Abstract
An innovative generative design strategy, based on shape grammar, is proposed for the minimum-weight design of diagrid tall buildings. By considering the building as a three-dimensional vertical cantilever beam with a tubular section under horizontal load, it is evident that bending and shear stiffness demands vary along the width and elevation of the building. Further, while the structural design of tall buildings is usually governed by stiffness, the predominant design criterion for diagrids could be the local strength demand, especially for low slenderness values, thanks to the inherent rigidity of the triangular pattern. Starting from these considerations, in this paper, a generative design strategy is proposed, able to find diagrid patterns that accommodate the differentiated stiffness demand along width/elevation and satisfy the predominant design criterion, stiffness or strength. The design strategy is applied to tall building models characterised by different slenderness values. The comparison to diagrid patterns analysed in previous literature works in terms of structural weight and performance parameters highlights the effectiveness of the design strategy and the efficiency of the generated patterns.
Highlights
Design is a typical “wicked problem” [1], namely an ill-structured problem, characterised by open-ended expectations, emerging constraints, non-quantifiable features, absence of global optimality and contradicting solution paths [2]
A paradigm shift has occurred in the structural design workflow thanks to Computational Design (CD) that fully entails the use of computation for the exploration of structural solutions and the development of design ideas [3,4]
The structural grammar was developed for generating the geometry of the pattern and sizing the relevant structural members
Summary
Design is a typical “wicked problem” [1], namely an ill-structured problem, characterised by open-ended expectations, emerging constraints, non-quantifiable features, absence of global optimality and contradicting solution paths [2]. GD tools are able to seek for uncommon solutions that usually do not fall within a standard and defined set of shapes/topology and cannot be anticipated in the phase of the algorithm writing, including so-called “happy accidents” [5] These characteristics make the approach widely used in fields like product design, mechanical engineering and architecture. The grammar is defined by such parameters and intertwined rules with which the algorithm makes a series of automated choices and decisions These decisions lead to a number—theoretically—infinite of geometries, where all possible solutions are considered as potentially feasible and efficient, despite not being imagined and anticipated in the phase of algorithm writing. For each solution generated by the shape grammar, a structural model is created, structural members are sized and analyses are carried out under design loads Both the generation of the design alternatives and the choice of the optimal one are demanded to optimisation algorithms. In the following sub-sections, the above phases are described in detail
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