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Record W2529619910 · doi:10.1115/1.4034852

Investigation of Optimum Refrigerant Charge and Fans' Speed for a Vehicle Air Conditioning System

2016· article· en· W2529619910 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Thermal Science and Engineering Applications · 2016
Typearticle
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsRefrigerantEvaporatorCondenser (optics)Air conditioningCoefficient of performanceAutomotive engineeringWater chillerRange (aeronautics)Computer scienceSimulationEnvironmental scienceMechanical engineeringEngineeringHeat exchangerAerospace engineeringPhysics

Abstract

fetched live from OpenAlex

In this study, the performance evaluation and optimization of a recently developed battery-powered vehicle air conditioning (BPVAC) system is investigated. A mathematical model is developed to simulate the thermodynamic and heat transfer characteristics of the BPVAC system and calculate the coefficient of performance (COP). Utilizing environmental chambers and a number of measuring equipment, an experimental setup is built to validate the model accuracy and to conduct performance optimization by changing the charge of refrigerant in the system. The model is validated and employed for performance simulation and optimization in a wide range of speed for the evaporator and condenser fans. The modeling results verify that for any operating condition an optimum performance can be achieved by adjusting the speed of condenser and evaporator fans. The optimum refrigerant charge is obtained, and a potential improvement of 10.5% is calculated for the performance of system under ANSI/AHRI 210/240-2008 specifications.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.187
Threshold uncertainty score0.177

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 head0.011
GPT teacher head0.210
Teacher spread0.199 · 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