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Record W4392596477 · doi:10.1016/j.isci.2024.109460

Derived energy storage systems from Brayton cycle

2024· article· en· W4392596477 on OpenAlexaff
Huan Guo, Yi Zhang, Yujie Xu, Xuezhi Zhou, Haisheng Chen

Bibliographic record

VenueiScience · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Thermodynamics and Statistical Mechanics
Canadian institutionsUniversity of Waterloo
FundersYouth Innovation Promotion AssociationYouth Innovation Promotion Association of the Chinese Academy of SciencesNational Natural Science Foundation of China
KeywordsBrayton cycleThermal energy storageEnergy storageWork (physics)ThermalThermal energyEnergy (signal processing)Computer scienceProcess engineeringTopology (electrical circuits)ThermodynamicsPhysicsEngineeringElectrical engineeringPower (physics)

Abstract

fetched live from OpenAlex

Various energy storage systems (ESS) can be derived from the Brayton cycle, with the most representative being compressed air energy storage and pumped thermal electricity storage systems. Although some important studies on above ESS are reported, the topological structure behind those systems (i.e., derivations of the Brayton cycle) has not been studied, and the underlying thermodynamic ideas still need to be further explored. This paper first introduces the topological structure and the symmetry of ESS and their based Brayton cycles. The formation method of ESS based on paths and separation points is specified. It is found that round-trip path can form ESS directly. Then various ESS formed are compared. Finally, the synergistic effect and gain principle of thermal cycle and ESS are revealed. This work helps to reveal the intrinsic relationship between thermal cycles and ESS, understand the general laws behind ESS, and guide the combination of thermal cycles and ESS.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.007
GPT teacher head0.238
Teacher spread0.232 · 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 designTheoretical or conceptual
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

Citations2
Published2024
Admission routes1
Has abstractyes

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