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Numerical Analysis of an Instrumented Steel-Reinforced Soil Wall

2014· article· en· W2004765786 on OpenAlexaff
Ivan Puig Damians, Richard J. Bathurst, Alejandro Josa, A. Lloret

Bibliographic record

VenueInternational Journal of Geomechanics · 2014
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsRoyal Military College of Canada
FundersUniversitat Politècnica de Catalunya
KeywordsFinite element methodStructural engineeringGeotechnical engineeringHardening (computing)Constitutive equationNumerical analysisGeologyBoundary value problemEngineeringMathematicsMaterials scienceComposite material

Abstract

fetched live from OpenAlex

The paper describes the results and lessons learned using a FEM model to simulate quantitative performance features of the Minnow Creek steel-strip reinforced soil wall structure located in the United States. The Minnow Creek Wall structure was constructed and instrumented in 1999. It is a unique case study because of the comprehensive measurements that were taken to record a wide range of wall performance features. Two different constitutive models for the soil were used (a linear-elastic Mohr-Coulomb model and hardening soil model with a Mohr-Coulomb failure criterion), and numerical outcomes were compared with physical measurements. The numerical results were shown to be sensitive to boundary conditions assumed at the toe of the wall. The generally encouraging agreement between physical and numerically predicted results gives confidence that commercial FEM software packages can be useful for the analysis and design of these types of structures, provided that care is taken in the selection of input parameters.

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 score0.006

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 head0.005
GPT teacher head0.211
Teacher spread0.206 · 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

Citations83
Published2014
Admission routes1
Has abstractyes

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