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Record W2781643526 · doi:10.1177/0306419017749801

Comparison of entropic and exergetic methods of quantification of loss of power due to irreversibilities in real processes using the Gouy–Stodola theorem

2018· article· en· W2781643526 on OpenAlexaff
Rajinder Pal

Bibliographic record

VenueInternational Journal of Mechanical Engineering Education · 2018
Typearticle
Languageen
FieldEngineering
TopicProcess Optimization and Integration
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsExergyThermodynamicsEntropy (arrow of time)Second law of thermodynamicsEntropy productionChemistryStatistical physicsNon-equilibrium thermodynamicsPhysics

Abstract

fetched live from OpenAlex

Thermodynamics offers two methods of quantification of irreversibilities in real processes, namely entropy generation method and exergy destruction method. The engineering students in different disciplines are generally taught only the entropy analysis of processes in their second, advanced level, course in thermodynamics. The exergy analysis of quantification of irreversibilities is rarely covered adequately in the undergraduate courses in thermodynamics, especially when chemical effects are involved where the concept of chemical exergy plays the key role. In this article, the entropy and exergy methods of quantification of irreversibilities are reviewed and are applied to two real processes: steady-state de-mixing of a binary gas mixture into pure components and steady-state combustion of carbon monoxide gas. According to the entropy generation method, the loss of power due to irreversibilities is proportional to the rate of total entropy production (internally and externally). According to the exergy destruction method, the loss of power is equal to the rate of total exergy destruction (internally and externally). Although the calculation procedures involved in the two methods are quite different, the two methods yield the same results in terms of the loss of power due to irreversibilities in the real processes considered in this article. Thus, the detailed calculations carried out in this work confirm that the two methods of quantification of irreversibilities are equivalent. The exergetic method has the advantage that only the knowledge of the exergies of the flowing streams at the inlet and outlet conditions is required in order to calculate the loss of power due to irreversibilities, whereas the entropic method requires a stepwise calculation scheme in going from the inlet conditions to the outlet conditions of the process flow streams. As the material presented in this article involves advanced level concepts in thermodynamics, the appropriate place for the introduction of this material to the engineering students is the second, advanced level, course in thermodynamics.

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)0.004
metaresearch head score (Gemma)0.008
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 score0.005
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.002
Science and technology studies0.0000.002
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.368
Teacher spread0.339 · 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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