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Computational study on heat transfer augmentation with pencil pin fins and ribbed surfaces in wedge channels

  • Venkatesh Goveraiahgari ORCID logo EMAIL logo , Prakash Babu Kanakavalli ORCID logo , Meenakshi Reddy Reddygari , Mallikarjuna Rao Pabbisetty and Satish Kumar Vutukur
Published/Copyright: October 31, 2025
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Abstract

Efficient turbine blade cooling is crucial. Conventional ribs improve heat transfer but cause pressure losses. This study introduces pencil-shaped pin fins with U- and zigzag-shaped ribs in wedge channels for improved cooling. A numerical study was performed across a Reynolds number range of 10,000–80,000 to assess the influence of U- and zigzag-shaped ribs with pencil pin fins on heat transfer, flow behavior, and pressure drop in a wedge-shaped channel. Zigzag ribs enhanced the Nusselt number by 14–21 %, while U-shaped ribs showed 12–18 % improvement over pencil pin fins, due to boundary layer disruption and secondary vortex formation. Zigzag ribs generated stronger turbulence and more complex flow, resulting in superior heat transfer. However, rib inclusion increased pressure losses. U-shaped ribs caused the highest pressure drop (35–63 %), whereas zigzag ribs showed a moderate increase (22–47 %) due to smoother flow redirection. Pencil pin fins maintained minimal flow resistance. Thermal Performance Factor (TPF) analysis revealed that zigzag ribs offered the best balance between heat transfer and pressure drop, with a 3.6–6.6 % improvement, while U-shaped ribs showed only 1.5–1.8 %. Overall, zigzag-shaped ribs provided the most efficient thermal-hydraulic performance.


Corresponding author: Venkatesh Goveraiahgari, Department of Mechanical Engineering, G Pulla Reddy Engineering College, Affliated to Jawaharlal Nehru Technological University Anantapur, Ananthapuramu, AP, India, E-mail:

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: The author has accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The author states no conflict of interest.

  6. Research funding: Not applicable.

  7. Data availability: Not applicable.

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Received: 2025-09-17
Accepted: 2025-10-14
Published Online: 2025-10-31

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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