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Record W2594539118 · doi:10.1016/j.proeng.2017.01.043

Modeling of Liquefaction using Two-phase FEM with UBC3D-PLM model

2017· article· en· W2594539118 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProcedia Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics Simulations and Interactions
Canadian institutionsMcMaster University
FundersRijkswaterstaatDeltaresStichting voor de Technische WetenschappenUniversiteit Utrecht
KeywordsLiquefactionFinite element methodGeotechnical engineeringSoil liquefactionEarthquake shaking tableDikeDeformation (meteorology)Benchmark (surveying)Phase (matter)EngineeringGeologyStructural engineeringChemistry

Abstract

fetched live from OpenAlex

Soil liquefaction describes a loss of strength of saturated sand upon sudden or cyclic loading. A slight disturbance of such a soil’s fabric might lead to severe damage, e.g. the collapse of sea dikes. Accurate modeling of the state transition between saturated soil and a liquefied soil-water mixture, as well as post-liquefaction phenomena, is crucial for the prediction of such damage. However, developing an appropriate numerical model remains a challenging problem, especially when the simulation involves dynamic large deformation processes. In order to make a first step towards an accurate simulation of soil liquefaction, a two-phase formulation of the finite element method (FEM) in conjunction with the elastoplastic UBC3D-PLM model is investigated. The performance of this approach is analyzed based on a shaking table benchmark.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.487
Threshold uncertainty score0.681

Codex and Gemma teacher scores by category

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

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 head0.276
Teacher spread0.254 · 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