Reaction-diffusion form (Gierer-Meinhardt process)
Reaction-diffusion form (Gierer-Meinhardt process)
Reaction-diffusion form (Gierer-Meinhardt process)
Reaction-diffusion form (Gierer-Meinhardt process)
Reaction-diffusion form (Gray-Scott process)
Reaction-diffusion form (Gray-Scott process)
Cellular automata (two successive states)
Cellular automata (three successive states)
Cellular automata (two successive states)
Cellular automata (two successive states)
Voxel-based Geometries (2009)
This project continues the exploration of a procedural approach to form. Rather than work with surfaces as in the subdivision experiments, this project uses volumetric cells - voxels - as its foundational geometry.
These voxels contain data that can interact with data of proximate voxels according to pre-established sets of rules. Through iterative interactions, data propagates across the voxel space, ultimately forming complex structures. These can be visualized as individual elements or as a continuous hull encompassing specific data values.
Two broad algorithms to control voxel interaction are explored: cellular automata similar to the Game of Life, and reaction diffusion processes. Cellular automata typically involve cells with binary states (on/off), determined by the states of surrounding voxels.
The latter process, reaction diffusion, allows multiple float values to be associated with each voxel. This process simulates chemical interactions between substances, and has been associated with pattern formation not only on a number of organisms, but also in the fields of geology and ecology.
Reaction-diffusion processes have garnered significant attention, though most experiments typically focus on 2D forms or extruded 2D patterns over time. This project uniquely applies these processes in three-dimensional space, shifting the focus from simple pattern formation to the emergence of complex spatial structures.
Similar to the subdivision experiments, the initial input—the starting state—is intentionally minimal, often just a single cell or line of cells with a divergent value. The process parameters are then allowed to fluctuate across both time and space, incorporating elements like spatial gradients, emitters, and vacuums.
While slight parameter adjustments can yield an astounding array of structures, controlling the output remains challenging due to its unpredictable nature. Even a minuscule change can result in an entirely different form or prevent any structure from materializing. Achieving a deliberate, architecturally constructive use of these processes is still a distant goal.
Unlike reaction-diffusion systems, cellular automata offer a relatively simpler and more controllable approach. Each cell holds a single parameter defining its state, rather than multiple values representing chemical concentrations, and its production rules are based solely on the states of its neighbors.
In 3D space, a cell's neighborhood can encompass six, eighteen, or twenty-six adjacent cells. Rules can be designed to preserve symmetry across all three axes or to introduce directionality into the system. Initial states can range from individual activated cells to vectors of cells or entire fields.
Similar to their 2D counterparts, many cellular automata systems display oscillating behaviors. Some dissolve into noise, others converge to a homogenous state, and some simply vanish. Emerging configurations can be visualized as hulls using a marching cubes algorithm.
The resulting structures exhibit and astounding variety of features. Yet one thing that they have in common is that they only function at a single global scale. There are no regional variations in the dimensions of the structure or in the level of detail. As such, their application in architecture appears better suited to generating components of a structure rather than the structure itself.
