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arXiv 2011.10888physics.flu-dynq-bio.QM
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简单鳗形游动者在参数子空间中的游动

Swimming through parameter subspaces of a simple anguilliform swimmer

Nicholas A. Battista

摘要:

几十年来,计算科学家一直在研究多种不同系统的游泳性能。大多数模型依赖于许多模型参数,并且性能对这些参数敏感。本文定性地确定了一个理想化的简单游泳模型的参数子空间,在该参数子空间中存在增强的游泳性能。一种具有鳗状运动方式的生物体。计算模型采用浸入边界法求解流体相互作用系统。1D游泳者通过动态地改变其优选的身体曲率来向前传播自身。观察表明,游泳运动员的表现似乎更敏感的流体规模和中风的频率,而不是在速度和加速度的变化,无论是作为一个整体的上行或下行。帕累托式的最优前沿也确定了运输成本和游泳速度的数据。虽然这种方法允许一个定位强大的参数子空间所需的性能在一个简单的方式,它是在模拟数量级的模拟比传统的流体-结构相互作用的研究的成本。

英文摘要:

Computational scientists have investigated swimming performance across a multitude of different systems for decades. Most models depend on numerous model parameters and performance is sensitive to those parameters. In this paper, parameter subspaces are qualitatively identified in which there exists enhanced swimming performance for an idealized, simple swimming model that resembles a C. elegans, an organism that exhibits an anguilliform mode of locomotion. The computational model uses the immersed boundary method to solve the fluid-interaction system. The 1D swimmer propagates itself forward by dynamically changing its preferred body curvature. Observations indicate that the swimmer's performance appears more sensitive to fluid scale and stroke frequency, rather than variations in the velocity and acceleration of either its upstroke or downstroke as a whole. Pareto-like optimal fronts were also identified within the data for the cost of transport and swimming speed. While this methodology allows one to locate robust parameter subspaces for desired performance in a straight-forward manner, it comes at the cost of simulating orders of magnitude more simulations than traditional fluid-structure interaction studies.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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