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Using commercial finite element packages for the study of earth deformations, sea levels and the state of stress

2004· article· en· W2139403704 on OpenAlexaff
Patrick Wu

Bibliographic record

VenueGeophysical Journal International · 2004
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsFinite element methodViscoelasticityStress (linguistics)Deformation (meteorology)Earth (classical element)Earth modelPhysicsMechanicsGeologyGeophysicsMeteorology

Abstract

fetched live from OpenAlex

Modifications to commercial finite element (FE) packages must be applied before they can be used for geophysical studies involving long wavelength deformation or viscoelasticity. This paper provides in detail how and why the commercial codes have to be modified when incompressibility is assumed. Both the non-self-gravitating flat earth and self-gravitating spherical earth will be considered. The latter involves an iterative procedure, which converges within 5 iterations. This is demonstrated both analytically and numerically. In addition, implementation of the gravitationally self-consistent sea level equation on a self-gravitating spherical earth is also described. Good agreement between numerical results obtained with this coupled finite-element method and the conventional spectral method is also demonstrated. In all cases, the interpretation of the outputs of FE models are particularly important in modelling the state of stress.

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)0.004
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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.036
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0360.014

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 head0.059
GPT teacher head0.288
Teacher spread0.229 · 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
GenreMethods

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

Citations185
Published2004
Admission routes1
Has abstractyes

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