MétaCan
Menu
Back to cohort
Record W2975558140 · doi:10.18280/acsm.430308

Empirical Relationships on Mechanical Properties of Class-F Fly Ash and GGBS Based Geopolymer Concrete

2019· article· en· W2975558140 on OpenAlexvenueno aff
Ramamohana Reddy Bellum, Karthikeyan Muniraj, Sri Rama Chand Madduru

Bibliographic record

VenueAnnales de Chimie Science des Matériaux · 2019
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsnot available
FundersVignan's Foundation for Science, Technology and Research
KeywordsFly ashGround granulated blast-furnace slagGeopolymer cementClass (philosophy)GeopolymerMaterials scienceComposite materialComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Ordinary Portland Cement (OPC) is one of the important materials used in the development of the construction industry. Production of OPC consumes lot of raw materials, emits extreme quantity of carbon dioxide (CO2) into atmosphere and highly energy-intensive. Thus, to reduce the production of cement so many attempts are done and an alternative binder was found. The alternative to cement concrete is geopolymer concrete (GC) and it is produced by mixing industrial by-products (rich in aluminosilicate) with an alkaline solution. This paper explores the mechanical properties and a representative non-linear equation was proposed for the relationship between splitting tensile Vs compressive strengths and flexural Vs compressive strengths of fly ash-GGBS synthesized GC cured at ambient temperature for 28 days. This work also presents empirical formulae for predicting elastic modulus of fly ash-GGBS synthesized GC. Equations were proposed to determine the splitting tensile strength, flexural strength and elastic modulus based on the compressive strength of GC. The obtained results are clearly indicating that the predicted (from proposed equations) splitting tensile and flexural strength values are very close to the experimental values. It is established that the formulae found in various codes and literature generally predict the higher values of the elastic modulus than those obtained using the proposed equation.

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 score0.116
Threshold uncertainty score0.428

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 head0.083
GPT teacher head0.285
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 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

Citations33
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueAnnales de Chimie Science des MatériauxSame topicConcrete and Cement Materials ResearchFrench-language works237,207