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Record W2908643410 · doi:10.1155/2019/3658125

Mechanical and Durability Characteristics of Latex‐Modified Fiber‐Reinforced Segment Concrete as a Function of Microsilica Content

2019· article· en· W2908643410 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

VenueAdvances in Civil Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsContech (Canada)
FundersNational Research Foundation of KoreaMinistry of EducationNational Research Foundation
KeywordsSilica fumeDurabilityMaterials scienceComposite materialFiberFiber-reinforced concreteReinforced concreteStructural engineeringCompressive strengthEngineering

Abstract

fetched live from OpenAlex

This study evaluated the performance of latex‐modified fiber‐reinforced concrete (RC) segments as a function of the substitution level of microsilica and type of reinforced fiber, to address the problem of corrosion of steel segments and steel‐reinforced fiber segments, which are commonly used to shield tunnel‐boring machine (TBM) tunnels in urban spaces. Our study compared macro synthetic, steel, and hybrid (macro synthetic fiber + polypropylene fiber) reinforcing fibers. The substitution levels of microsilica used were 0, 2, 4, and 6%. The target strengths were set at 40 and 60 MPa to test compressive strength, flexural strength, chloride ion penetration resistance, and impact resistance. Testing of latex‐modified and fiber‐reinforced segment concrete showed that the compressive strength, flexural strength, and chloride ion penetration resistance increased with an increasing substitution level of microsilica. These improvements were attributed to the densification of the concrete due to filling micropores with microsilica. Micro synthetic fiber was more effective in terms of improved compressive strength, flexural strength, and chloride ion penetration resistance than steel fiber. These results were due to the higher number of micro synthetic fibers per unit volume compared with steel fiber, which reduced the void volume and suppressed the development of internal cracks. The optimal microsilica content and fiber volume fraction of micro synthetic fiber were 6% and 1%, respectively. To evaluate the effects of the selected mixtures and hybrid fibers simultaneously, other mixing variables were fixed and a hybrid fiber mixture (combination of macro synthetic fibers and polypropylene fibers) was used. The hybrid fiber mixture produced better compressive strength, flexural strength, chloride ion penetration resistance, and impact resistance than the micro synthetic fibers.

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 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 score0.081
Threshold uncertainty score0.884

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 head0.009
GPT teacher head0.209
Teacher spread0.201 · 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