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Record W4388410355 · doi:10.2991/978-94-6463-258-3_18

Thermal Design of Small Modular Reactors in Northern Regions

2023· book-chapter· en· W4388410355 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAtlantis highlights in engineering/Atlantis Highlights in Engineering · 2023
Typebook-chapter
Languageen
FieldEngineering
TopicNuclear reactor physics and engineering
Canadian institutionsPolytechnique Montréal
FundersFonds de recherche du Québec – Nature et technologiesPolytechnique Montréal
KeywordsModular designThermalNuclear engineeringEnvironmental scienceGeographyEngineeringComputer scienceMeteorologyOperating system

Abstract

fetched live from OpenAlex

Small Modular Reactors (SMRs) are increasingly recognized as safer and more flexible alternatives to conventional nuclear power plants in today's industry.Their safety and flexibility, coupled with their lower time and capital investment requirements, make SMRs an ideal choice for clean energy in Canada's remote communities.These communities are currently heavily dependent on fossil fuels, and transitioning to clean energy sources like SMRs will be essential for Canada to achieve its net-zero emissions target by 2050.However, the application of SMR technology in permafrost regions affected by climate change raises concerns.Permafrost degradation can cause serious deformations and settlements, which can result in elevated maintenance costs and reduced durability of SMR infrastructure.With a warming climate, the traditional civil engineering approach of assuming climate stationarity is unreliable for ensuring safe and durable infrastructure.Therefore, a non-stationary climatic approach must be considered.This article presents a heat transfer model for permafrost foundations and investigates the combined effects of heat loss via SMRs and global warming on permafrost degradation.By examining the interaction between SMRs and permafrost degradation, the article sheds light on the potential risks and challenges associated with the use of SMRs in permafrost regions.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesMeta-epidemiology (narrow)
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 score0.423
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0040.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.016
GPT teacher head0.182
Teacher spread0.166 · 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