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Record W4391856685 · doi:10.26583/npe.2023.4.05

Towards a Uniform Description of Recombiners Performance by a Consistent CFD approach with the use of a Detailed Mechanism of Hydrogen Oxidation

2023· article· en· W4391856685 on OpenAlexaboutno aff
Vineet Alexander, I. Achakovskii Oleg, V. Ketlerov Vladimir, S. L. Soloviev, Huong Duong Quang

Bibliographic record

VenueIzvestiya Wysshikh Uchebnykh Zawedeniy Yadernaya Energetika · 2023
Typearticle
Languageen
FieldEngineering
TopicSpacecraft and Cryogenic Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsMechanism (biology)Computational fluid dynamicsComputer scienceHydrogenMechanicsChemistryPhysics

Abstract

fetched live from OpenAlex

This paper presents an overview of the European Union PARSOAR project, which consists in carrying out a state of the art on hydrogen passive autocatalytic recombiner (PAR) and a handbook guide for implementing these devices in nuclear power plants.This work is performed in the area « Operational Safety of Existing Installations » of the key action « Nuclear Fission » of the fifth Euratom Framework Programme (1998)(1999)(2000)(2001)(2002).Although lots of publications about recombiners have been published for the last ten years, no synthesis has been performing yet.The aim of the PARSOAR project is to make up this lack and to answer needs of all the nuclear technology partners.The project partners are representative of industry, safety organisations, and research institutes, coming from several countries (Belgium, Canada, France, Germany, and Switzerland).oooo

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)0.001
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.039
GPT teacher head0.195
Teacher spread0.156 · 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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueIzvestiya Wysshikh Uchebnykh Zawedeniy Yadernaya EnergetikaSame topicSpacecraft and Cryogenic TechnologiesFrench-language works237,207