Stochastic design for additive manufacture of true biomimetic populations

Groth, Jan-Hendrik; Magnini, Mirco; Tuck, Christopher; Clare, Adam

Abstract

Current biomimetic designs do not incorporate naturally occurring variance. Instead, the same unit cell is repeatedly copied and pasted to create a pattern. Existing stochastic designs use the same randomness for all parameters. However, nature teaches us that unit cells vary over several geometry defining parameters and that unit cells rarely overlap. Here, we present a methodology where a Gaussian distribution can be superimposed on any regular array of parametric unit cells. The standard deviation controls the randomness. The distance between unit cells is evaluated and used to define different parameters. This allows using different randomness for each parameter and prevents overlaps. Aspect ratios are introduced to define interdependent parameters. The methodology presented here provides a template for researchers to more accurately mimic the engineering performance of biological structures across multi-physics problems. This new design methodology lends itself perfectly to additive manufacturing.

Citation

Groth, J.-H., Magnini, M., Tuck, C., & Clare, A. (2022). Stochastic design for additive manufacture of true biomimetic populations. Additive Manufacturing, 55, Article 102739. https://doi.org/10.1016/j.addma.2022.102739

• Journal Article Type: Article
• Acceptance Date: Mar 4, 2022
• Online Publication Date: Apr 1, 2022
• Publication Date: Jul 1, 2022
• Deposit Date: May 4, 2022
• Journal: Additive Manufacturing
• Print ISSN: 2214-7810
• Electronic ISSN: 2214-8604
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 55
• Article Number: 102739
• DOI: https://doi.org/10.1016/j.addma.2022.102739
• Keywords: Industrial and Manufacturing Engineering; Engineering (miscellaneous); General Materials Science; Biomedical Engineering
• Public URL: https://nottingham-repository.worktribe.com/output/7655514
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S2214860422001439