SIM-AM 2025

Data-driven Shape Optimisation of Architected Materials

  • Azam, Farooq I (University College London)
  • Tan, PJ (University College London)
  • Bosi, Federico (University College London)

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The advancement of architected materials has gained significant traction through reduced-scale additive manufacturing, enabling precise control of geometrical features at micro- and nanoscales. This precision enables the tailoring of macroscopic properties, facilitating the development of high-strength, lightweight, architected materials with exceptional mechanical properties. While conventional periodic lattices rely on unit cells with struts of uniform cross-section, a strategic redistribution of material along the strut length presents an opportunity to enhance mechanical response, particularly in bending-dominated architectures [1]. This study presents a novel approach to developing and optimising architected materials by strategically redistributing solid material to enhance mechanical properties such as stiffness, plastic strength, and buckling resistance. A multi-objective parametric optimisation framework, integrating analytical models, numerical simulations, and machine learning algorithms, is employed to explore the design space and identify Pareto-optimal configurations. The research investigates both two- and three-dimensional strut- and shell-based lattice architectures, comparing bending- and stretch-dominated structures. The impact of material redistribution along struts and surfaces is assessed against conventional uniform-thickness lattices. Fabrication via polymeric and metallic additive manufacturing enables experimental validation through compression testing. Results demonstrate that bending-dominated architectures benefit significantly from material redistribution, exhibiting notable improvements in stiffness and plastic strength. In contrast, stretch-dominated lattices and buckling strength show limited enhancements. Additionally, optimised configurations exhibit strain-dependent auxetic behaviour. These findings highlight the potential of data-driven shape optimisation and material redistribution as powerful tools for designing lightweight, high-performance metamaterials. This framework provides a systematic strategy for engineering advanced materials with superior mechanical properties, offering broad applicability in structural engineering. REFERENCES [1] F.I. Azam, P.J. Tan, F. Bosi, Multi-objective parametric optimisation of architected hexagonal honeycomb with stepped struts, Materials & Design, Volume 250, 2025, 113569, ISSN 0264-1275, https://doi.org/10.1016/j.matdes.2024.113569.