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Unify MACH-Aero documentation (mdolab#2)
* Initial commit of public docs * Updating readme * Added OAS and OpenConcept to code docs listing * Adding instructions on how to compile and have user base MPI installations * minor change * Minor typos. * updated installation section * removed repostate, since it is broken for git * Adding a link to the newly added pyaerostructure python code documentation * First draft of C/Fortran package installation, WIP * Done with most of 3rd party packages, fixing table and cleanup * Finished rewrite of install 3rd Party Packages file - Reordered to have all C/Fortran sources first, then python - Written examples now install locally, mostly without sudo apt-get - Clearly state which versions are known to work (and not work). This is now done with the IMPORTANT block, and would benefit from others including their systems. - Added table of working stacks * Added issue and pull request templates * Remove authorship and commit descriptions per feedback * Fixing small typo from previous commit * Adding a bad numpy version that may result in problems with MACH codes * Updated 3rd party packages installation, mainly for the complex version build * Removing pyaerostructure since that should be private. Also removeing onld dafoam link * Adding link to DAFoam docs and cleaning up a bit. * Added the ASO page. * More cleaning of docs. Removing packages that are not needed. * Updating copyright date * Minor fix to the installation instructions. Removing non-referenced variable * Clarifying installation instructions * Removing tutorial for now * Minor fixes to the installation instructions * Fixed the ASO page. Added links to the new AeroOptTutorial page. * Fixed aeroOpt diagram * Initial add to Great Lakes setup * Added estimate start time on Great Lakes * Minor changes to previous commit for greatlakes setup, removed unnecessary things * Minor changes to MPI job execution * Changed the name of ASO framework to MACH-AERO. * Fixed the broken links. * Changed MACH-AERO to MACH-Aero. Tweaked intro. * Added a list of papers for all the modules in the MACH-Aero page. * Changed name of optFramework to machFramework. * Changed the rst and tex names. * Fixed the broken links. * Update buildbot script for automatic build of docs. * Minor edits to MACH-Aero page * Updated Tecplot Quick Macros section and added macro to apply TACS deformations * Fixed header lengths * updated greatlakes setup * add a comment about cgns installation * updated a bit * a change to petsc4py 3.7.0 installation * minor change to petsc4py installation * updated account name in greatlakes setup * added updated package versions to working stack * updated working stack and package version in 3rd party docs * further cleaned up PETSc instructions * removed LDSHARED hack with anaconda since we updated petsc4py * updated greatlakes instructions * updated package version and made pip install more consistent * removed author names * changed <uniqname> to $USER * various small changes to 3rd party page * removed CGNS linker instructions since they should be in the config files by default * reformatted the example bash script * added note on interactive job request * added greatlakes job cost estimation and cost information (mdolab#32) * added greatlakes job cost estimation and cost information * Adding some more useful aliases * Create CODEOWNERS * CGNS 3.3 fix (mdolab#33) * Added notes for CGNS with intel install and reorganized the secti… (mdolab#36) * Added notes for CGNS with intel install and reorganized the section a bit * some modifications to make clear about the cgnstools install * Update installFromScratch.rst (mdolab#37) * Removing tutorials (mdolab#41) * renamed $USER in slurm script (mdolab#44) * Update install instructions (mdolab#45) * updated CGNS install instructions (mdolab#47) * updated CGNS install instructions * created warning box * added options for greatlakes petsc installation (mdolab#46) * added options for greatlakes petsc installation * addressed Neils comments * addressed Eirikur comments * SWIG installation instructions (mdolab#48) * Stampede update (mdolab#50) * scripts update and TODOs * added tips for CGNS install * added tips on running jobs * directories section + rearranging notes * addressed comments * added the PYTHONPATH back * explained XSEDE vs TACC access * addressed comments Co-authored-by: Neil Wu <[email protected]> * removed cluster installation tuturials (mdolab#51) * Updating links to RTD (mdolab#52) * Updating links to RTD * More links and grammar * gitignored * added adflow paper reference to mach-aero. also added ds store to gitignore Co-authored-by: Anil Yildirim <[email protected]> * removed submodules * deleted deprecated files * updated index and MACH-Aero description * updated index and README * merged mach-aero tutorial * changed rst headings and refactor * minor change in hyperlink * formatting fixes * Update README.md * Update installFromScratch.rst * Adding cgnsutilities to optional packages and updating links from bitbucket to github Co-authored-by: Eirikur Jonsson <[email protected]> Co-authored-by: John Jasa <[email protected]> Co-authored-by: Eirikur Jonsson <[email protected]> Co-authored-by: Anil Yildirim <[email protected]> Co-authored-by: Joaquim R. R. A. Martins <[email protected]> Co-authored-by: Charles Mader <[email protected]> Co-authored-by: Ross Chaudhry <[email protected]> Co-authored-by: John Jasa <[email protected]> Co-authored-by: Ross S. Chaudhry <[email protected]> Co-authored-by: yqliaohk <[email protected]> Co-authored-by: Ping He <[email protected]> Co-authored-by: A-Gray-94 <[email protected]> Co-authored-by: Alasdair Gray <[email protected]> Co-authored-by: Sicheng He <[email protected]> Co-authored-by: yqliaohk <[email protected]> Co-authored-by: Josh Anibal <[email protected]> Co-authored-by: Marco Mangano <[email protected]> Co-authored-by: Shamsheer S. Chauhan <[email protected]>
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.github/CODEOWNERS

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* @mdolab/mach_aero_maintainers

.github/ISSUE_TEMPLATE.md

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---
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name: General issues template
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about: For all issues
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title: ''
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assignees: ''
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---
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.github/PULL_REQUEST_TEMPLATE.md

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## Purpose
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Explain the goal of this PR, if it addresses an existing issue be sure to link to it. Describe the big picture of your changes here, perhaps using a bullet list if multiple changes are done to accomplish a single goal. If it accomplishes multiple goals, it would be best to create separate PR's for each.
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README.md

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MACH-Aero
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=========
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This page is intended to introduce the aerodynamic shape optimization capability within MACH (framework for MDO of aircraft configurations with high fidelity). The MACH framework is developed by the Multidisciplinary Design Optimization Laboratory (MDO Lab) at the University of Michigan. More documentation can be found at https://mdolab-mach-aero-tutorial.readthedocs-hosted.com/en/latest/
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MACH-Aero consists of six major modules:
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- Pre-processing ([pyHyp](http://mdolab.engin.umich.edu/docs/packages/pyhyp/doc/index.html), [ANSYS ICEM-CFD](https://ansys.com>))
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- Optimizer ([pyOptSparse](http://mdolab.engin.umich.edu/docs/packages/pyoptsparse/doc/index.html))
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- Geometry parameterization ([pyGeo](http://mdolab.engin.umich.edu/docs/packages/pygeo/doc/index.html))
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- Volume mesh deformation ([IDWarp](http://mdolab.engin.umich.edu/docs/packages/idwarp/doc/index.html))
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- Flow simulation ([ADflow](http://mdolab.engin.umich.edu/docs/packages/adflow/doc/index.html), [DAFoam](https://dafoam.rtfd.io))
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- Adjoint computation ([ADflow](http://mdolab.engin.umich.edu/docs/packages/adflow/doc/index.html), [DAFoam](https://dafoam.rtfd.io))
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See the following papers for technical background of the above modules. **If you use these modules in publications, please cite the corresponding papers**.
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- Ruben E. Perez, Peter W. Jansen, Joaquim R.R.A. Martins, pyOpt: A Python-based object-oriented framework for nonlinear constrained optimization, Structural and Multidisciplinary Optimization 45, 101–118, 2012. https://doi.org/10.1007/s00158-011-0666-3 (**pyOptSparse**)
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- Gaetan K.W. Kenway, Graeme J. Kennedy, Joaquim R.R.A. Martins, A CAD-free approach to high-fidelity aerostructural optimization, Proceedings of the 13th AIAA/ISSMO Multidisciplinary Analysis Optimization Conference, Fort Worth, TX, 2010. https://doi.org/10.2514/6.2010-9231 (**pyGeo**)
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- Gaetan K.W. Kenway, Charles A. Mader, Ping He, Joaquim R.R.A. Martins, Effective adjoint approaches for computational fluid dynamics, Progress in Aerospace Sciences, 2019. https://doi.org/10.1016/j.paerosci.2019.05.002 (**ADflow**)
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- Anil Yildirim, Gaetan K.W. Kenway, Charles A. Mader, Joaquim R.R.A. Martins, A Jacobian-free approximate Newton–Krylov startup strategy for RANS simulations, Journal of Computational Physics, 2019. https://doi.org/10.1016/j.jcp.2019.06.018 (**ADflow**)
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- Ping He, Charles A. Mader, Joaquim R.R.A. Martins, Kevin J. Maki, An aerodynamic design optimization framework using a discrete adjoint approach with OpenFOAM, Computers \& Fluids 168, 285-303, 2018. https://doi.org/10.1016/j.compfluid.2018.04.012 (**DAFoam**)
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In addition to the above modules, MACH-Aero depends on: [baseClasses](http://mdolab.engin.umich.edu/docs/packages/baseclasses/doc/index.html), [multipoint](http://mdolab.engin.umich.edu/docs/packages/multipoint/doc/index.html), and [pySpline](http://mdolab.engin.umich.edu/docs/packages/pyspline/doc/index.html). To download MACH-Aero along with all its modules, run:
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git clone --recurse-submodules https://github.com/mdolab/MACH-Aero.git
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![MACH-Aero](MACH-Aero-Diagram.png)
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Generally, MACH-Aero starts with a baseline design and uses the derivatives (gradient) to find the most promising direction in the design space for improvement.
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This process is repeated until the optimality and feasibility conditions are satisfied.
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More specific process is as follows, taking the above figure as reference.
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Here we use the extended design structure matrix (XDSM) representation developed by Lambe and Martins (2012).
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The diagonal nodes represent the modules and the off-diagonal nodes represent the data.
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The black lines represent the process flow in the adjoint, whereas the thick gray lines represent the data flow.
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The number in each node represents the execution order:
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- First, we generate volume mesh for the baseline design geometry (pre-processing in process 1). Several mesh generation tools are available including [pyHyp](http://mdolab.engin.umich.edu/docs/packages/pyhyp/doc/index.html) and ICEM. Refer to [Surface Meshing](http://mdolab.engin.umich.edu/docs/packages/mach_aero_tutorials/doc/aero_icem.html), [Volume Meshing](http://mdolab.engin.umich.edu/docs/packages/mach_aero_tutorials/doc/aero_pyhyp.html), and [Mesh Manipulation](http://mdolab.engin.umich.edu/docs/packages/mach_aero_tutorials/doc/aero_cgnsutils.html) for more details. The generated mesh will be used later in process 4. In the pre-processing step, we also generate free-form deformation (FFD) points (process 3) that will be used later to morph the design surface. Refer to [Geometric Parameterization](http://mdolab.engin.umich.edu/docs/packages/mach_aero_tutorials/doc/opt_ffd.html).
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- Then, we give a set of baseline design variables to the optimizer (process 2). We use SNOPT as the optimizer who uses the SQP algorithm. We use [pyOptSparse]( http://mdolab.engin.umich.edu/docs/packages/pyoptsparse/doc/index.html) to facilitate the optimization problem setup. The optimizer will update the design variables and give them to the geometry parameterization module ([pyGeo](http://mdolab.engin.umich.edu/docs/packages/pygeo/doc/index.html); process 3). pyGeo receives the updated design variables and the FFD points generated in the pre-processing step, perform the deformation for the design surface, and outputs the deformed design surface to the mesh deformation module [IDWarp](http://mdolab.engin.umich.edu/docs/packages/idwarp/doc/index.html) in process 4. pyGeo also computes the values of geometric constraints and their derivatives with respect to the design variables (process 7).
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- Next, [IDWarp](http://mdolab.engin.umich.edu/docs/packages/idwarp/doc/index.html) deforms the volume mesh based on the updated design surface and outputs the updated volume mesh to the flow simulation module in process 5.
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- The flow simulation module receives the updated volume mesh and uses high-fidelity CFD tools (e.g., [ADflow](http://mdolab.engin.umich.edu/docs/packages/adflow/doc/index.html), [DAFoam](https://dafoam.rtfd.io) to compute the state variables (process 6) or physical fields (pressure, density, velocity, etc.). The flow simulation module also computes the objective and constrain functions (e.g., drag and lift; see process 7) and output the state variables to the adjoint computation module.
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- Then, the adjoint computation module (process 6) computes the total derivatives of objective and constraint functions with respect to the design variables (process 7) and gives them back to the optimizer in process 7. The benefit of using the adjoint method to compute derivatives is because its computational cost is independent of the number of design variables, which makes it attractive for handling large-scale, complex design problems such as aircraft design. There are two available adjoint solvers: [ADflow](http://mdolab.engin.umich.edu/docs/packages/adflow/doc/index.html), [DAFoam](https://dafoam.rtfd.io).
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- Finally, the optimizer receives the values and derivatives of objectives and constraints in process 7, performs the SQP computation, and outputs a set of updated design variables to pyGeo.
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The above process is repeated until the optimization converges (optimality and feasibility conditions satisfied).
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Refer to [MACH-Aero Tutorials](http://mdolab.engin.umich.edu/docs/packages/mach_aero_tutorials/doc/index.html) for tutorials.
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# MACH-Aero
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[![Documentation Status](https://readthedocs.com/projects/mdolab-mach-aero/badge/?version=latest)](https://mdolab-mach-aero.readthedocs-hosted.com/en/latest/?badge=latest)
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MACH-Aero is a framework for performing aerodynamic shape optimization.
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It contains the following core modules:
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- `baseClasses`
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- `pySpline`
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- `pyGeo`
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- `IDWarp`
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- `ADflow`
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- `pyOptSparse`
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And optional modules:
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- `pyHyp`
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- `multiPoint`
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- `DAFoam`
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Note that all the code for MACH-Aero are contained within the individual repositories above, which can be found on GitHub under the organization `mdolab`.
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This repository contains the following:
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- A description of the overall framework
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- Installation instructions which are shared across the various repositories
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- Tutorials for using MACH-Aero to perform aerodynamic shape optimization
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These docs can be accessed online at https://mdolab-mach-aero.readthedocs-hosted.com/.
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To run the tutorials yourself, you need to follow the installation instructions to install all the modules, then clone this repository to access the tutorial scripts.
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Tutorial walkthroughs are found on the documentation site.

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# -*- coding: utf-8 -*-
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#
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# MDOLAB Code documentation build configuration file, created by
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# sphinx-quickstart on Wed Nov 6 12:32:59 2013.
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#
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# This file is execfile()d with the current directory set to its containing dir.
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#
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# Note that not all possible configuration values are present in this
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# autogenerated file.
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#
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# All configuration values have a default; values that are commented out
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# serve to show the default.
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import sys
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import os
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# Add any Sphinx extension module names here, as strings. They can be extensions
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# coming with Sphinx (named 'sphinx.ext.*') or your custom ones.
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extensions = [
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"sphinxcontrib.bibtex"
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]
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numpydoc_show_class_members = False
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# Add any paths that contain templates here, relative to this directory.
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templates_path = ["_templates"]
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# The suffix of source filenames.
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source_suffix = ".rst"
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# The master toctree document.
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master_doc = "index"
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# General information about the project.
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project = u"MACH-Aero Documentation"
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copyright = "2020, MDO Lab"
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# List of patterns, relative to source directory, that match files and
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# directories to ignore when looking for source files.
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exclude_patterns = ["_build"]
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# Add any paths that contain custom themes here, relative to this directory.
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html_theme_path = ["themes"]
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html_theme = "sphinx_rtd_theme"
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# Add any paths that contain custom static files (such as style sheets) here,
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# relative to this directory. They are copied after the builtin static files,
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# so a file named "default.css" will overwrite the builtin "default.css".
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html_static_path = ["_static"]

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