Hydrothermal augmentation of flat plates via nature-inspired surface modifications using shark skin-mimetic structures
Bibliographic record
Abstract
Improvements in thermal and aerodynamic systems are fueled by biomimicry. Solar technologies inspired by photosynthesis improve energy capture, and vehicle designs that reduce drag are influenced by shark skin and bird flight. These nature-inspired solutions enhance efficiency, sustainability, and performance in the energy, transportation, and environmental engineering domains. The novelty of this work is numerically examining how rib designs inspired by shark denticles affect the fluid flow and heat transfer performance of a plate by comparing six distinct models (equipped with shark denticles) to a simple flat plate (without ribs). Each model introduces variations in denticle shape, arrangement, and angle. Two fluid flow regimes were examined in each section: laminar ( Re = 400–1,000) and turbulent ( Re = 5,000–20,000). According to the obtained numerical outcomes, the local Nusselt number and C f varied significantly among the models. The present work reported a maximum increase of almost 77.79 % in the average Nusselt number compared to the simple flat plate at Re = 20,000. This increase demonstrates the significant influence of the altered shark denticle geometry. Moreover, at Re = 400 in laminar flow, the friction coefficient reaches its maximum drop, about 36.67 % from the flat plate. This substantial decrease indicates the effectiveness of the angled denticle arrangement in reducing frictional resistance. As a result, geometries inspired by the denticles of sharks significantly improve heat transfer and lower drag. The outcomes demonstrate the potential of bio-inspired designs to enhance heat transfer and aerodynamic efficiency. • Biomimicry leverages nature-inspired designs for enhanced efficiency. • Shark denticle-inspired rib designs improve heat transfer by up to 64.97 %. • Angled denticle geometries reduce friction by up to 36 % in laminar flow. • Six models of denticle shapes and angles tested for diverse flow regimes. • Bio-inspired innovations improve drag reduction and aerodynamic performance.
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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) | 0.001 | 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".