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Record W2235245904

Study of the Breathing Effect of Reciprocating Compressor Under Duty Cycle Regulation (DCR) Capacity Control by Simulation and Experiment

2015· article· en· W2235245904 on OpenAlexvenueno aff
Zhengwei Nie, Qi Pan, Xiongpo Hou

Bibliographic record

VenueAdvances in natural science/Advances in natural sciences · 2015
Typearticle
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsReciprocating compressorSuctionGas compressorMechanicsFluentThermal expansion valveWork (physics)Reciprocating motionFlow (mathematics)Computational fluid dynamicsControl theory (sociology)EngineeringMechanical engineeringMaterials sciencePhysicsComputer scienceControl (management)
DOInot available

Abstract

fetched live from OpenAlex

Duty Cycle Regulation is a new method for capacity control of reciprocating compressor. Like other suction-valve-unloaded methods, the DCR method would inevitably cause the Breathing Effect. In this article, the internal flow and heat transfer in the compressor under DCR control are analyzed using CFD simulation. The geometrical model of the breathing effect has already been worked out. The numerical analysis and experimental research have been fulfilled. The flow conditions of the breathing effect during the DCR process, the temperature field in suction chamber and cylinder after some breathing effect cycles, and the capacity regulation results using DCR method are obtained. FLUENT is used to compute temperature variation after some periods of regulation. It is found that after 20 periods of regulation the suction temperature is about 32K higher than the one in normal process of compressor. Through the numerical analysis and experiment, it could be concluded that the temperature rise resulted from the breathing effect affects the suction and discharge temperature, capacity and energy consumption. Based on the results of this work, the performance of reciprocating compressor could be improved by eliminating the influence of breathing effect.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.003
Open science0.0010.000
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 head0.012
GPT teacher head0.309
Teacher spread0.297 · 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 designSimulation or modeling
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
Published2015
Admission routes1
Has abstractyes

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