Topology-inclusive aerodynamic shape optimisation using a cellular automata parameterisation.

Area of Science:

• Computational fluid dynamics
• Aerospace engineering
• Geometric modeling

Background:

• Complex geometries pose challenges in aerodynamic design.
• Existing parameterization methods may lack flexibility for arbitrary topologies.
• Optimizing multi-object aerodynamic configurations requires advanced tools.

Purpose of the Study:

• To present a novel geometry parameterization method driven by cellular automata.
• To enable the description of complex geometries with arbitrary topology.
• To optimize aerodynamic shapes for reduced drag, particularly in supersonic flow.

Main Methods:

• A volume-of-solid driven cellular automata approach for geometry parameterization.
• Approximation of smooth, minimum surface area geometries with localized volume constraints.
• Utilizing a geometry control mesh with adaptive refinement capabilities.
• Employing gradient-free optimization for aerodynamic shape design.

Main Results:

• Successful reconstruction of over 98% of aerofoil geometries within tolerance.
• Recovery of known analytical optima for supersonic flow conditions.
• Construction of multi-body aerodynamic geometries with significantly reduced drag compared to single-body optima.

Conclusions:

• The developed parameterization method effectively handles complex aerodynamic shapes.
• It enables the design of high-performance multi-body supersonic configurations.
• This approach offers a powerful tool for aerodynamic optimization and design.