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Record W2930802150 · doi:10.11159/icgre19.139

Strength Characteristics of Clay Stabilized with Fly-ash Based Geopolymer Incorporating Granulated Slag

2019· article· en· W2930802150 on OpenAlexvenueno aff
Hayder H. Abdullah, Mohamed A. Shahin

Bibliographic record

VenueProceedings of the World Congress on Civil, Structural, and Environmental Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsnot available
FundersHigher Committee for Education Development in Iraq
KeywordsFly ashGeopolymerSlag (welding)Materials scienceGeopolymer cementGround granulated blast-furnace slagWaste managementMetallurgyComposite materialEngineering

Abstract

fetched live from OpenAlex

The use of traditional binders (e.g., lime or cement) in soil stabilization faces many obstacles of environmental nature, and geopolymers have been recently become an attractive alternative binder that may overpasses such obstacles. However, the literature lacks detailed information in relation to the geo-mechanical characteristics of geopolymer-stabilized soils and this paper fills in part of this gap. The paper presents an evaluation of the stress-strain behavior of two natural clays of different mineralogy treated with fly-ash based geopolymer. Laboratory experiments were performed including the Unconfined Compressive Strength (UCS) tests and Consolidated Undrained (CU) triaxial tests under different confining pressures. The results indicate that the addition of geopolymer increases the strength and stiffness of clay, which contributes to higher uniaxial and triaxial peak stresses. The confining pressure was found to have a considerable influence on the stress-strain behavior and excess pore-water pressure obtained from the CU tests. The results also demonstrate that clay mineralogy is an important factor that affects the stress-strain performance of geopolymer-treated clay.

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 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 score0.119
Threshold uncertainty score0.821

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 head0.004
GPT teacher head0.174
Teacher spread0.170 · 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

Citations17
Published2019
Admission routes1
Has abstractyes

Explore more

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