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Record W3003713677 · doi:10.15392/bjrs.v9i1a.1499

A diffractometer project for Brazilian Multipurpose Reactor (RMB): McStas simulations and instrument optimization

2021· article· en· W3003713677 on OpenAlexfundno aff
Alexandre Pinho dos Santos Souza, Luiz P. de Oliveira, Fabiano Yokaichiya, Frederico A. Genezini, Margareth Kazuyo Kobayashi Dias Franco

Bibliographic record

VenueBrazilian Journal of Radiation Sciences · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear Physics and Applications
Canadian institutionsnot available
FundersIndigenous and Northern Affairs CanadaConselho Nacional de Desenvolvimento Científico e TecnológicoFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsDiffractometerNeutron fluxNeutronResearch reactorSample (material)Monte Carlo methodFlux (metallurgy)Position (finance)Nuclear engineeringNeutron scatteringNuclear physicsPhysicsOpticsComputer scienceMaterials scienceMathematicsEngineeringStatistics

Abstract

fetched live from OpenAlex

High-resolution diffractometer is one of the first instruments of the set of 15 priority neutron scattering instruments to be installed at the Brazilian Multipurpose Reactor (RMB). A basic project of this instrument consists of the existence of three guides through which neutrons pass from source to sample to guarantee maximum neutron flux at the sample position. In this study, we investigate guide geometry performance considering fixed diffractometer geometry and spatial arrangement. Comparisons between different guide shapes and supermirrors are performed using software based on the Monte Carlo method, McStas. Our conclusion shows that a better solution is splitting the initial flux into two different guides to obtain the maximum flux at the sample position.

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)0.002
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: Methods · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.026
GPT teacher head0.312
Teacher spread0.287 · 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
GenreMethods

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

Citations1
Published2021
Admission routes1
Has abstractyes

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Same venueBrazilian Journal of Radiation SciencesSame topicNuclear Physics and ApplicationsFrench-language works237,207