The fluctuating fluid velocities seen by particles entrained in a turbulent fluid have recently been modeled using a stochastic model based normalized Langevin Continuous Random Walk (CRW). This model has been quite successful in predicting particle dispersion in mildly complex flows. In the present study, we aim at validating the CRW model further against data collected in a challenging 3D geometry. We consider turbulent fluid mixing downstream of a T-junction using a hybrid Euler-Lagrange approach whereby tracer particle trajectories are computed and mixing of the streams deduced from the relative concentration of particles originating from the two inlet branches of the Tee. In a first simulation, RANS Reynolds Stress Model (RSM) is used to obtain the mean flow field, whereas the fluid fluctuations are specified from a CRW. Simulation results are compared to experimental data on mixing of two isothermal streams consisting of tap and de-ionized water, respectively. It is found that RSM-CRW yields strong under-prediction of the mixing. Closer look at the results shows that the Reynolds stresses, which are required inputs to the CRW, are poorly predicted with RSM. Detached Eddy Simulations (DES) are subsequently performed to provide the mean flow field, and the DES-CRW model predictions are found to compare quite well with the experimental data. (C) 2010 Elsevier B.V. All rights reserved.