Particle laden turbulent flows find applications in many industrial processes such as energy conversion, air pollution control, pneumatic conveying of solids, fluidized bed reactors etc. In these types of flows, there are strong coupling between the turbulent fluctuations in the fluid velocity fields, and the fluctuating velocities of the particles. Owing to this simultaneous analysis of both the phases give insight to the modeling of large scale engineering systems. Due to the complexity of the physics behind dense particulate flows, the current modeling paradigm is to rely on empirical correlations that require fine-tuning with the aid of experimental data. As a consequence, these over-simplified models are not predictive, and this limitation currently represents one of the main hurdles in advanced computational modeling of these reactors. We aim to develop the models based on the physical insight obtained from direct numerical simulations (DNS) and also carry experimental investigations of the moderately dense suspensions using advanced flow visualization methods such as Particle Image Velocimetry (PIV).