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Record W4385453003 · doi:10.11159/ijci.2023.004

Bearing Capacity and Strength of Fibre-Reinforced Sand: Experimental and Parametric Study

2023· article· en· W4385453003 on OpenAlexvenueno aff
Ruba Elmootassem, Haitham A. Badrawi, Magdi Elemam, Ashraf Amin

Bibliographic record

VenueInternational Journal of Civil Infrastructure · 2023
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsnot available
Fundersnot available
KeywordsBearing capacityParametric statisticsGeotechnical engineeringStructural engineeringLoad bearingBearing (navigation)GeologyMaterials scienceMathematicsEngineeringComputer scienceStatisticsArtificial intelligence

Abstract

fetched live from OpenAlex

In this paper, Polyolefin fibre which is produced from simple olefin (CnH2n) was mixed with dry sand to investigate the shear strength improvement of the admixture.Specimens with 0.5%, 1%, 1.5% and 2% fibre contents with yarns lengths of 15 mm and 30 mm are prepared in repeatable steps and tested in direct shear tests.Bearing capacity of hypothetical footing resting on ground surface of the tested fibre-reinforcedsand was estimated using Terzaghi's bearing capacity equation.Moreover, a parametric study includes thickness of reinforced layer, depth of foundation, and fibres content percent is conducted.In the parametric study, the continuous footing was analysed using procedures estimating the bearing capacity of layered soils.Results of shear strength tests indicated that, the inclusion of randomly distributed discrete fibres significantly improved the shear strength of sand.The optimum fibre percentage for improving both friction angle was about 1%.Adding fibre more than this ratio resulted in a significant reduction in soil shear strength parameters.The effect of fibre on sand apparent tensile cohesion is more pronounced compared to its effect on the friction angle.The parametric study indicates that having a continuous footing resting on a soil layer reinforced with 30 mm artificial fibres at 0.5% content provides the highest ultimate bearing capacity.Finally, the thickness of the reinforced layer and the depth of the foundation are among the parameters that affect bearing capacity.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score0.344

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 head0.008
GPT teacher head0.231
Teacher spread0.223 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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