Pan Yu, Lauder George V
Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA.
Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138, USA.
Integr Comp Biol. 2024 Sep 27;64(3):753-768. doi: 10.1093/icb/icae044.
Understanding the flow physics behind fish schooling poses significant challenges due to the difficulties in directly measuring hydrodynamic performance and the three-dimensional, chaotic, and complex flow structures generated by collective moving organisms. Numerous previous simulations and experiments have utilized computational, mechanical, or robotic models to represent live fish. And existing studies of live fish schools have contributed significantly to dissecting the complexities of fish schooling. But the scarcity of combined approaches that include both computational and experimental studies, ideally of the same fish schools, has limited our ability to understand the physical factors that are involved in fish collective behavior. This underscores the necessity of developing new approaches to working directly with live fish schools. An integrated method that combines experiments on live fish schools with computational fluid dynamics (CFD) simulations represents an innovative method of studying the hydrodynamics of fish schooling. CFD techniques can deliver accurate performance measurements and high-fidelity flow characteristics for comprehensive analysis. Concurrently, experimental approaches can capture the precise locomotor kinematics of fish and offer additional flow information through particle image velocimetry (PIV) measurements, potentially enhancing the accuracy and efficiency of CFD studies via advanced data assimilation techniques. The flow patterns observed in PIV experiments with fish schools and the complex hydrodynamic interactions revealed by integrated analyses highlight the complexity of fish schooling, prompting a reevaluation of the classic Weihs model of school dynamics. The synergy between CFD models and experimental data grants us comprehensive insights into the flow dynamics of fish schools, facilitating the evaluation of their functional significance and enabling comparative studies of schooling behavior. In addition, we consider the challenges in developing integrated analytical methods and suggest promising directions for future research.
由于直接测量水动力性能存在困难,以及集体移动生物所产生的三维、混沌且复杂的流动结构,理解鱼群游动背后的流动物理学面临重大挑战。此前众多模拟和实验利用计算、机械或机器人模型来代表活鱼。现有的关于活鱼群的研究在剖析鱼群游动的复杂性方面做出了重大贡献。但是,将计算研究与实验研究(理想情况下针对同一鱼群)相结合的方法较为匮乏,这限制了我们理解鱼群集体行为所涉及物理因素的能力。这凸显了开发直接针对活鱼群的新方法的必要性。一种将对活鱼群的实验与计算流体动力学(CFD)模拟相结合的综合方法,代表了一种研究鱼群游动力学的创新方法。CFD技术能够提供准确的性能测量结果和高保真的流动特性,以进行全面分析。同时,实验方法可以捕捉鱼精确的运动学信息,并通过粒子图像测速(PIV)测量提供额外的流动信息,有可能通过先进的数据同化技术提高CFD研究的准确性和效率。在对鱼群进行的PIV实验中观察到的流动模式以及综合分析所揭示的复杂水动力相互作用,凸显了鱼群游动的复杂性,促使人们重新评估经典的魏斯鱼群动力学模型。CFD模型与实验数据之间的协同作用,使我们能够全面洞察鱼群的流动动力学,有助于评估其功能意义,并能够对鱼群游动行为进行比较研究。此外,我们还考虑了开发综合分析方法时面临的挑战,并提出了未来研究的有前景的方向。