Innovation in hybrid mass timber high-rise construction : a case study of UBC’s Brock Commons project
Bibliographic record
Abstract
With the advocacy for sustainable construction on the rise, use of timber as the main building material is being championed in large-scale construction projects. While the advancement of engineered timber products is addressing some issues that previously limited the use of wood in high-rise construction, there are still challenges such as fire and weather safety, code compliance and negative public perceptions. One main gap in the available resources is the lack of a comprehensive and detailed case study of a high-rise project with wood as the main construction material to capture constraints and innovations necessary in creating success, which has formed the direction of this research. This thesis is focused on documenting a case study of the Brock Commons project, an 18 storey, hybrid timber-concrete residential high-rise located at the University of British Columbia, Vancouver campus, which is the tallest hybrid timber building in the world. The overall research objective was to identify and document the delivery of this innovative project, with a specific emphasis on the innovations necessary to make timber high-rise construction successful and the use of VDC tools in the design and pre-construction process. The case study documents the project context, the design process, the business and industry drivers, and the motivation for construction. Moreover, it investigates the motivations for all stakeholders, identifies the challenges and constraints, and captures the innovative solutions that were utilized to ensure project success. The case study also documents the innovative use of VDC to support prefabrication and overall project coordination. Specifically, it investigates the role of the VDC integrators in the project, the paths of communications with the different project team members, and the inputs and outputs of each phase of design and construction. This research identified lessons learned that can be applied to other construction projects where timber is the main structural component and a heavy use of VDC and pre-fabrication is required. Use of timber and innovative methods in construction have been consistently rising in the past decade, and this research aims to provide a starting point for future efforts in mass timber high-rise construction.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| 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".