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Record W580367976

Added Longevity with Thermoplastic Polymer Coated Structural Steel Plate

2013· article· en· W580367976 on OpenAlexaboutno aff
Anna West, Kevin Williams, P.A. Carroll

Bibliographic record

VenueTransportation Research Board 92nd Annual MeetingTransportation Research Board · 2013
Typearticle
Languageen
FieldMaterials Science
TopicCorrosion Behavior and Inhibition
Canadian institutionsnot available
Fundersnot available
KeywordsGalvanizationMaterials scienceCoatingThermoplasticComposite materialAbrasivePolymerDurabilityLayer (electronics)
DOInot available

Abstract

fetched live from OpenAlex

Basic corrugated steel pipes were invented in 1896 and have since evolved into buried steel structures with the possibility of spans reaching upwards of 120 ft (40 m). To meet increasing design life requirements, galvanized and polymer laminate coatings have been developed to extend the life of the steel. In general, galvanized coatings perform well in hard water and non-abrasive conditions whereas polymer coatings perform well in these conditions plus salt-laden, soft water and moderately abrasive environments. To date, polymer laminate systems have been restricted to shallow corrugation profiles with maximum spans of approximately 12 ft (3.6 m), thus limiting greater spanned buried steel structures as a solution in less adverse environments. A new thermoplastic polymer system, comprised of a zinc rich primer and ethylene acrylic acid topcoat, has been developed. This paper introduces the new thermoplastic polymer system, comparing it to polymer laminated, galvanized and aluminized type 2 coatings. The coating has been used successfully since 2005 and recently completed a series of performance testing. Testing suggests the thermoplastic polymer coating meets, and in most cases exceeds, the performance of competing technologies. Discussion is focused on the laboratory tests, a recently developed performance guideline and field installations. Nearly 10 years of field experience, with over 20 structures designed and manufactured in Canada alone, support the laboratory results obtained and presented, enabling readers to gain an understanding of applications this new coating facilitates.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.498
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0020.002
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.045
GPT teacher head0.341
Teacher spread0.296 · 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 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

Citations1
Published2013
Admission routes1
Has abstractyes

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