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Record W4395106226 · doi:10.9798/kosham.2024.24.2.77

Selection of Optimum Ternary Binder Systems that Enhance the Workability and Durability of Concrete used in Marine Railways

2024· article· en· W4395106226 on OpenAlexaff
TaeYoon Byun, K. H. Cho

Bibliographic record

VenueKorean Society of Hazard Mitigation · 2024
Typearticle
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsOptech (Canada)
Fundersnot available
KeywordsDurabilityCompressive strengthPortland cementMaterials scienceTernary operationComposite materialCuring (chemistry)Cement

Abstract

fetched live from OpenAlex

In this study, the improvement of the compressive strength and duradbility of concrete used in marine railways by adding binding agents was investigated. The test speciments used in the study comprised developed product A (DP_A), developed product B (DP_B), Ordinary Portland Cement (OPC), admixture A, and admixture B, in the study, the optimum ternary binder systems of the test specimens were identified. An optimum ternary binder system would facilitate the simultaneous enhancement of the durability and workability of concrete used on undersea tunnel linings and bridge structures. The compressive strength of each specimen tested after 16h could easily meet the specified standard target strength (> 3.0_MPa). Moreover, the 7d long term strength of each test specimen exceeded 3.0 MPa. When binders were used, the chloride penetration resistance (DP_A was exceptional)_2.741C (normal) and, 1.490C (low) following-28 and 91days. The surface diffustion coefficient of (DP_B) at 91days 9.12 (× 10-12, m<sup>2</sup>/sec) was higher than that of OPC 9.55 (× 10-12, m<sup>2</sup>/sec). However, the surface diffusion coefficient of (DP_A) was 4.15 (× 10-12, m<sup>2</sup>/sec) which was lower than OPC by approximately 57%, indicating the outstanding durability of DP_A.

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)0.001
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 score0.339
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.012
GPT teacher head0.228
Teacher spread0.216 · 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.

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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueKorean Society of Hazard MitigationSame topicConcrete Corrosion and DurabilityFrench-language works237,207