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Improving methods of strength design of normal sections of flexural concrete members reinforced with fiber-reinforced polymer bars

2020· article· en· W3049705928 on OpenAlexaboutno aff
Ilshat Mirsayapov, Igor A. Antakov, А Б Антаков

Bibliographic record

VenueIOP Conference Series Materials Science and Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsnot available
Fundersnot available
KeywordsFibre-reinforced plasticFlexural strengthUltimate tensile strengthReinforcementStructural engineeringBasalt fiberMaterials scienceSafety factorComposite materialGlass fiberFailure mode and effects analysisFiberEngineering

Abstract

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Abstract Theoretical and experimental studies of the strength of normal sections of flexural concrete members reinforced with FRP bars have been conducted. The test specimens were concrete beams 1810 mm long, with a rectangular section of 120×220 mm, reinforced with two bars in the tensile area. The beams were reinforced longitudinally with steel, glass fiber-reinforced polymer (GFRP) and basalt fiber-reinforced polymer (BFRP) bars. The design methods of guidelines of Russia, the USA, Canada and the European Union have been considered. There are two approaches to the strength design of normal sections – the European and the North American. The approach used in the design method of the Russian guideline SP 295.1325800.2017, when all partial safety factors are used in calculating the design characteristics of materials, causes an overestimation of the boundary values of relative depth of the compressed region ξ R . It leads to an inaccurate determination of the failure mode and possible over-reinforcement of the construction. Some corrections have been brought about to the design methods of the Russian guideline SP 295.1325800.2017. Factor β has been introduced, which takes into account prestressing of the reinforcement. As a result, the deviation of the theoretical evidence from the experimental values of failure moments decreased from 30.44 % to 13.2 %. Changes have been made to the approach for the application of safety factors, which allowed increasing the accuracy of determining the failure mode and bring the safety factor for members C to the value of 1.6 adopted by the authors.

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 categoriesMeta-epidemiology (narrow)
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 score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.018
GPT teacher head0.233
Teacher spread0.215 · 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 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

Citations3
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueIOP Conference Series Materials Science and EngineeringSame topicStructural Behavior of Reinforced ConcreteFrench-language works237,207