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Record W3034116499 · doi:10.3390/su12114645

Pelletization of Refuse-Derived Fuel with Varying Compositions of Plastic, Paper, Organic and Wood

2020· article· en· W3034116499 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

VenueSustainability · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicRecycling and Waste Management Techniques
Canadian institutionsUniversity of SaskatchewanUniversity of British Columbia
FundersMitacs
KeywordsPelletizingPelletsPelletMaterials scienceHeat of combustionRefuse-derived fuelWater contentWaste managementComposite materialDurabilityBiomass (ecology)Mixing (physics)Pulp and paper industryMunicipal solid wasteChemistryGeotechnical engineeringEngineeringCombustion

Abstract

fetched live from OpenAlex

The combustible fraction of municipal solid waste (MSW) is called refuse-derived fuel (RDF). RDF is a blend of heterogeneous materials and thus its handling is challenging. Pelletization is an efficient treatment to minimize the heterogeneity. In this research, typical RDF compositions were prepared by mixing several mass fractions of paper, plastic, household organic and wood. The collected compositions were ground, wetted to 20% moisture content (wet basis) and pelletized. Increasing the plastic content from 20% to 40% reduced the pelletization energy but increased the pellet’s calorific value. Pellets with higher plastic content generated more dust when exposed to shaking. Making durable pellets with 40% plastic content needed an increase in die temperature from 80 °C to 100 °C. Increasing the paper content from 30% to 50% increased the durability but consumed higher energy to form pellets. Paper particles increased the friction between pellet’s surface and die wall as was evident from expulsion energy. Force versus displacement curve for material compression revealed that the RDF compositions have rigid material characteristics.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.239

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 head0.006
GPT teacher head0.205
Teacher spread0.199 · 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