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Record W7021137731

Numerical modelling of steel members subjected to severe thermal loads

2001· article· en· W7021137731 on OpenAlexaffvenue

Bibliographic record

VenueNPARC · 2001
Typearticle
Languageen
FieldEngineering
TopicFire effects on concrete materials
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsDeflection (physics)Numerical modelsThermalBoundary value problemComputer simulationCompression (physics)Fire resistanceStructural failureStructural system
DOInot available

Abstract

fetched live from OpenAlex

This paper addresses the structural behaviour of cold-formed steel members subjected to axial compression and severe heating. Analytical approaches used in retrospective numerical simulations of fire resistance tests are discussed. The developed model reflects the structural failure modes observed in the experiments and gives appropriate consideration to thermally-induced stresses and deformations. The behaviour of loaded steel studs is shown to be sensitive to structural boundary conditions and non-uniform heating. The numerical techniques are described in detail and demonstrated in lateral deflection simulations. The model produces structural failure time (fire resistance) predictions that are consistent with experimental data.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
Threshold uncertainty score1.000

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)0.0010.000

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 head0.014
GPT teacher head0.207
Teacher spread0.193 · 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.

Study designSimulation or modeling
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

Citations2
Published2001
Admission routes2
Has abstractyes

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