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Record W4386755043 · doi:10.18280/rcma.330402

Enhancing the Performance and Durability of Eco-Friendly Mortar with Diss Fibers (Ampelodesmos mauritanicus)

2023· article· fr· W4386755043 on OpenAlexvenueno aff
Assia Abdelouahed, Kechkar Chiraz, Houria Hebhoub, Mouloud Merzoud, Ghania Boukhatem

Bibliographic record

VenueRevue des composites et des matériaux avancés · 2023
Typearticle
Languagefr
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsnot available
Fundersnot available
KeywordsDurabilityMortarEnvironmentally friendlyComposite materialMaterials scienceEcologyBiology

Abstract

fetched live from OpenAlex

This study investigates the potential use of Diss fibers as a sustainable alternative in ecoconstruction and civil engineering.The research introduced Diss fibers as aggregates, partially replacing conventional sand in mortar by volume with proportions of 1/3 and 2/3, aiming to create an eco-friendly and lighter mortar.In this context, various properties of the fresh mortars, such as density, workability, and occluded air content, were examined.Additionally, the mechanical performance in the hardened state, including compressive and flexural strengths, was evaluated.Durability parameters such as water absorption, capillary absorption, and resistance to aggressive media were also assessed.The results demonstrated that mortars incorporating Diss fibers were lighter and more workable.The inclusion of these fibers enhanced the flexural strength and chemical resistance, as evidenced by the low percentages of mass loss in aggressive solutions such as HCl and CH3COOH.However, the introduction of the fibers negatively influenced the mechanical resistance and water absorption-both by immersion and capillaritydue to the porosity introduced into the composites.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.198
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.018
GPT teacher head0.231
Teacher spread0.213 · 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 designSimulation or modeling
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

Citations7
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueRevue des composites et des matériaux avancésSame topicBIM and Construction IntegrationFrench-language works237,207