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Record W2328221202 · doi:10.1149/1.2939074

Chemistry in Surface Boundary Layers as Related to Flow Accelerated Corrosion of Carbon Steel in High Temperature Water

2008· article· en· W2328221202 on OpenAlexaff
Shunsuke Uchida, Masanori Naitoh, Yasushi Uehara, Hidetoshi Okada, Seiichi Koshizuka, D. H. Lister

Bibliographic record

VenueECS Transactions · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicErosion and Abrasive Machining
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsCorrosionFlow (mathematics)Boundary layerOxideCarbon steelComputational fluid dynamicsVolumetric flow rateCarbon fibersChemistryMaterials scienceMetallurgyChemical engineeringMechanicsComposite materialPhysicsEngineering

Abstract

fetched live from OpenAlex

Flow accelerated corrosion (FAC) is divided into two processes: the corrosion (chemical) process and the flow dynamics (physical) process. The former is the essential cause of FAC, while the latter accelerates its occurrence. Chemistry in the surface boundary layers was analyzed to evaluate FAC rates. First flow pattern and temperature in each elemental volume along the flow path were obtained with 1-3D computational flow dynamics (CFD) codes, next [O2] and [Fe2+] were calculated with a chemical reaction model based on the obtained flow pattern, and then calculated [Fe2+] was fed back to the environmental factors for the wall thinning calculation, at all points of interest, using the modified double oxide layer model. The effects of candidates for countermeasures, e.g., O2 injection and increasing pH, on FAC mitigation could be evaluated. Future wall thinning trends could also be predicted by the model.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score0.998

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)0.0020.000

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 head0.009
GPT teacher head0.220
Teacher spread0.211 · 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.

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

Citations6
Published2008
Admission routes1
Has abstractyes

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