Christian Beck
Recently there has been some progress in modeling the statistical properties of turbulent flows using simple superstatistical models. Here we briefly review the concept of superstatistics in turbulence. In particular, we discuss a superstatistical extension of the Sawford model and compare with experimental data.
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Accurate models of turbulent wind fields have become increasingly important in the atmospheric sciences, e.g., for the determination of spatiotemporal correlations in wind parks, the estimation of individual loads on turbine rotor and blades, or for the modeling of particle-turbulence interaction in atmospheric clouds or pollutant distributions in urban settings. Due to the prohibitive task of resolving the fields across a broad range of scales, one oftentimes has to resort to stochastic wind field models that fulfill specific, empirically observed, properties. Here, we present a new model for…
Superstatistical Approach to Turbulent Circulation Fluctuations
研究湍流环流波动的统计组织，发现环流概率分布函数可通过超统计方法描述，揭示湍流间歇性几何特征，为非扩展统计力学提供新视角。
Inpired by recent measurements of the velocity and acceleration statistics of Lagrangian tracer particles embedded in a turbulent quantum liquid we propose a new superstatistical model for the dynamics of tracer particles in quantum turbulence. Our model consists of random sequences S/N/S/... where the particle spends some time in the superfluid (S) and some time in the normal fluid (N). This model leads to a superposition of power law distributions generated in the superfluid and Gaussian distributions in the normal liquid, in excellent agreement with experimental measurements. We include mem…
An ensemble of Gaussian fields with multifractal statistics for turbulence
本文针对湍流场统计建模的挑战，提出将多重分形增量统计模型推广为高斯场集合的方法，通过设计子集合相关函数与权重实现多重分形统计特性，可生成任意奇异性谱且与DNS结果吻合，架起超统计、多重分形与泛函方法的桥梁。
We give an overview of the progress that has been made in recent years in understanding the dynamic multiscaling of homogeneous, isotropic turbulence and related problems. We emphasise the similarity of this problem with the dynamic scaling of time-dependent correlation functions in the vicinity of a critical point in, e.g., a spin system. The universality of dynamic-multiscaling exponents in fluid turbulence is explored by detailed simulations of the GOY shell model for fluid turbulence.
ONE of the main goals in the development of theory of chaotic dynamical system has been to make progress in understanding of turbulence. The attempts to related turbulence to chaotic motion got strong impetus from the celebrated paper by Ruelle and Takens . Considerable success has been achieved mainly in the area: the onset of turbulence. For fully developed turbulence, many questions remain unanswered. The aim of this letter is to show that there are dynamical systems that are much simpler than the Navier-Stokes equations but that can still have turbulent states and for which many concepts d…
Turbulence is a complex nonlinear and multi-scale phenomenon. Although the fundamental underlying Navier-Stokes equations have been known for two centuries, it remains extremely challenging to extract from them the statistical properties of turbulence. Therefore, for practical purpose, a sustained effort has been devoted to obtaining some effective description of turbulence, that we may call turbulence modelling, or statistical theory of turbulence. In this respect, the Renormalisation Group (RG) appears as a tool of choice, since it is precisely designed to provide effective theories from fun…
Turbulence closure modeling with machine learning approaches: A perspective
本文从视角角度审视机器学习在湍流闭合建模中的应用，识别基础物理挑战并评估ML能力，指出当前进展缓慢的原因，强调ML闭合模型的局限性，并倡导更审慎的使用框架。
The understanding of fluid turbulence has considerably progressed in recent years. The application of the methods of statistical mechanics to the description of the motion of fluid particles, i.e. to the Lagrangian dynamics, has led to a new quantitative theory of intermittency in turbulent transport. The first analytical description of anomalous scaling laws in turbulence has been obtained. The underlying physical mechanism reveals the role of statistical integrals of motion in non-equilibrium systems. For turbulent transport, the statistical conservation laws are hidden in the evolution of g…
Recent progress in the study of Cahn-Hilliard Navier-Stokes (CHNS) turbulence is summarized. This is an example of \textit{elastic turbulence}, which can occur in elastic (i.e. self-restoring) media. Such media exhibit memory due freezing-in laws, as does MHD, which in turn constrains the dynamics. We report new results in the theory of CHNS turbulence in 2D, with special emphasis on the role of structure (i.e. `blob') formation and its interaction with the dual cascade. The evolution of a concentration gradient in response to a single eddy -- analogous to flux expulsion in MHD -- is analyzed.…
The transitional and well-developed regimes of turbulent shear flows exhibit a variety of remarkable scaling laws that are only now beginning to be systematically studied and understood. In the first part of this article, we summarize recent progress in understanding the friction factor of turbulent flows in rough pipes and quasi-two-dimensional soap films, showing how the data obey a two-parameter scaling law known as roughness-induced criticality, and exhibit power-law scaling of friction factor with Reynolds number that depends on the precise form of the nature of the turbulent cascade. The…
The Weak Turbulence Theory has been applied to waves in thin elastic plates obeying the Föppl-Von Kármán dynamical equations. Subsequent experiments have shown a strong discrepancy between the theoretical predictions and the measurements. Both the dynamical equations and the Weak Turbulence Theory treatment require some restrictive hypotheses. Here a direct numerical simulation of the Föppl-Von Kármán equations is performed and reproduces qualitatively and quantitatively the experimental results when the experimentally measured damping rate of waves $γ_\mathbf{k}= a + bk^2$ is used. This confi…
The generation of magnetic field in an electrically conducting fluid generally involves the complicated nonlinear interaction of flow turbulence, rotation and field. This dynamo process is of great importance in geophysics, planetary science and astrophysics, since magnetic fields are known to play a key role in the dynamics of these systems. This paper gives an introduction to dynamo theory for the fluid dynamicist. It proceeds by laying the groundwork, introducing the equations and techniques that are at the heart of dynamo theory, before presenting some simple dynamo solutions. The problems…
Statistical Dynamics and Subgrid Modelling of Turbulence: From Isotropic to Inhomogeneous
本文回顾了湍流统计动力学闭合理论的发展历程，介绍了从各向同性到非均匀场景的多种高效可实现闭合模型，以及适配地球物理流动的亚网格模型，并提及该类理论在多领域的应用拓展。
Quantum Computing for nonlinear differential equations and turbulence
本文针对摩尔定律放缓背景下非线性微分方程与湍流模拟的计算需求，综述了非线性方程量子算法与量子硬件进展，并提出二者配对方案以开辟新模拟途径。
Turbulence is the most common state of astrophysical flows. In typical astrophysical fluids, turbulence is accompanied by strong magnetic fields, which has a large impact on the dynamics of the turbulent cascade. Recently, there has been a significant breakthrough on the theory of magnetohydrodynamic (MHD) turbulence. For the first time we have a scaling model that is supported by both observations and numerical simulations. We review recent progress in studies of both incompressible and compressible turbulence. We compare Iroshnikov-Kraichnan and Goldreich-Sridhar models, and discuss scalings…
AI Meets Turbulence Modeling: Complex Systems Perspective
该研究针对AI/ML在湍流建模中泛化差、成本高的问题，提出由Re和SK/ε参数化的湍流分类图谱，结合Weaver复杂性框架明确ML-RANS、SRS、PINNs的适用场景，建立了AI/ML湍流建模的物理基础部署框架。
A recent thrust in turbulence closure modeling research is to incorporate machine learning (ML) elements, such as neural networks, for the purpose of enhancing the predictive capability to a broader class of flows. Such a turbulence closure framework entails solving a system of equations comprised of ML functionals coupled with traditional (physics-based - PB) elements. While combining closure elements from fundamentally different ideologies can lead to unprecedented progress, there are many critical challenges that must be overcome. This study examines three such challenges: (i) Physical comp…
Anomalous Reynolds stress and dynamic mechanisms in two-dimensional elasto-inertial turbulence of viscoelastic channel flow
本研究系统考察二维弹性惯性湍流的统计特征与动力学机制，发现异常负贡献雷诺应力，并通过象限分析与动力学预算揭示其与三维EIT的异同，证实EIT的二维本质。
Progress in roughness research, mapping any given roughness geometry to its fluid dynamic behaviour, has been hampered by the lack of accurate and direct measurements of skin-friction drag, especially in open systems. The Taylor--Couette (TC) system has the benefit of being a closed system, but its potential for characterizing irregular, realistic, 3-D roughness has not been previously considered in depth. Here, we present direct numerical simulations (DNSs) of TC turbulence with sand grain roughness mounted on the inner cylinder. The model proposed by Scotti (\textit{Phys. Fluids}, vol. 18, 0…
Reynolds stress decay modeling informed by anisotropically forced homogeneous turbulence
本文利用各向异性强迫均匀湍流产生覆盖广泛各向异性状态的数据，据此评估并选择含三次项的雷诺应力衰减模型，验证其优于常用模型。
Recent progress regarding the noncanonical Hamiltonian formulation of extended magnetohydrodynamics (XMHD), a model with Hall drift and electron inertia, is summarized. The advantages of the Hamiltonian approach are invoked to study some general properties of XMHD turbulence, and to compare them against their ideal MHD counterparts. For instance, the helicity flux transfer rates for XMHD are computed, and Liouville's theorem for this model is also verified. The latter is used, in conjunction with the absolute equilibrium states, to arrive at the spectra for the invariants, and to determine the…
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