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Record W2522235680 · doi:10.13182/nt16-7

Validation and Application of the REKO-DIREKT Code for the Simulation of Passive Autocatalytic Recombiner Operational Behavior

2016· article· en· W2522235680 on OpenAlexfundno aff
Ernst-Arndt Reinecke, Stephan Kelm, Paul-Martin Steffen, Michael Klauck, Hans-Josef Allelein

Bibliographic record

VenueNuclear Technology · 2016
Typearticle
Languageen
FieldEngineering
TopicCombustion and Detonation Processes
Canadian institutionsnot available
FundersBundesministerium für Wirtschaft und EnergieAtomic Energy of Canada Limited
KeywordsNuclear engineeringEnvironmental scienceThermal hydraulicsCombustionBoiler (water heating)Process engineeringWaste managementChemistryEngineeringHeat transferMechanicsPhysics

Abstract

fetched live from OpenAlex

In order to reduce the accumulation of hydrogen and thus to mitigate the risk of combustion, many countries have installed passive autocatalytic recombiners (PARs) within light water reactor containments. The severe hydrogen combustion events of the recent Fukushima Daiichi accident are likely to incentivize an increased demand in upgrading nuclear power plants with PARs. Numerical simulation is an important tool for assessing PAR operation during a severe accident in terms of efficiency and proper installation. Advanced numerical PAR models are required for the challenging boundary conditions during a severe accident, for example, low oxygen amount, high steam amount, and presence of carbon monoxide. The REKO-DIREKT code has been developed in order to provide a PAR model capable of simulating complex PAR phenomena and at the same time being suitable for implementation in thermal-hydraulic codes.The development of REKO-DIREKT was supported by small-scale experiments performed at Forschungszentrum Juelich in the REKO facilities. These facilities allow the study of PAR-related single phenomena such as reaction kinetics under different conditions including variation of steam, oxygen, and carbon monoxide (REKO-3) and the chimney effect (REKO-4). Recently, the code has been validated against full-scale experiments performed in the Thermal-Hydraulics, Hydrogen, Aerosols, Iodine (THAI) facility at Eschborn, Germany, in the framework of the Organisation for Economic Co-operation and Development/Nuclear Energy Agency THAI project. By this, the code has proven its applicability for different PAR designs and for a broad range of boundary conditions (pressure of up to 3 bars, steam amount up to 60 vol %, low-oxygen conditions). REKO-DIREKT has been successfully implemented in the commercial computational fluid dynamics code ANSYS-CFX as well as in the LP code COCOSYS [Gesellschaft für Anlagen- und Reaktorsicherheit (GRS), Germany].

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)0.003
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: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.010
GPT teacher head0.243
Teacher spread0.233 · 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

Citations19
Published2016
Admission routes1
Has abstractyes

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