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Record W7133089092

The solubility of kraft recovery boiler precipitator ash

2006· dissertation· W7133089092 on OpenAlexfundno aff
Daniel Moreira Saturnino

Bibliographic record

VenueTSpace · 2006
Typedissertation
Language
FieldComputer Science
TopicChemical and Environmental Engineering Research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSolubilitySodiumSodium sulfatePotassium carbonateFly ashSodium carbonatePotassiumBoiler (water heating)
DOInot available

Abstract

fetched live from OpenAlex

Precipitator ash typically contains sodium sulfate (Na 2SO4), sodium carbonate (Na2CO3), sodium chloride (NaCl) and potassium salts. The solubility of precipitator ash in water is important information for ash treatment processes to maximize the removal efficiency of chloride and potassium while minimizing the losses of sodium and sulfur. Various techniques have been proposed to treat the precipitator ash due to its enrichment in Cl and K that play an important role on fouling and corrosion problems in recovery boilers. This thesis concerns a study on the solubility data of the system Na +, K+, Cl, CO32- and SO 42- in water using a thermodynamic model, OLI. The study results show that Cl concentration in the liquid increases with and increase in ash concentration, while sulfate concentration decreases. Temperature has little effect on the composition of the liquid phase for temperatures between 30 and 100°C, but has significant effect below 30°C.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.010
GPT teacher head0.284
Teacher spread0.274 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2006
Admission routes1
Has abstractyes

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