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Record W4365804082 · doi:10.1615/see2000.1130

DRYING OF VALUE-ADDED LIQUID WASTES

2023· article· en· W4365804082 on OpenAlexaboutno aff
Marzouk Benali, Mouloud Amazouz, Tadeusz Kudra

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Drying and Modeling
Canadian institutionsnot available
Fundersnot available
KeywordsSlurryWaste managementInertEnvironmental sciencePulp and paper industryPulp (tooth)Environmental engineeringChemistryEngineering

Abstract

fetched live from OpenAlex

The estimated quantity of sludge generated by the Canadian pulp and paper industry in 1995 was about 2.2 million tones of dry solids (tds) while that of municipal and meat-processing sludge was equal to 612,000 and 20,000 tds, respectively. As a result of landfill directives and national legislation which impose minimum solids content of 35% and carbon limit for wastes to be landfilled, major R&D efforts are directed in developing an effective and environmentally acceptable methods of sludge treatment and disposal. Thermal drying could be an attractive solution to sludge disposal especially for complex wastes containing fibres and/or sticky components such as animal fat. Because most of dry wastes have an intrinsic value, they can be beneficially recycled in agriculture, used as a fuel or serve as an inert support in such products as a cat litter. The proposed Jet Spouted Bed Dryer with inert particles (JSBD) is an advanced and energy efficient technology to obtain powders from solutions, slurries and pastes by drying on the surface of inert particles brought into intensive and random motion. The dryer presented here was developed to process otherwise hard-to-dry pulp and paper secondary sludge and meat processing sludge as currently used technologies do not guarantee product of required quality. Experimental results obtained on a 50kW-test bench demonstrate the technical feasibility of drying such sludges, which may contain up to 15% of fibres or up to 60% of fat. Also it is possible to obtain dry product in the form of fine powder with narrow size distribution and with an average particle diameter equal to 40 µm for meat processing sludge, and 136 µm for pulp and paper secondary sludge.

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 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)0.000
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 score0.043
Threshold uncertainty score0.149

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.038
GPT teacher head0.231
Teacher spread0.193 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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