Catenary Wooden Roof Structures: Precedent knowledge for future algorithmic design and construction optimisation
Bibliographic record
Abstract
The timber industry is expanding, including construction wood product applications such as glue-laminated wood products (R. Sikkema et al., 2023). To boost further utilisation of engineered wood products in architecture, further development and optimisation of related tectonic systems is required. Integration of digital design technologies in this endeavour presents opportunities for a more performative and spatially diverse architecture production, even in construction contexts typified by limited means and/or resources. This paper reports on historic precedent case study research that informs an ongoing larger study focussing on novel algorithmic methods for the design and production of lightweight, large-span, catenary glulam roof structures. Given their structural operation in full tension, catenary-based roof structures substantially reduce material needs when compared with those relying on straight beams (Wong and Crolla, 2019). Yet, the manufacture of their non-standard geometries typically requires costly bespoke hardware setups, having resulted in recent projects trending away from the more spatially engaging geometric experiments of the second half of the 20th century. The study hypothesis that the evolutionary design optimisation of this tectonic system has the potential to re-open and expand its practically available design solution space. This paper covers the review of a range of built projects employing catenary glulam roof system, starting from seminal historic precedents like the Festival Hall for the Swiss National Exhibition EXPO 1964 (A. Lozeron, Swiss, 1964) and the Wilkhahn Pavilions (Frei Otto, Germany, 1987), to contemporary examples, including the Grandview Heights Aquatic Centre (HCMA Architecture + Design, Canada, 2016). It analysis their structural concept, geometric and spatial complexity, fabrication and assembly protocols, applied construction detailing solutions, and more, with as aim to identify methods, tools, techniques, and construction details that can be taken forward in future research aimed at minimising construction complexity. Findings from this precedent study form the basis for the evolutionary-algorithmic design and construction method development that is part of the larger study. By expanding the tectonic system’s practically applicable architecture design solution space and facilitating architects’ access to a low-tech producible, spatially versatile, lightweight, eco-friendly, wooden roof structure typology, this study contributes to environmentally sustainable building.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".