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Record W4415278176 · doi:10.1016/j.rineng.2025.107759

Experimental study of heat and mass transfer in CO2 frost formation on a cryogenic cylinder

2025· article· en· W4415278176 on OpenAlexaff
Michael Adebayo Oyinloye, Sylvain Michaux, Sai Shrinivas Sreedharan, Madiba Burks Magara, William Lafayette Roberts

Bibliographic record

VenueResults in Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicSpacecraft and Cryogenic Technologies
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersKing Abdullah University of Science and Technology
KeywordsGrashof numberFrost (temperature)Reynolds numberHeptadecaneFlue gasFreezing pointThermal conductivityPorosity

Abstract

fetched live from OpenAlex

• An experimental setup has been designed to measure CO 2 frost thickness and mass deposition rates. • Frost porosity increases as both the Reynolds and Grashof numbers increase. • Frost density and thermal conductivity have an inverse dependence on Re and Gr. • An empirical relationship has been proposed to relate frost density to the Re, Gr and time. Cryogenic carbon capture (CCC) is one of the fastest-growing technologies for CO 2 emissions reduction. The fundamental basis of the technology is the ability of CO 2 to desublimate (gas to solid phase change) at temperatures and pressures below its triple point (-56.6°C, 5.1 atm). This allows for selective CO 2 separation from industrial gas streams in processes like natural gas sweetening and flue gas CO 2 stripping. The properties of CO 2 frost accumulated on surfaces in the CCC process are understudied. Most previous studies have focused on water frost, especially on aircraft wings. While correlations derived from water frost provide valuable insights, they are not fully representative of CO₂ frost behavior. This study focuses on the experimental investigation of the impact of Reynolds (Re) and Grashof (Gr) numbers on the properties of CO 2 frosts accumulated on a cylindrical cryogenic surface. A simulated flue gas composed of N 2 and CO 2 with a CO 2 concentration of 17% was used in all experiments. Our analysis reveals the significant influence of Reynolds (Re) and Grashof (Gr) numbers on frost deposition rate, thickness evolution, effective thermal conductivity, and void fraction. Increasing the Re leads to lower CO 2 mass accumulated but higher frost thickness. The findings further show that frost thickness is not representative of the mass of frost accumulated with time, as is usually assumed in 1D-simulation cases. Increasing the Grashof number reduces the frost with time. The findings provide valuable insights into the coupled heat and mass transfer mechanisms governing frost growth during CO₂ desublimation.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.009
GPT teacher head0.225
Teacher spread0.216 · 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".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

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