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Record W4408510533 · doi:10.1063/5.0261217

Lattice Boltzmann modeling of evaporation of porous media considering conjugate heat transfer

2025· article· en· W4408510533 on OpenAlexaff
Wenxi Tian, Linlin Fei, Chenglong Wang, Kailun Guo, Suizheng Qiu, G.H. Su, Dominique Derome, Jan Carmeliet

Bibliographic record

VenuePhysics of Fluids · 2025
Typearticle
Languageen
FieldEngineering
TopicLattice Boltzmann Simulation Studies
Canadian institutionsUniversité de Sherbrooke
FundersETH Zürich FoundationChina Scholarship Council
KeywordsPhysicsLattice Boltzmann methodsPorous mediumHeat transferEvaporationConjugateMechanicsPorosityThermodynamicsStatistical physicsMathematical analysis

Abstract

fetched live from OpenAlex

Evaporation of liquids from porous media plays a significant role in both natural and industrial applications. Evaporation is influenced by various factors, including porous structure, wettability, and thermal gradients, making it difficult to understand the underlying mechanisms and therefore manipulate the evaporation process. In the present study, a hybrid model combing the pseudopotential multiphase lattice Boltzmann method for the fluid field and a finite-difference solver for the energy equation is used to study the evaporation of porous media considering conjugate heat transfer. The flow field and temperature field are coupled via the Peng–Robinson equation of state, while the cascaded lattice Boltzmannn collision operator is employed to enhance the numerical stability. To account for contact angle effects, a validated geometric formulation scheme is applied. The model is utilized to investigate fluid flow and phase distribution in a porous material during evaporation occurring from the top boundary open to the environment and a constant heat flux (q) imposed at the bottom to provide energy input. In the absence of applied heat flux, the evaporation patterns with and without considering conjugate heat transfer are similar, though the latter yields a higher evaporation rate. The underlying mechanism is elucidated by analyzing the temperature field and energy budget. In contrast, thermal input (q ≠ 0) affects the evaporation rate when the heat-affected region reaches the evaporation front. Moreover, high heat input eventually dries out the bottom of the porous media, altering the evaporation dynamics. Regarding contact angle, a smaller contact angle strengthens capillary pumping from large pores to small pores, causing the evaporation front to extend into the small-pore region after the large-pore region is completely dried out. Due to the Kelvin effect, a larger contact angle results in higher vapor pressure near the liquid-vapor interface, promoting evaporation. This study explores the characteristics of the evaporation process in porous media and provides insights into the underlying mechanisms.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
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 head0.029
GPT teacher head0.260
Teacher spread0.232 · 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 designSimulation or modeling
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

Citations10
Published2025
Admission routes1
Has abstractyes

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