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Using a Biocell to Measure Effect of Compressive Settlement on Free Air Space and Microbial Activity In Windrow Composting

2001· article· en· W2334184306 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCompost Science & Utilization · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicComposting and Vermicomposting Techniques
Canadian institutionsUniversity of Manitoba
FundersUniversity of Manitoba
KeywordsMeasure (data warehouse)Settlement (finance)Air spaceSpace (punctuation)Compressive strengthEnvironmental scienceWaste managementEngineeringAerospace engineeringPhysicsComputer scienceWorld Wide WebThermodynamics

Abstract

fetched live from OpenAlex

AbstractThis paper describes the first equipment developed to include compressive loads in a physical model of the composting environment. This new type of composting reactor was named a biological load cell, or biocell for short. Our hypothesis was that the exclusion of compressive settlement in existing physical models may lead to errors if the data is used to design full-scale windrow composting facilities. Municipal biosolids were mixed with three organic amendments (wood chips, straw, and leaves) to yield mixture moisture contents of 55%. Compressive settlement analyses were completed by subjecting the mixtures to loads of 0, 4.3, 8.6, and 12.9 kPa using biocells. The effect of compressive settlement on microbial activity was investigated using the biosolids:leaf mixture under loaded (12.9 kPa) and unloaded conditions. The settlement behavior of all three mixtures was found to fit established soil compaction equations and new equations were developed to represent the vertical free air space (FAS) and bulk density profiles in composting systems. The FAS profiles indicated that existing physical models do not simulate the FAS conditions within a composting matrix and significant differences in microbial activity were observed between loaded and unloaded biocells. The microbial activity differences were attributed to the reduced FAS within the loaded biocells, which, in consequence, lead to lower pore space oxygen concentrations. It proved difficult, however, to simulate the air flow regime within a windrow composting matrix. To further develop the biocells, there is a need to investigate the in-situ stress conditions and natural draft ventilation rates of full-scale windrow systems. While further work is required to perfect the biocells as a physical model of the windrow composting environment, it has demonstrated its potential use for FAS analysis and as a standard bulk density apparatus. Using biocells, it is recommended that FAS curves be developed for a wide range of feedstock recipes. The biocell apparatus could also be developed as a standard bulk density test apparatus. Other important conclusions drawn from the work include: leaves should not be used as a bulking agent; wood chips showed superior bulking properties and are recommended for use in very high (3.7 m) windrows; straw showed intermediate bulking properties and should not be used for high windrows without further investigation; for all materials, compaction occurred rapidly after each incremental load, suggesting that windrow turning will do little to alleviate a low FAS problem associated with an incorrect composting recipe.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
Threshold uncertainty score0.432

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.067
GPT teacher head0.305
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it