Numerical Investigation of the Effect of Dimpled Surface on Convective Heat Transfer and Friction Factor in a Rectangular Channel


ASLAN E., Kahveci E. E., Kucur M., Korbahti B.

HEAT TRANSFER ENGINEERING, 2025 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1080/01457632.2025.2480905
  • Dergi Adı: HEAT TRANSFER ENGINEERING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Chemical Abstracts Core, Communication Abstracts, Compendex, INSPEC, Metadex, DIALNET, Civil Engineering Abstracts
  • Kocaeli Üniversitesi Adresli: Evet

Özet

Numerical simulations investigated the convective heat transfer and friction factor characteristics over the surface with an array of shallow dimples in a rectangular channel. Circular and oval dimples are used in a staggered arrangement. The finite volume method is used for numerical simulations. Three different dimple depth to diameter ratios (0.067, 0.1, and 0.2), two different longitudinal distances (21.6 mm and 24 mm), and three different oval dimple angles (30 degrees, 45 degrees, and 60 degrees) are considered. The Reynolds number ranged from 10000 to 60000. Validation is performed using experimental results at Reynolds number 50500 for circular dimples with depth to diameter ratios of 0.067, 0.1, and 0.2. Numerical results include friction factor, friction factor ratio, total Nusselt number, Nusselt number ratio, and performance dependent on Reynolds number. Depth to diameter ratio positively affects all parameters except performance, while oval dimple angles have minimal impact. Longitudinal distance negatively affects all parameters except performance, while the Reynolds number strongly influences all parameters. The total Nusselt number increases while the Nusselt number ratio remains nearly constant with increasing Reynolds number. Generally, the friction factor decreases, and the friction factor ratio increases with increasing Reynolds number. Correlations of friction factor ratio and Nusselt number ratio are suggested with deep neural network algorithm.