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Record W2207176483 · doi:10.1016/j.energy.2015.12.008

Energy and exergy analyses of a novel power cycle using the cold of LNG (liquefied natural gas) and low-temperature solar energy

2016· article· en· W2207176483 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnergy · 2016
Typearticle
Languageen
FieldEngineering
TopicThermodynamic and Exergetic Analyses of Power and Cooling Systems
Canadian institutionsUniversity of Ontario Institute of Technology
Fundersnot available
KeywordsLiquefied natural gasExergyOrganic Rankine cycleCogenerationRankine cycleWorking fluidExergy efficiencyRegenerative heat exchangerNuclear engineeringSolar energyEnvironmental scienceProcess engineeringCombined cycleEnergy recoveryNatural gasVaporizationWaste managementTurbineEngineeringElectricity generationHeat exchangerMechanical engineeringChemistryThermodynamicsWaste heatPower (physics)Energy (signal processing)Electrical engineering

Abstract

fetched live from OpenAlex

A new cogeneration system which uses CO2 (carbon dioxide) as a working fluid is proposed and analyzed. The system has high efficiency and no CO2 and other emissions. Thermal energy from a low temperature solar energy collector and the cold of LNG (liquefied natural gas) can be effectively utilized together. The system consists of a subcritical Rankine-like cycle, a solar collector and LNG vaporizing subsystems. By utilizing the LNG vaporization subsystem as the cycle cold sink, the cycle condensation process can be achieved at a temperature much lower than the ambient. Also, high-pressure liquid CO2 ready for disposal can be withdrawn from the cycle without consuming additional power. The effects of several key thermodynamic parameters on the system performance are examined based on various performance criteria. The results show that the performance of the system can be improved by adjusting the turbine inlet temperature, the LNG flow rate and the main heat characteristics of the solar energy system. Also, with a regenerator added to the cycle, a performance improvement is obtained that permits a reduction in the solar collector area. The energy and exergy efficiencies of the overall system are determined to be 60.1% and 61.3%, respectively.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.212
Threshold uncertainty score0.592

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.007
GPT teacher head0.219
Teacher spread0.211 · 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