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Record W4416120232 · doi:10.4236/gm.2025.153005

Swelling Soil Settlement Prevention by Stabilization with Quicklime Column in Diamniadio (Senegal)

2025· article· W4416120232 on OpenAlexaboutno aff
Hamed Fall, Déthiè Sarr, M. G. Sarr, Seynabou Ndiaye

Bibliographic record

VenueGeomaterials · 2025
Typearticle
Language
FieldEngineering
TopicGeotechnical and construction materials studies
Canadian institutionsnot available
Fundersnot available
KeywordsSettlement (finance)ShrinkageContext (archaeology)AridSoil waterHuman settlementPore water pressure

Abstract

fetched live from OpenAlex

The risk of geotechnical drought, otherwise known as the risk of clay shrinkage and swelling, has long been identified by geotechnical engineers, and can be seen in many countries (USA, France, Canada, Ethiopia, etc.). In fact, clay soils show variations in volume when their water content varies. These variations affect the functioning of foundations and buildings in contact with the soil. This shrink-swell phenomenon is the cause of frequent disorders, which can range from a simple crack to considerable damage. The consequences are more spectacular in arid and semi-arid regions. In Senegal, this problem is of particular concern, especially in the context of the Diamniadio urban development project, which is based on geological formations prone to this phenomenon. However, it should be noted that the consequences of geotechnical drought on structures are conditioned by a range of factors of different kinds, which can be acted upon to prevent damage. One of these factors is the nature of the soil. Techniques for stabilizing soils by adding quicklime have been developed to deal with this risk. This article presents the reduction of settlements through the use of quicklime columns (from 1.85 mm to 1.054 mm). An analysis of the effect of column diameter and spacing on settlement is presented. The results show that settlement decreases as the columns are spaced closer together, giving a smaller settlement for a column spacing of 1 m.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.070
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.208
Teacher spread0.204 · 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 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
Published2025
Admission routes1
Has abstractyes

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