to bring the power of modern computers to bear. The fact that the de Havilland Comet, the Boeing 707, F-104 Starfighter, the Concorde and the Phantom F-4, to name a few, were designed and built in the absence of even an Apple II computer, and in remarkably few years, has to be impressive to anyone even vaguely aware of the construction issues, the flight control problems, the safety concerns, and so on, that aircraft building involves. But I digress.)

Our interest wasn't really in flying but rather in the fascinating shapes we saw in all those three-view and cut-away drawings (the more detailed the better). As we entered our teens, we built more and more elaborate scale models from those drawings. Our Northrop Flying Wing, Gloster Javelin, Douglas X-3, and F-104A all measured about 3 feet, while the crowning achievement in our last years at high school and first years at university was a 6-ft model of the English Electric Lightning F-1A, a Mach 2 twin-engine fighter. This one was finished with a layer of Plastibond which we had to sand and fill, sand and fill, till all the little bubble holes were eliminated. We managed to mold the cockpit canopy from something called Perspex, and modeled two Firestreak missiles attached to the forward fuselage. Maybe the absence of TV had something to do with our perseverance. We were born in New Zealand and lived there till our 20s, and the first TV we ever saw belonged to a high school classmate's family around 1960. Today, no doubt, we'd have been glued to the Wings programs on the Discovery Channel.

We went separate ways following our bachelors' degrees in mathematics: Michael to the New Zealand Government's Department of Scientific and Industrial Research, and I to teaching mathematics at a high school (a reluctant choice, but opportunities were few in those days). The DSIR soon sponsored Michael to come to Stanford University, where his doctorate in numerical analysis led to a career in "mathematical programming" which is better referred to as constrained optimization, although the terms linear programming and nonlinear programming persist. As I've touched on above, this field involves elaborate software for minimizing quantities known as cost functions or objective functions subject to linear or nonlinear constraints (possibly hundreds or more of them), all with respect to certain variables (again, possibly hundreds or more).

This connection with my brother and his colleagues in optimization was to prove a useful one. First, though, I had to extract myself from teaching, and after five years I was definitely ready for a change. (Teaching is certainly a character-building endeavor, and dedicated teachers deserve much more recognition than our modern society tends to give them. But I urge would-be teachers to choose wisely: those late nights preparing for tomorrow's classes take their toll, as do the myriad other teaching duties and the inevitable students with behavioral problems. Twenty-seven years later, I still have occasional anxiety dreams of being up there in front of a class, unprepared.) Anyway, a 6-week visit to Michael in California made sense. Not knowing what the future held, I audited a few classes at Stanford, sat the GRE exam, and applied to the Computer Science Department, one of the first such departments in this country. Eventually I had the good fortune to be available when a Research Assistanceship came up, and that was the beginning of my second career. Just an MS in CS (focusing on numerical analysis) has served me well ever since. Interestingly, the Assistanceship initially involved a literature search on parallel algorithms for solving tridiagonal systems of equations--in 1972. Truly usable parallel computer systems have become a reality only in very recent years, yet here the universities were anticipating their requirements 25 years earlier.

One of the few job interviews I had upon graduating was with Informatics (now Sterling Software), who supported some of the research at NASA Ames. This proved a lucky choice, because it led to the involvement with aircraft design that as teenagers in New Zealand we could only vaguely dream of. Actually, most of the first five years was spent helping to analyze solar wind data from the instruments on board the Pioneer 10, Pioneer 11, and Pioneer Venus spacecraft. I was able to contribute what I had learned about solving least squares optimization problems to fit mathematical models to the data, which represented particles emanating from the Sun at about a million miles per hour.

I also had an introduction to wind tunnel data in those first years. At that time, Ames used a single, central computer (IBM 360/67 with two processors) to support not only all the wind tunnels but all other computing at Ames as well! Informatics designed and implemented a new Standardized Wind Tunnel System to run on dedicated minicomputers in each tunnel. My involvement was with some force/moment calculation utilities. Later, I worked on a separate data acquisition system for oscillating airfoils which evolved into another system known as the Fluid Mechanics Data Acquisition System. Around that time I was task manager for a group of 10 or so, but our numbers have dwindled with NASA budgets, and many good people have had to move on. Today, the budget situation is somewhat healthier.

A most intriguing project came along a few years ago: the Oblique All Wing project, which was the ultimate extrapolation of the idea long promoted by the famous aerodynamicist, R.T. Jones, who had invented the swept wing independently of the Germans during WW II. "R.T" was associated with Ames for many years, and, in his 80s, still came to many of our OAW meetings with further contributions. Ideally, an aircraft needs to vary the wing sweep in flight according to its speed. Pivoting a single wing in the middle rather than sweeping two wings symmetrically might save weight, at the expense of control complications because of the asymmetry. A low speed demonstrator had been built and flown, taking off with the wing pivoted 45 degrees forward and backward, for instance, and this aircraft can now be seen by the visitors center at Ames. However, for a large transport aircraft, avoiding the weight of a really massive pivot altogether seemed attractive. Moreover, as R.T.'s analyses showed long ago, long slender bodies are the most efficient. Therefore, he urged doing away with the fuselage completely, dispensing with any massive pivot, putting the passengers inside the wing, and flying the wing at a very high sweep during cruise as a long, slender body.

Our assignment, then, was to design wing sections around a fixed-size central passenger cabin to allow flight as efficient as possible at Mach 1.6 (~1,000 mph) at 68 degrees of sweep. The cabin had to be 10 ft high and carry 450 passengers, leading to an enormous wing span of more than 400 feet! Blending the outer wing panels into the cabin envelope proved to be a nice application of constrained optimization, while optimizing the wing sections was done with the rotor blade/yawed wing code using an unconstrained optimizer. I became involved enough to be chosen for a NASA Contractor of the Year award in 1993. There are way too many aspects to cover further here, but an intense team effort did indeed lead to the design, construction and wind tunnel testing of a magnificent, 7-ft steel and aluminum model with four under-the-wing engines. Our calculations and the experimental measurements both predicted that the concept was less efficient than the early hopeful claims, partly because of those pesky engines: their pylons had to be thick enough for the engines to pivot as the speed (and sweep) changed in flight. The laws of physics are extremely rigid, and outwitting Mother Nature doesn't come easily. Maybe, some day, the cost of fuel will be high enough that the idea will be revisited for its potential modest benefits, but for now, a conventional next-generation supersonic transport is sure to appear first.

Indeed, such a Mach 2.4 High Speed Civil Transport design project is what I've been supporting most recently, but details must be deferred because this outline is already too long. Suffice it to say that the aerodynamic design-by-optimization work is challenging and rewarding, and I will always feel grateful for having stumbled into it. I wish everybody could be so fortunate.

Rewarding though this career has been, my greatest fortune has been in meeting my wonderful wife, Ha (a truly good person who survived a harrowing escape from Vietnam by overloaded small boat in a storm). Our little boy, named after Uncle Michael, of course, is two now and couldn't be more delightful for his proud parents. He has mastered the letters of the alphabet and the numbers up to twelve. Watching that little character play and learn new things every day is the most fascinating and heart-warming part of our lives. I strongly recommend it!

Unfortunately, balancing a demanding job and family life is very difficult, and too often the family comes second. Regular exercise at racquetball and tennis aggravates the situation, yet not staying fit wouldn't be wise either. I've had to give up most of my reading, and rarely get to play the piano these days. Too little time in the day is my biggest regret, along with being too far away for too long from our loving mother. I hope little Michael grows up to find as fulfilling a life as I have, but that it's not 7,000 miles from home. Today, make a point of hugging your mom and dad--while you still can.

Parting Thoughts
For young people with mathematical inclinations wondering about careers, I would suggest that, while numerical optimization has already been applied effectively in many fields, there should be scope for a lot more of that in the future, including the work within NASA. Design of almost anything these days is done with computers--from planes and cars to refrigerators (I'm sure) and even computers themselves (e.g., for cooling them efficiently). Automating the determination of best designs is an opportunity for people familiar with optimization software to make valuable contributions.

Some applications, including the above, involve extremely expensive calculations (such as for the airflow about an aerodynamic shape). Normally, costly objective functions tend to limit the number of design variables that can be used at one time. However, a recent breakthrough has virtually made this conventional wisdom obsolete: some clever calculus shows how, at the expense of one more calculation similar to the airflow calculation, the sensitivities of the function being minimized to any number of variables--and hence a direction to move in the design space--can be calculated very cheaply. This is nontrivial stuff, but it helps illustrate the exciting possibilities made possible by recent advances in this very important field. Much larger problems than previously thought feasible are able to be tackled now.

Finally, I must take this opportunity to urge young people not to do one thing I did, and that is take more than 40 years to discover the symphonies of Gustav Mahler. He wrote 9 remarkable symphonies (or 10, really, but he was so afraid that 9 was a fateful number--because of how many other composers died after writing that many--that his real 9th he chose not to call a symphony). Mahler (1860-1911) was the greatest conductor of his time, and his marvellous orchestrations reflect that. His music is full of beautiful melodies, frequently two of them in parallel, and the emotions range from sublime joy to agonizing despair. If you haven't heard yet what he did with a minor key version of the Frere Jacque tune, you should start with his Symphony No. 1 (the "Titan")--see the third movement.

I would love to say more on this subject (such music having helped me through many long evenings on the job during our intense efforts to meet deadlines), but I've imposed on my readers too much already. Thanks for listening!


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