Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/170537
Title: An overview of developable surfaces in geometric modeling
Authors: Zhang, Yuzhe
Zheng, Jianmin
Keywords: Engineering::Computer science and engineering
Issue Date: 2022
Source: Zhang, Y. & Zheng, J. (2022). An overview of developable surfaces in geometric modeling. Recent Patents On Engineering, 16(5), e120521193305-. https://dx.doi.org/10.2174/1872212115666210512021156
Project: 2017-T2-1-076
Journal: Recent Patents on Engineering
Abstract: Background: A developable surface is a special ruled surface with vanishing Gaussian curvature. The study of developable surfaces is of interest in both academia and industry. The application of developable surfaces ranges from ship hulls, architecture to origami, clothes, etc., as they are suitable for the modeling of surfaces with materials that are not amenable to stretch like leather, paper, fiber, and sheet metal. Objective: We survey techniques and patents of developable surfaces in the field of geometric mod-eling. The theory, algorithms, and applications are discussed to provide a comprehensive summary for modeling developable surfaces. Methods: Prior methods that model smooth and discrete developable surfaces in diverse disciplines are collected and reviewed. In particular, our review focuses on c2, c2 and c2 developable surfaces, which are driven by the problems and challenges in the industry. Results: Many papers and patents of developable surface modeling are classified in this review pa-per. It is found that remarkable developments and improvements have been achieved in both analyt-ical computations and practical applications. Conclusion: Global piecewise-developable surfaces, exploration of shape space of developable sur-faces, joint optimization of geometry and physics, and other fundamental problems should be further studied.
URI: https://hdl.handle.net/10356/170537
ISSN: 1872-2121
DOI: 10.2174/1872212115666210512021156
Schools: School of Computer Science and Engineering 
Rights: © 2022 Bentham Science Publishers. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

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