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Record W4399921517 · doi:10.18280/mmep.110601

Engineering Properties of Gypseous Soils Improved with Natural and Industrial Fibers

2024· article· en· W4399921517 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMathematical Modelling and Engineering Problems · 2024
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsnot available
Fundersnot available
KeywordsNatural (archaeology)Soil waterGeotechnical engineeringGeologyEnvironmental scienceSoil sciencePaleontology

Abstract

fetched live from OpenAlex

The significant challenges facing geotechnical engineers concerning gypseous soils and their behavior under water flow require careful assessment of gypsum soil performance under wet conditions.Improving gypsum soils through the inclusion of enhanced additives is among the most widely employed methods.The major objective of the current study was to investigate the effect of fiber additives on the engineering properties of gypseous soils experimentally.Natural fiber has been mixed into sandy and clay soils in several studies, but gypseous soils have not been investigated.However, the study investigated the properties of gypseous soils with three gypsum content (19%, 36%, 62%) improved by an agricultural waste of sugarcane bagasse (SCF) used as natural fiber and polypropylene (PPF) as an industrial fiber, these materials are economic, renewable and eco-friendly.The effect of fibers on compaction characteristics, specific gravity, and shear strength parameters at both dry and soaked conditions (soaked in water for 1 day) is investigated.Fibers used by percentage (0-0.8%by weight of dried soil).From the result of soil improved by polypropylene fibers (PPF), The significant increase was observed in cohesion under both dry and soaked conditions, surpassing the cohesion increment observed in soil treated with SCF. in dry conditions for soil treated by (PPF) the increment was recorded (20%-126%), and for soil treated by (SCF), the increment was recorded (19%-81%).But the angle of internal friction of the soil improved by SCF in dry and soaked conditions was higher than that soil treated by PPF, in dry condition for soil treated by PPF the increment was recorded (8%-33%) and (21%-54%) for soil treated by SCF.shear strength parameters in the dry condition are more than the increment in soaked condition for treated soil by (PPF and SCF), also from the results can be obtained the optimum fiber content was 0.6%, and 0.4% for SCF and PPF respectively.The max. dry unit weight and specific gravity for three types of soils decreased by increasing fiber content but optimum moisture content increased by increasing fiber content.Lastly can be concluded the PPF gave better results than SCF.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.549
Threshold uncertainty score0.842

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 head0.017
GPT teacher head0.166
Teacher spread0.149 · 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