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Record W2018377671 · doi:10.1680/gein.9.0226

<b>Conversion of Geosynthetic Strain to Load Using Reinforcement Stiffness</b>

2002· article· en· W2018377671 on OpenAlexafffund
Dave Walters, Tom Allen, Richard J. Bathurst

Bibliographic record

VenueGeosynthetics International · 2002
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsRoyal Military College of CanadaQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaMinistère de la Défense NationaleU.S. Department of Transportation
KeywordsReinforcementGeosyntheticsStiffnessCreepGeotechnical engineeringStructural engineeringGeotextileMaterials scienceTension (geology)Composite materialGeologyEngineeringUltimate tensile strength

Abstract

fetched live from OpenAlex

Measurements indicative of the internal behavior of full-scale geosynthetic-reinforced soil walls typically consist of reinforcement strains and overall deformations. The focus of this paper is the development of a methodology that can be used to convert measured reinforcement strains to load using properly selected reinforcement stiffness values. The loading of the geosynthetic in the field can be simulated in the laboratory using creep, relaxation, and constant-rate-of-strain tests. It was found that in-isolation creep stiffness data is sufficiently accurate to estimate reinforcement loads from strain measurements, at least for geogrids and most woven geotextiles. The approach is validated using data from carefully instrumented wall case histories in which reinforcement loads were measured directly and compared to loads estimated from measured reinforcement strain data.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.018
GPT teacher head0.215
Teacher spread0.197 · 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 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

Citations104
Published2002
Admission routes2
Has abstractyes

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