id 
sigradi2018_1879 
authors 
Danesh Zand, Foroozan; Baghi, Ali; Kalantari, Saleh 
year 
2018 
title 
Digitally Fabricating Expandable Steel Structures Using Kirigami Patterns 
source 
SIGraDi 2018 [Proceedings of the 22nd Conference of the Iberoamerican Society of Digital Graphics  ISSN: 23186968] Brazil, São Carlos 7  9 November 2018, pp. 724731 
summary 
This article presents a computational approach to generating architectural forms for large spanning structures based on a “papercutting” technique. In this traditional artform, a flat sheet is cut and scored in such a way that a small application of force prompts it to expand into a threedimensional structure. To make these types of expandable structures feasible at an architectural scale, four challenges had to be met during the research. The first was to map the kinetic properties of a papercut model, investigating formative parameters such as the width and frequency of cuts to determine how they affect the resulting structure. The second challenge was to computationally simulate the papercut structure in an accurate fashion. We accomplished this task using finite element analysis in the Ansys software platform. The third challenge was to create a prediction model that could precisely forecast the characteristics of a papercutting pattern. We made significant strides in this demanding task by using a datamining approach and regression analysis through 400 simulations of various cutting patterns. The final challenge was to verify the efficiency and accuracy of our prediction model, which we accomplished through a series of physical prototypes. Our resulting computational papercutting system can be used to estimate optimal cutting patterns and to predict the resulting structural characteristics, thereby providing greater rigor to what has previously been an adhoc and experimental design approach. 
keywords 
Transformable Papercut; Design method; Prediction Model; Regression analysis; Physical prototype 
series 
SIGraDi 
email 
f.daneshzand@gmail.com 
full text 
file.pdf (945,959 bytes) 
references 
Contenttype: text/plain

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2019/05/20 09:14 
