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使用半范数约束进行流优化的变分框架。

Variational framework for flow optimization using seminorm constraints.

作者信息

Foures D P G, Caulfield C P, Schmid P J

机构信息

DAMTP, University of Cambridge, Centre for Mathematical Sciences, Cambridge, United Kindgom.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2012 Aug;86(2 Pt 2):026306. doi: 10.1103/PhysRevE.86.026306. Epub 2012 Aug 9.

Abstract

We present a general variational framework designed to consider constrained optimization and sensitivity analysis of spatially and temporally evolving flows defined as solutions of partial differential equations. We particularly focus on seminorm constraints which naturally arise for instance when the quantity which we wish to optimize can have contributions from several terms in the PDE through different physical mechanisms in a specific physical system. We show that this case implicitly requires that constraints be placed on the magnitude of complementary (with respect to the first constraining seminorm) seminorms of initial perturbations such that the sum of these complementary seminorms defines a total "true" norm of the state vector. A simple (true) norm constraint naturally satisfies this property. Therefore, the use of this framework requires the introduction of new parameters which describe the relative magnitude of the initial perturbation state vector calculated using the various constrained complementary seminorms to the magnitude calculated using the true norm, even for linear problems. We demonstrate that any required optimization has to be carried out by prescribing these new parameters as initial conditions on the admissible perturbations; the influence and significance of each seminorm component, partitioning the initial total norm of the perturbation, can then be considered quantitatively. To demonstrate the utility of this framework, we consider an idealized problem, the (linear) nonmodal stability analysis of a mean flow given by a "Reynolds averaging" of the one-dimensional stochastically forced Burgers equation. We close the mean flow equation by introducing a turbulent viscosity to model the turbulent mixing, which we allow to evolve subject to a new transport equation. Since we are interested in optimizing the relative amplification of the perturbation kinetic energy (i.e., the perturbation's "gain") this problem naturally requires the use of our new framework, as the kinetic energy is a seminorm of the full state velocity-viscosity vector, with a new adjustable parameter, describing the ratio of an appropriate viscosity seminorm to the sum of this viscosity seminorm and the kinetic energy seminorm. Using this framework, we demonstrate that the dynamics of the full system, allowing the turbulent viscosity to evolve subject to its transport equation, is qualitatively different from the behavior when the turbulent viscosity is "frozen" at a fixed, mean value, since a new mechanism of perturbation energy production appears, through the coupling of the evolving turbulent viscosity perturbation and the mean velocity field.

摘要

我们提出了一个通用的变分框架,旨在考虑将作为偏微分方程解定义的时空演化流的约束优化和灵敏度分析。我们特别关注半范数约束,例如当我们希望优化的量可以通过特定物理系统中的不同物理机制从偏微分方程中的几个项中产生贡献时,这种约束自然会出现。我们表明,这种情况隐含地要求对初始扰动的互补(相对于第一个约束半范数)半范数的大小施加约束,使得这些互补半范数的总和定义了状态向量的总“真实”范数。一个简单的(真实)范数约束自然满足此属性。因此,即使对于线性问题,使用此框架也需要引入新参数,这些参数描述了使用各种约束互补半范数计算的初始扰动状态向量的大小与使用真实范数计算的大小的相对大小。我们证明,任何所需的优化都必须通过将这些新参数规定为可允许扰动的初始条件来进行;然后可以定量地考虑划分扰动初始总范数的每个半范数分量的影响和意义。为了证明此框架的实用性,我们考虑一个理想化问题,即通过对一维随机强迫伯格斯方程进行“雷诺平均”给出的平均流的(线性)非模态稳定性分析。我们通过引入湍流粘性来封闭平均流方程,以模拟湍流混合,并允许其根据一个新的输运方程演化。由于我们对优化扰动动能的相对放大(即扰动的“增益”)感兴趣,这个问题自然需要使用我们的新框架,因为动能是全状态速度 - 粘性向量的半范数,有一个新的可调参数,描述适当粘性半范数与该粘性半范数和动能半范数之和的比率。使用这个框架,我们证明了允许湍流粘性根据其输运方程演化的全系统动力学与湍流粘性“冻结”在固定平均值时的行为在定性上是不同的,因为出现了一种新的扰动能量产生机制,这是通过演化的湍流粘性扰动与平均速度场的耦合产生的。

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