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Record W3116422317 · doi:10.18280/ijdne.150617

Bio-pellets Manufacture from Palm Fruit Skin as Renewable Alternative Fuels in Updraft Type Gasification Furnaces

2020· article· en· W3116422317 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Design & Nature and Ecodynamics · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicNatural Products and Applications
Canadian institutionsnot available
FundersDirektorat Jenderal Pendidikan Tinggi
KeywordsPelletsWaste managementRaw materialPulp and paper industryCombustionHeat of combustionEnvironmental scienceBriquetteBiomass (ecology)PelletRenewable energyStoveMaterials scienceCoalEngineeringChemistryComposite materialAgronomy

Abstract

fetched live from OpenAlex

Biomass is a suitable alternative to be used as fuel, but the use of biomass without prior processing can cause respiratory disease. In Indragiri Hilir Regency, the utilization of palm fruit skin waste is still minimal. Bio-pellet is a fuel derived from biomass waste that has gone through a densification process. The process of making bio-pellets is carried out by refining the raw materials, mixing the adhesives, printing the raw materials that are pressed under high pressure, and drying. The results of the research on the bio-pellet characteristic test of Nipah fruit peel waste according to its parameters obtained an average value of 1.28% water content, 0.51% ash content, 21.3% flying substance content, 76.88% bound carbon content and weight. type 1.41 gr / cm3. For the combustion test in the updraft type gasification furnace with the addition of 0.5kg, 0.3kg and 0.2kg of fuel, the results obtained from the rate of fuel consumption are 0.041kg / minute, 0.033kg / minute and 0.033kg respectively. /minute. In the results of combustion efficiency, the value according to SNI 7926: 2013 is the addition of 0.5kg of fuel at the beginning of ignition and 0.2 kg at the end of ignition, which is 0.04.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.575
Threshold uncertainty score0.273

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 integrity0.0000.001
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 head0.020
GPT teacher head0.252
Teacher spread0.232 · 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