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!

Exceptional students majoring in computer science, electrical engineering or similar are invited to apply for an internship at the Palo Alto Research Center (PARC) UAS Program. Interns participating in this program will work closely with members of the research staff on a fast paced research project. One paid internship of up to six months is available. Please submit resume to:  cuasinternship@parc.com

Responsibilities:

-Influence the development of a novel UAS platform

-Participate in the project from planning to field testing

-Explore publication or patent potential

Requirements:

-Graduate student in CS, EE or similar field preferred; qualified undergraduates will be considered

-Strong C++ experience

-OpenCV computer vision experience or similar