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About this course
(This page contains materials from the "About this course" section of the online course.)
The George Washington University MAE course catalog has the following entry for MAE 6226:
Aero/Hydrodynamics. 3 Credits. Inviscid flows in two and three dimensions and irrotational flow theory; conformal mapping and applications. Helmoltz theorems and vorticity dynamics. Applications such as airfoil theory, finite wing theory, panel methods, instabilities, free surface flow.
That's a lot for one semester!
The pre-requisite is a first-year graduate course in Fluid Mechanics, including flow kinematics, irrotational flow and the concept of boundary layer. Each year, a few students at GW request and are granted an exception from the prereq, however. And, to be honest, many students have passed their fluids course but did not learn some fundamental concepts (like the difference between streamline, streakline and pathline, for example).
And, as you might know, university professors in the US have a fair amount of leeway in the design of their courses.
So as I prepared to design this course in 2014, I asked myself: what is the one thing that I would like all students to learn from a classical aerodynamics course? After some reflection, the answer was: the principles of potential flows and panel-method solutions of aerodynamic flows.
Thus, the course builds—through a set of step-by-step lessons—the two-dimensional panel-method solution of flow around objects (like airfoils). We do this using computation as our instrument, from the beginning. Our lessons are written as Jupyter Notebooks, which are published openly on the course GitHub repository.
This course aims to provide a foundation in the classical theories of aerodynamics of ideal fluids, as they apply to aerospace engineering design, and competency in solution methods and understanding of their approximation power and sources of error.
Students will ...
- appreciate the approximations that are made to tackle aerodynamics for engineering purposes, and understand their limitations;
- learn the classical use of potential-flow theory in aerodynamics;
- implement computational solutions of potential flow with panel methods;
- read and learn to summarize and critique literature of classical aerodynamics;
- gain understanding of how mathematical analysis of ideal flows can be used for engineering design of real systems;
- gain experience documenting and presenting the fruits of their study.
This section provides additional information for those students registered for MAE 6226 at the George Washington University. It is not relevant to followers of this course from outside GW.
If you've made it this far, you've already registered for this course in GW's OpenEdX system. Thanks!
You will need also a GitHub account to keep your own work synchronized between machines, and keep a full history of changes (and backup). Your instructor will ask you for your GitHub handle to check your work periodically.
How to work on GitHub
The idea is to keep all your files for the course under complete history tracking. If you work consistently every week (like you should), your progress will be evident via the "commits" on your GitHub repository.
Create a new repository for this class—you can call it "mae6226," for example. For every new class, or topic you are working on, you can create a new Jupyter notebook, and add this file to be tracked by git. For every incremental bit of work on this file, you will synchronize with your GitHub account via three commands:
git add <name of file>
git commit -m "commit message"
git push
If you've previously made changes in another computer, and pushed them to GitHub, you will have to start by "pulling" those changes into the machine you're going to continue your work on—from your version-controlled directory for the course, use:
git pull
In Fall 2017, we worked with the GW Library Instructional Technology Laboratory to deploy Jupyter in cloud servers for you. You can access from any browser at http://go.gwu.edu/jupyter Just log in with your GW credentials and you're good to go!
This will bring up a file browser that will show the contents of your home directory on the server. Click on New, on the top right, and then select Python 3 at the bottom to create your first notebook.