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Record W2980407137 · doi:10.1177/1056789519881484

Post-fire damage assessment and capacity based modeling of concrete exposed to elevated temperature

2019· article· en· W2980407137 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

VenueInternational Journal of Damage Mechanics · 2019
Typearticle
Languageen
FieldEngineering
TopicFire effects on concrete materials
Canadian institutionsCarleton University
FundersScience and Engineering Research Board
KeywordsSpallResidual strengthMaterials scienceFlexural strengthStructural engineeringUltimate tensile strengthCompressive strengthComposite materialGeotechnical engineeringEngineering

Abstract

fetched live from OpenAlex

Fire represents one of the significant hazards encountered by civil infrastructures, and thus providing appropriate fire safety measures is a major requirement in a building design for ensuring the safety of the occupants. Minimizing fire-induced damage and collapse of structural systems are the primary objectives in the design of concrete structures. An experimental investigation has been carried out to examine the mechanical properties such as compressive, tensile and flexural strengths of concrete exposed to elevated temperature following standard fire curve as per ISO 834. Capacity-based standards have been formulated to predict the residual strength of various grades of concrete exposed to various duration of heating. Stress strain behaviour, elastic modulus, weight loss, spalling and thermal crack pattern of specimens were also investigated. Water–cement ratio and porosity of concrete were found to be the critical factors for strength loss of concrete. A relationship is established between weight loss and strength loss of concrete. Higher grades of concrete were found to have more weight and strength loss than those of lower grades.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.664
Threshold uncertainty score0.740

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.010
GPT teacher head0.238
Teacher spread0.228 · 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