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EFFECTS OF INTERCOOLING ON THE PERFORMANCE OF AN IRREVERSIBLE REGENERATIVE MODIFIED BRAYTON CYCLE

2007· article· en· W2091142509 on OpenAlexvenueno aff
S. K. Tyagi, J. Chen, S.C. Kaushik, Chuansong Wu

Bibliographic record

VenueInternational Journal of Power and Energy Systems · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Thermodynamics and Statistical Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsBrayton cycleTurbineIntercoolerOverall pressure ratioCombined cycleGas turbinesMechanical engineeringControl theory (sociology)EngineeringAutomotive engineeringNuclear engineeringGas compressorComputer science

Abstract

fetched live from OpenAlex

The irreversible cycle model of a regenerative intercooled modified Brayton cycle heat engine has been established for the finite heat capacities of external reservoirs. The power output has been optimized with respect to the cycle temperatures and the optimum performance parameters are calculated for a typical set of operating condition. It is found that there are optimal values of the intercooling and cycle pressure ratios as well as the turbine outlet temperature at which the cycle attains the maximum performance but the optimal values of these parameters are different for different cycle parameters such as the intercooling and cycle pressure ratios, turbine outlet temperature, etc. Moreover, the design problems of some important parameters are discussed in detail, and consequently, the optimum criteria for the intercooling and cycle pressure ratios and the turbine outlet temperature are obtained. The results obtained here are general and some important conclusions in the relevant references may be directly derived from this paper.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.005
GPT teacher head0.238
Teacher spread0.233 · 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

Citations10
Published2007
Admission routes1
Has abstractyes

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