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Record W3045367086 · doi:10.5194/angeo-38-881-2020

Evaluation of possible corrosion enhancement due to telluric currents: case study of the Bolivia–Brazil pipeline

2020· article· en· W3045367086 on OpenAlexfundno aff
Joyrles Fernandes de Moraes, Igo Paulino, L. R. Alves, C. M. Denardini

Bibliographic record

VenueAnnales Geophysicae · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsnot available
FundersFundação de Apoio à Pesquisa do Estado da ParaíbaConselho Nacional de Desenvolvimento Científico e TecnológicoMinistério da Ciência, Tecnologia e InovaçãoCanadian Natural Resources Limited
KeywordsEarth's magnetic fieldCorrosionSpace weatherGeomagnetic stormStormEnvironmental scienceGeologyMagnetometerGeophysicsMeteorologyMagnetic fieldSoil scienceMaterials sciencePhysicsMetallurgy

Abstract

fetched live from OpenAlex

Abstract. The electric field induced in the Bolivia–Brazil gas pipeline (GASBOL) was calculated by using the distributed source line transmission (DSLT) theory during several space weather events. We used geomagnetic data collected by a fluxgate magnetometer located at São José dos Campos (23.2∘ S, 45.9∘ W). The total corrosion rate was calculated by using the Gummow (2002) methodology and was based on the assumption of a 1 cm hole in the coating of the pipeline. The calculations were performed at the ends of pipeline where the largest “out-of-phase” pipe-to-soil potential (PSP) variations were obtained. The variations in PSP during the 17 March 2015 geomagnetic storm have led to the greatest corrosion rate of the analyzed events. All the space weather events evaluated with high terminating impedance may have contributed to increases in the corrosion process. The applied technique can be used to evaluate the corrosion rate due to the high telluric activity associated with the geomagnetic storms at specific locations.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.974
Threshold uncertainty score0.399

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 science0.0000.000
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 head0.055
GPT teacher head0.316
Teacher spread0.261 · 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

Citations10
Published2020
Admission routes1
Has abstractyes

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