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.

涡流在自然界中随处可见，从空气动力学（翼尖涡流）到水生动物（鱼和水母）的推进，再到人类发声过程中喉部的涡流脱落，涡流动力学已被广泛研究了数十年，研究和利用了这种相互作用。具有可变形/主动结构的涡流用于流量控制、能量收集和生物启发/仿生学已经为该领域注入了新的活力。该提案重点关注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声带力学的理解和建模；在人类语言中，长期目标（10年以上）是帮助病理修复的手术计划，这两个研究方向的共同核心机制是充满涡流的流体流与顺应表面的双向耦合；也就是说，表面（能量收集器或声带组织）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，该研究计划设想建立一个彻底且可靠的模型。通过理论分析、计算建模以及实验测试和验证的结合，对涡流与可变形结构的相互作用有基本的了解，以促进对能量收集和语音建模的理解。该研究计划将重点开发适用于这两个研究领域的工具。 ，以及这些工具的特定轨道实施，用于解决特定领域的研究问题，初始模型开发将侧重于（二维）涡旋偶极子和（三维）环（i）穿过顺应床并关联压力场和频率。涡流对随时间变化的壁变形的影响；以及（ii）以不同角度冲击柔顺结构并探索冲击力学，控制无量纲参数将发生参数变化以及三维现象（例如边缘效应）的重要性。将探讨冲击过程中的结构和涡流拉伸以及随后的涡流破裂，​为了确保特定问题的结果，能量收集轨道将重点关注能量收集设备的开发和验证以及最大化最佳参数和性能标准的评估。能量提取，而语音轨道将研究穿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。该项目将优化基于智能材料的能量。收集设备和改进的语音模型结合了涡流效应。