CAREER: Automated physics-based distillation of coherent structures and mechanisms in unsteady and turbulent flows

职业：基于物理的自动蒸馏非定常和湍流中的相干结构和机制

• 批准号: 2238770
• 负责人: Scott Dawson
• 金额: $ 51.63万
• 依托单位: Illinois Institute of Technology
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-12-01 至 2027-11-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2238770&HistoricalAwards=false
• 关键词: CAREER; Automated; physics; based; distillation

Identifying and understanding the fundamental mechanisms that sustain unsteady and turbulent flows is important for ensuring accurate prediction and effective optimization and control across a broad range of applications, such as for reducing drag on aerodynamic vehicles, improving efficiency in wind energy harvesting devices, and improving patient outcomes via cardiovascular flows. While we have a good understanding of such mechanisms for simple flows, new tools will be required to obtain similar levels of understanding for a broader range of applications of real-world relevance. This project will develop methods that enable such mechanisms to be identified in an automated and unambiguous manner, with minimal data and computational requirements. These technical developments will be coupled with educational and outreach initiatives involving the research community, university students in coursework and research, K-12 students, and members of local community groups on Chicago's South Side.The proposed research will develop two central ideas to address the challenge identified above, with an overall goal of developing a methodology to isolate dominant coherent structures and mechanisms in an unambiguous, automated, and computationally efficient manner. The first idea involves applying sparsity-promoting methods to physics-based modeling tools to uncover minimal-physics models without needing the human insight and/or trial-and-error that would otherwise be required. The second idea considers methods to approximate the behavior of these mechanisms using analytic rather than numerical methods, leveraging ideas from wave-packet pseudo-spectral theory. This formulation in turn enables additional analysis methods conducive to studying a broader class of mechanisms, in particular allowing for highly nonlinear behavior to be modeled. To demonstrate their utility, these methods will be applied on a range of fluid flows, including incompressible and compressible parallel shear flows, flows with secondary mean flow components induced by sidewalls, and cardiovascular flows with more complex geometries. An improved ability to identify and manipulate the coherent structures that exist within turbulent flows can benefit a broad range of applications, with the potential to decrease friction drag on air, sea, and ground transport vehicles, increase the efficiency of wind turbines, and enhance understanding and treatment of cardiovascular diseases.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

确定和理解维持不稳定和动荡流的基本机制对于确保在广泛应用中的准确预测和有效优化和控制方面非常重要，例如减少对空气动力学车辆的阻力，提高风能收集设备的效率，以及通过心血管流量提高患者的效率。虽然我们对简单流的这种机制有很好的了解，但需要新工具才能获得相似的理解水平，以了解实际相关性的更广泛的应用。该项目将开发方法，使这些机制能够以最小的数据和计算要求以自动化和明确的方式识别。这些技术发展将加上涉及研究社区，课程和研究的大学生，K-12学生以及芝加哥南部地区的本地社区团体的成员的教育和外展计划。拟议的研究将开发两个核心思想，以应对上述挑战，并在整体上鉴定出一种方法，以开发一种方法论，以隔离统一的相干结构和机制，并能够自动地构成自动化，并自动地，并自动地构成了构成的挑战。第一个想法涉及将刺激性促进方法应用于基于物理的建模工具，以发现最小的物理学模型，而无需人类的洞察力和/或试验和/或试用和/或试验，否则就需要。第二个思想考虑使用分析方法而非数值方法来近似这些机制的行为的方法，从而利用了Wave Packet Pseudo-Spectral理论的思想。该公式反过来促进了有利于研究更广泛的机制的其他分析方法，特别是允许对高度非线性行为进行建模。为了证明它们的效用，这些方法将应用于一系列流体流，包括不可压缩且可压缩的平行剪切流，以及由侧壁诱导的次级平均流量成分以及具有更复杂几何形状的次级平均流量成分和心血管流动。提高了识别和操纵动荡流中存在的相干结构的能力的提高能力可以使广泛的应用受益，并有可能减少对空气，海洋和地面运输车辆的摩擦阻力，提高风力涡轮机的效率，并增强风血管疾病的理解和治疗，这些奖项通过评估NSF的智力及其范围的范围，这反映了NSF的范围和范围的范围。 标准。