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ADflow is a finite volume RANS solver tailored for gradient-based . . . ADflow is a flow solver developed by the MDO Lab at the University of Michigan It solves the compressible Euler, laminar Navier–Stokes and Reynolds-averaged Navier–Stokes equations using structured multi-block and overset meshes
Software · MDO Lab ADflow: (pronounced "A-D-flow") CFD solver that can handle structured multi-block and overset meshes It includes an adjoint solver for computing derivatives and can be used in the MACH-Aero framework for aerodynamic shape optimization
Introduction — ADflow documentation Although its primary objective in this program was to compute the flows in the rotating components of jet engines, ADflow has been developed as a completely general solver, and it is therefore applicable to a variety of other types of problems, including external aerodynamic flows
adflow doc tutorial. rst at main · mdolab adflow · GitHub Before running ADflow we need a CGNS mesh The mesh must be in meters For a complete tutorial on using MACH, including meshing, please refer to the :ref:`MACH-Aero tutorial <mach-aero:mach-aero-tutorial-intro>` The following shows how to get started with ADflow by running the mdo_tutorial wing problem
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Analysis with ADflow — MACH-Aero Documentation documentation When ADflow is instantiated, it reads in the mesh and then waits for the user to dictate further operations Before running the case, we can choose to set up some additional output options
Solvers — ADflow documentation ADflow is capable of switching between solver algorithms during a solution procedure This process is controlled with the relative convergence metric, which is the ratio of current residual norm and the initial residual norm