Estimating the Size of Temporary Facilities in Construction Site Layout Planning Using Simulation
Bibliographic record
Abstract
This paper proposes a framework for estimating size of temporary facilities, a crucial task for construction site layout planning. Underestimation of facility size can lead to facility space shortage, productivity loss, and safety problems; overestimation results in lack of space for other facilities. Some temporary facilities have fixed or predetermined sizes. For other facilities, size depends on progress of activities and may vary over project duration. This study focuses on the latter, and implements simulation as a suitable planning tool to estimate size of activity-dependent facilities. Existing studies on site layout planning do not fully address this topic, and current practice often is based on experts' experience. In this study, simulation is implemented to model the construction process, and space is considered a resource in the model. Utilization of the resource over time indicates the space requirement trend over the project time. The main contribution of this work is estimation of the maximum required size of activity-dependent facilities and its variation over time. The case study presented demonstrates practicality of the proposed approach and capability of simulation in this area.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".