arXiv subjects

Andrey V. Kuznetsov

Publications and source records attributed to Andrey V. Kuznetsov.

12 recordsLinked to original sources

arXiv2026

Macroscale vortex impingement at a porous-fluid interface induces local heat-transfer enhancement

Externally generated wakes can impinge on porous layers in several practical heat transfer applications. However, the transport of these macroscale vortices and their resulting influence on heat transfer in the porous layer remain unknown. In this paper, two-dimensional pore-resolved simulations are used to examine a square-bluff-body wake impinging on a porous layer composed of an in-line array of heated square obstacles at Re = 500-4000, Pr = 0.7 and 7.0, and porosities $ϕ$ = 0.75, 0.85, and 0.95. The incident macroscale vortices break down starting immediately at the porous-fluid interface. Following macroscale turbulent thermal transport in this entrance region, fluctuations farther downstream are aligned with the pore geometry and are generated at the microscale level by pore-throat shear, separation, and repeated obstacle wakes. Direct impact locally improves heat transfer at the porous-fluid interface by increasing the local Nusselt number relative to a non-impingement region. The interfacial heat-transfer enhancement varies with porosity, Reynolds number, and Prandtl number, with a peak enhancement of 18.2% observed for $ϕ$ = 0.85, Pr = 7.0, and Re = 1000. The wake-associated macroscale turbulent heat-flux contribution decays within a consistence entrance region extending approximately 3-4 unit cells into the porous layer across all investigated porosities, Reynolds numbers, and Prandtl numbers. For Re$\ge$1000, the persistent wake momentum deficit subsequently causes the heat-transfer contrast to become negative, resulting in lower heat transfer in the impingement region than in the non-impingement region.

physics.flu-dyn↗

arXiv2026

Scale Collapse of Vortices at Porous-Fluid Interfaces

The interaction between externally generated turbulence and porous media is central to many engineering and environmental flows, yet the fate of macroscale vortical structures at a porous/fluid interface remains uncharacterized. By numerically simulating the turbulent flow using a two-dimensional (2D) direct numerical simulation (DNS), we investigate the penetration, breakdown, and turbulent kinetic energy (TKE) transport of macroscale vortices impinging on porous matrices with high porosities $ϕ$ = 0.80-0.95. For all porosities considered, macroscale vortices collapse abruptly at the porous interface and do not persist within the matrix, supporting the pore-scale prevalence of turbulence even under strong external forcing. Although vortex impingement injects TKE into the porous medium through turbulent transport at the interface, this supplied TKE is rapidly redistributed and dissipated as the flow reorganizes to satisfy pore-scale geometric constraints. Deeper within the porous layer, turbulence is sustained primarily by local shear production associated with pore-scale velocity gradients, and the internal flow becomes increasingly independent of upstream conditions. Variations in porosity modulate the balance between production and dissipation of TKE by altering geometric confinement and the local flow conditions within the pores although the dominant turbulent length scale within the porous matrix remains set by the pore size. These results demonstrate that porous media act as a robust geometric filter that enforces pore-scale-dominated turbulence regardless of the external forcing.

physics.flu-dyn↗

arXiv2026

Effect of Microscale Turbulent Structures Dynamics on Forced Convection in Turbulent Porous Media Flow

The influence of microscale flow structures (smaller than the pore size) on turbulent heat transfer in porous media has not been yet investigated. The goal of this study is to determine the influence of the micro-vortices on convection heat transfer in turbulent porous media flow. Turbulent flow in a homogeneous porous medium was investigated using Large Eddy Simulation (LES) at a Reynolds number of 300. We observed that the convection heat transfer characteristics are dependent on whether the micro-vortices are attached or detached from the surface of the obstacle. There is a spectral correlation between the Nusselt number and the pressure instabilities due to vortex shedding. A secondary flow instability occurs due to high pressure regions forming periodically near the converging pathway between obstacles. This causes local adverse pressure gradient, affecting the flow velocity and convection heat transfer. This study has been performed for obstacles with shapes of square and circular cylinders at porosities of 0.50 and 0.87. Understanding the dominant modes that affect convection heat transfer can aid in finding an optimum geometry for the porous medium.

physics.flu-dyn↗

arXiv2026

Turbulent Microscale Flow Field Prediction In Porous Media Using Convolutional Neural Networks

Turbulence modeling in porous media can be greatly improved by combining high-resolution numerical methods with modern data-driven techniques. The development of accurate macroscale models (length scale greater than the pore size) will enable real-time systemic simulations of porous media flow. We consider the case of turbulent flow in homogeneous porous media, typically encountered in engineered porous media (heat exchangers, metamaterials, combustors, etc.). The underlying microscale flow field is inhomogeneous and determined by the geometry of the porous medium. Neural Networks are able to resolve the geometry-dependence and the non-linearity of porous media turbulent flow. We are proposing to separate the macroscale model into individual blocks that predict a unique aspect of the microscale flow, such as microscale spatial flow distribution and vortex dynamics. In the present work, we determine the feasibility of the prediction of the Reynolds-averaged microscale flow patterns by using Convolutional Neural Networks (CNN). The porous medium is represented by using a square lattice arrangement of circular cylinder solid obstacles. The pore-scale Reynolds number of the flow is 300. The porosity of the porous medium is varied from 0.45 to 0.92 with 60 steps. The microscale flow field is simulated by using Large Eddy Simulation (LES) with a compact sixth-order finite difference method. We demonstrate satisfactory prediction of the microscale flow field using the CNN with a global error less than 10%. We vary the number of training samples to study the deterioration of the model accuracy. The CNN model offers a O(106) speedup over LES with only 10% loss in accuracy.

physics.flu-dyn↗

arXiv2025

Instabilities and bifurcations in turbulent porous media flow

Microscale turbulent flow in porous media is conducive to the development of flow instabilities due to strong vortical and shearing flow occurring within the pore space. When the flow instabilities around individual solid obstacles interact with numerous others within the porous medium, unique symmetry-breaking phenomena emerge as a result. This paper focuses on investigations of the vortex dynamics and flow instabilities behind solid obstacles in porous media, emphasizing how solid obstacle geometry and porosity influence both microscale and macroscale flow behavior. Two distinct symmetry-breaking mechanisms were identified in different porosity ranges. In low porosity media (< 0.8), a "deviatory flow" phenomenon occurs, where the macroscale flow deviates from the direction of applied pressure gradient at Reynolds numbers above 500. Deviatory flow is a source of macroscale Reynolds stress anisotropy, which is counterbalanced by a diminished vortex core size. In the intermediate porosity regime (0.8-0.95), a "jetting flow" mechanism creates asymmetric microscale velocity channels in the pore space through temporally biased vortex shedding, occurring during the transition to turbulence. Both symmetry-breaking phenomena are critically influenced by solid obstacle shape, porosity, and Reynolds number. Circularity of solid obstacle geometry and an adequately high Reynolds number provide critical conditions for symmetry-breaking, whereas porosity can be used to parametrize the degree of symmetry-breaking. This paper provides fundamental insights into the intricate flow dynamics in porous media, offering a comprehensive understanding of how microscale vortex interactions generate macroscale flow asymmetries across different geometric configurations.

physics.flu-dyn↗

arXiv2025

Symmetry-breaking of turbulent flow due to asymmetric vortex shedding in periodic porous media

In this paper, we report new insight into a symmetry-breaking phenomenon that occurs for turbulent flow in periodic porous media composed of cylindrical solid obstacles with circular cross-section. We have used Large Eddy Simulation to investigate the symmetry-breaking phenomenon by varying the porosity (0.57-0.99) and the pore scale Reynolds number (37-1,000). Asymmetrical flow distribution is observed in the intermediate porosity flow regime for values of porosities between 0.8 and 0.9, which is characterized by the formation of alternating low and high velocity flow channels above and below the solid obstacles. These channels are parallel to the direction of the flow. Correspondingly, the microscale vortices formed behind the solid obstacles exhibit a bias in the shedding direction. The transition from symmetric to asymmetric flow occurs in between the Reynolds numbers of 37 (laminar) and 100 (turbulent). A Hopf bifurcation resulting in unsteady oscillatory laminar flow marks the origin of a secondary flow instability arising from the interaction of the shear layers around the solid obstacle. When turbulence emerges, stochastic phase difference in the vortex wake oscillations caused by the secondary flow instability results in flow symmetry breaking. We note that symmetry breaking does not occur for cylindrical solid obstacles with square cross-section due to the presence of sharp vertices in the solid obstacle surface. At the macroscale level, symmetry-breaking results in residual transverse drag force components acting on the solid obstacle surfaces. Symmetry-breaking promotes attached flow on the solid obstacle surface, which is potentially beneficial for improving transport properties at the solid obstacle surface such as convection heat flux.

physics.flu-dyn↗

arXiv2023

Convolution Neural Network Model Framework to Predict Microscale Drag Force for Turbulent Flow in Porous Media

Convolution Neural Networks (CNN) are well-suited to model the nonlinear relationship between the microscale geometry of porous media and the corresponding flow distribution, thereby accurately and efficiently coupling the flow behavior at the micro- and macro- scale levels. In this paper, we have identified the challenges involved in implementing CNNs for macroscale model closure in the turbulent flow regime, particularly in the prediction of the drag force components arising from the microscale level. We report that significant error is incurred in the crucial data preparation step when the Reynolds averaged pressure and velocity distributions are interpolated from unstructured stretched grids used for Large Eddy Simulation (LES) to the structured uniform grids used by the CNN model. We show that the range of the microscale velocity values is 10 times larger than the range of the pressure values. This invalidates the use of the mean squared error loss function to train the CNN model for multivariate prediction. We have developed a CNN model framework that addresses these challenges by proposing a conservative interpolation method and a normalized mean squared error loss function. We simulated a model dataset to train the CNN for turbulent flow prediction in periodic porous media composed of cylindrical solid obstacles with square cross-section by varying the porosity in the range 0.3 to 0.88. We demonstrate that the resulting CNN model predicts the pressure and viscous drag forces with less than 10% mean absolute error when compared to LES while offering a speedup of O(10^6).

physics.flu-dyn↗

arXiv2023

Flow regimes and types of solid obstacle surface roughness in turbulent heat transfer inside periodic porous media

The focus of this paper is to systematically study the influence of solid obstacle surface roughness in porous media on the microscale flow physics and report its effect on macroscale drag and Nusselt number. The Reynolds averaged flow field is numerically simulated for a flow through a periodic porous medium consisting of an in-line arrangement of square cylinders with square roughness particles on the cylinder surface. Two flow regimes are identified with respect to the surface roughness particle height: fine and coarse roughness regimes. The effect of the roughness particles in the fine roughness regime is limited to the near-wall boundary layer around the solid obstacle surface. In the coarse roughness regime, the roughness particles modify the microscale flow field in the entire pore space of the porous medium. In the fine roughness regime, the heat transfer from the rough solid obstacles to the fluid inside the porous medium is less than that from a smooth solid obstacle. In the coarse roughness regime, there is an enhancement in the heat transfer from the rough solid obstacle to the fluid inside the porous medium. Total drag reduction is also observed in the fine roughness regime for the smallest roughness particle height. The surface roughness particle spacing determines the fractional area of the solid obstacle surface covered by recirculating, reattached, and stagnating flow. As the roughness particle spacing increases, there are two competing factors for the heat transfer rate: increase due to more surface area covered by reattached flow, and decrease due to the decrease in the number of roughness particles on the solid obstacle surface. Decreasing the porosity and increasing the Reynolds number amplify the effect of the surface roughness on the microscale flow.

physics.flu-dyn↗

arXiv2022

The Evolution of Turbulent Micro-vortices and their Effect on Convection Heat Transfer in Porous Media

New insight into the contribution of the microscale vortex evolution towards convection heat transfer in porous media is presented in this paper. The objective is to determine how the microscale vortices influence convection heat transfer in turbulent flow inside porous media. The microscale temperature distribution is analyzed using flow visualization in 2D using streamlines and in 3D using Q structures. The pertinent observations are supplemented with the comparison of surface skin friction and heat transfer using: (1) surface skin friction lines and (2) joint PDF of pressure and skin friction coefficients, along with the Nusselt number. The microscale flow phenomena observed are corroborated with the features of the frequency spectra of the drag coefficient and macroscale Nusselt number. The Large Eddy Simulation technique is used to investigate the flow field inside a periodic porous medium. The Reynolds numbers of the flow are 300 and 500. The porous medium consists of solid obstacles in the shape of square and circular cylinders. Two distinct flow regimes are represented by using the porosities of 0.50 and 0.87. The results show that the surface Nusselt number distribution is dependent on whether the micro-vortices are attached to or detached from the surface of the obstacle. The spectra of the macroscale Nusselt number and the pressure drag are similar signifying a correlation between the dynamics of heat transfer and the microscale turbulent structures. Both vortex shedding and secondary flow instabilities are observed that significantly influence the Nusselt number. The fundamental insight gained in this paper can inform the development of more robust macroscale models of convection heat transfer in turbulent flow in porous media.

physics.flu-dyn↗

arXiv2021

Effects of Pore-scale on the Macroscopic Properties of Natural Convection in Porous Media

Natural convection in porous media is a fundamental process for the long-term storage of CO2 in deep saline aquifers. Typically, details of mass transfer in porous media are inferred from the numerical solution of the volume-averaged Darcy-Oberbeck-Boussinesq (DOB) equations, even though these equations do not account for the microscopic properties of a porous medium. According to the DOB equations, natural convection in a porous medium is uniquely determined by the Rayleigh number. However, in contrast with experiments, DOB simulations yield a linear scaling of the Sherwood number with the Rayleigh number (Ra) for high values of Ra (Ra>>1,300). Here, we perform Direct Numerical Simulations (DNS), fully resolving the flow field within the pores. We show that the boundary layer thickness is determined by the pore size instead of the Rayleigh number, as previously assumed. The mega- and proto- plume sizes increase with the pore size. Our DNS results exhibit a nonlinear scaling of the Sherwood number at high porosity, and for the same Rayleigh number, higher Sherwood numbers are predicted by DNS at lower porosities. It can be concluded that the scaling of the Sherwood number depends on the porosity and the pore-scale parameters, which is consistent with experimental studies.

physics.flu-dyn↗

arXiv2020

Modeling tau transport in the axon initial segment

By assuming that tau protein can be in seven kinetic states, we developed a model of tau protein transport in the axon and in the axon initial segment (AIS). Two separate sets of kinetic constants were determined, one in the axon and the other in the AIS. This was done by fitting the model predictions in the axon with experimental results and by fitting the model predictions in the AIS with the assumed linear increase of the total tau concentration in the AIS. The calibrated model was used to make predictions about tau transport in the axon and in the AIS. To the best of our knowledge, this is the first paper that presents a mathematical model of tau transport in the AIS. Our modeling results suggest that binding of free tau to MTs creates a negative gradient of free tau in the AIS. This leads to diffusion-driven tau transport from the soma into the AIS. The model further suggests that slow axonal transport and diffusion-driven transport of tau work together in the AIS, moving tau anterogradely. Our numerical results predict an interplay between these two mechanisms: as the distance from the soma increases, the diffusion-driven transport decreases, while motor-driven transport becomes larger. Thus, the machinery in the AIS works as a pump, moving tau into the axon.

q-bio.SC↗

arXiv2020

Modeling transport and mean age of dense core vesicles in large axonal arbors

A model simulating transport of dense core vesicles (DCVs) in type II axonal terminals of Drosophila motoneurons has been developed. The morphology of type II terminals is characterized by the large number of en passant boutons. The lack of both scaled up DCV transport and scaled down DCV capture in boutons results in a less efficient supply of DCVs to distal boutons. Furthermore, the large number of boutons that DCVs pass as they move anterogradely, until they reach the most distal bouton, may lead to the capture of a majority of DCVs before they turn around in the most distal bouton to move in the retrograde direction. This may lead to a reduced retrograde flux of DCVs and a lack of DCV circulation in type II terminals. The developed model simulates DCV concentrations in boutons, DCV fluxes between the boutons, age density distributions of DCVs, and the mean age of DCVs in various boutons. Unlike published experimental observations, our model predicts DCV circulation in type II terminals after these terminals are filled to saturation. This disagreement is likely because experimentally observed terminals were not at steady-state, but rather were accumulating DCVs for later release. Our estimates show that the number of DCVs in the transiting state is much smaller than that in the resident state. DCVs traveling in the axon, rather than DCVs transiting in the terminal, may provide a reserve of DCVs for replenishing boutons after a release. The techniques for modeling transport of DCVs developed in our paper can be used to model the transport of other organelles in axons.

q-bio.NC↗