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Record W1527555980 · doi:10.1002/9783527603978.mst0449

Coated Particle Fuels for High‐Temperature Reactors

2015· other· en· W1527555980 on OpenAlexaff
M.J. Kania, H. Nabielek, Hubertus Nickel

Bibliographic record

VenueMaterials Science and Technology · 2015
Typeother
Languageen
FieldMaterials Science
TopicNuclear Materials and Properties
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsMaterials scienceSilicon carbideCeramicParticle (ecology)Composite materialNuclear engineering

Abstract

fetched live from OpenAlex

The article contains sections titled: Introduction History ofHTGRsand Coated Particle Fuel Development HTGRsBuilt and Operated HTGRsDesigned but Not Built Modular Reactors (1980sDesign) Current Modular Reactor Designs Coated Particle Fuel Development Development in theUK Development inGermany Development in theUS Recent Directions Fuel Manufacturing Processes FuelKernel Manufacture Powder Metallurgical Process Sol–Gel Process Gel‐Precipitation Process forUO2Kernels Gel‐Precipitation Process forUCOKernels Fabrication ofPuO2Kernels Ceramic Coatings by CVD Pyrolytic Carbon (PyC) Coatings Silicon Carbide (SiC) Coatings Fuel Element Manufacture Spherical Fuel Elements for Pebble‐Bed Cores Hexagonal‐Block Fuel Elements for Prismatic Cores HTGRFuel Materials Properties Properties ofUO2Fuel Kernels Thermal Properties ofUO2 Mechanical Properties ofUO2 Swelling Rate ofUO2 Properties of Pyrolytic Carbon (PyC) Coatings Thermal Properties ofPyC Theoretical Density ofPyC Mechanical Properties ofPyC Irradiation‐Induced Dimensional Change ofPyC Properties of Silicon Carbide (SiC) Coatings Thermal Properties ofSiC Mechanical Properties ofSiC Swelling Rate ofSiC Fuel Quality Control and Performance Evaluation Quality Control ofUO2Kernels Quality Control of Coated Particles Quality Control of Spherical Fuel Elements Failure Statistics and Performance Requirements The Mathematics of Failure Statistics Statistical Analysis of Fuel Element Manufacture Statistical Analysis of Irradiation Performance Statistical Analysis of Accident Condition Performance Comparison to Performance Requirements Fuel Performance under Normal Operating Conditions Irradiation Testing of Modern UO2TRISO‐Coated Particles Accelerated Irradiations in Material Test Reactors HFR‐P4 Test SL‐P1 Test HFR‐K3 Test FRJ2‐K13 Test FRJ2‐K15 Test FRJ2‐P27 Test Conduct of the Accelerated Tests HTRMODUL Proof Tests HFR‐K5 andHFR‐K6 AVRReal‐Time Irradiation Testing Performance Assessment for Normal Operating Conditions Fuel Performance under Accident Conditions Simulation of Core Heat‐Up after Depressurization under Dry Conditions Analysis of Accident Simulation Testing Behavior after Water and Air Ingress Simulation of Water Ingress Simulation of Air Ingress HTGRFission Product Generation and Transport Fission Product Generation Fission Product Transport Equivalent Sphere Model for Gas Release Recoil Release from Fuel Kernel Release from Post‐Irradiation Heating Tests Release of Short‐LivedXeandKrIsotopes Retention by a Single Coating Layer Release for a Single Shell Diffusion Data for Coating Layers Applicability and Uncertainties of Transport Data Transport and Release from Fuel Elements in Reactor Tests andHTGRs Fission Product Chemistry andCOGeneration inUO2 Coated Particle Failure Mechanisms Pressure‐Induced Failure Internal Gas Pressure Buildup Predicting Pre

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.025
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0250.007

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 head0.015
GPT teacher head0.236
Teacher spread0.221 · 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 designBench or experimental
Domainnot available
GenreOther

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

Citations15
Published2015
Admission routes1
Has abstractyes

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