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Record W4241544284 · doi:10.32920/ryerson.14655279.v1

The Heat Transport System in a Heavy Water Nuclear Reactor

2021· preprint· en· W4241544284 on OpenAlexaffabout
Arber Puci

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsNuclear engineeringNuclear powerNuclear reactorCoolantNuclear power plantEnvironmental scienceNuclear reactor coreNuclear fissionDecay heatWaste managementFissionNuclear physicsEngineeringNeutronPhysics

Abstract

fetched live from OpenAlex

Nuclear power provided 10% of the world's electricity. In Ontario Nuclear provides the base electrical load on the grid. Nuclear power is very unique. It is able to release a tremendous amount of power if it is not controlled properly. There is three objectives that are required to be meet at all times when running a Nuclear power plant. These are called the three C’s. The three C’s are Control, Cool and Contain. The nuclear reaction in a power plant is required to be controlled, at all times. This is completed by maintaining the nuclear fission reaction in the reactor. The Nuclear fission reaction releases radioactivity. This radioactivity needs to be contained in the reactor and not released in the environment, at any cost. The reactor is required to be cooled at all times. This report will provide a basis on controlling the heat on a nuclear reactor. This design of the Instrumentation and Control of the Heat Transport System for a CANDU REACTOR, will be discussed in detail in this report. The Heat transport system is responsible to maintain the coolant mass balance of the nuclear power plant. The main control goal is to stabilize the water level at a reference value and to suppress the effect of various disturbances.

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 score0.377
Threshold uncertainty score0.807

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.166
Teacher spread0.160 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

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