Exploring hierarchical nested riblet technology for reducing turbulent drag

Turbulent drag reduction is a critical challenge in aviation, shipping, pipeline transportation, and new energy vehicles, significantly impacting energy consumption and emissions. Consequently, advancing drag reduction technology for turbulent boundary layers is essential. Over the past thirty years, both industry and academia have focused on developing more eco-friendly and cost-effective methods.

Riblets, flow-aligned micro-groove surfaces that are inspired by shark skin microstructures, can reduce skin-friction drag by up to 9.9%. They offer a lightweight, zero-power, and economically viable solution for reducing drag. Ou et al. introduced a hierarchical nested riblet (HNR) design — a pair of low riblets added between traditional riblets, dividing it into primary and secondary riblets — that markedly enhances drag reduction performance in channel experiments. Numerical simulations of the HNR surface indicate that its drag reduction capabilities surpass those of traditional uniform riblets by approximately 70%.

The impressive performance of HNR surfaces provides insights for optimizing other bionic riblet technologies, with significant implications for aerodynamic drag reduction in high-speed transportation.

“If the riblet can achieve greater drag reduction, this will lead to better energy savings, which is beneficial for reducing the cost of high-speed maritime transportation and water utility systems,” said author Yang He.

Simulations of current riblet technology remain microscopic, rendering the creation of large-scale numerical simulations for aircraft or other transport modes challenging.

“It is impossible to apply numerical simulations to actual or scale aircraft or other means of transportation,” Yang He said. “So far, no relevant numerical modeling methods have been developed to deal with these problems. This is work that needs to be done in the future.”

Source: “Hierarchical nested riblet surface for higher drag reduction in turbulent boundary layer,” by Zhaoyang Ou, Zidan Zhou, Wenyuan Zhou, Daoyuan Wang, Kun Zhang, Zeyu Kong, Yalin Tang, Yang He, and Weizheng Yuan, Physics of Fluids (2024). The article can be accessed at https://doi.org/10.1063/5.0230521 .