Venturi D, Karniadakis G E
Division of Applied Mathematics, Providence, RI 02912, USA.
Proc Math Phys Eng Sci. 2014 Jun 8;470(2166):20130754. doi: 10.1098/rspa.2013.0754.
Determining the statistical properties of stochastic nonlinear systems is of major interest across many disciplines. Currently, there are no general efficient methods to deal with this challenging problem that involves high dimensionality, low regularity and random frequencies. We propose a framework for stochastic analysis in nonlinear dynamical systems based on goal-oriented probability density function (PDF) methods. The key idea stems from techniques of irreversible statistical mechanics, and it relies on deriving evolution equations for the PDF of quantities of interest, e.g. functionals of the solution to systems of stochastic ordinary and partial differential equations. Such quantities could be low-dimensional objects in infinite dimensional phase spaces. We develop the goal-oriented PDF method in the context of the time-convolutionless Nakajima-Zwanzig-Mori formalism. We address the question of approximation of reduced-order density equations by multi-level coarse graining, perturbation series and operator cumulant resummation. Numerical examples are presented for stochastic resonance and stochastic advection-reaction problems.
确定随机非线性系统的统计特性在许多学科中都备受关注。目前,尚无通用有效的方法来处理这个具有挑战性的问题,该问题涉及高维性、低正则性和随机频率。我们基于目标导向概率密度函数(PDF)方法,提出了一个用于非线性动力系统随机分析的框架。其关键思想源于不可逆统计力学技术,它依赖于推导感兴趣量的PDF的演化方程,例如随机常微分方程和偏微分方程组解的泛函。这些量可能是无限维相空间中的低维对象。我们在无时域卷积的中岛 - 茨万齐格 - 森形式体系的背景下开发目标导向PDF方法。我们通过多级粗粒化、微扰级数和算子累积量重整化来解决降阶密度方程的近似问题。给出了随机共振和随机平流 - 反应问题的数值示例。