Airfoil optimization via CFD: reducing drag by 18%
How computational simulation enables iterating hundreds of geometries without physical prototypes. A real case of aerodynamic optimization using OpenFOAM and genetic algorithms.
Technical articles on CFD, biomimetics, materials engineering and everything in between. No hype, no marketing — just applied science.
How computational simulation enables iterating hundreds of geometries without physical prototypes. A real case of aerodynamic optimization using OpenFOAM and genetic algorithms.
Shark skin micro-grooves reduce friction by 9.9%. We analyze surface physics, how to replicate them in composites, and the industrial applications emerging.
Ply stacking defines stiffness, weight and strength. How FEA analysis enables predicting first-ply failure, interlaminar delamination and optimal fiber direction in each layer.
The Volume of Fluid (VOF) method captures the interface between two immiscible fluids. From cavity ventilation to propeller cavitation, we break down its fundamentals and applications.
The hexagonal honeycomb is the maximum-strength, minimum-density structure found in nature. We analyze its geometry, how to model it with finite elements, and its applications in ultralight sandwich panels.
Laser powder bed fusion (LPBF) enables geometries impossible by traditional machining. From AM-oriented design to residual stresses and post-process treatments.
Choosing the right turbulence model in OpenFOAM: k-omega SST vs Spalart-Allmaras compared against experimental data for aerodynamic flows.
LES captures unsteady flow physics that RANS misses, but at 50x the cost. When does the trade-off make sense for real engineering projects?
Humpback whale flipper tubercles delay stall and improve post-stall lift. CFD analysis shows how sinusoidal leading edges can redesign wings, turbines, and fans.
Superhydrophobic surfaces inspired by lotus leaves use dual-scale roughness to achieve contact angles above 150 degrees. Multiphase CFD reveals how it works.
The Non-dominated Sorting Genetic Algorithm (NSGA-II) explained step by step: Pareto dominance, crowding distance, tournament selection and elitism.
When each CFD evaluation takes hours, Bayesian optimization finds the optimum with 10x fewer iterations using Gaussian Processes as surrogate models.