A comprehensive study of temperature data during the filling and post-closure phases at a landfill in Québec, Canada: Application of a thermal–mechanical–biological model
Bibliographic record
Abstract
A 12-year field study on municipal solid waste (MSW) stabilization in Northern climates was conducted at Ste. Sophie landfill in Québec, Canada. Temperature and settlement data were collected from 12 instrument bundles placed at varying depths in two vertical columns within the waste during the filling and post-closure phases. The data demonstrated a 12-18 month delay in temperature rise during the filling stages due to frozen or partially frozen MSW and highlighted ambient temperature effects at shallow depths. A thermal-mechanical-biological (TMB) model was developed and calibrated to simulate the impact of temperatures on MSW stabilization, particularly emphasizing landfills without leachate recirculation in Northern climates. The biological model related anaerobic heat generation from MSW with temperature and expended energy from biodegradation. The resultant heat was integrated into the thermal model, allowing for the simulation of heat transfer through conduction. The thermal parameters were expressed as a function of density, which was updated in the mechanical model that combined a Generalized Kelvin-Voigt model with a biodegradation-induced strain term. This term was represented as the ratio of expended energy over time to total potential expended energy of the waste. The TMB model effectively predicted MSW behaviour, considering temperature rise delays in cold and sharp rises in warm conditions. This is essential for optimizing landfill operations by promoting waste stabilization before applying the final cover.
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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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".