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IASS-SLTE Symposium 2014: Shells, Membranes and Spatial Structures: Footprints


IASS Symposium 2014

SESSION: Structural Morphology 1: Design and Engineering Computing

Form exploration and GA-based optimization of lattice towers comparing with Shukhov Water Tower

< Table of Contents for Structural Morphology 1: Design and Engineering Computing
  • Proceedings Name: IASS-SLTE Symposium 2014: Shells, Membranes and Spatial Structures: Footprints
  • ISSN: (Electronic Version) 2518-6582
  • Session: Structural Morphology 1: Design and Engineering Computing
  • Title: Form exploration and GA-based optimization of lattice towers comparing with Shukhov Water Tower
  • Author(s): Anahita KHODADADI, Peter VON BUELOW
  • Keywords: Topology Optimization, Genetic Algorithm, Formex Configuration processing, Lattice Towers
Abstract
The main objective of this research is to develop a form exploration technique based on parametric form generation using concepts of Formex algebra and evolutionary optimization based on ParaGen approach. Accordingly, the design process of the lattice towers with polygon bases is studied. The focus of this research is to demonstrate the ability of a computational form-finding method in multi-objective design, and to offer arrays of comparable good solutions instead of a single “optimal” form. In addition, the Shukhov water tower is considered in order to draw a comparison between the results of the presented form finding technique and a well known successful design. First, different tower configurations are described through geometrical concepts of Formex algebra. Formex algebra is a mathematical system that allows the designer to define geometrical formulation of forms. The geometrical parameters used in formulations are the base shape of the towers, frequency of elements along the height of the tower, diameter of bottom base and the mesh patterns. The constant parameters, such as the height of the tower and diameter of the top are set to match the values of the Shukhov water tower. Then, the ParaGen framework uses a non-destructive, dynamic population GA (NDDP GA) to fill a database with solutions linked to a variety of performance characteristics. The database of solutions can then be explored for any single or multi-objective performance criteria. Because the solutions are linked to descriptive images, the exploration process takes place at both a visual qualitative level as well as a performance driven quantitative level. For the purpose of comparison, the properties of A-36 structural steel pipe sections are used. Using STAAD.Pro (Bentley Systems) for the analysis, it was also possible to size all members using AISC steel code as well as collect additional performance parameters such as deflection and modal frequency. At last, results are entered into a SQL database which is linked to visual images of the designs. This allows for the comparison of designs both visually and using quantitative data. Pareto front graphs were produced based on the computational study, and the best performing results are plotted on these graphs in which the Shukhov water tower is also located for comparison. In conclusion, the strengths and concerns of applying the proposed method are also discussed, and it is explained how designers can expand their design perspective and be provided with arrays of appropriate solutions, instead of simply one best solution, using a dynamic process of form generation and optimization.

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