Software produced in research has a bad rap. “Researchy” codes might have very powerful capabilities, but be plagued by the following issues:
Part of this is because researchers are usually scientists first and coders second (or fifth…). There is an incentive to make progress quickly, finish the paper, and then move on to the next, novel topic. The net result is a huge supply of software that consumed thousands of hours but never gets used again. You think social science has a replication crisis? Good luck trying to replicate a paper involving most research codes.
Another problem is that academic labs have a lot of turnover. Students are constanly entering the lab without much software development experience, then graduating and leaving a few years later. This leads to a loss of institutional memory about why parts of the codebase are the way they are.
You know who else deals with similar issues? The entire tech industry. Various software engineering methodologies (agile, spiral, extreme programming, etc.) have been proposed over the years to solve these issues. It’s an industry for authors and consultants, but there are some valuable practices to be found here as well.
I am keenly aware of several of my notable bad habits and I really want to break them. To name a few:
My PhD advisor mentioned the book Atomic Habits by James Clear on a number of occasions lately so I figured I would give it a try.
Overall, Atomic Habits is a worthwhile read and I think some of the tools will marginally improve my life. Hopefully, over time, that marginal improvement will compound into something significant.
In this article, I’ll attempt to summarize the actionable parts of the book. I will start by giving an overview of the major arguments of the book, then close by describing some of the more tangible tools and techniques that the author recommends.
As an optimization engineer and researcher, I am always thinking about how to optimize my life. Lately, I have been thinking particularly about the value of high-variance strategies. I am a pretty risk-averse person, generally preferring a known, acceptable option to the prospect of an unknown but potentially great (or terrible) option. One of my resolutions for 2020 is to be more thoughtful about situations that warrant taking bigger risks, and to be mindful about my biases which push me towards low-variance strategies even when they aren’t the best choice.
Computational fluid dynamics (CFD) is an indispensable tool in aerospace engineering. These expensive simulations produce a large amount of three-dimensional flow data, and in order to gain understanding from the results we employ interactive visualization. We generally use purpose-built desktop applications such as Tecplot or Ensight to do this. However, the software is expensive and this makes it difficult to share results (other than in simple 2D renderings). In this post, I will demonstrate how to create web-based, interactive, 3D visualizations of surface pressure data using a free and open-source software stack.
Check out this example result from one of my earlier research papers! (Flexible Formulation of Spatial Integration Constraints in Aerodynamic Shape Optimization )
Hydrogen fuel for aircraft, while seemingly a recent idea, is almost as historic as jet aviation itself. This post, the start of a series on hydrogen power for aviation applications, will dive into the history of hydrogen-powered flight, from the secretive days of the Cold War to the clean power demonstrator projects of the present day.
Hydrogen has long seemed attractive to aircraft designers as a fuel source because it has desirable physical properties. Compared to kerosene jet fuel, it holds tremendous energy per unit weight: hydrogen measures as high as 142 MJ/kg, while jet fuel holds about 42 MJ/kg. This promises longer range. Per the Breguet range equation:
where is the fuel heating value (a.k.a. specific energy), is the propulsive and thermodynamic combined efficiency, is the gravitational constant, is the lift to drag ratio, and is the weight.
We see that the range is, to first order, linear with specific energy of the fuel. In this simple analysis, hydrogen looks about three times better than kerosene on range! Hydrogen also burns very easily, which improves engine operability at the corners of the operating envelope (especially at high altitude).
Hydrogen also burns cleanly, producing only water vapor and heat (when burned very lean - NOx is a concern otherwise). When used in a fuel cell, no carbon emissions are produced. In the modern era, the environmental benefits of hydrogen fuel could be its greatest selling point (assuming that it can be generated in a sustainable way).
In reality, the range benefit is greatly reduced due to the low density of hydrogen, which causes the airframe to grow (increasing weight and drag). I will discuss these tradeoffs in the next post.
EASA dropped big news on Monday, announcing a proposed special condition under which electric VTOL aircraft under 2000kg may be certified in the European Union. This is the most concrete pathway to certification from a major western regulator and is sure to be followed closely by the FAA (which tends to keep regulations in sync with Europe for the most part, and vice versa). I'll take a quick look at the updated rule and identify the novel issues raised. Several of the points are sure to be contentious, and I expect the public comment period to be quite lively.
The Olympics are about both training the human body to its highest potential and harnessing creative engineering to gain a competitive edge. At the Winter Olympics in particular, technology plays a key role in athletes' competitiveness. As I have time, I hope to write a quick post on how aerospace engineering principles apply to athletic performance at Winter Olympic sports. Today's topic: speed skating.
Full disclosure: I'm an aerodynamicist and a cyclist but I can barely skate.
Speed skating is both a sprint and endurance sport, with events from 500m to 10km. Because of the extremely low friction of the skates on the ice, the primary force reducing an athlete's speed is aerodynamic drag. Reducing drag is, therefore, a paramount consideration in achieving a spot on the podium.
Streamlined shapes are usually much longer than they are wide. When air or water flows over a streamlined shape (like a fish, or an airplane), it remains attached over almost the entire length. Streamlined shapes usually have very modest curvature, and they generally come to a point on the downwind / trailing side. Swimmers do a great job of streamlining, as seen by Michael Phelps in the video below. Skeleton and luge athletes do the same thing. Generally, streamlined shapes have the lowest drag.
Two months of eVTOL developments in one post!
It’s common knowledge that most new technologies are overhyped during early development. Technology advisory firm Gartner terms this process the hype cycle and suggests that there are five stages. Sure, it's made up and it's not really a cycle, but we'll go with it:
I just moved back to Ann Arbor and started school, so the last several weeks have seen a large number of important stories pile up. Let's address some of them here:
Well, I may have been too ambitious with the idea of a "weekly" tempo for my last blog post. So much was announced at Paris but the following weeks were slow. I've been gathering updates since then and my plan is to post when I reach a critical mass of material or when a feature-worthy development comes along.
AIAA recently posted a live stream from the "Aircraft Electric Propulsion: Transforming Aviation" track at AIAA AVIATION 2017. I wasn't able to attend in person, so it was great to be able to review the panel discussion and questions.
The panel featured speakers from E/S Aero, the American Helicopter Society, NASA Glenn, CALSTART, and Zunum Aero.