Stability-Aware Simplification of Curve Networks
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Date
2022-07
Publication Type
Conference Paper
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yes
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Abstract
Designing curve networks for fabrication requires simultaneous consideration of structural stability, cost effectiveness, and visual appeal—complex, interrelated objectives that make manual design a difficult and tedious task. We present a novel method for fabrication-aware simplification of curve networks, algorithmically selecting a stable subset of given 3D curves. While traditionally stability is measured as magnitude of deformation induced by a set of pre-defined loads, predicting applied forces for common day objects can be challenging. Instead, we directly optimize for minimal deformation under the worst-case load.
Our technical contribution is a novel formulation of 3D curve network simplification for worst-case stability, leading to a mixed-integer semi-definite programming problem (MI-SDP). We show that while solving MI-SDP directly is infeasible, a physical insight suggests an efficient greedy approximation algorithm. We demonstrate the potential of our approach on a variety of curve network designs and validate its effectiveness compared to simpler alternatives using numerical experiments.
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Publication status
published
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Book title
SIGGRAPH '22: ACM SIGGRAPH 2022 Conference Proceedings
Journal / series
Volume
Pages / Article No.
20
Publisher
Association for Computing Machinery
Event
Special Interest Group on Computer Graphics and Interactive Techniques Conference (SIGGRAPH 2022)
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Methods
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Date collected
Date created
Subject
fabrication-aware design; stability; curve networks
Organisational unit
09620 - Coros, Stelian / Coros, Stelian