
Birds and many other living organisms rely on large old trees for their survival. However, these trees are rapidly disappearing from many landscapes. The regrowth of such trees takes hundreds of years, and in many disturbed landscapes, wildlife populations cannot persist without temporary human-made replacement structures. In 2022, Mirra et al. [1] conducted a study on the AI-based generation of 3D models, or visual abstractions, of large old trees. An AI agent analysed a dataset of these trees to identify features that appeal to animals and generated forms that approximated these features. The researchers also evaluated the usefulness of the AI-generated forms as artificial replacements for trees using morphological and cost criteria. Building on this research, we developed our pavilion entry for the IASS 2024 design competition. Our focus was on creating (1) a design strategy to translate the AI-generated visual abstractions into buildable tensegrities, and (2) a fabrication method that facilitates the transport, assembly, and disassembly of these structures using repurposed and biodegradable materials. We named this prototype “FloaTree”. We have constructed prototype tests in Melbourne, Australia, and will build the full-scale pavilion during the annual IASS symposium in Zurich, Switzerland, in August 2024.
Sustainable architecture, Structural engineering, Architectural design, Biodiversity conservation, Architecture engineering
Sustainable architecture, Structural engineering, Architectural design, Biodiversity conservation, Architecture engineering
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
