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Record W2804387026 · doi:10.22215/etd/2015-10728

Fire Resistance of Partially Protected Cross-Laminated Timber Rooms

2015· dissertation· en· W2804387026 on OpenAlexafffund
Alejandro Medina Hevia

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicFire dynamics and safety research
Canadian institutionsCarleton University
FundersFPInnovations
KeywordsCharringCeiling (cloud)Cross laminated timberGypsumFire testGlazingFire resistanceStructural engineeringParametric statisticsHeat transferOriented strand boardEnvironmental scienceEngineeringMaterials scienceComposite materialMathematics

Abstract

fetched live from OpenAlex

This thesis studies the fire behaviour of Cross Laminated Timber (CLT) panels in partially protected rooms.A one-dimensional heat transfer model was developed to determine the fire resistance of CLT floor and wall panels.During this study, three room fire tests were conducted at Carleton University Fire Research Laboratory to determine the maximum percentage of unprotected CLT surface area that will yield similar results to that of a fully protected room.The rooms had a single opening and were constructed entirely using 3-ply, 105 mm thick CLT panels.A non-standard, parametric fire using furniture and clothing as fuel was used and 2 layers of gypsum board were used to cover the ceiling and the protected walls.The Heat Release Rate, temperature, charring rate and gypsum falloff time of each test was collected.The results obtained from the room test were then compared to the numerical heat transfer model to evaluate its accuracy.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.011
GPT teacher head0.284
Teacher spread0.273 · 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 source (direct Gemma or distilled Codex), 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

Citations23
Published2015
Admission routes2
Has abstractyes

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