Speaker
Description
We develop and analyze a random field model for the reconstruction of inhomogeneous turbulence from characteristic flow quantities provided by k-epsilon simulations. The model is based on stochastic integrals that combine moving average and Fourier-type representations in time and space, respectively, where both the time integration kernel and the spatial energy spectrum depend on the macroscopically varying characteristic quantities. The structure of the model is derived from standard spectral representations of homogeneous fields by means of a two-scale approach in combination with specific stochastic integral transformations. Our approach allows for a rigorous analytical verification of the desired statistical properties and is accessible to numerical simulation.
