We wrote a computer program to generate 3D forms using a mathematical simulation of Reaction-diffusion, and used this software to grow the designs of the reaction collection. Parameters of the simulation can be varied for differing effects, creating different types or directions of pattern. These parameters are controlled and change through space to express design intent. The process begins on an imported underlying surface, and a 3-dimensional object is formed by embossing or removing material from that surface based on the chemical concentration present at each point in space. Multiple scales of pattern and simulation are used to create more detailed forms.
Inspiration
Reaction-diffusion (RD) is a canonical example of complex behavior that emerges from a simple set of rules. RD models a set of substances that are diffusing, or spreading; these substances also react with one another to create new substances. This simple idea has been suggested as a model for a diverse set of biological phenomena. All kinds of animals from fish to zebras display interesting color patterns on their skin and shells which play important roles in their behavior. However, the underlying cause of these patterns is still not understood. In 1952, Alan Turing suggested the RD system as an answer to not only this question but also the more general one of why cells differentiate. How do individual cells locate themselves in the larger scale structure and pattern of an organism? The patterns seen on the animals occur over a scale much larger than a cell, yet they display remarkable self-similarity on every part of the animal’s body.
Turing studied the behavior of a complex system in which two substances interact with each other and diffuse at different rates. He proved mathematically that such a system can form stable periodic patterns even from uniform starting conditions. One of the most interesting things about RD is that you can have a homogeneous system where every cell is doing exactly the same action (for instance just producing a certain amount of some chemicals); but from this one process a large scale structure emerges.
SIMULATING REACTION-DIFFUSION
One of the intriguing aspects of reaction-diffusion is how a simple chemical system can produce a variety of patterns through small changes. Nervous System’s reaction diffusion experiments use the Gray-Scott model. This describes a system of two chemicals, often referred to as U and V, where U and V combine in a reaction to form more of V. Additionally, chemical U is produced at a certain rate, while chemical V naturally decays at a fixed rate. Changing just these rates of production and decay results in patterns of dots, lines, holes, or spirals.
By working with multiple scales, varying parameters, and using anisotropic diffusion (in which chemicals flow more easily in one direction than another), it is possible to sculpt reaction-diffusion patterns.
algorithm processing reaction