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Impact Assessment of Pozzolanic Material Coupled with River Bed Aggregate on Expansive Behavior of High Strength Concrete

2022· article· en· W4400612321 on OpenAlexaff
Muhammad Imran, Muhammad Sanaullah, Muhammad Qasim Mahmood, Syed Muhammad Hassan, Muzzamil Hussain, Shahid Ali

Bibliographic record

VenueInternational Journal of Economic and Environmental Geology · 2022
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsPozzolanExpansiveAggregate (composite)Geotechnical engineeringPozzolanic activityMaterials scienceCompressive strengthComposite materialCementGeologyPortland cement

Abstract

fetched live from OpenAlex

High strength concrete is widely used in engineering structures. Present work is an effort for suitability assessment of river bed aggregates in high strength concrete to be used at structural units of Dam (Spillway & Powerhouse) and the vulnerability of placed concrete expansion. Multiple sizes of coarse aggregate (5-20mm, 20-40mm, and 40-80mm) from Beor river bed material have been tested for physical (water absorption, crushing index, soundness, shape, and bulk density), and mineralogical characterization. Concrete Mix Design (CMD) for Spillway has been optimized using Fly ash and river aggregate that achieved the Unconfined Compressional Strength (UCS) up to 32.5 MPa. The accelerated mortar bar test (AMBT) has been introduced to gauge the reactive aggregates used in CMD.. Expansive properties of concrete were observed at the age of 7 days and 28 days that demonstrate more expansion of the specimen with slag rather than the Fly ash. Results of AMBT suggest that a minimum proportion of GGBS (40%) is needed to limit the AMBT expansion to less than 0.1% for crushed river bed aggregate and sand from the Beor source. The petrographical characterization of coarse aggregate shows the presence of deformed quartz in the coarse aggregate, which directly relates to water absorption (Wa), suggesting its suceseptility to Alkali-Silica Reaction (ASR). Modifications in Pozzolanic additives in CMD indicates that 30% mixing of Fly ash can reduce the expansion rate of concrete up to 96.15%.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.622
Threshold uncertainty score0.997

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)0.0040.000

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 head0.007
GPT teacher head0.243
Teacher spread0.236 · 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 designObservational
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
Published2022
Admission routes1
Has abstractyes

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Same venueInternational Journal of Economic and Environmental GeologySame topicConcrete and Cement Materials ResearchFrench-language works237,207