panels act as a weather screen for the Observatory, hence their design integrates layers intended for protection. In phase one, we can differentiate between three layers: the base -which provides structural stability and integrates wooden fittings to attach to a substructure-, the sacrificial overhang layer -which extrudes outwards to protect the base by redirecting water runoff-, and a connective layer -which stitches over the first two. The printing geometry is created using a generative algorithm to generate a grid based pattern. The three layers are differentiated through material specification. Woodflour fibres are used for the base, giving a yellow hue, bark and cotton for the overhang layers resulting in a dark brown colour, while the connective layer printed with cotton fibres has a blue tone. The panels are attached to the substructure through a French cleat system at the top edge and four bespoke connectors along the side edges to reduce warping.
In this experimental setup, the panes are tracked through computer vision processes as they are exposed to weather conditions. As damage is observe, the panels are removed from the observatory and repaired off-site. The repair workflow consists of registering and identifying deterioration conditions in a digital environment, followed by a corrective action through 3D printing. The contrast created by varying the fiber colour and height of the panels can create a connection between the initial design and repair workflow. The parameters informing the design link to the data streams from the registration output in the diagnosis process, allowing identification of the regions requiring repair. The panels are installed again on the observatory, entering a new cycle of exposure, monitoring and repair.
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).