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Record W4410632679 · doi:10.22215/etd/2024-16434

Structural Assessment of Glued-Laminated Timber Columns Subjected to Real Fires

2024· dissertation· en· W4410632679 on OpenAlexaboutno aff
Saba Seyedrazavi

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsStructural engineeringForensic engineeringEngineeringColumn (typography)

Abstract

fetched live from OpenAlex

This thesis investigates the performance and post-fire structural integrity of glued-laminated (glulam) columns when exposed to real fires. The primary objective of the Mass Timber Demonstration Fire Test Program (MTDFTP) in Ottawa was to conduct large-scale fire tests to explore construction fire safety, fire behavior in open office spaces and residential areas, and the impact of exposed mass timber elements on fire intensity and duration. Detailed visual inspections and axial compression testing of the MTDFTP columns indicated differences between actual charring rates and rates predicted by CSA O86 (2019), and Eurocode 5 (2004). Uneven charring and adhesive degradation were significant factors affecting post-fire performance. Despite extensive charring, the columns retained much of their structural integrity, supporting potential repairs over replacement. This research gives an insight into the charring behaviour of glulam columns and recommends updates to fire safety standards, enhancing fire resistance and safety of timber structures.

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)0.000
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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.008
GPT teacher head0.265
Teacher spread0.257 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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Same topicWood Treatment and PropertiesFrench-language works237,207