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Record W3159330769 · doi:10.1115/1.4049738

Energy, Exergy, Environmental (3E) and Parametric Assessment of a Triple-Pressure Reheat Combined-Cycle Power Plant

2021· article· en· W3159330769 on OpenAlexaff
David S.‐K. Ting, Rupp Carriveau, Amin Kardgar

Bibliographic record

VenueJournal of Energy Resources Technology · 2021
Typearticle
Languageen
FieldEngineering
TopicThermodynamic and Exergetic Analyses of Power and Cooling Systems
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsExergyCombined cycleSteam-electric power stationHeat recovery steam generatorNuclear engineeringGas compressorSteam turbineCondenser (optics)Environmental scienceCombustorRankine cycleMass flow rateCombustionGas turbinesEngineeringProcess engineeringThermodynamicsMechanical engineeringPower (physics)ChemistryPhysics

Abstract

fetched live from OpenAlex

Abstract In this study, energy, exergy, and environmental (3E) assessments have been conducted on a proposed combined-cycle power plant (CCPP) with three pressure levels of the HRSG and reheating process. 3E design approaches cross-link mechano-electric and environmental objectives. Herewith, the suggested combined-cycle is formed by a gas unit, condenser, steam turbines, triple-pressure heat recovery steam generator (HRSG) and also utilizes reheat facilities and auxiliary components. It is observed that more than 56% of total exergy destruction occurs in the combustor, followed by HRSG (15.29%), steam turbines (roughly 15.02%), gas turbine (8.93%), air compressor (1.79%), and condenser (0.66%). A parametric study is also presented that examines the sensitivity of performance indicators to various environmental states, steam pressures, pinch points, and steam mass flow rates. Moreover, it is presented that the implementation of Siemens SGT-100-1S over other GT configurations can considerably reduce deficiency of the overall cycle. The effects of each contaminant mass flowrate (NOx, CO, UHC, and CO2) and adiabatic flame temperature (AFT) are also studied when the gas unit operates under partial power and incomplete combustion conditions. In conclusion, a number of potential causes of irreversibilities and corrective optimization guidance are offered for each main equipment of the CCPP.

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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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)0.0010.000

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 head0.003
GPT teacher head0.191
Teacher spread0.188 · 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

Citations18
Published2021
Admission routes1
Has abstractyes

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