A simulation-based decision support tool for integrating site layout and construction planning of tunneling projects
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose Integrating construction and site layout planning in mechanized tunnel infrastructure projects is essential due to the mutual impacts of construction planning and site layout decisions. Simulation can incorporate site layout planning and construction planning of tunneling projects in a unified environment. However, simulation adoption by industry practitioners has remained relatively limited due to the special skills required for building and using simulation models. Therefore, this paper aims to create a simple-to-use simulation tool that supports site layout and construction operation planning of tunneling projects. This tool intends to promote the simulation application in site layout planning. Design/methodology/approach The current paper proposes simulation as a decision support tool (DST) to provide an integrated environment for modeling tunnel construction operations, site layout and capturing the mutual impacts. A special purpose simulation (SPS) tool was customized and developed for typical mechanized tunneling projects, by tunnel boring machines, to facilitate building the model and allow access to users with limited simulation knowledge. Findings The results show that the developed SPS tool is of great assistance to construction industry practitioners to analyze a variety of site layout and construction plan scenarios and make informed decisions based on its comprehensive and intuitive outputs. Originality/value The main contribution of this research is to promote simulation application in site layout planning of tunneling projects through the development of a simple-to-use tool, which has sufficient details for site layout planning and constraints. The developed DST enables planners to make decisions simultaneously on the site layout, other construction planning variables and identify the most efficient plan.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it