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Record W3021140832 · doi:10.1016/j.heliyon.2020.e03823

Free convection of a suspension containing nano-encapsulated phase change material in a porous cavity; local thermal non-equilibrium model

2020· article· en· W3021140832 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHeliyon · 2020
Typearticle
Languageen
FieldEngineering
TopicPhase Change Materials Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSuspension (topology)Phase changePorous mediumMaterials scienceNano-ThermalPhase-change materialPorosityNatural convectionMechanicsThermodynamicsConvectionChemical engineeringComposite materialPhysicsEngineering

Abstract

fetched live from OpenAlex

Due to the instinctive temperature-dependent heat capacity of the Nano-Encapsulated Phase Change Material (NEPCM), there is a growing interest in the potential applications of such materials in heat transfer. As such, steady-state natural convection in a porous enclosure saturated with nanofluid using NEPCMs has been investigated in this study. The cavity is assumed to have constant hot and cold temperatures at the left and right vertical boundaries, respectively, and fully insulated from the bottom and top walls. Considering the Local Thermal Non-equilibrium (LTNE) approach for the porous structure, the governing equations are first non-dimensionalized and then solved by employing the finite element Galerkin method. The impact of different parameters, such as porous thermal conductivity ( k s ), solid-fluid interface heat transfer (10 ≤ H ≤ 10 5 ), Stefan number (0.2 ≤ Ste ≤ 1), and volume fraction of nanoparticles (0.0 ≤ φ ≤ 0.05) on the patterns of the fluid and solid isotherms, streamlines and the contours of the heat capacity ratio, fusion temperature (0.05 ≤ θ f ≤ 1), local and average Nusselt numbers, and overall heat transfer ratio has been studied. It is shown that improving the porous thermal conductivity not only leads to an increase in the rate of heat transfer but also augments the fluid flow inside the cavity. For low values of the Ste , the rate of heat, transferred in the porous enclosure, is intensified. However, regardless of the amount of the Stefan number, the maximum rate of heat transfer is achievable when the non-dimensional fusion temperature is approximately 0.5. Employing NEPCMs in a highly conductive porous structure is more efficacious only when the phases are in the state of local thermal equilibrium. Nonetheless, the rate of heat transfer is higher when the Local thermal non-equilibrium is validated between the phases. Besides, for poor thermal conductivity of the porous medium like glass balls (LTE condition), adding 5% of the nano-encapsulated phase change materials to pure water can boost the rate of heat transfer up to 47% (for Ste = 0.2 and θ f = 0.5). This thermal investigation of NEPCMs shows in detail how advantageous are these nanoparticles in heat transfer and opens up an avenue for further application-based studies.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.403
Threshold uncertainty score0.895

Codex and Gemma teacher scores by category

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

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 head0.058
GPT teacher head0.285
Teacher spread0.227 · 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