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Turbulent flows over a randomly packed, porous substrate are commonly encountered in many aerospace applications, for example, noise reduction and damping on trailing edges of wings, porous ablative heat shields for atmospheric reentry, as well as environmental applications of heat and pollutant transport over stream and riverbeds, vegetation and forest canopies, among others. The inertia-dominated, turbulent flow in the boundary layer is coupled with the diffusion-dominated, Darcy-like flow within the porous medium. The permeability (K) of the medium facilitates interfacial transport that results in enhanced mixing and drag as turbulence can penetrate into the top porous layers. This transport of mass and momentum across the interface is first investigated by performing pore-resolved, direct numerical simulations of flow over a randomly packed porous bed of monodispersed, spherical particles at permeability Reynolds numbers (ReK) of 2.56, 5.17, and 8.94 (Karra et al., JFM 2023). Time-space averaging is used to quantify the Reynolds stress, forminduced stress, mean flow and shear penetration depths, and mixing length at the interface. The probability distribution functions (PDFs) of normalized local bed stress are found to collapse for all Reynolds numbers. Significant contributions to the net drag and lift forces on porous grains come from the top layer, the PDFs of fluctuations in forces due to interfacial turbulence are symmetric with heavy tails, and can be well represented by a non-Gaussian model fit. Next, an upscaled model based on volume-averaged Navier-Stokes (VaNS) equations (Whitaker, 1999) is developed. The porous medium is represented by bed-normal variation in porosity and closures for drag forces are provided by a modified Ergun equation with Forchheimer corrections for inertial terms. The upscaled VaNS model is shown to predict the mean flow, Reynolds stresses, bed shear stress, and the net momentum exchange across the interface fairly accurately as compared to the DNS data. Pressure fluctuation statistics at the interface; however, are under predicted. This is attributed to the local protrusions of the sediment particles present in the pore-resolved study, but absent in the diffuse porosity model. The VaNS approach results in significant reduction in the computational cost compared to the pore-resolved simulations. Further improvements to the model by introducing local, grain-scale porosity variations are being investigated.
About the speaker:
Dr. Apte is professor of Mechanical Engineering at the Oregon State University. He grew up in the city of Pune (India) and received his BS (1994) in Mechanical Engineering from the University of Pune (CoEP), MS (1996) from the Indian Institute of Science, Bangalore (IISC) and the doctorate degree in Mechanical and Nuclear Engineering from Pennsylvania State University (PennState) (2000). Following his Ph.D., Dr. Apte joined the Center for Turbulence Research (CTR) and the Center for Integrated Turbulence Simulations (CITS) at Stanford University as an Engineering Research Associate. He joined Oregon State University in October 2005.
Dr. Apte's research interests are in the areas of computational modeling and analysis of two-phase turbulent flows. His research group develops new algorithms for predictive simulations of two-phase flows using Direct Numerical Simulation (DNS) or Large-eddy Simulation (LES) techniques.
Dr. Apte is currently a member of the American Physical Society (APS-DFD), American Geophysical Union (AGU), and the Institute for Liquid Atomization and Spray Systems (ILASS). He is also a reviewer of several top journals in the thermal fluid sciences, such as Journal of Fluid Mechanics, Journal of Computational Physics, International Journal of Multiphase Flow, Physical Review Fluids, Journal of Fluids Engineering, among others.
Dr. Apte loves distance running, trail running, and cycling. He enjoys hiking and camping with his wife Archana and two kids.