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Record W3133017639 · doi:10.1155/2021/6626750

Flexible Temporary Shield in Soft and Sensitive Clay: 3D FE Modelling of Experimental Field Test

2021· article· en· W3133017639 on OpenAlexafffund
Miah Alam, Omar Chaallal, Bertrand Galy

Bibliographic record

VenueModelling and Simulation in Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsInstitut de recherche Robert-Sauvé en santé et en sécurité du travailÉcole de Technologie Supérieure
FundersInstitut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail
KeywordsShieldMaterials scienceGeotechnical engineeringField (mathematics)Test (biology)Composite materialStructural engineeringForensic engineeringMechanical engineeringEngineeringGeologyPetrology

Abstract

fetched live from OpenAlex

A finite-element (FE) numerical study using PLAXIS-3D software was carried out to reproduce and validate a full-scale experimental in situ test and to investigate the earth pressure on a flexible temporary trench box shield in soft and sensitive clay soil. The excavation trench model was 6 m (20 ft) deep and was considered as nonlinear and anisotropic clay. A 45 kPa (0.94 ksf) surface overload on top of the soil near the trench box was also simulated to produce a maximum load case on the flexible wall of the shield. Both Mohr-Coulomb (MC) and hardening soil (HS) constitutive soil models were considered for FE analysis. Different values of the modulus reduction factor (MRF) and the coefficient of earth pressure at rest ( K 0 ) were considered to validate the model. For a specific shear strength profile, FE analysis with a linear elastoplastic soil model showed relatively small differences in soil pressure with the field test results along the depth of the trench. Results were also compared with the predictions of well-established analytical formulae.

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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.222
Teacher spread0.200 · 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

Citations3
Published2021
Admission routes2
Has abstractyes

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