BIM-Based Co-Simulation of Fire and Occupants’ Behavior for Safe Construction Rehabilitation Planning
Bibliographic record
Abstract
Construction renovation projects increase the risk of structural fire, mostly due to the accumulation of combustible construction materials and waste. In particular, when the building remains operational during such projects, the redistribution of occupants and interruptions with access corridors/exit egress can exponentially increase the risk for the occupants. Most construction projects are, however, planned and scheduled merely based on the time and budget criteria. While safety is considered paramount and is meant to be applied as a hard constraint in the scheduling stage, in practice, safe evacuation considerations are reduced to rules of thumb and general code guidelines. In this paper, we propose simulation as a tool to introduce safety under structural fire, as a decision criterion, to be mixed with time and budget for selecting the best construction schedule alternative. We have used the BIM (building information model) to extract the building’s spatial and physical properties; and have applied co-simulation of fire, through computational fluid dynamics (CFD), and occupants’ evacuation behavior, through agent-based modeling (ABM) to estimate the average and maximum required safe egress time for various construction sequencing alternatives. This parameter is then used as a third decision criterion, combined with the project’s cost and duration, to evaluate construction schedule alternatives. We applied our method to a three-floor fire zone in a high-rise educational building in Montreal, and our results show that considering the fire safety criterion can make a difference in the final construction schedule. Our proposed method suggests an additional metric for evaluating renovation projects’ construction plans, particularly in congested buildings which need to remain fully or partially operational during the renovation. Thus, this method can be employed by safety officers and facility managers, as well as construction project planners to guide accounting for fire incidents while planning for these types of projects.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".