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Record W3008947596 · doi:10.1016/j.jobe.2020.101291

Structural performance of fiber reinforced lightweight self-compacting concrete beams subjected to accelerated corrosion

2020· article· en· W3008947596 on OpenAlexafffund
Khandaker M. Anwar Hossain, Ismail Hossain, Tanvir Manzur

Bibliographic record

VenueJournal of Building Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDurabilityMaterials scienceCorrosionHigh-density polyethyleneComposite materialSpallCrackingBeam (structure)ToughnessDuctility (Earth science)Flexural strengthStructural engineeringPolyethyleneCreep

Abstract

fetched live from OpenAlex

Lightweight self-compacting concrete (LWSCC) is gaining popularity since it inherits the best properties of both the lightweight concrete (LWC) and SCC. Addition of fibers to LWSCC can further enhance its performance by improving ductility, crack bridging and energy absorption capacity. However, fiber reinforced LWSCC (FRLWSCC) could have durability issues due to its relative high permeability resulting from porous lightweight aggregates (LWA). Hence, proper investigation on durability performance of FRLWSCC is essential for its long term sustainable application. Despite such importance, no significant research findings are available in literature on durability of FRLWSCC. In this study, the durability of FRLWSCC beams were investigated through accelerated corrosion testing. Both corrosion resistance and structural performance of FRLWSCC beams were evaluated. The structural response of un-corroded beams was also assessed and compared with their corroded counterparts. The FRLWSCC was prepared using three types of fibers; i.e., Polyvinyl Alcohol (PVA), Crumb Rubber (CR) and High Density Poly Ethylene (HDPE) fibers. The LWSCC-HDPE beam exhibited superior corrosion resistance as compared to LWSCC-PVA and LWSCC-CR beams. The LWSCC-HDPE beam experienced a lesser amount of mass loss of reinforcement, fewer cracks and less spalling. Moreover, it sustained the maximum residual peak load and showed higher post-cracking shear resistance.

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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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)0.0010.000

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 head0.015
GPT teacher head0.222
Teacher spread0.207 · 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

Citations41
Published2020
Admission routes2
Has abstractyes

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Same venueJournal of Building EngineeringSame topicInnovative concrete reinforcement materialsFrench-language works237,207