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Record W4255975716 · doi:10.1115/fbc2003-163

Revamping of 4 x 58 MWth Pulverized Coal-Fired Boilers With Circulating Fluidized Bed Firing

2003· article· en· W4255975716 on OpenAlexaff
Amar K. Sen, L. Miller, Pallab Basu, Animesh Dutta

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIron and Steelmaking Processes
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPulverized coal-fired boilerFluidized bed combustionEnvironmental scienceWaste managementFly ashCoalNOxThermal power stationBoiler (water heating)CombustionElectricityEngineeringChemistry

Abstract

fetched live from OpenAlex

A techno-economic feasibility study has been conducted to investigate revamping four 58 MWth (15 MWe) pulverized-coal (PC) boilers with circulating fluidized bed (CFB) firing. The steam generators at Amarkantak Thermal Power Station in Chachai, Madhya Pradesh, are owned by Madhya Pradesh State Electricity Board (MPSEB), supplied by Simmering-Graz-Pauker AG of Vienna, Austria, and commissioned in mid-1965. The study reveals that: (i) CFB revamping of the boilers is technically feasible and economically sound; (ii) Performance improvement of the plant is significant in terms of such indices as plant load factor, forced outage and auxiliary oil consumption, among others. The expected performance improvement is due in large part to the elimination of key outage-prone components such as pulverizers (mills) and burners. (iii) There is significant improvement in emissions performance due to the reduction in emissions of NOx and fly ash; (iv) The financial analysis indicates that the CFB revamping option gives the highest return on investment compared to alternatives.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.197
Teacher spread0.185 · 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 designNot applicable
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

Citations2
Published2003
Admission routes1
Has abstractyes

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