Mathematical modelling of composting processes using finite element method
Bibliographic record
Abstract
Composting is one element of waste management.It allows waste to be transformed into a valuable product.The processes involved and the final product, however, may vary in terms of quality, efficiency or security.Models have been established to represent some features of the composting process, but never all of them together.We hypothesized that all the key features from the literature could be gathered in one model.This model should be qualitatively faithful, reliable, and easily adapted to any situation.We used COMSOL TM , software that uses proven algorithms and the finite element method to solve partial differential equations in high spatial resolution in up to three dimensions.The behavior of this model was studied through parameter variations and sensitivity analysis.Patterns in temperature, biomass, substrate, oxygen and water concentration curves were consistent with the typical curves found in literature about composting.Initial water concentration and airflow were found to have an important impact on the composting process, while inlet air temperature did not.The resolution of the mathematical problem in a two-dimensional, longitudinal cross-section of the rectangular vessel allowed the observation of spatial patterns.This model can be used as a basis for further studies as new features are easy to implement.It can likewise be adapted to any apparatus, which makes it useful for comparative analysis.The suggested model, however, has yet to be validated against a physical system and this should be the next step.iii conditions exprimentales, ce qui en fait un bon outil comparatif.Cependant, le modle suggr doit d'abord tre valid par des donnes exprimentales.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".