UAV Trip-Strip Optimizer

Can a passive trip strip force transition early enough to reduce low-Reynolds-number separation losses without adding more drag than it saves? At low Re, laminar separation and transition dominate drag. A trip can trigger transition earlier to reduce separation — but the strip is itself a source of drag. So the study compares three cases:

The solver couples a vortex-sheet panel method with an integral boundary-layer model. Geometry is spline-refined and repanelled before the potential-flow system is solved. I refactored the original interactive solver into a reusable solve_case() workflow so angle-of-attack and design sweeps could be automated.

The viscous solver marches independently along the upper and lower surfaces from the stagnation point, using Thwaites' integral laminar method followed by numerical integration of the turbulent layer.

I extended the solver so a trip can force transition at a chosen position, switching between natural and forced transition, with explicit tracking of the forced-transition location for later optimisation.

A trip only takes effect if it occurs before natural transition or laminar separation. Downstream of either, it becomes a no-op.

A 2D section is not enough for a UAV wing, so the 2D aerodynamic database is coupled to a Prandtl lifting-line model:

J = weighted L/D − variability − penalties

The nominal idealised ranking put E387, 2° root incidence, uniform trip near x/c = 0.45 as the highest-scoring strategy under that objective.

Still an ideal forced-transition result — no physical trip drag yet.

Rather than trusting one optimisation setup, I varied its assumptions — mission-speed weighting, span-station count, separation-location shift and trip penalty. Across 81 sensitivity cases the winning strategy was not fixed:

The ideal trip was deliberately not the final answer. A real strip must actually trigger transition and pay its own drag. I added a physical-trip model using roughness Reynolds number Re_k and trip height / momentum thickness k / θ, only counting a strip as effective when its local state exceeds the configured thresholds. Its drag is kept separate from the profile drag:

Cd,total = Cd,profile + Cd,trip

The physical-trip calibration is a screening model, not a measured hardware calibration — the code labels its threshold / drag coefficients as heuristic or fallback where appropriate.

The strips generally did trigger transition — so the finding is not simply “the strips did not work.”

The strongest average physical candidate — final low-Re design, 0.1 mm zigzag — still came in at roughly ΔL/D = −5.86 relative to the clean aerofoil. The strips generally worked as transition devices, but their added drag outweighed the benefit from reduced separation.

Clean aerofoil selected. The study asked “should we use a trip?” — and the evidence answered no.

E387 predictions were compared with digitised experimental data from NASA TM-4062 across multiple Reynolds numbers and angles of attack. Lift trends reproduced more reliably than drag in the most low-Re / separation-bubble-sensitive cases.

The project also generates XFOIL and AVL input decks for independent follow-up, but those external binaries were not available in the recorded environment, so those comparisons were not run.

A separate Python verification port cross-checked forced-transition behaviour when MATLAB was unavailable.