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Record W1486113489

DESAIN PROTOTIPE MESIN RECOVERY DAN RECYCLE PORTABLE (JINJING) SEBAGAI PERALATAN PERBAIKAN PADA MESIN PENDINGIN DENGAN REFRIGERAN R22

2015· article· id· W1486113489 on OpenAlexaboutno aff
Billy Andang Baruna, T K Berkah Fajar

Bibliographic record

VenueJurnal Teknik Mesin Undip · 2015
Typearticle
Languageid
FieldEngineering
TopicEngineering and Technology Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsRefrigerantGlobal-warming potentialOzone layerMontreal ProtocolAir conditioningProcess engineeringEnvironmental scienceOzone depletionEngineeringComputer scienceOzoneMechanical engineeringHeat exchangerMeteorologyGreenhouse gasGeographyGeology
DOInot available

Abstract

fetched live from OpenAlex

One of the environmental issues in this century that becomes the world’s concern is global warming and the destruction of the ozone layer. The cause of the damage or depletion of the ozone layer is by the emitted Bahan Perusak Ozon (BPO) from a variety of activities, either in using or producing goods that contain BPO. An example of BPO that is made by human is synthetic substances, the synthetic substances that have a quite high effect in polluting the environment is the refrigerant. Refrigerant R22 is a refrigerant that has Ozone Depletion Potential (ODP) value of 0.06 and Global Warming Potential (GWP) value of 1700. The value of the ODP and GWP is quite high and affects the environmental destruction. Therefore, it is designed a recovery and recycling machine of refrigerant R22. The purpose of this study is to design a recoveryrecycle machine (2R) and calculate and determine the components of the recovery and recycling prototype machine that are easy to be carried and to be used. The design process of 2R machine uses VDI 2221 and VDI 2225 guidelines. Identify the problem, make a list of needs (requirements list), make the working principle, build working structures, make morphology tables, make technical and economic evaluation, as well as make sketches of 2R machine, are the steps of 2R machine design process. 2R machine design is aimed at cooling machine Air-Conditioner vapor compression cycle and the type of refrigerant used is R22. The current existing recoveryrecycle machine is only for refrigerant R12 and R134. Therefore, 2R machine is designed for refrigerant R22 which has much smaller weight and size than 2R existing machine with a weight target of 20 kg and a volume of 0,036 m3. From the calculation result and tools selection, it is generated 2R machine with specifications of 20 kg of weight, length of 40 cm, width of 30 cm, height of 30 cm, hermetic compressor of 0.25 HP (186.5 Watts) 1 piece, condenser of 2050 btu/hr 1 piece, a piece of 1 ½ inch oil separator brand EMERSON, ¼ inch copper pipe, 2 pieces of filter dryer brand EMERSON and 2 pieces of pressure gauge. With the use of recycled R22 that was wasted to the atmosphere and potentially damage the ozone layer, now it can be reused. This supports the world's commitment to reduce and stop the use of bahan perusak ozon (BPO) for both household and industrial needs in the long run

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0290.007

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 head0.025
GPT teacher head0.245
Teacher spread0.220 · 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 designBench or experimental
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
Published2015
Admission routes1
Has abstractyes

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