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Record W2164219603

Convective mass transfer between a hydrodynamically developed airflow and liquid water with and without a vapor permeable membrane

2007· article· en· W2164219603 on OpenAlexfundno aff
Conrad R. Iskra

Bibliographic record

VenueUniversity Library - University of Saskatchewan (University of Saskatchewan) · 2007
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAirflowMass transferConvectionMechanicsWater vaporEnvironmental scienceMeteorologyThermodynamicsPhysics
DOInot available

Abstract

fetched live from OpenAlex

The convective mass transfer coefficient is determined for evaporation in a horizontal rectangular duct, which forms the test section of the transient moisture transfer (TMT) facility. In the test facility, a short pan is situated in the lower panel of the duct where a hydrodynamically fully developed laminar or turbulent airflow passes over the surface of the water. The measured convective mass transfer coefficients have uncertainties that are typically less than ±10% and are presented for Reynolds numbers (ReD) between 560 and 8,100, Rayleigh numbers (RaD) between 6,100 and 82,500, inverse Graetz numbers (Gz) between 0.003 and 0.037, and operating conditions factors (H*) between -3.6 and -1.4. The measured convective mass transfer coefficients are found to increase as ReD, RaD, Gz and H* increase and these effects are included in the Sherwood number (ShD) correlations presented in this thesis, which summarize the experimental data. An analogy between heat and mass transfer is developed to determine the convective heat transfer coefficients from the experimentally determined ShD correlations. The convective heat transfer coefficient is found to be a function of ShD and the ratio between heat and moisture transfer potentials (S*) between the surface of the water and the airflow in the experiment. The analogy is used in the development of a new method that converts a pure heat transfer NuD (i.e., heat transfer with no mass transfer) and a pure mass transfer ShD (i.e., mass transfer with no heat transfer) into NuD and ShD that are for simultaneous heat and mass transfer. The method is used to convert a pure heat transfer NuD from the literature into the NuD and ShD numbers measured in this thesis. The results of the new method agree within experimental uncertainty bounds, while the results of the traditional method do not, indicating that the new method is more applicable than the traditional analogy between heat and mass transfer during simultaneous heat and mass transfer.A numerical model is developed that simulates convective heat and mass transfer for a vapor permeable Tyvek® membrane placed between an airflow and liquid water. The boundary conditions imposed on the surfaces of the membrane within the model are typical of the conditions that are present within the TMT facility. The convective heat and mass transfer coefficients measured in this thesis are applied in the model to determine the heat and moisture transfer through the membrane. The numerical results show that the membrane responds very quickly to a step change in temperature and relative humidity of the air stream. Since the transients occur over a short period of time (less than 1 minute), it is feasible to use a steady-state model to determine the heat and mass transfer rates through the material for HVAC applications.The TMT facility is also used to measure the heat and moisture transfer through a vapor permeable Tyvek® membrane. The membrane is in contact with a water surface on its underside and air is passed over its top surface with convective boundary conditions. The experimental data are used to verify the numerically determined moisture transfer rate through the Tyvek® membrane. The numerical model is able to determine the mass transfer rates for a range of testing conditions within ±26% of the experimental data. The differences between the experiment and the model could be due to a slightly different mass transfer coefficient for flow over Tyvek® than for flow over a free water surface.

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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.005
GPT teacher head0.147
Teacher spread0.142 · 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

Citations9
Published2007
Admission routes1
Has abstractno

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