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Record W2074580377 · doi:10.1115/icone18-29998

Thermal Aspects of Using Uranium Mononitride Fuel in a SuperCritical Water-Cooled Reactor at Maximum Heat Flux Conditions

2010· article· en· W2074580377 on OpenAlexafffund
Ashley Milner, Caleb Pascoe, Hemal Patel, Wargha Peiman, Graham Richards, Igor Pioro

Bibliographic record

Venue18th International Conference on Nuclear Engineering: Volume 2 · 2010
Typearticle
Languageen
FieldEngineering
TopicHeat transfer and supercritical fluids
Canadian institutionsOntario Tech University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSupercritical fluidNuclear engineeringCoolantLight-water reactorMaterials scienceNuclear reactorThermal efficiencyElectricity generationUraniumDecay heatWaste managementEnvironmental scienceChemistryThermodynamicsMechanical engineeringEngineeringPower (physics)Metallurgy

Abstract

fetched live from OpenAlex

Generation IV nuclear reactor technology is increasing in popularity worldwide. One of the six Generation-IV-reactor types are SuperCritical Water-cooled Reactors (SCWRs). The main objective of SCWRs is to increase substantially thermal efficiency of Nuclear Power Plants (NPPs) and thus, to reduce electricity costs. This reactor type is developed from concepts of both Light Water Reactors (LWRs) and supercritical fossil-fired steam generators. The SCWR is similar to a LWR, but operates at a higher pressure and temperature. The coolant used in a SCWR is light water, which has supercritical pressures and temperatures during operation. Typical light water operating parameters for SCWRs are a pressure of 25 MPa, an inlet temperature of 280–350°C, and an outlet temperature up to 625°C. Currently, NPPs have thermal efficiency about of 30–35%, whereas SCW NPPs will operate with thermal efficiencies of 45–50%. Furthermore, since SCWRs have significantly higher water parameters than current water-cooled reactors, they are able to support co-generation of hydrogen. Studies conducted on fuel-channel options for SCWRs have shown that using uranium dioxide (UO2) as a fuel at supercritical-water conditions might be questionable. The industry accepted limit for the fuel centerline temperature is 1850°C and using UO2 would exceed this limit at certain conditions. Because of this problem, there have been other fuel options considered with a higher thermal conductivity. A generic 43-element bundle for an SCWR, using uranium mononitride (UN) as the fuel, is discussed in this paper. The material for the sheath is Inconel-600, because it has a high resistance to corrosion and can adhere to the maximum sheath-temperature design limit of 850°C. For the purpose of this paper, the bundle will be analyzed at its maximum heat flux. This will verify if the fuel centerline temperature does not exceed 1850°C and that the sheath temperature remains below the limit of 850°C.

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)0.000
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.018
GPT teacher head0.241
Teacher spread0.222 · 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

Citations0
Published2010
Admission routes2
Has abstractyes

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