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Record W3097870141 · doi:10.2118/202853-ms

CO2 – Green Refrigeration for FPSOs

2020· article· en· W3097870141 on OpenAlexaboutno aff
Ben Adamson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsRefrigerantFlammable liquidRefrigerationMontreal ProtocolEnvironmental sciencePropaneGlobal-warming potentialAir conditioningWaste managementSupercritical fluidOzone layerProcess engineeringOzoneGreenhouse gasChemistryEngineeringMechanical engineeringHeat exchanger

Abstract

fetched live from OpenAlex

Abstract FPSOs usually require refrigeration, for removal of condensates and/or water before export of produced gas, or for treatment of gas to be used on board as fuel gas. This paper describes on-board refrigeration using a new combination of different concepts, none of which individually are new, to deliver refrigeration for FPSOs with environmental, cost, space and weight advantages. Usually, FPSO owners specify a non-flammable refrigerant, and most current applications use R-134a refrigerant. However, R-134a is a hydrofluorocarbon with high global warming potential (GWP = 1300). These high-GWP refrigerants are being phased out under the 2016 Kigali amendment to the Montreal protocol, and are already banned for new applications in many European countries. Low-GWP alternatives to R-134a include hydrocarbons such as propane (GWP = 3), ammonia (GWP = 0), hydrofluoroolefines (HFOs) and CO2 (GWP = 1). HFOs are new synthetic refrigerants with GWP generally <150, but are flammable, though less flammable than propane. CO2 was widely used as a refrigerant up to the 1930s, particularly in marine applications, but was superseded by early synthetic refrigerants such as R-12 and R-22, which were then phased out in the 1990s after discovery of ozone depletion effects. CO2 is limited in air-cooled applications at high ambient temperature conditions such as tropical climates, due to the high-pressure side of the system becoming supercritical, leading to high operating pressure and low efficiency. However, FPSOs mainly operate in deep water, and even where surface water temperature is high, say +30 deg.C as in the tropics, cold water below +20 deg.C, can be found at depths of 100-200 m, even at the equator. Use of cold seawater via deep inlet risers is already used for some other FPSO applications, and if used for cooling in CO2 refrigeration systems, the system can operate at subcritical conditions, power becomes competitive and an optimised CO2 refrigeration system can have lower power, smaller footprint and lower weight, compared to a similar optimised R-134a refrigeration system. CO2 is now a viable refrigerant for FPSOs, with environmental, cost, weight and operational advantages over R-134a. Using CO2 as above is a new combination of known concepts, none of which individually are new, to achieve a new and better refrigeration outcome specifically for FPSOs. It is not a proprietary technology of any company.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.024
GPT teacher head0.216
Teacher spread0.191 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2020
Admission routes1
Has abstractyes

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