MétaCan
Menu
Back to cohort
Record W4406874269 · doi:10.1016/j.firesaf.2025.104346

Large-scale compartment fires to develop a self-extinction design framework for mass timber-Part 2: Results, analysis and design implications

2025· article· en· W4406874269 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.

Bibliographic record

VenueFire Safety Journal · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsUniversity of WaterlooUniversity of British Columbia
FundersAustralian Research Council
KeywordsScale (ratio)Compartment (ship)Poison controlEngineeringEnvironmental scienceForensic engineeringArchitectural engineeringComputer scienceGeologyMedical emergencyGeographyMedicine

Abstract

fetched live from OpenAlex

A bstract This paper seeks to provide key fundamental knowledge underpinning the use of self-extinction principles as part of a design framework for buildings with engineered mass timber structures. The results from six compartment fire experiments in a cross-laminated timber (CLT) enclosure with different ratios of exposed timber are presented and analyzed to establish the effects of timber exposure on the dynamics of a fire and on the potential of the fire to self-extinguish. The results show the relevance of four key parameters that need to be considered concurrently when assessing self-extinction in mass timber compartments: (a) the characteristic time for burnout of the movable fuel load, (b) the characteristic time for the occurrence of char fall-off, (c) the characteristic time for the occurrence of encapsulation failure, and (d) the heat exchange within the compartment after consumption of the moveable fuel. Self-extinction was attained only when the characteristic time for the occurrence of char fall-off was longer than the characteristic time for burn-out and the heat exchange after burn-out resulted in a heat flux below a well-defined threshold. The position of the exposed timber surfaces affected the magnitude of the threshold heat flux. If the characteristic time for burn-out was greater than the characteristic time for encapsulation failure, self-extinction was not observed to occur. • Six large-scale CLT compartment fires to establish self-extinction conditions. • Fuel burnout before encapsulation failure or char fall-off was paramount. • Oxidation of charring fuel created thermal feedback loop, hindering self-extinction. • Self-extinction threshold heat flux for timber surfaces dependent on orientation. • Char fall-off occurred in slim range unsuitable for unitary surrogate temperature.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.378
Threshold uncertainty score0.842

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
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 head0.014
GPT teacher head0.264
Teacher spread0.249 · 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