期刊
COMPUTER AIDED GEOMETRIC DESIGN
卷 93, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.cagd.2022.102074
关键词
Discrete differential geometry; Architectural geometry; Weingarten surface; Characteristic parameterization; Constant ratio of principal curvatures; Principal symmetric net
资金
- KAUST baseline funding [BAS/1/1679-01-01]
- Austrian Science Fund [I 2978]
Motivated by applications in architectural geometry, this study focuses on surfaces with a constant ratio of principal curvatures (CRPC surfaces), and explores their characteristic parameterizations. The research introduces characteristic parameterizations for rotational CRPC surfaces and discrete CRPC surfaces, and demonstrates efficient computation methods through numerical optimization. These surfaces have potential applications in computational design and mathematical studies of the CRPC surfaces.
Motivated by applications in architectural geometry, we study and compute surfaces with a constant ratio of principal curvatures (CRPC surfaces) based on their characteristic parameterizations. For negative Gaussian curvature K, these parameterizations are asymptotic. For positive K they are conjugate and symmetric with respect to the principal curvature directions. CRPC surfaces are described by characteristic parameterizations whose parameter lines form a constant angle. We use them to derive characteristic parameterizations of rotational CRPC surfaces in a simple geometric way. Pairs of such surfaces with principal curvature ratio kappa(1)/kappa(2) = +/- a can be seen as equilibrium shapes and reciprocal force diagrams of each other. We then introduce discrete CRPC surfaces, expressed via discrete isogonal characteristic nets, and show how to efficiently compute them through numerical optimization. In particular, we derive discrete helical and spiral CRPC surfaces. We provide various ways how these and other special types of CRPC surfaces can serve as a basis for computational design of more general CRPC surfaces. Our computational tools may also serve as an experimental basis for mathematical studies of the largely unexplored class of CRPC surfaces. (C) 2022 Elsevier B.V. All rights reserved.
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