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Record W2132939456 · doi:10.3184/096034008x330798

Sulphidation resistance of composite boiler tube materials

2008· article· en· W2132939456 on OpenAlexaff
J.R. Kish, Philip Eng, Douglas Singbeil, James R. Keiser

Bibliographic record

VenueMaterials at High Temperatures · 2008
Typearticle
Languageen
FieldEngineering
TopicHigh-Temperature Coating Behaviors
Canadian institutionsFPInnovations
FundersOak Ridge National LaboratoryOffice of Energy Efficiency and Renewable Energy
KeywordsCorrosionMaterials scienceMetallurgyComposite numberBoiler (water heating)Cladding (metalworking)Tube furnaceChromiumAlloyHigh-temperature corrosionBlack liquorWeldingComposite materialTube (container)Waste managementChemical engineering

Abstract

fetched live from OpenAlex

A lab-based testing program was undertaken to generate data to better define the sulphidation resistance of composite tubes installed in the lower-furnace section of black liquor recovery boilers. All composite tube cladding alloys tested were observed to have an acceptable corrosion rate at normal operating temperatures (up to 400°C) in the synthetic lower-furnace gaseous environment tested (1% H2S–99% N2). This acceptable corrosion resistance is due to the expected formation of a relatively protective chromium-rich inner sulphide scale. An increase in temperature up to 560°C was found to significantly increase the corrosion rate. Of the various alloys tested, Alloy HR11N exhibited the lowest corrosion rate at each of the three temperatures tested. Moreover, the corrosion rate was found not to be strongly dependent on the fabrication route (weld overlay versus co-extruded). To minimize corrosion, operating conditions that promote prolonged exposure to elevated temperatures in the lower-furnace section of black liquor recovery boilers should be avoided, regardless of the type of composite tube installed.

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 categoriesMeta-epidemiology (narrow), Insufficient 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 score0.042
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.008
GPT teacher head0.205
Teacher spread0.197 · 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

Citations1
Published2008
Admission routes1
Has abstractyes

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