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Record W2329638523 · doi:10.1115/imece2015-52874

Non-Linear Damping Identification in Nuclear Systems Under External Excitation

2015· article· en· W2329638523 on OpenAlexafffund
Joachim Delannoy, Marco Amabili, Brett Matthews, Brian Painter, Kostas Karazis

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHydraulic and Pneumatic Systems
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsVibrationExcitationStructural engineeringDamping ratioCoolantMaterials scienceEngineeringMechanical engineeringAcousticsPhysics

Abstract

fetched live from OpenAlex

In Pressurized Water Reactors (PWR) the fluid-structure interaction between the coolant and fuel assemblies is an important phenomenon that is directly associated to safety and performance issues for the nuclear industry. Fuel assemblies are formed by bundling fuel rods, long slender pressurized tubes containing uranium pellets, with hollow guide and instrumentation tubes using a number of spacer grids for support. In order to correctly simulate the response of a fuel assembly under external excitation, an investigation of the system damping is necessary. Recent study shows that the damping may grow significantly with the vibration amplitude, increasing the safety factor. In order to address this issue, the present study has developed a tool to identify the vibration characteristics of non-linear mechanical systems from experimental forced vibration data obtained at different excitation levels. In particular, this project focuses on the damping identification. A parameter identification methodology for non-linear systems, based on harmonic balance method, is used to identify the damping governing the motion of such systems. The tool has been developed by using hardening non-linear responses of two sandwich panel and a metal plate subjected to external harmonic excitation. The method has been validated by comparison with the damping identified by the full non-linear model of the two sandwich panels. In the three cases, an increase of damping with the vibration amplitude is found and discussed.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.288
Threshold uncertainty score0.701

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.037
GPT teacher head0.255
Teacher spread0.218 · 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 teacher head, 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

Citations5
Published2015
Admission routes2
Has abstractyes

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