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Record W4408505827 · doi:10.1080/19648189.2025.2477073

Durability assessment of masonry specimens built with waste fibre added cementitious composite in acidic environment

2025· article· en· W4408505827 on OpenAlexaff
Nikhil Ranjan, Sanket Nayak, Sreekanta Das

Bibliographic record

VenueEuropean Journal of Environmental and Civil engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsDurabilityMasonryCementitiousComposite numberCementComposite materialMaterials scienceGeotechnical engineeringWaste managementStructural engineeringEngineering

Abstract

fetched live from OpenAlex

The mortar strengthening method to augment the seismic performance of masonry buildings has become popular due to its easy application and significant improvement. However, the durability aspect of such fibre-reinforced structures is rare in the literature. Hence, the current research focuses on studying the durability of mortar/masonry specimens built with fibre-reinforced mortar against acidic environments. Three waste fibres, i.e., polyethylene terephthalate (PET), coconut, and nylon, with proportions (by weight) of 0.75%, 0.30%, and 0.20%, respectively, were used to reinforce the mortar. The specimens were exposed to 3% H2SO4 (sulphuric acid) solution for 180 and 360 days. Compression tests on mortar cubes and diagonal shear and flexural tests were carried out on masonry wallettes. It was noticed that the acidic solution had the most severe effect on unreinforced specimens compared to fibre-reinforced specimens. The reduction in change in weight (%), compressive strength (%), shear strength (%), and flexural strength (%) in the case of fibre-reinforced specimens was up to 45.1%, 27.4%, 46.5%, and 38.2%, respectively, compared to their corresponding unreinforced specimens. Furthermore, PET and nylon fibre-reinforced specimens outperformed coconut fibre-reinforced specimens. Hence, it was concluded that synthetic fibre-reinforced mortar is the better option for masonry structures for an acidic environment.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.666
Threshold uncertainty score0.794

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 head0.176
Teacher spread0.172 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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