Augmentation of Plate-Fin Heat Exchanger Performance with Support of Various Types of Fin Configurations
Bibliographic record
Abstract
A plate fin heat exchanger PFHE is a form of compact heat exchanger CHE containing of a block of alternating layers of fins and flat separators known as parting sheets. In this paper, 3-dimensional incompressible laminar flow and heat transfer in a (PFHE) has been investigated numerically. The influences using different fin configurations and the effect of the offset of these fins, on thermal and hydro-dynamic fields are presented. The cases of study for the PFHE are established, by using the fins with different configurations (plain rectangular (PR) and it's offset (OR), plain triangular (PT) and it's offset (OT) which is a novel shape, and a novel combination of a two fin shapes, between rectangular and triangular (ORT)). The upper and lower plates are exposed to a constant heat flux and the working fluid is air where chosen under a laminar range of (Re) number (600 to 1400). The laminar flow and heat transfer is governed by continuity, momentum and energy equations. ANSYS FLUENT (2021 R1) is used to get the numerical results, based on finite volume method. One of the most utilized fins for a PFHE is the offset fin arrangement due to its higher heat change amount, adjustable structure, and enhances flow turbulence and heat transfer coefficient by interrupting the thermal boundary layer. The obtained results of using of the offset configuration increases the Nusselt number by 20.32% and 17.82% for OSF rectangular and OSF triangular, respectively as compared with the with plain configurations, as a result, a significant heat transfer enhancement is observed. And significant increase in the friction-factor is found to be 79.8% and 48.7% for OT and ORT, as compared with the PT. It can be observed that use of the OSF configuration leads to greater f-factor for triangular configuration values. In addition, the temperature fields for the primary and secondary flows were showed in a contour diagram.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".