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Record W1970739799 · doi:10.5006/1.3278344

Corrosion of Bed Nozzle Alloys in a Wood-Waste Fluidized Bed Power Boiler

2007· article· en· W1970739799 on OpenAlexaff
J.R. Kish, Douglas Singbeil, P. Eng, O. Posein, R. Seguin

Bibliographic record

VenueCORROSION · 2007
Typearticle
Languageen
FieldEngineering
TopicHigh Temperature Alloys and Creep
Canadian institutionsCatalyst Paper (Canada)Nordion (Canada)
Fundersnot available
KeywordsCorrosionMetallurgyMaterials scienceNozzleAlloyFluidized bed combustionBoiler (water heating)Fluidized bedWaste managementEngineering

Abstract

fetched live from OpenAlex

A field test was conducted to identify a more corrosion-resistant material than Type 310H (UNS S31009) stainless steel, from which to fabricate bed nozzles for a fluidized bed power boiler that burns salt-laden wood-waste (hogged) fuel. Test nozzles fabricated from Type 310H stainless steel, Alloys 556 (UNS R30556), 59 (UNS N06059), HR160 (UNS N12160), and 625 (UNS N06625) were installed, subsequently removed, and examined as a function of time. Of the various alloys tested, Alloys 625 and HR160 had the best performance in terms of the amount of thickness loss, and the extent of internal damage exhibited. However, those alloys were still susceptible to corrosion by the fireside (fluidized bed) environment and, therefore, will require replacement over time. Despite the observed corrosion, those two alloys significantly extended the nozzle life beyond that of Type 310H stainless steel. Nozzle design was found to have a strong influence on the apparent corrosion resistance of Alloy 625 and, therefore, represents a promising preventive solution possibility. The reason for the marked improvement remains unresolved at this time.

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 score0.007
Threshold uncertainty score0.898

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 head0.006
GPT teacher head0.212
Teacher spread0.206 · 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

Citations5
Published2007
Admission routes1
Has abstractyes

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