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Record W2803120393 · doi:10.14447/jnmes.v21i2.454

Impact of Experimental Parameters on Degradation Mechanism and Service Life Prediction of CFRP Anode during Simulated ICCP Process

2018· article· en· W2803120393 on OpenAlexvenueno aff
Hongfang Sun, Jian Liu, Kun Chu, Shazim Ali Memon, Zhuo Cen, Xiaogang Zhang, Dawang Li, Feng Xing

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2018
Typearticle
Languageen
FieldEngineering
TopicConcrete Corrosion and Durability
Canadian institutionsnot available
Fundersnot available
KeywordsAnodeElectrolyteDegradation (telecommunications)Service lifeCathodic protectionConsistency (knowledge bases)Current densityCurrent (fluid)Computer scienceMaterials scienceEnvironmental scienceChemistryComposite materialEngineeringElectrical engineeringTelecommunicationsPhysicsElectrode

Abstract

fetched live from OpenAlex

In actual building structure, it usually takes tens of years for the degradation to be significantly observed during impressed current cathodic protection (ICCP) process. Thus, simulated ICCP with aqueous electrolyte (instead of concrete) was used as an accelerated method to study degradation mechanism and make service life prediction. In this work, the impact of parameters including current (density) and NaCl electrolyte concentration on the degradation mechanism and service life prediction was evaluated for a simulated ICCP system with CFRP as anode. Experiments were performed with different levels of applied current (4, 10, and 20 mA) as well as with different NaCl electrolyte concentrations (3, 10, and 20% by mass). Test results showed that under all the designed conditions, both chlorination and oxidation reaction occurred during the simulated ICCP process, ensuring consistency of mechanism. From the aspect of service life prediction of CFRP, it was found that the system was not sensitive to the concentration of NaCl electrolyte but was much more influenced by the current (density) applied. Thus, for the simulated ICCP system, the current (density) should be carefully chosen since a tiny change in level of current may cause a large variation in service life prediction.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.430

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 head0.019
GPT teacher head0.269
Teacher spread0.250 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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