The Vortex/Structure Dance: Exploring Coupled Interactions for Energy Harvesting and Speech Modeling Applications

涡旋/结构之舞：探索能量收集和语音建模应用的耦合相互作用

• 批准号: RGPIN-2015-05778
• 负责人: Peterson, Sean
• 金额: $ 2.11万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=638681
• 关键词: Vortex; Structure; Dance; Exploring; Coupled

Vortices abound in nature, appearing in fields ranging from aerodynamics (wing tip vortices) to propulsion of aquatic animals (fish and jellyfish) to vortex shedding in the larynx during human phonation. While vortex dynamics has been studied extensively for decades, examining and exploiting the interaction of vortices with deformable/active structures for flow control, energy harvesting, and bio-inspiration/biomimicry has reinvigorated the field. This proposal focuses on two seemingly disparate but intimately related areas of importance in engineering and medicine: namely, small-scale fluidic energy harvesting using deformable smart-materials for powering micro-electronic devices, including remote sensing networks; and understanding and modeling vocal fold mechanics in human speech with the long term goal (10+ years) of aiding in surgical planning for pathology remediation. The shared core mechanics of these two research tracks is the bi-directional coupling of a vortex-laden fluid flow with a compliant surface; that is, the surface (either the energy harvester or the vocal fold tissue) deforms due to the pressure field in the adjacent fluid flow, which, in turn, alters the fluid boundary condition. As such, this research program envisions establishing a thorough and fundamental understanding of the interaction of vortices with deformable structures via a mix of theoretical analysis, computational modeling, and experimental testing and validation for advancing understanding of energy harvesting and speech modeling. This research program will focus on the development of tools applicable to both research foci, as well as the track-specific implementation of these tools for addressing field-specific research questions. Initial model development will focus on (two-dimensional) vortex dipoles and (three-dimensional) rings (i) passing over a compliant bed and relating the pressure field and frequency of the vortices to the time-variant wall deformation; and (ii) impacting a compliant structure at various angles and exploring the impact mechanics. The governing dimensionless parameters will be varied parametrically and the importance of three-dimensional phenomena, such as edge effects on the structure and vortex stretching during impact and subsequent vortex breakdown, will be explored.  To ensure problem-specific outcomes, the energy harvesting track will focus on development and validation of energy harvesting devices and evaluation of the optimal parameters and performance criteria for maximizing energy extraction, while the speech track will investigate the impact of vortices passing through the vocal tract on the self-sustained oscillations of the vocal folds for both symmetric and asymmetric tissue properties. This project will lead to optimized smart material-based energy harvesting devices and improved speech models incorporating vortex effects.

涡流在自然界中比比皆是，出现在从空气动力学（翼尖涡流）到水生动物（鱼和水母）的推进力，再到人类发声时喉部的涡流脱落等领域。虽然涡流动力学已经被广泛研究了几十年，但研究和利用涡流与可变形/主动结构的相互作用来进行流量控制，能量收集和生物灵感/仿生已经重振了该领域。该提案侧重于工程和医学中两个看似不同但密切相关的重要领域：即，使用可变形智能材料为微电子设备（包括遥感网络）提供动力的小规模流体能量收集;以及理解和建模人类语音中的声带力学，长期目标（10年以上）是帮助病理修复的手术规划。这两个研究轨道的共同核心力学是充满涡流的流体流与柔性表面的双向耦合;也就是说，表面（能量采集器或声带组织）由于相邻流体流中的压力场而变形，这反过来又改变了流体边界条件。因此，该研究计划设想通过理论分析，计算建模以及实验测试和验证的混合，建立对涡流与可变形结构相互作用的全面和基本的理解，以促进对能量收集和语音建模的理解。该研究计划将侧重于开发适用于两个研究重点的工具，以及针对具体领域研究问题的这些工具的跟踪实施。最初的模型开发将集中在（二维）涡流偶极子和（三维）环（一）通过一个顺应床和相关的压力场和频率的涡流随时间变化的壁变形;和（二）在不同的角度冲击一个顺应结构和探索的冲击力学。控制无量纲参数将随参数变化，并将探讨三维现象的重要性，如边缘对结构的影响和碰撞期间的涡流拉伸以及随后的涡流破裂。 为了确保针对具体问题的结果，能量收集轨道将侧重于开发和验证能量收集设备，并评估最佳参数和性能标准，以最大限度地提高能量提取，而语音轨道将研究通过声道的涡流对对称和不对称组织特性的声带自持振荡的影响。该项目将导致优化的智能材料为基础的能量收集设备和改进的语音模型纳入涡流效应。