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Effect of Reynolds number variation on thermal performance and flow characteristics of heart pin fins in trailing edge

  • Venkatesh Goveraiahgari ORCID logo EMAIL logo , Prakash Babu Kanakavalli ORCID logo , Rajendra Shimpi , Meenakshi Reddy Reddygari and Deenadayalan Ganapathi
Published/Copyright: December 17, 2025
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Abstract

Gas turbine blades must be effectively cooled in order to maintain durability and operational efficiency in high-temperature environments. A dependable technique for improving heat transfer in turbine cooling channels is pin-fin cooling. Using both experimental and computational analysis, this work examines the thermal and flow properties of circular and heart-shaped pin fins in a wedge channel. Numerical simulations were carried out to compare the performance of three staggered rows of heart-shaped and circular pin fins, each with a diameter of 12 mm, across a Reynolds number range of 10,000–80,000. This study uses both computational fluid dynamics (CFD) analysis and experimental methods to examine the thermal-hydraulic performance of circular and heart-shaped pin fins. With a 15–25 % higher Nusselt number than the circular pin fins throughout a range of Reynolds numbers, the results show that the heart-shaped pin fins improves heat transfer performance. Moreover, the heart-shaped pin fins offers improved flow performance, resulting in a 5–10 % reduction in pressure drop relative to the circular pin fins. Heat transfer is further enhanced with the addition of fins. The heart-shaped pin fins exhibit a 10–20 % higher heat transfer coefficient compared to the circular pin fins. Additionally, the heart-shaped pin fins attains a 20–30 % enhancement in the thermal performance factor (TPF) relative to the circular pin fins.


Corresponding author: Venkatesh Goveraiahgari, Department of Mechanical Engineering, G Pulla Reddy Engineering College, Affiliated to Jawaharlal Nehru Technological University Anantapur, Ananthapuramu, Kurnool, A.P., 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: 2025-11-13
Accepted: 2025-12-03
Published Online: 2025-12-17

© 2025 Walter de Gruyter GmbH, Berlin/Boston

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