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Record W4402850497 · doi:10.7250/bjrbe.2024-19.645

Influence of Ceramic Waste and Cement on the Mechanical and Hydraulic Properties, and Microstructure of the Road Sub-Base Layer

2024· article· en· W4402850497 on OpenAlexaboutno aff
Sadek Deboucha, Hocine Ziani, Abderrachid Amriou, Walid Maherzi, Walid Deboucha

Bibliographic record

VenueThe Baltic Journal of Road and Bridge Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsnot available
Fundersnot available
KeywordsMicrostructureCementMaterials scienceCompressive strengthGeotechnical engineeringPermeameterPortland cementConsolidation (business)Composite materialPermeability (electromagnetism)CeramicEnvironmental scienceHydraulic conductivitySoil waterGeologySoil science

Abstract

fetched live from OpenAlex

This study examines cement and ceramic waste (CW) for the sub-base layer of roads. This innovative method can do away with the risks associated with improper disposal of industrial waste. To achieve this objective, several proportions of cement and CW were used, ranging from 1.5 to 2% and 5% to 15%, respectively. The aim of the work was to examine the influences of CW and ordinary Portland cement (OPC) on the unconfined compressive strength (UCS), permeability, consolidation, and microstructures of untreated and treated soil of road sub-base layer. The Guelph permeameter, UCS, permeability, and one- dimensional consolidation were among the laboratory and in-situ tests that were examined; the microstructures were characterised using SEM, infrared (IR), and mercury intrusion porosimetry (MIP). The findings indicated that the high permeability of the natural soil caused harm to our road soon after construction. Applying 5 to 15% CW reduced permeability by approximately 100% and settlement by around 43%. Furthermore, under wet and immersed conditions, mixing CW and OPC with soil raised UCS by approximately 182% and 20 times, respectively. This study demonstrated that by enhancing the geotechnical properties of soil, CW and OPC combined with it could be used as a road sub-base layer material.

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 score0.222
Threshold uncertainty score0.216

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 head0.015
GPT teacher head0.207
Teacher spread0.192 · 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 venueThe Baltic Journal of Road and Bridge EngineeringSame topicConcrete and Cement Materials ResearchFrench-language works237,207