Suspensions of solid particles in viscous fluids are among the simplest complex fluids, yet they exhibit remarkably rich and nonlinear rheological behavior under deformation. Depending on particle interactions and volume fraction, such systems can jam, shear-thicken, or shear-thin. Understanding how suspension properties such as viscosity and normal stress differences evolve under varying flow conditions is crucial for both fundamental science and numerous industrial applications, including food, cosmetics, and pharmaceutical processing. For dense suspensions of rigid particles with excluded-volume interactions, the steady-state viscosity diverges near the shear jamming point, which depends strongly on interparticle friction. While previous simulations have primarily incorporated sliding friction, experimental results suggest that this alone cannot explain the observed jamming behavior. Recent studies indicate that including rolling friction - resistance to the relative rotation of contacting particles - brings simulated jamming fractions into quantitative agreement with experiments. Rolling friction effectively mimics the geometrical constraints found in non-spherical particles and provides a more realistic description of suspension microdynamics. This project aims to systematically investigate the effects of rolling friction on dense suspension rheology using our in-house OpenFOAM-based solver. By incorporating a rolling friction model into the particle-particle interaction framework, we will explore its impact on shear thickening, stress evolution, and microstructural transitions. The simulations are computationally intensive, requiring high spatial and temporal resolution as well as extensive parameter sweeps over friction coefficients and particle concentrations. The requested NAISS computational resources will enable large-scale 2D and 3D simulations to identify the missing physical mechanisms in current theories of shear thickening, providing a predictive understanding of frictional effects in complex suspensions.