Rhizaerial explores the continuous grading of a biopolymer composite material. It extends the circular design framework for biopolymer composites within architectural application by formulating new design and fabrication approaches that engage with and respond to the inherent variability of resource availability.
In Rhizaerial, we design and fabricate a suspended ceiling structure whose geometry, expression and material specification vary locally. This interior system of connected curved components is robotically printed in a 3d porous lattice structure that allows light to pass through while maintaining structural integrity. The project develops the design and fabrication methods that enables this targeted variation.
Rhizerial develops methods for varying material composition in response to resource availability. Reclaimed and residual resources are characterised by highly dynamic changes to their accessibility and value. To work efficiently with cascading, this project develops a broad recipe space and aligned new material specification approaches that support exploration and responsiveness to locally available resources.
The project uses machine learning to navigate this recipe space. The project connects Design of Experiments to a Parameterless SOM method. This method allows us to use the specific properties of tested material formulations to make predictions about of properties of untested recipes in an open and exploratory way.
The biopolymer composite is printed robotically onto a shaped mould mounted to a turntable. Two separate material feeds are mixed at the nozzle, and locally air cooled to speed reprinting. Material grading occurs throughout the plane and section of each vault.
The Eco-Metabolistic Architecture project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 101019693).
The Eco-Metabolistic Architecture project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 101019693).