Hierarchical material optimization

By Miguel Arcilla Cuaycong

Skyline College

Assembles all possible configurations of a structural level in a Hierarchical Material.

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Version 1.0 - published on 28 Oct 2019

doi:10.21981/FBHG-9T90 cite this

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Materials that occur in nature commonly consist of complex architectures arranged in a hierarchy that can be observed at different length scales. However, the design of hierarchical materials is often challenging due to the enormous size of their design space. This tool utilizes an algorithm to provide all possible configurations(topologies) of a structural level in a Hierarchical Material. This data lists all the topologies expressed in a matrix and can be downloaded as a txt file. 


[1] General Motors

[2] Dr. Pablo Zavattieri 

Sponsored by


[1] Ulrike G. K. Wegst, Hao Bai, Eduardo Saiz, Antoni P. Tomsia & Robert O. Ritchie. “Bioinspired structural materials”

[2] Kristiaan W. Hector, et al. “Mechanics of Chiral Honeycomb Architectures with Phase Transformations”

[3] Markus J. Buehler, et al. “De novo composite design based on machine learning algorithm” & “Bioinspired hierarchical composite design using machine learning: simulation, additive manufacturing, and experiment.”

[4] K.A Seffen, S. Pellegrino. ”Deployment dynamics of tape springs”

Cite this work

Researchers should cite this work as follows:

  • Miguel Arcilla Cuaycong (2019), "Hierarchical material optimization," https://nanohub.org/resources/3dmatopt. (DOI: 10.21981/FBHG-9T90).

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