Construction waste management at source : a Building Information Modeling based system dynamic approach
Bibliographic record
Abstract
Construction waste is considered a major contributor of solid wastes in municipal landfills. As per the Canadian construction industry, construction, renovation, and demolition (CRD) wastes constitute 27% of total municipal wastes disposed to landfills. Many researchers have stated that 75% of wastes generated by construction industries have residual value. They can be even recycled, salvaged, and/or reused. In such circumstances, construction wastes have to go for recycling, which is as costly and environmentally harmful as going for new material. Sustainable and practical solutions then have to: (i) minimize the construction waste at source during the project construction phase, and (ii) optimize the material usage of the ‘proposed construction’ in the design phase itself. To achieve both of these objectives, virtual construction techniques, which can forecast potential waste of a given project with cost and schedule variations, are required. However, there are only a few studies carried out to analyse the complex relationships among the design, rework, material management, and construction functions in waste management. The waste should be avoided at source by considering the entire life cycle performance of the project. Building Information Modeling (BIM) is a relatively new and much unexplored area in construction waste management. BIM has immense potential with today’s computing power and technology. The aim of this thesis is to enhance use of BIM to minimize construction waste at source by micro-mapping objects and spaces with a novel use of dynamic simulation techniques and earned value management methods. System Dynamic Modeling (SDM) is an effective tool to analyse the pattern of changes in variables of a system over time. The use of the SDM enables projects to be managed more effectively with respect to waste management policy assessment. This thesis proposes a method of dealing with the complexity, interrelationships, and dynamics of Design-Bid-Build projects. Firstly, a BIM-Partnering approach for public construction procurement is presented with the aim to reduce construction waste right at source, early in the design stage. Then, a reinforcement cutting waste optimization technique integrated with BIM is presented. Finally, a dynamic model integrated with BIM; to minimize construction waste at source is presented.
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How this classification was reachedexpand
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 | 0.000 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".