Synthetic Turbulence with Prescribed Probability Density Function and Application to Scalar Quantities Occurring in Reactive Flows

Abstract Based on a (synthetic) turbulent signal which obeys a Gaussian probability density function (PDF) together with some form of prescribed two-point statistics (i.e. integral length or time scales or turbulent energy spectrum), a simple algorithm is proposed to transform the original signal, such that it follows a new target PDF. It is shown that for many practical applications the transformation does not change the integral length or time scale more than a few per cent. The algorithm can be combined with any turbulence generator. It has applications for prescribing boundary or initial conditions of non-Gaussian signals in scale resolving simulations of turbulent flows, such as passive scalars like temperature, bounded passive scalars occurring in reactive flows or velocity signals close to walls.