HanleyCFD posts UAV high‑fidelity CFD tutorial

Computational fluid dynamics is a way to turn airflow into a math problem, with a computer solving the Navier-Stokes equations for mass, momentum, and energy instead of building a wind-tunnel model first. NASA describes it as using numerical methods to solve approximations of those equations on high-speed computers. (nasa.gov) For a small unmanned aerial vehicle, that math is trying to predict the invisible things a pilot only notices later, like lift, drag, and where the flow starts peeling off the wing. A few degrees of angle of attack, which NASA defines as the angle between the wing’s chord line and the flight direction, can change drag sharply. (nasa.gov) The hard part in most computational fluid dynamics work is not pressing “solve.” The hard part is building the volume grid, which is the 3D net of tiny cells around the aircraft that the solver uses like graph paper wrapped around a shape. (hanleyinnovations.com) Patrick Hanley’s tutorial is built around that bottleneck. His Stallion 3D workflow starts from a stereo lithography, or STL, geometry file, then auto-generates the grid, sizes the computational domain, and lets the user set speed, angle of attack, sideslip, altitude, and propulsion options before solving. (hanleyinnovations.com) That matters for student teams because a fixed-wing unmanned aerial vehicle can be modeled from the same geometry they already export from Open Vehicle Sketch Pad, or OpenVSP, and Hanley’s own demo page pitches exactly that handoff from design tool to aerodynamics solver. (hanleyinnovations.com) His recent unmanned aerial vehicle example on YouTube shows a fixed-wing aircraft going through automatic setup instead of the manual meshing that usually eats a weekend. The video description says the software automatically sizes the domain, generates the grid on import, and applies default solver settings to get lift and drag results quickly. (youtube.com) The software is aimed at higher-speed work too, not just slow campus drones. Hanley’s product page says Stallion 3D solves the compressible Navier-Stokes equations for subsonic, transonic, and supersonic flow, which is the speed range where shock waves and compressibility start changing the answer. (hanleyinnovations.com) On the same page, Hanley says the code uses three-dimensional compressible Reynolds-averaged Navier-Stokes with a k-epsilon turbulence model. That is the engineering version of averaging out the smallest swirls in the air so a laptop can still estimate the big forces and moments on the aircraft. (hanleyinnovations.com) He also shows why this is meant for early design trades, not just pretty flow pictures. The output includes lift coefficient, drag coefficient, pitching moment, full force and moment breakdowns, and pressure, Mach number, velocity, and temperature visualizations that can be compared across design iterations. (hanleyinnovations.com) Hanley’s validation examples are the pitch to skeptical engineers. He cites comparisons against NASA CFL3D results for the ONERA M-6 transonic wing, NASA Technical Memorandum 4117 data for the HL-20 lifting body, and a DrivAer car case with about 1.7 million cells and drag near 0.29. (hanleyinnovations.com) The practical message in the tutorial is that a small unmanned aerial vehicle team does not need to wait for a full aerospace simulation stack before checking whether one nose shape, wing incidence, or fairing is obviously worse than another. Hanley’s own blog frames Stallion 3D as a tool for “same-day aerodynamics insight” and repeatable A/B trade studies before a heavier computational fluid dynamics campaign makes sense. (hanleyinnovations.com)