Yifei Zhong
Papers
1
Total Citations
6
H-Index
1
About
Yifei Zhong is a rising researcher in computational fluid dynamics and bio-inspired hydrodynamics, with a focus on understanding the collective motion of aquatic organisms. Their key research areas include fish schooling dynamics, immersed boundary methods, and lattice Boltzmann simulations. Zhong’s most notable contribution is the development of a non-iterative, immersed boundary-lattice Boltzmann method (IB-LBM) to investigate how different motion parameters affect the hydrodynamic interactions within fish school subsystems. Their 2023 study, which has already garnered 6 citations, provides critical insights into the complex, often counterintuitive, energy-saving mechanisms and flow patterns that emerge when fish swim in coordinated groups. This work bridges the gap between theoretical biology and practical engineering, offering a foundation for designing more efficient underwater vehicles and robotic swarms. By numerically simulating two-dimensional fish-like bodies, Zhong has demonstrated how subtle changes in phase and spacing can dramatically alter the collective hydrodynamics—a finding that has implications for both biological understanding and biomimetic design. Their innovative approach to solving fluid-structure interaction problems marks them as a promising voice in the field of computational biomechanics.
Research Focus
Key Achievements
Top Papers
- 1