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Record W2062099840 · doi:10.3997/2214-4609.20141097

Forward Modelling of Geophysical Electromagnetic Data on Unstructured Grids Using a Finite-volume Approach

2014· article· en· W2062099840 on OpenAlexaff
Hormoz Jahandari, Colin G. Farquharson

Bibliographic record

VenueProceedings · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsInterpolation (computer graphics)Unstructured gridFinite volume methodTetrahedronDiscretizationComputationElectromagnetic fieldElectric fieldMaxwell's equationsAlgorithmComputer scienceMathematical analysisGeometryApplied mathematicsMathematicsGridPhysicsMechanics

Abstract

fetched live from OpenAlex

Summary The application of unstructured grids can improve the solution of total field electromagnetic problems as these grids allow efficient local refinement of the mesh at the locations of high field gradients. Unstructured grids also provide the flexibility required for representing arbitrary topography and subsurface interfaces. This study investigates the generalization of the standard Yee’s staggered scheme to unstructured tetrahedral-Voronoï grids using a finite-volume approach. We discretize the Helmholtz equation for the electric field in the frequency domain and solve the problem to find the projection of the total electric field along the edges of the tetrahedral elements. To compute the electric and magnetic fields at the observation points an interpolation technique is employed which uses the edge vector interpolation functions of the tetrahedral elements. An example is included which shows the computation of the total and secondary fields due to an electric source in a halfspace that contains an anomalous body. The results show good agreement with those from the literature.

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 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.832
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.044
GPT teacher head0.238
Teacher spread0.194 · 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 teacher head, 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

Citations1
Published2014
Admission routes1
Has abstractyes

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