CAREER: New Mechanisms for Stability, Regularity and Long Time Dynamics of Partial Differential Equations

职业:偏微分方程稳定性、正则性和长期动力学的新机制

基本信息

  • 批准号:
    1945179
  • 负责人:
  • 金额:
    $ 42.5万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2020
  • 资助国家:
    美国
  • 起止时间:
    2020-07-01 至 2025-06-30
  • 项目状态:
    未结题

项目摘要

The project focuses on mathematical analysis of nonlinear partial differential equations that are inspired by fluid dynamics and wave propagation. Understanding the dynamics of incompressible fluids, such as water and air at subsonic speed, is important for a variety of applications, ranging from the design of airplanes, boats and motors, to the study of oceans and the atmosphere. Coherent structures, such as vortices (eddies) and shear flows, are prominent features in fluid dynamics. The formation, stability, and evolution of coherent structures are critical fluid phenomena to understand in order to reduce drag, oscillation, and instability in scientific and engineering applications. The PI will develop new, innovative mathematical methods to analyze the dynamic properties of physically important coherent structures, which can resolve theoretical difficulties as well as provide powerful mathematical tools for practical applications. The PI will also study the interaction of radiation and particles in the context of wave maps, which have a deep connection to the classical field theories from mathematical physics. The proposed projects provide an ideal training ground for junior researchers in applying cutting edge mathematical analysis to study sophisticated physical phenomena in fluid dynamics and wave propagation. Graduate students will be actively involved in these research projects. The PI and collaborators aim to develop new methods that can effectively combine precise spectral and Fourier analysis in the context of nonlinear asymptotic stability problems of fluid dynamics. In many physical problems, the analysis of large coherent structures requires precise spectral analysis for the linearized flow, while Fourier analysis has proved indispensable in uncovering delicate nonlinear interactions. Thus, the techniques developed in the project may have a wider range of applications in other technically challenging perturbative problems. The PI will also study simpler models of fluid equations in an effort to understand the interaction and balance between vorticity stretching and vorticity transportation effects, which play a fundamental role in the regularity theory of three-dimensional Euler equations. For the wave maps equation, the main goal is to extend the "channel of energy" argument for outgoing waves to this technically challenging model to study the decoupling of radiation from solitons in a non-perturbative regime. These projects provide a wide range of problems for graduate students, who will learn to use tools from spectral analysis, Fourier analysis, dynamical systems, and numerical simulation, in the study of physically significant problems.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.
该项目着重于受流体动力学和波传播启发的非线性偏微分方程的数学分析。了解不可压缩流体的动态,例如以亚音速速度的水和空气,对于各种应用非常重要,范围从飞机,船只和电动机的设计到海洋和大气层的研究。相干结构,例如涡旋(涡流)和剪切流,是流体动力学的突出特征。相干结构的形成,稳定性和演变是要理解的关键流体现象,以减少科学和工程应用中的阻力,振荡和不稳定性。 PI将开发新的创新数学方法,以分析物理上重要的一致结构的动态特性,这些结构可以解决理论上的困难,并为实用应用提供强大的数学工具。 PI还将在波图的背景下研究辐射和颗粒的相互作用,这些波浪与数学物理学与经典的现场理论有着深厚的联系。拟议的项目为初级研究人员提供了理想的培训理由,以应用尖端数学分析来研究流体动力学和波传播中的复杂物理现象。研究生将积极参与这些研究项目。 PI和合作者旨在开发新方法,这些方法可以在非线性渐近稳定性问题的情况下有效地结合精确的光谱和傅立叶分析。在许多物理问题中,对大型相干结构的分析需要线性化流量的精确光谱分析,而傅立叶分析在发现精致的非线性相互作用中是必不可少的。因此,项目中开发的技术可能在其他技术挑战性的扰动问题中具有更广泛的应用。 PI还将研究流体方程式的更简单模型,以了解涡度拉伸和涡度传输效应之间的相互作用和平衡,这些效果在三维Euler方程的规则性理论中起着基本作用。对于波图方程,主要目标是将波浪的“能量渠道”论证扩展到该技术挑战性的模型,以研究非扰动制度中孤子的辐射脱钩。这些项目为研究生提供了各种各样的问题,他们将学习从光谱分析,傅立叶分析,动力学系统和数值模拟中学习工具,在研究物理上具有重要意义的问题中。该奖项反映了NSF的法定任务,并被认为值得通过基金会的知识分子和更广泛的影响来通过评估来通过评估来获得支持。

项目成果

期刊论文数量(4)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Nonlinear inviscid damping near monotonic shear flows
  • DOI:
    10.4310/acta.2023.v230.n2.a2
  • 发表时间:
    2020-01
  • 期刊:
  • 影响因子:
    3.7
  • 作者:
    A. Ionescu;H. Jia
  • 通讯作者:
    A. Ionescu;H. Jia
Linear Vortex Symmetrization: The Spectral Density Function
线性涡旋对称化:谱密度函数
Uniform Linear Inviscid Damping and Enhanced Dissipation Near Monotonic Shear Flows in High Reynolds Number Regime (I): The Whole Space Case
高雷诺数状态下的均匀线性无粘阻尼和增强耗散近单调剪切流 (I):整个空间案例
On the Stability of Shear Flows in Bounded Channels, II: Non-monotonic Shear Flows
关于有界通道中剪切流的稳定性,II:非单调剪切流
  • DOI:
    10.1007/s10013-023-00661-z
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0.8
  • 作者:
    Ionescu, Alexandru D.;Iyer, Sameer;Jia, Hao
  • 通讯作者:
    Jia, Hao
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Hao Jia其他文献

Pairwise Regression Weight Contrasts: Models for Allocating Psychological Resources
成对回归权重对比:心理资源分配模型
AIOC: An All-In-One-Card Hardware Design for Financial Market Trading System
AIOC:金融市场交易系统一体化卡硬件设计
Long noncoding RNA MALAT1 sponging miR-26a-5p to modulate Smad1 contributes to colorectal cancer progression by regulating autophagy
长非编码 RNA MALAT1 海绵 miR-26a-5p 调节 Smad1 通过调节自噬促进结直肠癌进展
  • DOI:
    10.1093/carcin/bgab069
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    4.7
  • 作者:
    Jiamin Zhou;Miao Wang;Anrong Mao;Yiming Zhao;Longrong Wang;Ye Xu;Hao Jia;Lu Wang
  • 通讯作者:
    Lu Wang
A Neuromorphic Processing System With Spike-Driven SNN Processor for Wearable ECG Classification
具有尖峰驱动 SNN 处理器的神经形态处理系统,用于可穿戴心电图分类
Nonflammable electrolyte for rechargeable lithium battery with sulfur based composite cathode materials
硫基复合正极材料可充电锂电池不可燃电解液
  • DOI:
    10.1016/j.jpowsour.2012.09.021
  • 发表时间:
    2013-02
  • 期刊:
  • 影响因子:
    9.2
  • 作者:
    Fengjiao Lin;Jiulin Wang;Hao Jia;Charles W. Monroe;Jun Yang;Yanna Nuli
  • 通讯作者:
    Yanna Nuli

Hao Jia的其他文献

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{{ truncateString('Hao Jia', 18)}}的其他基金

Conference: Recent advances in nonlinear Partial Differential Equations
会议:非线性偏微分方程的最新进展
  • 批准号:
    2346780
  • 财政年份:
    2024
  • 资助金额:
    $ 42.5万
  • 项目类别:
    Standard Grant
FRG: Collaborative Research: Singularities in Incompressible Flows: Computer Assisted Proofs and Physics-Informed Neural Networks
FRG:协作研究:不可压缩流中的奇异性:计算机辅助证明和物理信息神经网络
  • 批准号:
    2245021
  • 财政年份:
    2023
  • 资助金额:
    $ 42.5万
  • 项目类别:
    Standard Grant

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介导人肠内分泌细胞分化和功能的机制
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