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Record W7043870196

Turbine Trip Event Analysis In A Boiling Water Reactor Using RELAP5/Mod3.4

2023· dissertation· en· W7043870196 on OpenAlexfundno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2023
Typedissertation
Languageen
FieldMaterials Science
TopicX-ray Diffraction in Crystallography
Canadian institutionsnot available
FundersMcMaster University
KeywordsBoiling water reactorTurbineCladding (metalworking)BoilingNuclear power plantSteam turbineNucleate boilingPower station
DOInot available

Abstract

fetched live from OpenAlex

This study explores the behavior of a Boiling Water Reactor (BWR) during a turbine trip scenario initiated by the abrupt closure of the turbine stop valve. The RELAP5/Mod3.4 code is employed to make calculations using the Laguna Verde Nuclear Power Plant input model provided by Innovative Software Systems Company. The event sequences and initial boundary conditions are sourced from the Boiling Water Reactor Turbine Trip 2 Benchmark created by NEA. Results are subsequently compared against the benchmark values. In order to gauge the risk of a turbine trip event leading to elevated power, which could in turn cause Critical Heat Flux (CHF)-related issues in cladding temperature, a best-estimate case is developed. Our findings indicate that the closure of the turbine stop valve (TSV) resulted in a collapse of the void fraction within the reactor core. Although the core power doubled the initial level, the negative feedback mechanism effectively suppressed the power pulse. Throughout the transient phase, the maximum cladding temperature stayed below the CHF threshold, a fact attributable to the fuel's conductivity and the rapid progression of the transient. We further analyzed three hypothetical scenarios to test the computational boundaries of the plant model. The third scenario, which combines conditions from the first two, produced elevated outcomes (6500MW core power, 598K cladding temperature, and 7900kPa dome pressure) as expected. Notably, while the CHF limit remained unbreached in this scenario, literature reviews suggest potential core meltdown risks in subsequent stages of this calculation. Our sensitivity analyses determined that variations in the gamma heating coefficient or the maximum time step of the calculations have little to no impact on core power or peak cladding temperature. Conversely, we noted a significant reduction, approximately 35\%, in the power peak, underscoring the high sensitivity of the parameters to the initial triggering of the SCRAM mechanism. Our results also recommend rapid and early actuation of the BPV as a measure to dampen the pressure wave, consequently decreasing both the power peak and peak cladding temperatures.

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)0.001
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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.020
GPT teacher head0.245
Teacher spread0.226 · 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

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