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Record W3092190678 · doi:10.4006/0836-1398-33.3.283

Energy saving and climate change mitigation through improved thermodynamic efficiency

2020· article· en· W3092190678 on OpenAlex
Emilio Panarella

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePhysics Essays · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Thermodynamics and Statistical Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsCarnot cycleAllowance (engineering)Work (physics)Thermodynamic cycleLimit (mathematics)Second law of thermodynamicsEfficient energy useThermodynamicsLaws of thermodynamicsPhysicsEconomicsMathematicsEngineeringOperations management

Abstract

fetched live from OpenAlex

The second Law of Thermodynamics is fundamental in the analysis of thermodynamic cycles. It dictates that the conversion of heat to work is limited. It reaches an upper limit in a classical thermodynamic cycle, and such a limit is provided by the Carnot cycle, which is the most efficient. Motivated by a recent allowance of a patent to this author (U.S. Patent 10,079,075), the present study tutorially attempts to expand on the subject and shows that the efficiency can go above the Carnot efficiency, provided a novel cycle is used, and heat, rather than being discarded, is recirculated in the same engine used to generate work. The significant energy saving consequential to this finding and climate change mitigation are reported.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.977
Threshold uncertainty score0.733

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.016
GPT teacher head0.244
Teacher spread0.228 · 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