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Record W4403077820 · doi:10.1016/j.elstat.2024.103983

Experimental study of electrostatic charging related to prevention of fire and dust explosions in wood processing facilities

2024· article· en· W4403077820 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

VenueJournal of Electrostatics · 2024
Typearticle
Languageen
FieldEngineering
TopicCombustion and Detonation Processes
Canadian institutionsUniversity of British Columbia
FundersWorkSafeBC
KeywordsEnvironmental scienceWaste managementDust explosionEngineeringForensic engineeringMaterials science

Abstract

fetched live from OpenAlex

To address the concern of fire and dust explosions in wood processing facilities, the charging behavior on wood dust particles and air hoses during the air-blow cleaning operation were investigated. The effective work function, unit weight and surface roughness were key parameters influencing the charge accumulation on air hoses. The use of compressed air with lower velocity and higher moisture content could reduce the charge generation on airborne wood particles. Particle size, shape and wood species affect the charging behavior of wood dust. Conductive surface and moisture could help charges to be dissipated fast from wood dust particles. • Charge generation on wood dust depends on air velocity, humidity, and contact material. • Some species of wood dust tend to generate more charge than the others. • Charge on dry wood dust decays very slowly on all tested surfaces. • Moisture and grounding could speed up the charge decay. • The effective work function, unit weight and surface roughness affect charge accumulation on air hoses.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score0.340

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 head0.015
GPT teacher head0.288
Teacher spread0.272 · 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