MétaCan
Menu
Back to cohort
Record W4293115946 · doi:10.11159/htff22.141

A Heat Transfer Analysis of Axial and Radial Functionally Graded Ceramic Foams Solar Air Receivers

2022· article· en· W4293115946 on OpenAlexvenueno aff
Assunta Andreozzi, Marcello Iasiello

Bibliographic record

VenueProceedings of the World Congress on Mechanical, Chemical, and Material Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicRadiative Heat Transfer Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceHeat transferCeramicComposite materialMechanicsPhysics

Abstract

fetched live from OpenAlex

Volumetric solar receiver are promising as heat transfer devices in concentrated solar power applications because they allow to reduce heat losses at the receiver entrance when compared to more conventional tubular receivers.Among various porous materials, ceramic foams have been shown to be promising because of their extended heat transfer area and effective thermal conductivity, especially when they are manufactured by considering variable morphologies thanks to modern techniques like additive manufacturing.In this contribution, porous media numerical simulations are presented for fluid flow and heat transfer in ceramic foams receiver with different porosity functions on either axial or radial directions, and also when porosity varies on both directions.Such simulations are performed by employing Beer-Lambert law to model radiative heat transfer, and a Gaussian distribution for the incoming radiation.Results are obtained by constraining the average porosity for the different cases, showing that graded foams allow to obtain more or less similar outflow temperatures, but with reduced heat losses at the receiver entrance and also with less uniform velocity profiles to promote heat convection in some critical points of the receiver.

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 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 score0.008
Threshold uncertainty score0.929

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.006
GPT teacher head0.180
Teacher spread0.174 · 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 teacher head, 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the World Congress on Mechanical, Chemical, and Material EngineeringSame topicRadiative Heat Transfer StudiesFrench-language works237,207