Related Experiment Video
Updated: Aug 15, 2026

Methods for Measuring the Orientation and Rotation Rate of 3D-printed Particles in Turbulence
Published on: June 24, 2016
Stochastic rotation dynamics. II. Transport coefficients, numerics, and long-time tails
1Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota 55455, USA.
Abstract:
A discrete-time projection operation technique was used to derive the Green-Kubo relations for the transport coefficients of a recently introduced stochastic model for fluid dynamics in a previous paper (Part 1). The most important feature of the analysis was the incorporation of a new grid shifting procedure which was shown to guarantee Galilean invariance for arbitrary Mach number and temperature. This paper (Part 2) contains a detailed analysis of the transport coefficients of this model. An exact calculation of the first terms in the stress correlation function in the limit of infinite particle density is presented, which explicitly accounts for the cell structure introduced to define the collision environment. It is also shown that this cell structure can lead to additional contributions to the transport coefficients even at large mean free paths. Explicit expressions for all transport coefficients are derived and compared with simulation results. Long-time tails in the velocity, stress, and heat-flux autocorrelation functions are measured and shown to be in excellent agreement with the predictions of mode-coupling theory.
Related Concept Videos
Reynolds Transport Theorem
Equation of Rotational Dynamics
Navier–Stokes Equations
Poisson's And Laplace's Equation
Kinematic Equations for Rotation
For instance, imagine a point A on a rigid body engaged in circular motion. The translational velocity of this particular point can be calculated by taking the time derivatives of the displacement equation, which essentially measures the...
Conservation of Angular Momentum: Application
