The impacts of temperature and thermal properties on municipal solid waste stabilization
Bibliographic record
Abstract
Instrument bundles placed within the Ste. Sophie landfill (Quebec, Canada) have been collecting temperature, settlement, and oxygen data since 2009. The temperature and settlement of the landfill were modelled using the finite element software COMSOL Multiphysics. The COMSOL optimization module was utilized to determine the thermal conductivity and specific heat of the waste as a function of time and depth. An anaerobic heat generation coefficient was employed to decrease the overall heat generated in the domain and a new latent heat value was assumed. The concept of total expended energy was used to replace the time-dependent biodegradation-induced settlement term with a temperaturedependent biodegradation-induced settlement term. The new term better accounts for the delayed biodegradation process observed in cold climate wastes. The model was in good agreement with the temperature and settlement data collected from the Ste. Sophie landfill. A simulation was run in order to study the effects of placement conditions on waste settlement and stabilization. It was found that waste placement temperature has an impact on overall settlement at the landfill. By strategically placing waste throughout the year, more waste can be placed during the filling stages of the landfill, simultaneously bringing increased revenues to landfill operators while decreasing the environmental burden of landfills.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 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".