Biogas production from chicken food waste and cow manure via multi-stages anaerobic digestion
Bibliographic record
Abstract
Biogas is a clean and renewable form of energy that can be produced from organic waste via anaerobic digestion using a bio-digester. Fixed dome, floating drum and plug flow digester is few of typical digester design that has been used around the world. The sizes of these reactors varies depending on the organic loading rate of the available organic waste as well as the retention time of the substrate inside the reactor. In most cases, bio-digester requires large area, constant agitation and very stable environment. Despite its numerous advantages, the potential of biogas technology depends on many factors including feedstock type, reactor design and operation parameters. Even though many studies have been done to understand the effect of these factors, there are not many study that focus on the design of the reactor to optimize the potential of biogas production from food waste. In this study, the use of multi stage reactor that requires smaller footprint will be tested to enhance the gas production rate from solid substrates (food waste and other organic materials). The study includes experiment to study the effect of stages inside the reactor, composition of substrate and size of food waste on the biogas production. The results show that the stages do have effect on the gas production. With the present of stages inside the reactor, the gas production can be increased up to 30 %. In addition, the amount of protein increases gas production. However, if the protein hydrolysis rate is high, it can disturb the process since the methanogenesis favour neutral pH.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 source (direct Gemma or distilled Codex), 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".