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Record W2261175038

Numerical Modeling of Soil Liquefaction at Slope Site

2006· article· en· W2261175038 on OpenAlexaboutno aff
Park Sung-Sik

Bibliographic record

VenueJournal of the Korean GEO-environmental Society · 2006
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsCentrifugeLiquefactionGeotechnical engineeringMohr–Coulomb theoryPore water pressureConstitutive equationSoil liquefactionSettlement (finance)GeologyShear (geology)Yield (engineering)Flow (mathematics)Effective stressEngineeringStructural engineeringFinite element methodMechanicsMaterials scienceComputer science
DOInot available

Abstract

fetched live from OpenAlex

A fully coupled effective stress dynamic analysis procedure for modeling seismic liquefaction on slope is presented. An elasto-plastic formulation is used for the constitutive model UBCSAND in which the yield loci are radial lines of constant stress ratio and the flow rule is non-associated. This is incorporated into the 2D version of Fast Lagrangian Analysis of Continua (FLAC) by modifying the existing Mohr-Coulomb model. This numerical procedure is used to simulate centrifuge test data from the Rensselaer Polytechnic Institute (RPI). UBCSAND is first calibrated to cyclic direct simple shear tests performed on Nevada sand. Both pre- and post-liquefaction behaviour is captured. The centrifuge test is then modeled and the predicted accelerations, excess porewater pressures, and displacements are compared with the measurements. The results are shown to be in general agreement. The procedure is currently being used in the design of liquefaction remediation measures for a number of dam, bridge, tunnel, and pipeline projects in Western Canada.

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 score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.004
GPT teacher head0.156
Teacher spread0.153 · 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

Citations2
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Korean GEO-environmental Society→Same topicGeotechnical Engineering and Soil Mechanics→French-language works237,207→