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Record W4385240939 · doi:10.1038/s44172-023-00096-x

A symmetry analysis methodology for general energy conversion systems

2023· article· en· W4385240939 on OpenAlexaff
Huan Guo, Yujie Xu, Yifu Li, Lujing Huang, Haisheng Chen

Bibliographic record

VenueCommunications Engineering · 2023
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
KeywordsCarnot cycleSymmetry (geometry)Work (physics)Work outputBrayton cycleReflection symmetryConstant (computer programming)Thermodynamic cycleRotational symmetryEnergy (signal processing)Theoretical physicsPhysicsStatistical physicsThermodynamicsMathematicsMechanicsComputer scienceQuantum mechanicsGeometryHeat exchanger

Abstract

fetched live from OpenAlex

Abstract Symmetry is a useful concept that has guided many scientific developments in fields such as structural engineering, data, and materials science. Here we apply a symmetry analysis method to explore the relationship between symmetry, output work and efficiency in macroscopic energy conversion systems. Brayton cycle is used as an example. A specific potential-displacement-energy (PDE) diagram was established for system symmetry analysis. Results prove that the symmetry of thermodynamic cycles could predict the output work and the efficiency. Stronger rotational symmetry generates more work while reflection symmetry leads to higher efficiency at constant specific heat capacity ( c p ). The condition for varied c p to keep intermediate maximum-work temperature constant is greatly broaden. A more symmetrical cycle with higher efficiency and larger output work is designed based on the symmetry analysis results. The results could also be applied to other thermodynamic cycles, such as Carnot cycle, which provides insights to design more efficient energy conversion cycles.

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)0.001
metaresearch head score (Gemma)0.002
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: Methods · Consensus signal: Methods
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.049
GPT teacher head0.317
Teacher spread0.268 · 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
GenreMethods

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

Citations10
Published2023
Admission routes1
Has abstractyes

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