description
Ongoing R&D project continuing to build out a variety of tools and workflows for the purpose of Computational Design for Additive Manufacturing using Houdini. This project explores utilizing volumetric fields to store data in order to drive pattern density for additive infill patterns.
The density gradients are driven by the location of parts in order to provide a more materially optimized infill pattern. This provides a number of benefits including the ability to tune patterns for weight reduction, flexibility or stress resistance, reduction of material use, variable porosity for airflow or thermal transfer, and others.
This procedural system can take in a variety of part shapes and design parameters in order to generate automated and optimized infill patterns across multiple typologies.
The parts have been rendered to mimic the appearance of a translucent bio-based resin, such as PEGDA.
More to come.
