MétaCan
Menu
Back to cohort
Record W2985287946 · doi:10.1108/jsfe-10-2019-0034

Experimental determination of the residual compressive strength of concrete columns subjected to different fire durations and load ratios

2020· article· en· W2985287946 on OpenAlexaff
Anjaly Nair, Osama Salem

Bibliographic record

VenueJournal of Structural Fire Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicFire effects on concrete materials
Canadian institutionsLakehead University
Fundersnot available
KeywordsRetrofittingCompressive strengthResidual strengthResidualStructural engineeringMaterials scienceColumn (typography)Bearing capacityFire testFire protectionComposite materialEngineeringMathematicsCivil engineering

Abstract

fetched live from OpenAlex

Purpose At elevated temperatures, concrete undergoes changes in its mechanical and thermal properties, which mainly cause degradation of strength and eventually may lead to the failure of the structure. Retrofitting is a desirable option to rehabilitate fire damaged concrete structures. However, to ensure safe reuse of fire-exposed buildings and to adopt proper retrofitting methods, it is essential to evaluate the residual load-bearing capacity of such fire-damaged reinforced concrete structures. The focus of the experimental study presented in this paper aims to investigate the fire performance of concrete columns exposed to a standard fire, and then evaluate its residual compressive strengths after fire exposure of different durations. Design/methodology/approach To effectively study the fire performance of such columns, eight identical 200 × 200 × 1,500-mm high reinforced concrete columns test specimens were subjected to two different fire exposure (1- and 2-h) while being loaded with two different load ratios (20% and 40% of the column ultimate design axial compressive load). In a subsequent stage and after complete cooling down, residual compressive strength capacity tests were performed on each fire exposed column. Findings Experimental results revealed that the columns never regain its original capacity after being subjected to a standard fire and that the residual compressive strength capacity dropped to almost 50% and 30% of its ambient temperature capacity for the columns exposed to 1- and 2-h fire durations, respectively. It was also noticed that, for the tested columns, the applied load ratio has much less effect on the column’s residual compressive strength compared to that of the fire duration. Originality/value According to the unique outcomes of this experimental study and, as the fire-damaged concrete columns possessed considerable residual compressive strength, in particular those exposed to shorter fire duration, it is anticipated that with proper retrofitting techniques such as fiber-reinforced polymers (FRP) wrapping, the fire-damaged columns can be rehabilitated to regain at least portion of its lost load-bearing capacities. Accordingly, the residual compressive resistance data obtained from this study can be effectively used but not directly to adopt optimal retrofitting strategies for such fire-damaged concrete columns, as well as to be used in validating numerical models that can be usefully used to account for the thermally-induced degradation of the mechanical properties of concrete material and ultimately predict the residual compressive strengths and deformations of concrete columns subjected to different load intensity ratios for various fire durations.

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 score0.002
Threshold uncertainty score0.006

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)0.0020.000

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 head0.007
GPT teacher head0.207
Teacher spread0.200 · 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

Citations13
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Structural Fire EngineeringSame topicFire effects on concrete materialsFrench-language works237,207