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Record W4416948001 · doi:10.1680/jgere.24.00054

Effect of voids on soil-nailed wall performance; a numerical study

2025· article· en· W4416948001 on OpenAlexaff
Ali M. Rajabi, Keivan Rasooly, S. M. S. Ghorashi

Bibliographic record

VenueGeotechnical Research · 2025
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsVoid (composites)Deformation (meteorology)Horizontal and verticalSurface (topology)Computer simulation

Abstract

fetched live from OpenAlex

Studying the interaction between voids and retaining structures is vitally important, since the performance of such structures may negatively affected by nearby voids such as aqueducts, metro tunnels, and water collection tunnels in heavily urbanised areas. In this study, the impact of horizontal voids on a soil-nailed wall performance has been investigated. Horizontal deformations and ground surface settlements of a soil-nailed wall, which is close to a void, are analysed by simulation in ABAQUS. The results show that increasing the diameter of the voids leads to the exacerbation of horizontal deformation and vertical ground settlement. At a constant distance from the soil-nailed wall, the void closer to the surface of the ground had a greater destructive influence on wall performance. The worst state for the wall was occurred by a void, having 12 m diameter and situated at 16 m in depth from the surface. The acquired results were 34% and 350% increase for horizontal deformation and ground settlement, respectively.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.017
GPT teacher head0.328
Teacher spread0.311 · 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 source (direct Gemma or distilled Codex), 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
Published2025
Admission routes1
Has abstractyes

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