Design Analysis of Mass Timber and Volumetric Modular Strategies as Counterproposals for an Existing Reinforced Concrete Hotel
Bibliographic record
Abstract
Construction professionals work in silos and use traditional design and construction methods. The growing demand for rapidly built and high-quality construction is making off-site manufacturing mainstream. Studies have shown that collaboration among all stakeholders is a necessary component for success in the construction of such buildings. This multidisciplinary study of an existing concrete hotel aims to explore an alternative structural design in mass timber or volumetric modular construction. To this end, the reinforced concrete floor plan of Club Med de Charlevoix in Quebec, Canada, was used as a benchmark for two different structural systems. The first strategy investigated CLT (cross-laminated timber) and glulam columns to replicate the reinforced concrete system (column–slab), while the second involved maximum prefabrication (volumetric modular construction). Both mass timber and volumetric modular strategies can lead to a smaller carbon footprint. The main conclusion is that the plan should be designed from the outset to be either traditional or prefabricated since major changes are required if the choice is made to switch from one system to the other. Moreover, when structural systems maximize off-site construction, such as volumetric modular construction, the various professions need to be included during early planning. This is necessary to avoid task duplication and prevent the neglect of considerations such as manufacturable dimensions and partition organization.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".