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Record W4409555806 · doi:10.5006/c2006-06163

Cathodic Protection of Pipelines in High Resistivity Soils and the Effect of Seasonal Changes

2006· article· en· W4409555806 on OpenAlexaffabout
Fraser King, Greg Van Boven, Kurt Lawson, Neil Thompson, P.F. Nichols

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsUnion Gas (Canada)Nova Chemicals (Canada)
Fundersnot available
KeywordsCathodic protectionElectrical resistivity and conductivityPipeline transportSoil resistivitySoil waterMaterials scienceCorrosionEnvironmental scienceMetallurgySoil scienceEnvironmental engineeringElectrochemistryElectrical engineeringChemistryEngineeringElectrode

Abstract

fetched live from OpenAlex

Abstract Seasonal fluctuations in temperature and soil moisture content can affect the cathodic protection of underground pipelines. These effects are particularly pronounced in high-resistivity soils which can experience large fluctuations in soil resistivity because of episodic or seasonal changes in moisture content. Under some circumstances it can be difficult to demonstrate compliance with various CP criteria, even though the moisture content is so low that corrosion is unlikely to be a significant problem. This paper describes the results of a study to investigate the effect of seasonal changes on the protection of pipelines in high-resistivity soil. In addition to establishing the nature and magnitude of the seasonal fluctuations, a second aim was to demonstrate that corrosion rates are low even when compliance with a given CP criterion cannot be demonstrated. Environmental and CP measurements were made on operating pipelines in both Canada and the U.S. Daily monitoring of soil characteristics such as resistivity, pH, temperature and oxygen content was performed at the pipeline to soil interface using a novel pipe-depth probe and automated measurement system. Coupons were used to measure on-, off-, and native potentials, also on a daily basis, as well as native corrosion rates during periodic site visits. A method is proposed for predicting corrosion rates of polarized coupons to demonstrate that rates are low in high-resistivity soils even though compliance with a particular CP criterion may not be met.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.565
Threshold uncertainty score0.170

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 communication0.0000.000
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 head0.006
GPT teacher head0.224
Teacher spread0.217 · 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 designBench or experimental
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

Citations0
Published2006
Admission routes2
Has abstractyes

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