Shape grammar implementation tools play an important role in the generation of designs. Most of the available tools were created to allow the application of shape grammar rules without restrictions. This is largely because shape grammars are context free, as such, the application of a rule is not controlled during derivation. This is also the reason some generate designs that have parts that are too small for the human eye to see. This work presents a tool that allows the addition of bag context to shape grammar rules such that it automatically allows when a rule should be applied based on a defined range. Bag context represents information that is not part of a developing design but instead evolves separately during a derivation. This helps to generate an infinite number of images that are similar but not identical. This tool could offer a wide range of application areas such as aiding the teaching of shape grammar or bag context shape grammar implementation in formal language classes or higher learning in general, a framework to support designers for the development of an improved bag context shape grammar interpreter tool, and others.
Structural optimization is a promising form-finding technique for the architectural schematic design phase of buildings. However, most published case studies tend to reduce practical design and analysis problems into simplified theoretical models in which materiality, geometry and loading conditions are over-simplified. This paper presents a structural optimization case study that allows the inclusion of complexity using Grasshopper and Matlab. The optimization process includes an automated update of structural size, shape and topology, material properties, and loading conditions. The method is applied to a parametric skyscraper design problem to demonstrate the use of Grasshopper to expedite the implementation of a complex problem and thereby facilitate the architectural schematic design phase.
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