Nonlinear Topology Optimisation for Stretchable Mechanical Structures

Project outline:

This project aims to develop a novel computational framework for design of stretchable mechanical structures with tailored, exceptional performance. It will address a critical methodological gap in “inverse design” of novel stretchable structures by advancing numerical modelling, data-driven, and optimisation approaches in a nonlinear regime.

Project Background

Stretchable mechanical structures are a subset of mechanical megastructures that can undergo desired large deformations while maintaining structural integrity and functionality. These stretchable structures incorporate soft and/or hard materials with extraordinary multiscale geometric features and nonlinear mechanisms, enabling them to stretch, bend, twist, compress, or experience sudden changes in deformation without permanent damage.

Most existing designs for stretchable mechanical structures largely rely on intuition-driven or bioinspired approaches. They are often time-consuming and substantially limited in design flexibility, making it challenging to meet growing demands for extreme functional properties.

Project Aim

This project will investigate nonlinear topology optimisation approaches for development of stretchable mechanical structures.

Research Objectives

1. Nonlinear finite element modelling and characterisation

Conduct numerical modelling via nonlinear finite element analysis and physics-informed neural networks

Materials characterisation for soft, textile and hyper elastic materials

2. Design optimisation for programmed mechanical response

Perform size, shape, or topology optimisation

Combine with deep learning-based optimisation approach

Additive manufacturing through FDM, SLA, SLS printing technologies

Expected outcomes

The PhD project will generate novel numerical algorithms and design strategies, opening a new research avenue in computational optimisation for stretchable mechanical structures.