Continuous, self-sustaining smouldering destruction of simulated faeces
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
A new approach for the rapid destruction of human waste using smouldering combustion is presented. Recently, self-sustaining smouldering combustion was shown to destroy the organic component of simulated human solid waste and dog faeces resulting in the sanitization of all pathogens using a batch process (Yermán et al., 2015). Here, a continuous smouldering process is demonstrated for the first time, allowing for a much smaller reactor size and much less energy input per mass of waste treated. The self-sustained smouldering of simulated human faeces mixed with sand is evaluated over long periods (more than 16 h) based on a single ignition. The key process of intermittent self-sustained smouldering, in which the reaction is terminated and restarted by only turning the air off and on, is demonstrated. Experiments examine the influence of two key operator controls: airflow rate and set elevation of the quasi-steady-state smouldering front in a 37 cm high reactor. Quasi-steady-state fuel destruction rates from 93 g/h to 12 g/h were achieved by varying the superficial flow velocity from 7.4 cm/s to 0.11 cm/s, the latter with a velocity approximately an order of magnitude lower than possible for a self-sustaining reaction in an equivalent batch system. Excess energy of up to 140 J/g of sand was recovered from the clean sand produced in each cycle, which could be used to further increase the energy efficiency of this novel waste treatment system.
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.
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 | 0.000 |
| 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