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contributor authorHill, Noah
contributor authorEbert, Matt
contributor authorMaurice, Mena
contributor authorKrishnamurthy, Vinayak
date accessioned2024-04-24T22:32:58Z
date available2024-04-24T22:32:58Z
date copyright12/15/2023 12:00:00 AM
date issued2023
identifier issn1530-9827
identifier otherjcise_24_5_051003.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4295427
description abstractWe present a novel methodology to generate mechanical structures based on fractal geometry using the chaos game, which generates self-similar point-sets within a polygon. Using the Voronoi decomposition of these points, we are able to generate groups of self-similar structures that can be related back to their chaos game parameters, namely, the polygonal domain, fractional distance, and number of samples. Our approach explores the use of forward design of generative structures, which in some cases can be easier to use for designing than inverse generative design techniques. To this end, the central hypothesis of our work is that structures generated using the chaos game can generate families of self-similar structures that, while not identical, exhibit similar mechanical behavior in a statistical sense. We present a systematic study of these self-similar structures through modal analysis and tensile loading and demonstrate a preliminary confirmation of our hypothesis.
publisherThe American Society of Mechanical Engineers (ASME)
titleCellular Chaos: Statistically Self-Similar Structures Based on Chaos Game
typeJournal Paper
journal volume24
journal issue5
journal titleJournal of Computing and Information Science in Engineering
identifier doi10.1115/1.4063987
journal fristpage51003-1
journal lastpage51003-12
page12
treeJournal of Computing and Information Science in Engineering:;2023:;volume( 024 ):;issue: 005
contenttypeFulltext


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