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Computational form‐finding of tension membrane structures—Non‐finite element approaches: Part 3. Comparison of mesh constraint methods
Author(s) -
Brew J. S.,
Lewis W. J.
Publication year - 2002
Publication title -
international journal for numerical methods in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 168
eISSN - 1097-0207
pISSN - 0029-5981
DOI - 10.1002/nme.581
Subject(s) - finite element method , piecewise , dynamic relaxation , relaxation (psychology) , mathematics , representation (politics) , algorithm , computer science , mathematical optimization , mathematical analysis , structural engineering , geometry , engineering , psychology , social psychology , politics , political science , law
Abstract This paper, presented in three parts, discusses a computational methodology for form‐finding of tension membrane structures (TMS), or fabric structures, used as roofing forms. The term ‘form‐finding’ describes a process of finding the shape of a TMS under its initial tension. Such a shape is neither known a priori , nor can it be described by a simple mathematical function. The work is motivated by the need to provide an efficient numerical tool, which will allow a better integration of the design/analysis/manufacture of TMS. A particular category of structural forms is considered, known as minimal surface membranes (such as can be reproduced by soap films). The numerical method adopted throughout is dynamic relaxation (DR) with kinetic damping. Part 1 gave a background to the problem of TMS design, described the DR method, and presented a new form‐finding methodology based on the Laplace–Young equation and the use of cubic splines to give a full, piecewise, analytical description of the surface. Part 2 described an alternative and novel approach to form‐finding, based on a constant tension field and faceted (triangular mesh) representation of the minimal surface. Techniques for controlling mesh distortion were presented, and the effects of mesh control on the accuracy and computational efficiency of the solution, as well as on the subsequent stages in design, were examined. Part 3 gives a comparison of the performance of the initial method (Part 1) and the faceted approximations (Part 2). Functional relations, which encapsulate the numerical efficiency of each method, are presented. Copyright © 2002 John Wiley & Sons, Ltd.