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Modeling and Control of a Boiling Water Small Modular Reactor Cogeneration System for District Heating Applications

2025· article· W4416343017 on OpenAlexaff
Muhammad Abuelhamd, Claudio Cañnizares, Daniel Sohm, Elyas Ahmed, Ismael El-Samahy

Bibliographic record

Venuenot available
Typearticle
Language
FieldEngineering
TopicIntegrated Energy Systems Optimization
Canadian institutionsIndependent Electricity System OperatorUniversity of Waterloo
Fundersnot available
KeywordsCogenerationModular designPipingTransient (computer programming)BoilingThermal power stationThermal hydraulicsTroubleshootingSystem dynamicsThermal

Abstract

fetched live from OpenAlex

This poster presents a novel approach for modeling and controlling a Small Modular Reactor (SMR) cogeneration power plant for District Heating Network (DHN) applications, aimed at decarbonizing energy systems. Existing studies, such as [1], do not adequately address key dynamics, including piping heat losses, thermal delays, variations in thermal demand, transient thermal responses, and dynamic interactions within the DHN, which limits the model’s ability to accurately assess system stability and its transient thermo-electrical performance under fluctuating load conditions. Additionally, the absence of proper multi-timescale dynamic analysis restricts the model’s ability to capture both short-term dynamics (seconds to minutes), which are critical for transient stability, and long-term behavior (hours to days), which is necessary for understanding daily thermal load variations. Thus, the main contribution of this paper is the development of a comprehensive cogeneration power plant model based on a Boiling Water SMR (BWSMR), which is distinct from the Integrated Pressurized Water Reactor (IPWR) model in [1].

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.932
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.008
GPT teacher head0.197
Teacher spread0.189 · 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.

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
Published2025
Admission routes1
Has abstractyes

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