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Record W4409537664 · doi:10.5006/c2002-02215

Coatings Performance under Marine Environment

2002· article· en· W4409537664 on OpenAlexaff
Z. M. Muntasser, M. M. Al-Darbi, M. R. Islam

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSurface Roughness and Optical Measurements
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMaterials scienceEnvironmental scienceMetallurgyComputer scienceMarine engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract Marine atmosphere with its high level of salinity and humidity is very corrosive. It has been estimated that the direct cost of marine corrosion worldwide is between 50 and 80 billion dollars every year. However, coating the industry is responsible for almost 40 % of this cost. While polymer-based coatings have been used successfully to prevent corrosion in other parts of the world, few such coatings appear to have success in the marine environment. In this paper a new type of coating (properties of both a high performance epoxy and acrylic polyurethane) was tested for preventing corrosion in the marine environment. To have a better understanding of mechanisms of attack and the long-term effects of coatings, salt fog corrosion tests were conducted to ascertain the corrosion protection capability of various coating systems in different thickness including the new coating. Using scanning electronic microscope (SEM) and profilemeters the onset and growth of corrosion were observed. A protocol was developed to identify performance and efficiency of these systems, which can help suppliers and engineers in developing a long life coating systems for marine structure.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.365
Threshold uncertainty score1.000

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)0.0070.001

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 head0.024
GPT teacher head0.168
Teacher spread0.144 · 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; both teacher heads agree on what is shown here.

Study designSimulation or modeling
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
Published2002
Admission routes1
Has abstractyes

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