Computationally Driven Material Ecologies employ a data–driven approach—including computational design, structural simulation, and toolpath planning—to fine–tune digital fabrication processes and customize material performance and properties. Within additive manufacturing, precise control of material deposition enables the application of gradient algorithms, rheology analytics, raster orientation, and non–planar toolpaths to exceed the performance of original materials.
These emergent material behaviors introduce new environmental and ecological structures for materials that were not previously recognized. This approach enables the efficient use of materials to achieve enhanced performance, supporting sustainable fabrication with limited resources. Ranging from microscale to large–scale additive manufacturing, this computationally driven approach supports the integration of fabrication tool limitation to preserve emergent material behaviors at scale.
In this section, two interrelated projects are highlighted: Raster Orientation Effects and Non–Planar Reinforcement, demonstrating how precise raster–orientation patterning enables the formation of composite shell structures.
Raster Orientation in Large-Scale Robotic 3D Printing of SCF-PLA
This work is structured in two complementary phases that link material characterization with architectural-scale fabrication. Phase 1 establishes a fundamental understanding of how raster orientation and material composition influence the mechanical and…
Axisymmetric Column No. 1
Description Axisymmetric Column No. 1 exemplifies a novel approach to large-scale robotic additive manufacturing, utilizing curved-layer fused filament fabrication (CLFFF) on a pre-stretched textile. It explores how patterning affects CLFFF printing to develop a…