The Goal: To answer fundamental questions regarding randomness and defects in optimal design,
like: are random structures and materials ever optimal? In this endeavour, efficient modelling and
inverse design approaches that are able to handle large scale structures and materials with random
perturbations and defects shall be developed and implemented.
Topology Optimization is an inverse design method based on repeated physics simulations, gradient
evaluations and deterministic design updates used to determine optimal material distributions for
mechanical and multiphysics structures and materials.
Background: Nature exhibits plethora of random structures with remarkable properties, whereas
man-made materials are mostly periodic – possibly due to manufacturing and modelling challenges.
Random structures are often postulated to be more robust and efficient than periodic ones, but this has
never been systematically investigated or proved.
Challenges: Existing inverse design tools are unable to handle large scale randomness and defects.
Including these either require brute force, extremely large scale simulations or the implementation of
new and advanced perturbation and Bloch-mode expansion formalisms within unit cell studies.
Ingredients: Efficient algorithms for handling super large-scale random structures as well as small
scale but very complex perturbation-based approaches must be established. Developed methods
will be applied to design of structures and materials with: extremal strength, crack resistance,
energy absorption, mechanical, optical, optomechanical and quantumoptomechanical resonators,
thermofluidic boundary layer control a.o.
Impact: Additive Manufacturing (AM) technologies provide extreme geometric freedom but suffer
from material and geometric uncertainties. Becoming able to prevent and/or exploit effects of
randomness will allow exploring extremities of material-property space and lift AM to a new level.
Examples are lightweight materials, impact absorbers, sport equipment, and advanced sensors that
reduce environmental impact, improve transportation safety or provide more advanced and energy
efficient devices.