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Record W4407548789 · doi:10.1002/fam.3283

Propagation of Smouldering in Wood Dust Deposits Ignited by Embedded Hot Bodies

2025· article· en· W4407548789 on OpenAlexaff
Chang Li, Jinglin Zhang, Chunmiao Yuan, Zhenguo Du, Paul Amyotte, Zenghui Zhao, Ronghua Li, Weizhao Liang, Zhiqun Xie

Bibliographic record

VenueFire and Materials · 2025
Typearticle
Languageen
FieldEngineering
TopicCombustion and Detonation Processes
Canadian institutionsDalhousie University
FundersFundamental Research Funds for the Central UniversitiesNational Natural Science Foundation of China
KeywordsEnvironmental scienceForensic engineeringEngineeringMining engineeringWaste management

Abstract

fetched live from OpenAlex

ABSTRACT Combustible dust poses a hazard to industry in two ways, i.e., reactive as a cloud or reactive as a pile. This paper deals with the smouldering behaviour of wood dust deposits initiated by hot bodies. Effects of embedded depth and airflow condition are investigated. Two sizes of wood dust are selected as test samples, namely wood powder and wood chip. The results indicate that under the same hot bodies embedded depth, wood chip combustion propagates faster than wood powder in general due to its unique flocculent structure. Due to the increased insulation effect of the wood dust layer, the temperature at the same measuring point is higher than that of the wood chip layer. In addition, under airflow conditions, the smouldering propagation of wood deposits is significantly higher than that without airflow (2.42 and 4.34 m/s) for both wood powder and wood chip samples. However, the deposited wood powder has a lower minimum ignition temperature than wood chip. Accumulated wood dust in considered to have a greater fire risk in powder form.

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 score0.007
Threshold uncertainty score0.228

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 head0.007
GPT teacher head0.224
Teacher spread0.217 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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