Digital fabrication technologies greatly enhance and extend manufacturing possibilities. However, we are still relatively limited in our ability to fully exploit these new methods and create complex architectural structures with performance-driven properties. We argue that entirely new computational approaches are needed, using scalable generative encodings and advanced bio-inspired form finding processes. This paper presents a novel generative model that can create functional and expressive geometries by evolving volumetric gradient patterns. Using three case studies, we demonstrate the key advantages of our approach. We demonstrate, using simulation followed by physical fabrication, that our approach is useful for exploring complex, yet buildable geometries in early stage design. Our new method is therefore suitable for performance-driven form finding tasks such as structural optimization, and holds vast potential for designing exotic multi-material and functionally graded materials in future applications.
|Title of host publication||Proceedings of the 34th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA 14: Design Agency)|
|Publication status||Published - 2014|