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Record W2058685040 · doi:10.1115/1.1340621

Design and Performance Verification of a 62-MWt CFB Boiler

2000· article· en· W2058685040 on OpenAlexafffund
Kefa Cen, Pallab Basu, Leming Cheng, Meng Fang, Zeyu Luo

Bibliographic record

VenueJournal of Engineering for Gas Turbines and Power · 2000
Typearticle
Languageen
FieldEngineering
TopicAdvanced Control Systems Optimization
Canadian institutionsDalhousie University
FundersZhejiang UniversityDalhousie University
KeywordsBoiler (water heating)CoalFluidized bed combustionEngineeringNuclear engineeringWaste management

Abstract

fetched live from OpenAlex

The present paper discusses the goals and methods of design of a circulating fluidized bed (CFB) boiler: A 62-MWt (75-T/h) CFB boiler was designed manually using experience and available published data. The design was regenerated by an Expert System for evaluation and confirmation of the manual design. Design choices and resulting surface areas from these two approaches were compared and validated. Final confirmation of the design can be obtained only from operation of the boiler. The boiler was built and commissioned in the Jiangshu Province, China, firing the design coal. A comprehensive test program was undertaken to monitor the performance of the boiler. Predicted performance from both the manual design and the Expert System is compared with those measured in the boiler. A reasonable agreement between the predicted performance and measured values was obtained, which confirmed both experience-based design decision and that from the Expert System.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.005
GPT teacher head0.180
Teacher spread0.175 · 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 designSimulation or modeling
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

Citations6
Published2000
Admission routes2
Has abstractyes

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