Colloquia

Samenvatting

This thesis presents a simulation-based Bayesian optimisation framework for the design of shear-resistant flexures (SRFs) used in morphing aircraft control surfaces. Gaussian-process surrogate models, combined with constrained acquisition strategies, enable efficient exploration of a complex structural design space evaluated via finite-element simulations. The framework optimises trade-offs between shear stiffness, bending compliance, and strain limits. In addition, the study evaluates the performance of single-objective versus multi-objective optimisation strategies and analyses the influence of different dimensional parameterisations of the SRF geometry. The results provide insights into effective optimisation strategies for high-dimensional morphing-structure design problems.