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Strengthening Square and Circular Low-Strength Concrete Columns with Fiber-Reinforced Cementitious Matrix: Experimental Investigation

2022· article· en· W4210660160 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

VenuePractice Periodical on Structural Design and Construction · 2022
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsDuctility (Earth science)Materials scienceSquare (algebra)Structural engineeringComposite materialColumn (typography)CementitiousCross section (physics)Compressive strengthReinforcementCementGeometryMathematicsCreepEngineering

Abstract

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This study investigated the efficiency of strengthening low-strength RC short columns with fiber-reinforced cementitious matrix (FRCM). Twelve columns were cast with concrete with a compressive strength of 18 MPa. All columns had a reinforcement ratio of 1.5%. The investigated parameters were the column cross section (square or circular), the spacing between the ties (90 and 180 mm) selected based on the columns’ dimensions, and the number of FRCM layers used in wrapping the columns [zero, two, and four layers of paraphenylene-ben-zobisoxazole (PBO) FRCM]. All columns had a clear height of 800 mm and were tested monotonically until failure. Results showed that for columns wrapped with two PBO-FRCM layers, using a tie spacing of 90 mm eliminated the effect of varying the cross section. However, circular columns showed a higher increase in capacity than square columns for a tie spacing of 180 mm, where the increase was 40%. For all columns wrapped with four PBO-FRCM layers, the cross-section shape was the sole influence on ultimate capacity, where circular columns noticeably showed a more improved capacity. Also, column load–strain relationships were only influenced by the tie spacing. All strengthened columns showed improved ductility with the increase in PBO-FRCM layers. Using existing design provisions, the theoretical capacity of the columns was calculated, and results showed that the code underestimates ultimate capacity, where the theoretical capacities were lower than the experimental ones by 5%–20%.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.459
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 studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.231
Teacher spread0.221 · 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