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Record W4221068058 · doi:10.1139/tcsme-2021-0205

Numerical investigation of fluid flow and heat characteristics of a roughened solar air heater with novel V-shaped ribs

2022· article· en· W4221068058 on OpenAlexvenueno aff
Usman Allauddin, Waqar A. Khan, Saim E. Ali, Syed Muhammad Mehdi Haider, Abdul S. Ahmed, Abdur Rehman, Patrick G. Verdin

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsNusselt numberTurbulenceComputational fluid dynamicsMechanicsReynolds numberHeat transferMaterials scienceThermalAirflowThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Solar air heaters convert clean solar energy into useable heat and thus have a wide range of applications. Computational fluid dynamics (CFD) can aid in the design and development of solar air heaters with optimized thermal efficiency. A detailed numerical study was conducted to investigate the fluid flow and heat transfer characteristics of a roughened solar air heater with novel V-shaped ribs having staggered elements. Three-dimensional steady-state numerical simulations were performed using the k− ε Re-Normalisation Group (RNG) turbulence model, and results were found to be in excellent agreement with experimental data. The effect of rib spacing was studied through varying the rib pitch to rib height ratio P: e = 6–14, for Reynolds numbers (Re) in the range of 4000–14 000. A significant enhancement in the rib-roughened solar air heater's thermal performance was observed. It was also established that an increment in P: e from 6 to 10 increases the Nusselt number (Nu) for all Re values investigated. About 72.6% Nu enhancement was predicted for P: e = 10 at Re = 12 000. It was further observed that an increment in P: e from 10 to 14 decreases the Nu for all values of Re considered.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.798
Threshold uncertainty score0.666

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 head0.009
GPT teacher head0.171
Teacher spread0.162 · 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 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

Citations3
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicHeat Transfer MechanismsFrench-language works237,207