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        "author": "Athul P. Girija",
        "author_email": "athulpg007@gmail.com",
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            "Development Status :: 5 - Production/Stable",
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            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
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            "Topic :: Scientific/Engineering",
            "Topic :: Scientific/Engineering :: Mathematics",
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        "description": "# AMAT\n\nAerocapture Mission Analysis Tool (AMAT) is designed to provide rapid mission analysis capability for aerocapture and Entry, Descent, and Landing (EDL) mission concepts to the planetary science community. AMAT was developed at the [Advanced Astrodynamics Concepts (AAC)](https://engineering.purdue.edu/AAC/) research group at Purdue University.\n\n\nSee [AMAT documentation](https://amat.readthedocs.io) for more details. \n\n[![Documentation Status](https://readthedocs.org/projects/amat/badge/?version=master)](https://amat.readthedocs.io/en/master/?badge=master) [![DOI](https://joss.theoj.org/papers/10.21105/joss.03710/status.svg)](https://doi.org/10.21105/joss.03710) [![PyPI version](https://badge.fury.io/py/AMAT.svg)](https://badge.fury.io/py/AMAT)\n\nIf you find AMAT useful in your work, please consider citing us: Girija et al., (2021). AMAT: A Python package for rapid conceptual design of aerocapture and atmospheric Entry, Descent, and Landing (EDL) missions in a Jupyter environment. *Journal of Open Source Software*, 6(67), 3710, [DOI: 10.21105/joss.03710](https://doi.org/10.21105/joss.03710)\n\n\nPlease note the public release version has a minimal working interplanetary dataset to run some of the example Jupyter notebooks because of data sharing policies of external collaborators.\n\n## Capabilities\n\nAMAT allows the user to perform low-fidelity broad sweep parametric studies; as well as high fidelity Monte Carlo simulations to quantify aerocapture performance. AMAT supports analysis for all atmosphere-bearing destinations in the Solar System: Venus, Earth, Mars, Jupiter, Saturn, Titan, Uranus, and Neptune.\n\n### Venus Aerocapture Trajectories\n![Venus Aerocapture Trajectory and Heating](https://raw.githubusercontent.com/athulpg007/AMAT/master/plots/craig-lyne-altitude-higher-res-lower-size.png)\n![Venus Aerocapture Trajectory and Heating](https://raw.githubusercontent.com/athulpg007/AMAT/master/plots/craig-lyne-heating-higher-res-lower-size.png)\n### Neptune Aerocapture Feasibility Chart\n![Neptune Aerocapture Feasibility](https://raw.githubusercontent.com/athulpg007/AMAT/master/plots/girijaSaikia2019b-higher-res-lower-size.png)\n### Monte Carlo Simulations\n![Monte Carlo Simulations](https://raw.githubusercontent.com/athulpg007/AMAT/master/plots/girijaSaikia2020b-fig-13-N5000.png)\n![Monte Carlo Simulations](https://raw.githubusercontent.com/athulpg007/AMAT/master/plots/girijaSaikia2020b-apo-histogram-N5000.png)\n\n\n## What kind of problems can AMAT solve?\n\nAMAT can be used to quickly assess the feasibility of an aerocapture mission concept using aerocapture feasibiility charts, and perform trade studies involving vehicle type, control authority, thermal protection system materials, and useful delivered mass to orbit. AMAT can also be used to set up and run high-fidelity Monte Carlo simulations of aerocapture trajectories considering delivery errors, atmospheric uncertainties, and aerodynamic uncertainties to evaluate system performance under uncertainty.\n\n### Examples\n\nAMAT comes with a number of example [Jupyter notebooks](https://amat.readthedocs.io/en/master/jupyter_link.html) to help users get started. The examples inculde:\n\n1. Venus aerocapture assesssment study\n2. Titan aerocapture assessment study\n3. Neptune aerocapture using blunt-body aeroshells\n4. Drag modulation aerocapture asssessment\n5. Planetary probe entry at various Solar System destinations\n\n## Features\n\n* Easy installation, only standard dependencies\n* Many examples and recreation of results from published literature\n* Extensive documented source code\n* Can be used for probe and lander Entry, Descent, Landing (EDL) calculations\n* Comes with a standard set of nominal atmospheric models\n\n## Installation \n\nNote: AMAT is designed to work with Python 3.0 or greater. You must have a Python 3 installation in your system.\n\nThere are three ways to install AMAT. \n\n### Option 1 : Install from pip (recommended)\n\nNote: Python Package Index limits the amount of additional data that can be packaged in the distribution, hence all data cannot be included in the built version. You will need to clone the GitHub repository to get the required data files, examples, and start using AMAT.\n\n#### For Linux/MacOS machines:\n  * ```$ pip install AMAT```\n  * ```$ git clone https://github.com/athulpg007/AMAT.git```\n\nIf you are unable to clone the repository, you can download the repository as a .zip file from GitHub and extract it.\n\nOnce AMAT is installed, run an example Jupyter notebook to check everything works correctly.\n  * ```$ cd AMAT/examples```\n  * ```$ jupyter-notebook```\n\nNote that you will need jupyterlab and pandas (for some examples) to run the example notebooks. Use ```pip install jupyterlab pandas``` to install Jupyter and pandas if it is not already installed on your system. \n\n\nThis will display the full list of example Jupyter notebooks included with AMAT.  Open and run the ```example-01-hello-world``` notebook to get started with AMAT.\n\n#### For Windows machines:\n\nYou must have Anaconda installed. Open the Anaconda Prompt terminal:\n  * ```$ pip install AMAT```\n\nOpen a Windows Powershell terminal and clone the GitHub reporistory. You must have Git installed.\n  * ```$ git clone https://github.com/athulpg007/AMAT.git```\n\nRun an example Jupyter notebook. From the Anaconda Prompt terminal:\n  * ```$ cd AMAT/examples```\n  * ```$ jupyter-notebook```\n\nNote that you will need jupyterlab and pandas (for some examples) to run the example notebooks. Use ```pip install jupyterlab pandas``` to install Jupyter and pandas if it is not already installed on your system. \n\n\nThis will display the full list of example Jupyter notebooks included with AMAT. Open and run the ```example-01-hello-world``` notebook to get started with AMAT.\n\n\n### Option 2 : Install from source\n\nThis will clone the repository from GitHub and install AMAT from the source code.\n\n#### For Linux/MacOS machines:\n\nMake sure you have numpy, scipy, matplotlib and pandas installed. Most likely you already have these installed. If not, use the following commands to install these dependenies first. Open a terminal window (on Linux machines) and type the following commands. You must have pip installed.\n  * ```$ pip install numpy scipy matplotlib pandas jupyterlab```\n\nClone the GitHub repository and install AMAT.\n  * ```$ git clone https://github.com/athulpg007/AMAT.git```\n  * ```$ cd AMAT```\n  * ```$ python setup.py install```\n  * ```$ cd examples```\n  * ```$ jupyter-notebook```\n\n#### For Windows machines:\n\nOpen the Anaconda Prompt terminal to install the prerequisite packages.\n  * ```$ pip install numpy scipy matplotlib```\n\nOpen a Windows Powershell terminal, clone the GitHub repository and install AMAT.\n  * ```$ git clone https://github.com/athulpg007/AMAT.git```\n  * ```$ cd AMAT```\n  * ```$ python setup.py install```\n  * ```$ cd examples```\n  * ```$ jupyter-notebook```\n\nNote that you will need jupyterlab and pandas (for some examples) to run the example notebooks. Use ```pip install jupyterlab pandas``` to install Jupyter and pandas if it is not already installed on your system. \n\n\nTo uninstall AMAT:\n\n1. If you installed AMAT using pip:\n  * ```$ pip uninstall AMAT```\n\n2. If you installed AMAT from source, from the main AMAT directory:\n  * ```$ python setup.py develop -u```\n\nThis will remove the AMAT installation from Python. You may simply delete the root folder where AMAT was installed to completely remove the files.\n\n\n### Option 3 : Install in a virutalenv\n\nIf you plan to modifty the source code or add features, the recommended option is to to install it in a virtual environment. \n\n1. Change directory to where you want the virtual environment to be created.\n  * ```$ cd home/path```\n\n2. Create a virutal environment and activate it.\n\nOn Linux/MacOS machines:\n  * ```$ python3 -m venv env1```\n  * ```$ source env1/bin/activate```\n\nOn Windows machines (from Anaconda Prompt):\n  * ```$ conda create --name env1```\n  * ```$ conda activate env1```\n  * ```$ conda install pip```\n\n4. Follow the steps outlined in Option #2 (build from source) to clone the repository and install AMAT. If you make changes to the source code, remove the existing installation, update the setup file with a new version number, and re-install:\n  * ```$ python setup.py develop -u```\n  * ```$ python setup.py install```\n\nIf you want to create a new distrubution package:\n  * ```$ python3 setup.py sdist bdist_wheel```\n\nTo re-make docs if you made changes to the source code (you must have Sphinx installed):\n  * ```$ cd ~root/docs```\n  * ```$ sphinx-apidoc -f -o source/ ../```\n  * ```$ make html```\n\nIf you added a new AMAT module, appropriate changes must be made to docs/source/AMAT.rst.\n\n## Usage\n\n  * ```from AMAT.planet import Planet```\n  * ```from AMAT.vehicle import Vehicle```\n  * ```from AMAT.launcher import Launcher```\n\n## License\n\nAMAT is an open source project licensed under the GNU General Public License Version 3.\n\n## Credits\n\nParts of the AMAT source code were originally developed in support of contracts between AAC and the Jet Propulsion Laboratory for various aerocapture mission studies between 2016 and 2020. Samples of atmospheric data from Global Reference Atmospheric Model (GRAM) software is used for illustration purpose only, and was developed by NASA Marshall Space Flight Center. The use of these GRAM models does not imply endorsement by NASA in any way whatsoever. A minimal working set of atmospheric profiles is included with AMAT to run the example notebooks. A minimal working interplanetary trajctory dataset is included with AMAT. The dataset was generated at Purdue University using the STOUR software package by Alec Mudek, and is also derived from trajectories published in the NASA Ice Giants Pre-Decadal Mission Study. The author plans to augment the interplanetary dataset with more publicly available information as it becomes available.\n\n## Support and Contribution\n\nIf you wish to contribute or report an issue, feel free to [contact me](mailto:athulpg007@gmail.com) or to use the [issue tracker](https://github.com/athulpg007/AMAT/issues) and [pull requests](https://github.com/athulpg007/AMAT/pulls) from the [code repository](https://github.com/athulpg007/AMAT).\n\nIf you wish to make a contribution, you can do as follows:\n\n * fork the GitHub repository \n * create a feature branch from *master* \n * add your feature and document it\n * run the tests \n * open a pull request\n\n## Extras\n\nThe AMAT repository includes representative atmospheric profiles for Solar System bodies, an Excel sheet with a comprehensive literature review of aerocapture, sample feasibility charts for aerocapture at all destinations, reference journal articles (by the author), a PDF version of the documentation, and the author's Ph.D. dissertation which provides more details on the methods and algorithms implemented in AMAT.\n\n## Reference Articles\n\nResults from these articles are used as benchmark examples.\n\n1. Craig, Scott, and James Evans Lyne. \"Parametric Study of Aerocapture for Missions to Venus.\" Journal of Spacecraft and Rockets Vol. 42, No. 6, pp. 1035-1038. [DOI: 10.2514/1.2589](https://arc.aiaa.org/doi/10.2514/1.2589)\n\n2. Putnam and Braun, \"Drag-Modulation Flight-Control System Options for Planetary Aerocapture\", Journal of Spacecraft and Rockets, Vol. 51, No. 1, 2014. [DOI:10.2514/1.A32589](https://arc.aiaa.org/doi/10.2514/1.A32589)\n\n3. Lu, Ye, and Sarag J. Saikia. \"Feasibility Assessment of Aerocapture for Future Titan Orbiter Missions.\" Journal of Spacecraft and Rockets Vol. 55, No. 5, pp. 1125-1135. [DOI: 10.2514/1.A34121](https://arc.aiaa.org/doi/10.2514/1.A34121)\n\n4. Girija, A. P., Lu, Y., & Saikia, S. J. \"Feasibility and Mass-Benefit Analysis of Aerocapture for Missions to Venus\". Journal of Spacecraft and Rockets, Vol. 57, No. 1, pp. 58-73. [DOI: 10.2514/1.A34529](https://arc.aiaa.org/doi/10.2514/1.A34529)\n\n5. Girija, A. P. et al. \"Feasibility and Performance Analysis of Neptune\nAerocapture Using Heritage Blunt-Body Aeroshells\", Journal of Spacecraft and Rockets, Vol. 57, No. 6, pp. 1186-1203. [DOI: 10.2514/1.A34719](https://arc.aiaa.org/doi/full/10.2514/1.A34719)\n\n6. Girija A. P. et al. \"Quantitative Assessment of Aerocapture and Applications to Future Missions\", Journal of Spacecraft and Rockets, 2022.\n[DOI: 10.2514/1.A35214](https://arc.aiaa.org/doi/full/10.2514/1.A35214)\n\n",
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