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_posts/2018-06-15-FAQ.md

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@@ -30,53 +30,40 @@ Alright, you dove in and now you're stuck. You've come to a good starting point.
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<br>
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## How do I get started?
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### How do I get started?
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* Download SUAVE’s current release on our [download](/download/) page. Specific steps and further instructions for additional software requirements are also listed there.
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* Get familiar with the code using our [guides](guides/). Be sure to start the [BOEING 737 Tutorial](/guides/boeing_737-800.html) for a basic introduction and the Regional Jet Optimization For the optimization tools
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* Get familiar with the code using our [guides](guides/). Be sure to start the [Boeing 737 Tutorial](/guides/boeing_737-800.html) for a basic introduction and the Regional Jet Optimization for the optimization tools.
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* Ask any remaining questions on the [forum](/forum)
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## What version of Python should I use?
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SUAVE has been proven to work on 32bit versions of Python 2.7.
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### What version of Python should I use?
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SUAVE is developed in Python 2.7.
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## Can I use SUAVE for my own research?
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### Can I use SUAVE for my own research?
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Yes, you may! Please cite our papers:
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- [T. Lukaczyk, A. Wendorff, E. Botero, T. MacDonald, T. Momose, A. Variyar, J. M. Vegh, M. Colonno, T. Economon, J. J. Alonso, T. Orra, C. Ilario, "SUAVE: An Open-Source Environment for Multi-Fidelity Conceptual Vehicle Design", 16th AIAA Multidisciplinary Analysis and Optimization Conference, Dallas, TX, June 2015.](http://adl.stanford.edu/papers/suave-open-source.pdf)
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- [E. Botero, A. Wendorff, T. MacDonald, A. Variyar, J. M. Vegh, T. Lukaczyk, J. J. Alonso, T. Orra, C. Ilario da Silva. "SUAVE: An Open-Source Environment for Conceptual Vehicle Design and Optimization", 54th AIAA Aerospace Sciences Meeting, San Diego, CA, January 2016.](http://adl.stanford.edu/papers/suave-optimization.pdf)
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## How can I contribute?
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### How can I contribute?
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We encourage SUAVE users to expand the environment according to their personal interests. The main areas to be developed are listed [here](/develop/#areas-of-development).
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## How can I best get in touch with you?
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### How can I best get in touch with you or ask for help?
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The [forum](/forum) is our main point of contact for SUAVE discussions.
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## I am having trouble with my SUAVE code. Where can I find help?
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The [forum](/forum) is your best friend.
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### Where can I see the recent additions to the SUAVE environment?
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Go and check the develop branch on our [GitHub site](https://github.com/suavecode/SUAVE). This branch contains new features that are functional but not necessarily ready for release. Everything in this branch is added to the master branch at the next release. Several other feature branches can also be seen here. These are typically under active development. For any more information on what is available please ask on the [forum](/forum)
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## Where can I see the recent additions to the SUAVE environment?
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Go and check the develop branch on our [GitHub site](https://github.com/suavecode/SUAVE).
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## Are there plans to make a Graphical User Interface?
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### Are there plans to make a Graphical User Interface?
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The core development team is currently not planning on developing a GUI, but you can help! Contact us via the [forum](/forum).
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## How is a mission solved?
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### How is a mission solved?
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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.
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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.
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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!
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## How can I be more SUAVE?
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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.
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## What can SUAVE do for me?
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SUAVE is designed to make cool airplanes. This will make you rich, famous, and more attractive.
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## Will SUAVE change the World?
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Certainly. Why is this even a question?
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## Will SUAVE give me super powers?
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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.
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<!--- For more information see this [guide](). -->

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