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Design with SADSF method and analyses of elastic properties of torsion-loaded structures based on double-tee sections ‎

Markiewicz Ireneusz

Journal of Theoretical and Applied Mechanics

2019

Vol. 57 nr 1

115--126

The paper presents results of the preliminary strength design using the method of statically admissible discontinuous stress fields (SADSF) of two new and interesting thin-walled structures based on double-tee sections. Although these constructions are intended to carry torsion moment loads, all their surfaces are accessible from outside. The paper is completed with the selected results of linearly-elastic FEM analyses of the presented solutions. They show surprisingly good strength properties and significantly higher load-carrying capacity comparing to structures designed in an intuitive way. The objectives of the paper, among other things, are as follows: popularization of the SADSF method, presentation of its new solutions and confirmation of practical usefulness in the design of thin-walled structures.

Structural optimization using topological and shape sensitivity via a level set method

Allaire G., Gournay F. de, Jouve F., Toader A.-M.

Control and Cybernetics

2005

Vol. 34, no 1

59-80

A numerical coupling of two recent methods in shape and topology optimization of structures is proposed. On the one hand, the level set method, based on the classical shape derivative, is known to easily handle boundary propagation with topological changes. However, in practice it does not allow for the nucleation of new holes (at least in 2-d). On the other hand, the bubble or topological gradient method is precisely designed for introducing new holes in the optimization process. Therefore, the coupling of these two method yields an efficient, algorithm which can escape from local minima in a given topological class of shapes. Both methods rely on the notion of gradient computed through an adjoint analysis, and have a low CPU cost since they capture a shape on a fixed Eulerian mesh. The main advantage of our coupled algorithm is to make the resulting optimal design largely independent of the initial guess.