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Record W113560535 · doi:10.5006/c2010-10113

Use of Geomagnetic Data for Evaluation of Telluric Effects on Pipelines

2010· article· en· W113560535 on OpenAlexaffabout
L. Trichtchenko, P. Fernberg, Michael D. Harrison

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsPipeline transportEarth's magnetic fieldGeologyEnvironmental sciencePetroleum engineeringPhysicsMagnetic field

Abstract

fetched live from OpenAlex

Abstract Telluric currents interfere with cathodic protection systems and cause variations in pipe-to-soil potentials, which can exceed the levels recommended for protection of the pipeline steel. The amplitudes of telluric currents observed in a pipeline depend on three factors: (1) the level of the geomagnetic activity, (2) conductivity of the underlying earth and (3) pipeline electromagnetic properties and geometric parameters. These factors have been incorporated into mathematical models that are used to estimate the pipe-to-soil potential variations due to telluric activity. The time when pipe-to-soil potential variations exceed the recommended level can be different depending on the different telluric activity at the pipeline locations. To evaluate this, a simple model for the telluric electric field has been set up, based on the geomagnetic data and an earth conductivity model. A statistical study based on the long records of the geomagnetic data from Canadian magnetic observatories and conductivity structures of the deep earth allows evaluating telluric activity for 30 years period. In order to show the geographical areas with different levels of activity, a set of maps has been produced and is available through Atlas of Canada web page: http://atlas.nrcan.gc.ca/auth/english/maps/environmentlnaturalhazards/space_weather. The estimated telluric electric fields were used as an input to model pipe-to-soil potential variations on a pipeline. In order to do this, the developed pipeline model has been incorporated to provide an on-line service for different users. The on-line service allows the user to evaluate the pipe-to-soil potential fluctuations at a particular location for a user-defined pipeline.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.992
Threshold uncertainty score0.648

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.089
GPT teacher head0.320
Teacher spread0.232 · 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 designOther design
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

Citations3
Published2010
Admission routes2
Has abstractyes

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