Effect of glycerol on densification of agricultural biomass
Bibliographic record
Abstract
Experiments were conducted to verify the effect of adding glycerol for pelleting of selected agricultural crop residues, namely, wheat, barley, oat and canola straw. Single pelleting tests were conducted to study the effect of biomass type, hammer mill screen size, and crude glycerol content (co-product of biodiesel industry) on pellet quality (density and durability), ash content and gross heat of combustion. Four types of biomass were ground at three different hammer mill screen sizes of 6.4, 3.2 and 1.6 mm. Each biomass was mixed with three levels of glycerol of 2.5%, 5.0% and 7.5% by weight. Pellets were made at a pre-set load of 4 400 N (138.9 MPa) using single-pelleting unit attached to an Instron testing machine. Quality of pellets was determined by measuring pellet density, relaxed density, durability (measured by pellet drop test) and specific energy required to make a pellet. The gross heat of combustion and ash content of pellets were also determined and compared. The highest pellet density (988-1 133 kg/m3) and relaxed density (992-1 142 kg/m3) were obtained from biomass ground using a hammer mill screen size of 6.4 mm. A decrease in hammer mill screen size resulted in reduced durability. The highest durability of biomass obtained from hammer mill screen size of 6.4 mm ranged from 97%-100%. Addition of glycerol resulted in lower ash content in majority of pellets. The highest gross heat of combustion was observed in pellets made from wheat straw with 7.5% glycerol content (38.3 MJ/kg). Addition of glycerol resulted in lower pellet densities, lower ash content, no change in durability and higher gross heating values. DOI: 10.3965/j.ijabe.20150801.009 Citation: Emami S, Tabil L G, Adapa P. Effect of glycerol on densification of agricultural biomass. Int J Agric & Biol Eng, 2015; 8(1): 64－73.
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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 | 0.000 | 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 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".