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Record W4231746757 · doi:10.11159/icsect20.166

Mineral Slag used as an Alternative of Cement in Concrete

2020· article· en· W4231746757 on OpenAlexvenueno aff
Eskinder Desta Shumuye, Jun Zhao, Zike Wang

Bibliographic record

VenueProceedings of the World Congress on Civil, Structural, and Environmental Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsnot available
FundersRecruitment Program of Global ExpertsNational Natural Science Foundation of China
KeywordsCementSlag (welding)MineralMaterials scienceMetallurgyEnvironmental science

Abstract

fetched live from OpenAlex

This paper summarizes the results of experimental studies carried out at Zhengzhou University, school of Mechanics and Engineering Science, research laboratory, on the performance of concrete produced by combining ordinary Portland cement (OPC) with ground-granulated blast furnace slag (GGBS).Concrete specimens cast with OPC and various percentage of GGBS (0%, 30%, 50%, and 70%) were subjected to high temperature exposure and extensive experimental test reproducing basic freeze-thaw cycle and a chloride-ion attack to determine their combined effects within the concrete samples.From the experimental studies comparisons were made on the physical, mechanical, and microstructural properties in compassion with ordinary Portland cement concrete (OPC).Further, durability of GGBS cement concrete such as exposure to chloride ion attack and freeze-thaw action in compassion with various percentage of GGBS and ordinary Portland cement concrete of similar mixture composition were analyzed.The microstructure, mineralogical composition, and pore size distribution of concrete specimens were determined via Scanning electron microscopy analysis (SEM), and X-ray diffraction (XRD).The result demonstrated that when the exposure temperature increases from 200 ºC to 400 ºC, the residual compressive strength was fluctuating for all concrete group; and compressive strength and chloride ion exposure of the concrete decreased with the increasing of slag content.The SEM and EDS results showed an increase in carbonation rate with increasing of slag content.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.011
GPT teacher head0.212
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 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

Citations2
Published2020
Admission routes1
Has abstractyes

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Same venueProceedings of the World Congress on Civil, Structural, and Environmental EngineeringSame topicConcrete and Cement Materials ResearchFrench-language works237,207