Unlike a top-down approach which is essentially a decomposition of the whole geometry, a bottom-up design is departing from the point of a single, unique component. The component is making its way through multiplication to a greater collection or cluster of individual pieces that are changing their shape or behaviour according to local agents and rules. In another word, a self-organized system translated from small-scale elements to a large architectural volume without predictable geometrical outcome. One of the growing systems among various self-organizations is Cellular Automata.
In simple terms, Cellular Automata is based on a principle of single cell situated on two- dimensional orthogonal grid and population of it's neighbouring fields. There are two populations known as Moore neighbourhood and von Neumann neighbourhood. Both rules are omnidirectional at first level of population, however Moore's system is occupying entire space around the primary cell, further growing in all possible directions, whilst von Neumann's is extending only in direction of 4 sides of it's original cell. For the purpose of this research, these two rules are converted into truncated tetrahedron and their 3dimensional self-organized behaviour is analysed through Stereoscopic visualisation.
First part of the research is a study of a family of 6 complex components, each fitting within the boundary of truncated tetrahedron. This primitive solid has 4 large and 4 small sides allowing for multiplication in diagonal directions throughout space. Nevertheless, because of the object's angles, the growth is never linear. Instead it is expanding in spherical, volumetric fashion or directionally, in a spiral line, depending on local attributes and parameters. The rule of 6 components is organizing multiplication system from level 01 to 06, where single element grows up to 52 pieces. For each expansion the component is automatically changing it's morphology and behaviour, thus creating unanticipated result. The application of 3D stereoscopic views is helping in understanding these results before they proceed to design or fabrication process
Aggregation Research 2013
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