I would like to introduce droneCFD.com to the DiyDrones community. The purpose of droneCFD is to reduce the complexity of running Openfoam CFD simulations on small unmanned aircraft geometries. To do this, droneCFD uses the OpenFoam toolkit for meshing and flow solving, with a little extra automation to handle case setup, simulation domain configuration and parallel execution.

To get started with DroneCFD, you need to have OpenFoam 2.3.0 and PyFoam installed on your machine. You can install droneCFD using 'pip install droneCFD'. You can double check that OpenFoam is installed correctly by running 'dcCheck' in a terminal. Your first simulation only requires you to type 'dcRun', which will run a simulation based on a reference geometry packaged with droneCFD. More details can be found at dronecfd.com/gettingstarted.

This project was the result of many frustrating hours trying to simulate flow around a novel small unmanned aircraft geometry. It is far from perfect, but I'm hoping feedback and lots of testing will help improve it.

The code is located on Github, and I've setup a webpage with a details and a forum for collecting feedback. Please take a look, try it out and let me know what you think!

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  • Hey Andreas,

    Sorry about that, it appears there were some issues with the email server. Thanks for bringing it to my attention. Can you give me a try and let me know if it works?

  • 100KM
    Wow! Nice!
  • Anderl, 

    Thanks for the comment! I hope to expand on droneCFD to make it even more useful to sUAS designers. I would like to get to the point where OpenFOAM simulations can be used not only for aircraft design, but also for motor selection, accurate flight time predictions and perhaps even as a basis for a JSBsim model that can be used for virtual aircraft tuning. Keep checking in on the software, I'll be adding some new features soon!  

  • Chris, I find this is an amazing contribution. Congrats.

  • Navier-Stokes CFD simulations are quite lengthy, so it isn't a specific problem with this software. However, I feel your pain. The reason why you would choose this type of simulation is to work out an estimate of parasitic drag for the geometry. The alternative way to get this information is by wind tunnel testing (or flight testing).

    While I haven't tried, it may also be possible to run simulations on AWS or Google Compute. If you need to simulate many geometries quickly, this may be the way to go.

  • "Once the simulation has finished (~1:35 hours on an i7-3370k processor)"  =(

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