More Python Resources
Python for Mechanical and Aerospace Engineering is more of a starter
book for mechanical and aerospace engineering. Here is a list of more advanced
topics that you can view, use, and contribute to after you have completed
this book.
This list will be updated as more resources are found or become available,
so check back frequently!
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Orbital Mechanics in Python: reddit post
here
and first YouTube video here
-
AeroSandbox: a Python package for simultaneously optimizing an aircraft’s
aerodynamics, structures, propulsion, mission trajectory, stability, and more.
Website here and GitHub page
here
-
Ptera Software: an open-source package for analyzing flapping wing
flight. GitHub page here
-
CFD Python: learn the foundations of Computational Fluid Dynamics (CFD)
by coding solutions to the basic partial differential equations that
describe the physics of fluid flow. Website
here,
YouTube lecture series
here, and
GitHub page here
-
SimuPy Flight: open source scientific computing tools to implement
a simulation framework for flight vehicles in Python.
GitHub page here
-
XPlane Connect: allows users to control aircraft and receive
state information from aircraft simulated in X-Plane using functions
written in C, C++, Java, MATLAB, or Python in real time over the network.
GitHub page here
-
NASA Python Software: Python programs and libraries available as part
of NASA's Technology Transfer Program.
Website here
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Python for Science and Engineering: exercises, examples and blog articles
on using Python 3 for science and engineering applications.
Website here
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SUAVE: conceptual level aircraft design environment built with
the ability to analyze and optimize both conventional and
unconventional designs.
Website here
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Huracan: open source, 0-dimensional, object-oriented airbreathing
engine modelling package for preliminary analysis and design of
airbreathing engines, divulgation and educational purposes.
Website here and GitHub page
here
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PyCycle: hermodynamic cycle modeling library, designed primarily to
model jet engine performance. It is built on top of the OpenMDAO framework
and the design is heavily inspired by NASA's NPSS software. It is
recommended that you are familiar with OpenMDAO or NPSS before using
the library.
GitHub page
here
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MONTE: JPL's signature astrodynamic computing platform, supporting
all phases of space mission development from early space design and
analysis through flight navigation services. Unfortunately, it requires a
license to use.
Website here
-
Astropy: common core package for astronomy in Python. And, it
handles units!
Website here