Alright, you dove in and now you’re stuck. You’ve come to a good starting point. If this FAQ fails you then we suggest you go through tutorials, maybe our paper, send us a question in the forum, or if all else fails start reading code. Don’t worry the code is more readable than most engineering textbooks.

## How do I get started?

• Get familiar with the code using our guides. Be sure to start the BOEING 737 Tutorial for a basic introduction and the Regional Jet Optimization For the optimization tools
• Ask any remaining questions on the forum

## What version of Python should I use?

SUAVE has been proven to work on 32bit versions of Python 2.7.

## Can I use SUAVE for my own research?

Yes, you may! Please cite our papers:

## How can I contribute?

We encourage SUAVE users to expand the environment according to their personal interests. The main areas to be developed are listed here.

## How can I best get in touch with you?

The forum is our main point of contact for SUAVE discussions.

## I am having trouble with my SUAVE code. Where can I find help?

The forum is your best friend.

## Where can I see the recent additions to the SUAVE environment?

Go and check the develop branch on our GitHub site.

## Are there plans to make a Graphical User Interface?

The core development team is currently not planning on developing a GUI, but you can help! Contact us via the forum.

## How is a mission solved?

A mission is divided into segments, for example climb, cruise, etc… Then the segment is divided into discrete points that are cosine spaced in time. These make up Chebyshev collocation points. One of the beauties of this method is the integration and differentiation operator. So if you know the velocity at every point, then you can get accelerations and vice-versa.

The default value is 16 points in each segment for SUAVE. However, our internal numerical experiments have shown highly accurate results with ~0.1% error with only 4 control points and ~.0001% error with 8 as measured from a very highly refined answered.

For each control point there are various unknowns and residuals. An example of an unknown would be pitch angle, and a residual would be the forces in the Z direction. After performing an analysis using the unknowns the residuals are calculated. These unknowns and residuals are iterated through a hybrid solver (much like a Newton method) in SciPy to converge the residual to zero. Voila, with a little magic you have results!

## How can I be more SUAVE?

Try running SUAVE daily. Unpeer reviewed non-statistical unpublished research has shown time and again that SUAVE developers are amazing. That is because they work with SUAVE on a daily basis. This gives them power over aerospace that only super humans posses. In turn that power is manifested in confidence, smoothness, and elegance that every human will adore.

## What can SUAVE do for me?

SUAVE is designed to make cool airplanes. This will make you rich, famous, and more attractive.

## Will SUAVE change the World?

Certainly. Why is this even a question?

## Will SUAVE give me super powers?

Unfortunately SUAVE cannot give you super powers. However there is hope, SUAVE is the perfect starting point to perform conceptual design studies on your flying Iron Man suit (some code development required). The energy network in SUAVE is ideal for modeling the arc reactor and the power transfer to the propulsors. Although you will not gain super powers from SUAVE it might still make you a super hero, or maybe a super villain should you choose that route.