The motion of flexible fibers through structured fluidic environments is ubiquitous in nature and industrial applications. Most often, their dynamics results from the complex interplay between internal elastic stresses, contact forces and hydrodynamic interactions with the walls and obstacles. By means of numerical simulations, experiments and analytical predictions, we investigate the dynamics of flexible fibers settling in a viscous fluid embedded with obstacles of arbitrary shapes. We identify and characterize two types of events: trapping and gliding, for which we detail the mechanisms at play. We observe nontrivial trapping conformations on sharp obstacles that result from a subtle balance between elasticity, gravity and friction. In the gliding case, a flexible fiber reorients and drifts sideways after sliding along the obstacle. The subsequent lateral displacement is large compared to the fiber length and strongly depends on its mechanical and geometrical properties. We show how these effects can be leveraged to propose a new strategy to sort particles based on their size and/or elasticity. This approach has the major advantage of being simple to implement and fully passive, since no energy is needed.

中文翻译：

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障碍物引起的横向分散和柔性纤维在粘性流体中的非平凡捕获

柔性纤维在结构化流体环境中的运动在自然界和工业应用中无处不在。大多数情况下，它们的动力学是由内部弹性应力、接触力以及与墙壁和障碍物的流体动力相互作用之间复杂的相互作用产生的。通过数值模拟、实验和分析预测，我们研究了柔性纤维在嵌入任意形状障碍物的粘性流体中的动力学。我们识别并描述了两种类型的事件：诱捕和滑翔，我们详细说明了其中的机制。我们观察到尖锐障碍物上的非平凡陷阱构象，这是由弹性、重力和摩擦力之间的微妙平衡引起的。在滑翔情况下，柔性纤维在沿着障碍物滑动后重新定向并侧向漂移。随后的横向位移与纤维长度相比很大，并且很大程度上取决于其机械和几何特性。我们展示了如何利用这些影响来提出一种新的策略，以根据粒子的大小和/或弹性对粒子进行分类。这种方法的主要优点是易于实施和完全被动，因为不需要能量。