CFC2023

Data-driven modeling of the turbulence modulation phenomenon with the P-DNS method

  • Gimenez, Juan M (CIMNE)
  • Oñate, Eugenio (CIMNE)
  • Idelsohn, Sergio R (CIMNE)

Please login to view abstract download link

The study of particle-laden flows with the multiscale Pseudo-Direct Numerical Simulation (P-DNS) method requires the design of a representative volume element (RVE) for the isolated modeling of the behavior of the finer scales. A set of numerical RVE experiments for a wide range of volume fractions, particle distribution sizes, and inertial forces introduced as shear loads are carried out. The systematic analysis of the mean statistics of the carrier flow dynamic response allows us to develop a surrogate model that summarizes the behavior of the turbulence modulation phenomenon due to the dispersed phase. The results confirm that the onset and evolution of instabilities in particle-laden flows can differ drastically from those in homogeneous flows. In agreement with previous numerical and experimental references, if mass loading is high enough, large particles can augment the turbulence while small particles can attenuate it. Moreover, the relationship between the dispersed phase volume fraction, the spread of diameters, and shear stresses applied to the system are quantified and reported. Driven by this high-fidelity microscopic flow data through the surrogate model, the P-DNS framework is evaluated in benchmark case studies for particle-laden turbulent flow. Here it was shown that the P-DNS ability for turbulence modulation modeling improves the accuracy of the predictions for measured quantities.