This contribution presents the Pseudo-Direct Numerical Simulation (P-DNS) methodology, a multiscale computational framework for turbulent-flow simulation in which the solution fields are decomposed into coarse and fine-scale contributions. By applying a computational homogenization procedure to the fine-scale dynamics, a closed set of governing equations is obtained for the coarse scale, where additional inertial stress terms account for the averaged influence of the unresolved turbulent fluctuations. The fine-scale contribution is obtained offline by Direct Numerical Simulations of Representative Volume Elements (RVEs) subject to parameterized local flow conditions. These simulations provide equilibrium inertial stresses, which are stored in compact databases and reused during the global simulation. Since the RVEs are defined in a dimensionless and canonical manner, the resulting databases are computed only once and can be applied to different global configurations, as long as the local coarse-scale conditions fall within the parameter space of the fine-scale data. Non-equilibrium effects are incorporated through a memory-based evolution of the inertial stresses, governed by a relaxation time calibrated from dedicated non-equilibrium RVE simulations. Distinct bulk and wall RVEs are employed to represent turbulence in free-shear regions and in the vicinity of solid boundaries. The wall RVE embeds the dynamics of turbulent boundary layers, enabling the use of coarser, wall-modeled–type grids near solid surfaces, while the bulk RVE informs grid requirements in the flow interior. This unified treatment allows P-DNS to operate on grids that are substantially coarser than those required by wall-resolved simulations. The methodology is illustrated through applications to incompressible and weakly compressible turbulent flows, including classical and benchmark configurations such as turbulent boundary layers, free-shear flows, bluff-body aerodynamics (e.g. Ahmed body), external aerodynamics of airfoils, wings and wind turbines, as well as full vehicle-scale configurations (DrivAer). Results are compared against experimental data, reference numerical solutions, and established benchmark databases, demonstrating the potential of P-DNS as a physics-based, scale-bridging approach for high-fidelity turbulence simulation.