5 citations · 5 across the 3 of their papers we have counts for
6 papers · 1 filter
Single inertial particle statistics in turbulent flows from Lagrangian velocity models
J. Friedrich, B. Viggiano, M. Bourgoin +2
We present the extension of a modeling technique for Lagrangian tracer particles [B. Viggiano et al., J. Fluid Mech.(2020), vol. 900, A27] which accounts for the effects of particl…
Explicit construction of joint multipoint statistics in complex systems
J. Friedrich, J. Peinke, A. Pumir +1
Complex systems often involve random fluctuations for which self-similar properties in space and time play an important role. Fractional Brownian motions, characterized by a single…
Multi-level stochastic refinement for complex time series and fields: A Data-Driven Approach
M. Sinhuber, J. Friedrich, R. Grauer +1
Spatio-temporally extended nonlinear systems often exhibit a remarkable complexity in space and time. In many cases, extensive datasets of such systems are difficult to obtain, yet…
Probability Density Functions in Homogeneous and Isotropic Magneto-Hydrodynamic Turbulence
J. Friedrich
We derive a hierarchy of evolution equations for multi-point probability density functions in magneto-hydrodynamic (MHD) turbulence. We discuss the relation to the moment hierarchy…
Modelling Lagrangian velocity and acceleration in turbulent flows as infinitely differentiable stochastic processes
Bianca Viggiano, Jan Friedrich, Romain Volk +3
We develop a stochastic model for Lagrangian velocity as it is observed in experimental and numerical fully developed turbulent flows. We define it as the unique statistically stat…
Multiscale velocity correlations in turbulence and Burgers turbulence: Fusion rules, Markov processes in scale, and multifractal predictions
Jan Friedrich, Georgios Margazoglou, Luca Biferale +1
We compare different approaches towards an effective description of multi-scale velocity field correlations in turbulence. Predictions made by the operator product expansion, the s…