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Computational Design of Lightweight Structures
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Computational Design of Lightweight Structures : Form Finding and Optimization

Book Details

Format Hardback or Cased Book
ISBN-10 1848216742
ISBN-13 9781848216747
Publisher ISTE Ltd and John Wiley & Sons Inc
Imprint ISTE Ltd and John Wiley & Sons Inc
Country of Manufacture US
Country of Publication GB
Publication Date Feb 28th, 2014
Print length 136 Pages
Weight 426 grams
Dimensions 24.30 x 16.30 x 1.90 cms
Product Classification: Structural engineering
Ksh 25,000.00
Werezi Extended Catalogue 0 in stock

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The author of this book presents a general, robust, and easy-to-use method that can handle many design parameters efficiently. Following an introduction, Chapter 1 presents the general concepts of truss layout optimization, starting from topology optimization where structural component sizes and system connectivity are simultaneously optimized. To fully realize the potential of truss layout optimization for the design of lightweight structures, the consideration of geometrical variables is then introduced. Chapter 2 addresses truss geometry and topology optimization by combining mathematical programming and structural mechanics: the structural properties of the optimal solution are used for devising the novel formulation. To avoid singularities arising in optimal configurations, this approach disaggregates the equilibrium equations and fully integrates their basic elements within the optimization formulation. The resulting tool incorporates elastic and plastic design, stress and displacement constraints, as well as self-weight and multiple loading. The inherent slenderness of lightweight structures requires the study of stability issues. As a remedy, Chapter 3 proposes a conceptually simple but efficient method to include local and nodal stability constraints in the formulation. Several numerical examples illustrate the impact of stability considerations on the optimal design. Finally, the investigation on realistic design problems in Chapter 4 confirms the practical applicability of the proposed method. It is shown how we can generate a range of optimal designs by varying design settings.

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