Designing for Pre-Fabrication and Assembly in the Construction of UBCäó»s Tall Wood Building
Bibliographic record
Abstract
The construction of a 53 m, 18 story mass timber high-rise on the Vancouver campus of the University of British Columbia poses significant challenges in its design, approval, procurement and construction. As a way to facilitate the project delivery process, the project team called upon extensive use of virtual design and construction (VDC) and building information modelling (BIM) that are supported through a 3rd party VDC service provider. One of the key uses of BIM and VDC in the project is extensive design for pre-fabrication and assembly of mass timber elements and envelope panels as well as mechanical elements. The processes, techniques and tools used to support design for pre-fabrication and assembly on the UBC Tall Wood Building project are presented in this paper. The challenges and lessons learned in the deployment and use of these tools and processes and their impact on project delivery are also discussed. Lastly, the trade-offs and design considerations that support design for pre-fabrication and assembly are examined. Initial findings indicate that the design for pre-fabrication and assembly process is a highly involved and collaborative process which requires the presence of key decision makers up front in the project delivery process. They also indicate that the involvement of a 3rd party BIM and VDC modeller, using highly sophisticated digital tools, is necessary to ensure proper information flow and capture relating to the elements being designed for pre-fabrication and assembly. Ultimately, in the context of mass timber high-rise construction, where competitive advantage over other approaches resides in speed and quality of execution, aesthetic and sustainability concerns notwithstanding, designing for pre-fabrication and assembly is key in ensuring the projectäó»s economic viability.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".