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Record W3137018738 · doi:10.18280/rcma.310101

Experimental Investigation of Rubberized Functionally Graded Concrete

2021· article· en· W3137018738 on OpenAlexvenueno aff
Sumit Choudhary, Rajesh Gupta, Abhishek Jain, Sandeep Chaudhary

Bibliographic record

VenueRevue des composites et des matériaux avancés · 2021
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsnot available
FundersMalaviya National Institute of Technology, JaipurDivision of Materials ResearchDepartment of Science and Technology, Ministry of Science and Technology, India
KeywordsMaterials scienceFlexural strengthCompressive strengthPrecast concreteShrinkageComposite materialAggregate (composite)MicrostructureScanning electron microscopeStructural engineeringEngineering

Abstract

fetched live from OpenAlex

Concrete is a basic engineering material used for developing modern structures. The engineering properties of structures can be enhanced by using different concrete grades in the same structural element based on its specific requirement in functionally graded concrete (FGC). For meticulous critical inspection, an experimental investigation was prosecuted on three different types of concrete (conventional concrete (CC), rubber fiber concrete (RFC) and rubberized functionally graded concrete (RFGC)), and their properties were compared. The fine aggregate was substituted (by volume) with waste rubber fiber by 5, 10, 15, 20 and 30% to prepare RFC and RFGC. Tests were performed on concrete samples to analyze compressive strength, flexural strength, water permeability, and drying shrinkage. Moreover, scanning electron microscopy (SEM) was utilized to observe the microstructures. Results indicated that RFGC performed better than CC and RFC and can be used to prepare precast structures and for the applications where high flexural load acts.

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 score0.021
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)0.0000.000

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 head0.058
GPT teacher head0.260
Teacher spread0.202 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueRevue des composites et des matériaux avancésSame topicInnovative concrete reinforcement materialsFrench-language works237,207