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Record W1527555980 · doi:10.1002/9783527603978.mst0449

Coated Particle Fuels for High‐Temperature Reactors

2015· other· en· W1527555980 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

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 of HTGRs and Coated Particle Fuel Development HTGRs Built and Operated HTGRs Designed but Not Built Modular Reactors (1980 s Design) Current Modular Reactor Designs Coated Particle Fuel Development Development in the UK Development in G ermany Development in the US Recent Directions Fuel Manufacturing Processes Fuel K ernel Manufacture Powder Metallurgical Process Sol–Gel Process Gel‐Precipitation Process for UO 2 Kernels Gel‐Precipitation Process for UCO Kernels Fabrication of PuO 2 Kernels 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 HTGR Fuel Materials Properties Properties of UO 2 Fuel Kernels Thermal Properties of UO 2 Mechanical Properties of UO 2 Swelling Rate of UO 2 Properties of Pyrolytic Carbon ( PyC ) Coatings Thermal Properties of PyC Theoretical Density of PyC Mechanical Properties of PyC Irradiation‐Induced Dimensional Change of PyC Properties of Silicon Carbide ( SiC ) Coatings Thermal Properties of SiC Mechanical Properties of SiC Swelling Rate of SiC Fuel Quality Control and Performance Evaluation Quality Control of UO 2 Kernels 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 UO 2 TRISO‐Coated Particles Accelerated Irradiations in Material Test Reactors HFR ‐ P 4 Test SL ‐ P 1 Test HFR ‐ K 3 Test FRJ 2‐ K 13 Test FRJ 2‐ K 15 Test FRJ 2‐ P 27 Test Conduct of the Accelerated Tests HTR MODUL Proof Tests HFR ‐ K 5 and HFR‐K 6 AVR Real‐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 HTGR Fission 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‐Lived Xe and Kr Isotopes 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 and HTGRs Fission Product Chemistry and CO Generation in UO 2 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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.107
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
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