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Record W3209144661 · doi:10.1115/1.4052808

Synergy of a Small Modular Reactor for Addressing Remote Communities Non-Nuclear Waste

2021· article· en· W3209144661 on OpenAlexafffund
Glenn Harvel

Bibliographic record

VenueJournal of Nuclear Engineering and Radiation Science · 2021
Typearticle
Languageen
FieldMaterials Science
TopicGraphite, nuclear technology, radiation studies
Canadian institutionsOntario Tech University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWork (physics)Modular designEnvironmental scienceRange (aeronautics)Radioactive wasteWaste managementEnvironmental economicsComputer scienceEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Abstract Small modular reactors (SMRs) are a popular topic with a significant number of designs with a wide range of sizes. The motivation of this type of work is to find alternative uses for the SMRs so that the thermal energy is more effectively used and hence the SMR is more economical. This work is similar in that it studies the synergy that might exist between a remote community and the SMR. Most work for SMRs is related to remote communities with the impact as one-way, that is the benefit of the SMR to the community yet the SMR is a separate plant. The consideration here is that the SMR could be used to burn the nonnuclear waste products of the community and return useful products. An example is the plastics generated by the community can be converted into usable synthetic fuel, such as kerosene, by using the heat energy of the SMR. The SMR then has a dependency on the community waste stream. In this manner, the environmental load of the community is reduced yet the community also obtains a locally produced fuel that could be used for heating or transport outside of the community. Considering that diesel fuel costs can be extremely high in remote communities, methods to reduce the fuel costs, including the manufacture of their own fuel, can result in a synergistic or symbiotic relationship between the community and the SMR and the community can then have a centralized energy area for supporting neighboring communities.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.857
Threshold uncertainty score0.404

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.023
GPT teacher head0.244
Teacher spread0.221 · 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 designBench or experimental
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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