Properties of Naturally Settled Hog Manure in Outdoor Lagoons
Bibliographic record
Abstract
The objective of this study was to experimentally determine the physical properties of naturally settled hog manure collected from outdoor lagoons. Specifically, this investigation focused on the variation of bulk density, particle size distribution, and viscosity with depth from the lagoon surface and total solids concentration. The effects of temperature and shear rate on viscosity were also studied. The literature contains several studies on the physical properties of hog manure; however, comprehensive data as a function of temperature and total solids concentration are not available. Manure collected from various depths and locations within two lagoons varied in total solids concentration from 0.7% to 37.1%. Bulk density and particle size distribution were empirically determined at room temperature for all samples. Particle size distribution was determined using both microscopic imaging and sieve tests; particles detected ranged in size from 1 m to several mm. It was found that the Rosin-Rammler distribution provided a good fit for the distribution of particle diameters. The rheology of the manure was investigated for samples between 0.7% and 13.1% total solids at temperatures of 15C, 25C, 40C, and 60C and shear rates ranging from 0.0066 to 44 s-1. Surface samples with total solids concentrations under 3.6% were found to exhibit Newtonian behavior; however, bottom sludge samples with over 6.5% TS showed both non-Newtonian and time-dependent characteristics. Two intermediate samples behaved as pseudoplastic fluids and could be described using the power law. In general, apparent viscosity increased exponentially with total solids concentration, but decreased with temperature according to the Arrhenius equation.
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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".