Simulation Of Channel Flow Research Articles

Roughness-Resolved Large-Eddy Simulation of Additive Manufacturing-Like Channel Flows

Abstract In the last decade, progresses in additive manufacturing (AM) have paved the way for optimized heat exchangers whose disruptive design will heavily rely on predictive numerical simulations. However, due to typical roughness induced by AM, current wall models used in steady and unsteady 3D Navier–Stokes simulations do not take into account such characteristics. For the development and assessment of novel wall models for AM, a high-fidelity roughness-resolved large-eddy simulation (RRLES) database is built. This article describes the numerical setup and the methodology used for conducting RRLES, from surface generation to postprocessing. In addition, three different cases representing two printing directions plus a streamwise and spanwise isotropic case are investigated. While the roughness distributions are the same in the three cases, the effective slope (ES) is very different, and the impact of this parameter on turbulence and heat transfer is analyzed at different Reynolds numbers.

Effects of the hidden errors in the bounce back scheme on the lattice Boltzmann simulation of the turbulent channel flow using the multiple-relaxation-time collision model

In our recent paper [Dong et al., Phys. Fluids 34, 093608 (2022)], it is shown that hidden errors can be introduced by a bounce back scheme at the boundary nodes, due to the fact that it may not be entirely consistent with the Chapman–Enskog approximation of the lattice Boltzmann equation applied to the interior nodes. In this paper, we investigate the effects of these hidden errors on the lattice Boltzmann simulation of the turbulent channel flow with a multiple-relaxation-time (MRT) collision model, extending our previous study using the Bhatnagar–Gross–Krook and two-relaxation-time collision models applied to laminar non-uniform viscous flows. A theoretical framework for identifying the hidden errors in the MRT model is developed, and the hidden errors in two bounce back schemes, namely, the off-wall and on-wall bounce back schemes, are derived in terms of the hydrodynamic variables and relaxation rates. The results reveal several important differences in the expression of hidden errors between the two bounce back schemes. The analysis also points to a correction for the on-wall bounce back scheme when the external force is present. A set of six simulations of the turbulent channel flow, using the two bounce back schemes and three grid resolutions, are, then, performed to demonstrate that the magnitude of the hidden errors can significantly affect the simulated turbulence statistics, the local consistency with the Navier–Stokes equations, and the numerical stability.

A priori assessment of nonlocal data-driven wall modeling in large eddy simulation

In the present study, a priori assessment is performed on the ability of the convolutional neural network (CNN) for wall-modeling in large eddy simulation. The data used for the training process are provided by the direct numerical simulation (DNS) of the turbulent channel flow. Initially, a study is carried out on the input choices of CNN, and the effect of different flow parameters on establishing a wall model is investigated. Then, the influence of the wall-normal distance on the established data-driven wall model is studied by choosing the CNN input data from two regions of the inner layer (y+>10,y/δ<0.1) and the logarithmic layer. The performance of the obtained CNN wall models based on the inputs from the two regions is further investigated by feeding the network with the data outside the training range. In the next step, the models are tested under various conditions, including a different grid size and a higher Reynolds number. The results show that the models using the inner layer (excluding y+≤10) data as the CNN input have better accuracy in establishing a wall model compared to the models based on the input data in the logarithmic layer, especially when implemented outside the training range. After optimizing the hyperparameters of CNN, a high correlation coefficient of 0.9324 is achieved between the wall shear stress calculated using the filtered DNS data and predicted by the best CNN wall model, which is trained using the data in the inner layer, excluding y+≤10. The performance of the CNN wall model is also compared with the existing wall-stress models, and it is shown that the CNN wall model has better accuracy in establishing a wall model. Additionally, the CNN wall model is shown to have good performance when applied to a different grid size or a higher Reynolds number.

Phononic-subsurface flow stabilization by subwavelength locally resonant metamaterials

The interactions between a solid surface and a fluid flow underlie dynamical processes relevant to air, sea, and land vehicle performance and numerous other technologies. Key among these processes are unstable flow disturbances that contribute to fundamental transformations in the flow field. Precise control of these disturbances is possible by introducing a phononic subsurface (PSub). This comprises locally attaching a finite phononic structure nominally perpendicular to an elastic surface exposed to the flowing fluid. This structure experiences ongoing excitation by an unstable flow mode, or more than one mode, traveling in conjunction with the mean flow. The excitation generates small deformations at the surface that trigger elastic wave propagation within the structure, traveling away from the flow and reflecting at the end of the structure to return to the fluid-structure interface and back into the flow. By targeted tuning of the unit-cell and finite-structure characteristics of the PSub, the returning waves may be devised to resonate and reenter the flow out of phase, leading to significant destructive interference of the continuously incoming flow waves near the surface and subsequently to their attenuation over the spatial extent of the control region. This entire mechanism is passive, responsive, and engineered offline without needing coupled fluid-structure simulations; only the flow instability’s frequency, wavelength, and overall modal characteristics must be known. Disturbance stabilization in a wall-bounded transitional flow leads to delay in laminar-to-turbulent transition and reduction in skin-friction drag. Destabilization is also possible by alternatively designing the PSub to induce constructive interference, which is beneficial for delaying flow separation and enhancing chemical mixing and combustion. In this paper, we present a PSub in the form of a locally resonant elastic metamaterial, designed to operate in the elastic subwavelength regime and hence being significantly shorter in length compared to a phononic-crystal-based PSub. This is enabled by utilizing a sub-hybridization resonance. Using direct numerical simulations of channel flows, both types of PSubs are investigated, and their controlled spatial and energetic influence on the wall-bounded flow behavior is demonstrated and analyzed. We show that the PSub’s effect is spatially localized as intended, with a rapidly diminishing streamwise influence away from its location in the subsurface.

Effects of mean shear on the vortex identification and the orientation statistics

This work compares the threshold applied to the swirling strength as well as the vortex orientation statistics in the total and fluctuating velocity fields using direct numerical simulations of compressible and incompressible turbulent channel flows. It is concluded that the difference in the swirling strength for vortex identification is minimal in the logarithmic region such that these two situations share the same threshold. Regarding the vortex orientation, the inclination angle remains similar. However, as the wall-normal distance increases, a more and more obvious distinction is noticed for its orientation with respect to the spanwise (z) direction. It is mainly due to their intrinsic differences and attendant contrasting preference for the vortex identification, i.e., vortices rotating in the −z direction for the total velocity field and in the z direction for the fluctuating one. These observations function as a reasonable explanation for various remarks in previous studies.

Simulation of open channel flows by an explicit incompressible mesh-free method

Simulation of open channel flows by an explicit incompressible mesh-free method

Large eddy simulations of the turbulent channel flow over dimpled surfaces

Reducing skin friction has a key role in the efficiency of rail, highway, and airway transport vehicles or naval systems such as ships and underwater vehicles. In recent years, there is a growing interest in investigating turbulent drag-reducing capabilities of dimpled surfaces, which have great potential as a passive solution, while there still exists highly conflicting views and drag reduction rates reported in the literature as well as a lack of information about the drag reduction mechanism. In this study, large-eddy simulations (LES) were performed to investigate the characteristics and physical mechanism of the fluid flow over dimpled surfaces in a fully developed channel flow. The Reynolds number based on the channel height and the mean bulk velocity was nearly 5600 for all cases examined. Within the framework of the study, various dimple depth to diameter ratios as well as different dimple arrangements and geometries were considered. The detailed mean and instantaneous flow fields, turbulent kinetic energy budget and spectral characteristics of the flow are presented. The study revealed the potential of the dimpled surface in reducing skin friction and provided critical information about the flow features affecting the performance of the dimples.

Wavelet-based adaptive large-eddy simulation of supersonic channel flow with different thermal boundary conditions

This work investigates the effect of different thermal wall boundary conditions on the wavelet-based adaptive large-eddy simulation of supersonic turbulent channel flow. The compressible flow governing equations are expressed in terms of wavelet-based Favre-filtered variables and are supplied with the anisotropic minimum dissipation closure model. Various computations are performed, where the resolved temperature field is constrained by either Dirichlet (isothermal) or Neumann (adiabatic) boundary conditions at the walls. The turbulence diagnostics include mean flow features and turbulent fluctuations statistics. The successful comparison with reference direct numerical simulations demonstrates the validity and the efficiency of the wavelet-based adaptive approach for wall-bounded turbulent compressible flow, regardless of the thermal boundary conditions that are imposed.

Non-equilibrium extension of the explicit algebraic subgrid-scale stress model with application to turbulent channel flow at low Reynolds numbers

An extension of the explicit algebraic subgrid-scale (SGS) stress model (EASSM) of Marstorp et al. [J. Fluid Mech. 639, 403–432 (2009)] is proposed to account for the non-local equilibrium between the production, P, and viscous dissipation, ϵ, of the SGS turbulent kinetic energy in its formulation. The original derivation of the EASSM uses the equilibrium assumption P=ϵ, whereas in the current new derivation, a cubic algebraic equation is extracted for P/ϵ from the modeled transport equation for the SGS stress anisotropy, which can be solved to improve the EASSM predictions with less than 4% additional computational costs per time step. The performance of the extended EASSM is assessed in large-eddy simulation of plane turbulent channel flow at Reτ=587 and 179 for a wide range of resolutions, where deviations from the local equilibrium assumption are expected at the vicinity of the walls. The enhanced EASSM formulation lowers resolution dependence of the model predictions and improves its predictions at low resolutions. The improvements affected major one-point turbulence statistics of interest, such as the wall shear stress, mean velocity, Reynolds stresses, and SGS dissipation as well as the two-point velocity correlations and premultiplied spanwise spectra of the streamwise velocity. The predicted mean P/ϵ also reasonably agrees with the filtered direct numerical simulation data.

Uniform momentum and temperature zones in unstably stratified turbulent flows

Wall-bounded turbulent flows exhibit a zonal arrangement, in which streamwise velocity organizes into uniform momentum zones (UMZs), separated by thin layers of elevated interfacial shear. While significant research efforts have focused on these structural features in neutrally stratified flows, the effects of unstable thermal stratification on UMZs and on analogous uniform temperature zones (UTZs) have not been considered previously. In this article, statistical properties of UMZs and UTZs are investigated using a suite of large eddy simulations of unstably stratified turbulent channel flow spanning weakly to highly convective conditions. When normalized by the friction velocity and stability-dependent mixing length, the mean velocity gradient based on UMZ interfacial velocity jumps and the vorticity thickness exhibits good collapse for all stabilities, establishing a link between UMZ properties and scaling predictions from Monin–Obukhov similarity theory. A similar relationship is found between UTZ properties and surface-layer scaling of the mean temperature gradient. In the mixed layer, mean UMZ depth is quasi-constant with wall-normal distance, while the deepest UTZs are found in the centre of the boundary layer. These instantaneous structures are found to be linked to the well-mixed velocity and temperature profiles in the convective mixed layer. Conditional averaging indicates that both UMZ and UTZ interfaces are associated with ejections of momentum and warm updrafts below the interface and sweeps of momentum and cool downdrafts above the interface. These results demonstrate a tangible connection between instantaneous structural features, mean properties and scaling laws in unstably stratified flows.

Direct numerical simulation of particle-laden flow in an open channel at

We perform two-way coupled direct numerical simulation of particle-laden flow in an open channel at a friction Reynolds number ( $Re_{\tau }$ ) of 5186, which exhibits many characteristics of high-Reynolds-number wall-bounded turbulence, such as the distinct separation of scales in the inner and outer layers. Three representative cases, an unladen case and low- and high-Stokes-number particle-laden cases, are performed to investigate the turbulent modification by particles. To this end, we compare several statistical quantities to understand the particle effect on momentum exchange and interphasial energy transfer. The modulation of large-scale motions (LSMs) and very-large-scale motions (VLSMs) are analysed using spectral information, and we find that the LSMs and VLSMs are generally weakened in the inner and outer layers, which is qualitatively different from similar simulations at lower Reynolds numbers ( $Re_{\tau } \approx 500$ ). The spatial structures are investigated with correlation analysis, and inclined VLSMs are observed in the near-wall region, with decreased inclination angles by particles. The particles tend to widen and shorten the spanwise and streamwise extent of coherent structures, respectively. Furthermore, we find that the vorticity vector displays a preferential alignment with the eigenvector corresponding to the intermediate eigenvalue of the strain-rate tensor, independent of the particle Stokes number.

A wall stress model to predict high-Reynolds number flow over rough walls

Wall-modeled large eddy simulation of turbulent channel flow with rough walls was performed for Reynolds numbers of Reτr=615–2080. The eddy viscosity parameter in a wall stress model was modified to include the effects of wall roughness. Symmetric and asymmetric channel flows were studied for transitionally and fully rough states with ks+=62 and 112, respectively. The wall shear stress was estimated based on the velocity field within the wall layer using the total shear stress term. For the wall layer, the matching point was located well above the height of the virtual roughness elements. The numerical predictions for the mean velocity profile and Reynolds stresses compared well with the experimental data. The prediction for the mean velocity shift due to roughness agreed with the experimental measurements and empirical correlations. For the asymmetric channel flows with roughness on only one wall, the numerical simulations correctly reproduced the displacement of the mean flow away from the rough wall. Overall, the proposed wall-model allows for the prediction of the effects of wall roughness without resolving the geometry of the roughness elements on the wall. This is consistent with the goal of performing large eddy simulations of wall-bounded flows at high-Reynolds numbers with minimal resolution of the wall region, which results in a much reduced computational cost.

Turbulence control for drag reduction through deep reinforcement learning

Deep reinforcement learning was applied to turbulence control for drag reduction in direct numerical simulation of turbulent channel flow. The learning determines the optimal distribution of wall blowing and suction based on the wall shear stress information. From an investigation of the optimal actuation fields, two distinct drag reduction mechanisms were identified. One of them, which had not previously been recognized, attempts to cancel the near-wall sweep and ejection events.

Numerical Determination of the Equivalent Sand Roughness of a Turbopump’s Surface and Its Roughness Influence on the Pump Characteristics

The correct computation of flows over rough surfaces in technical systems, such as in turbomachines, is a significant issue for proper simulations of their performance data. Once the flow over rough surfaces is adequately computed in these machines, simulations become more trustworthy and can replace experimental prototyping. Roughness modelling approaches are often implemented in a solver to account for roughness effects in flow simulations. In these approaches, the equivalent sand roughness ks must be defined as a characteristic parameter of the rough surface. However, it is difficult to determine the corresponding ks-value for a surface roughness. In this context, this paper shows a novel and time-efficient numerical method, the discrete porosity method (DPM), which can be used to determine the ks-value of a rough surface. Applying this method, channel flow simulations were performed with an irregularly distributed cast iron surface from a turbopumps volute. After identifying the fully rough regime, the equivalent sand roughness was determined and a match with ks-values from literature data was found. Subsequently, the established ks-value for cast iron was used in a turbopump simulation with rough walls. The performance data of the pump were validated by experiments and a good agreement between the experimental and simulated performance data was found.

Effect of high skewness and kurtosis on turbulent channel flow over irregular rough walls

The skewness of the roughness height distribution is one of the key topographical parameters that govern roughness effects on wall-bounded turbulence. In this paper mathematical bounds for realisable values of skewness and kurtosis are discussed in the context of irregular multi-scale rough surfaces, which are representative of typical forms of engineering roughness. The properties of a set of irregular rough surfaces fully covered by roughness features with very high positive and negative skewness and high kurtosis are investigated using direct numerical simulations of turbulent channel flow at . While an increase of the roughness function is observed at moderate skewness values in line with empirical predictions and previous results for moderately skewed surfaces, the roughness function saturates at extreme values of skewness. Overall, the roughness effect is found to be more sensitive to skewness over the negative skewness range compared to the positive skewness range. Surface pressure statistics show that for surfaces with extreme skewness fully covered by roughness features extreme pits or peaks do not dominate the roughness effect and that surrounding roughness features (‘background’ roughness) retain a significant influence. This is because, while extreme roughness features emerge as skewness approaches high positive or negative values, they tend to be sparse decreasing their overall impact on the wall-bounded flow.

Divergence-free turbulent inflow data from realistic covariance tensor

Scale-resolving computational fluid dynamics (CFD) methods require carefully constructed boundary conditions to produce accurate results. The inflow data should be unsteady and the successive realizations must follow specific statistics while ideally having a particular correlation in both space and time. A method for generating synthetic correlated stochastic data from uncorrelated sequences is detailed and applied to the problem of inflow turbulence generation for CFD simulations. The technique constructs divergence-free anisotropic random fields with the sensible spectrum and complete complex correlation in space and time. A realistic two-point correlation tensor is inferred from first and second moments and a set of heuristic recommendations based on turbulent flow observations. These statistics are readily available in most practical cases making the technique highly versatile. The approach is computationally efficient with the use of eigendecomposition to reduce the resources required depending on the accuracy needed. Demonstration of the method is provided with the simulation of a turbulent channel flow and a square duct flow, and validation is done against existing numerical data.

Numerical simulation of two-phase flow in gas diffusion layer and gas channel of proton exchange membrane fuel cells

Liquid water within the cathode Gas Diffusion Layer (GDL) and Gas Channel (GC) of Proton Exchange Membrane Fuel Cells (PEMFCs) is strongly coupled to gas transport properties, thereby affecting the electrochemical conversion rates. In this study, the GDL and GC regions are utilized as the simulation domain, which differs from previous studies that only focused on any one of them. A Volume of Fluid (VOF) method is adopted to numerically investigate the two-phase flow (gas and liquid) behavior, e.g., water transport pattern evolution, water coverage ratio as well as local and total water saturation. To obtain GDL geometries, an in-house geometry-based method is developed for GDL reconstruction. Furthermore, to study the effect of GDL carbon fiber diameter, the same procedure is used to reconstruct three GDL structures by varying the carbon fiber diameter but keeping the porosity and geometric dimensions constant. The wall wettability is introduced with static contact angles at carbon fiber surfaces and channel walls. The results show that the GDL fiber microstructure has a significant impact on the two-phase flow patterns in the cathode field. Different stages of two-phase flow pattern evolution in both cathode domains are observed. The liquid water in the GDL experiences water invasion, spreading, and rising, followed by the droplet breakthrough in the GDL/GC interface. In the GC, the water droplets randomly experience accumulation, combination, attachment, and detachment. Due to the difference in surface wettability, the water coverage of the GDL/GC interface is smaller than that of the channel side and top walls. It is also found that the water saturation inside the GDL stabilizes after the water breakthrough, while local water saturation at the interface keeps irregular oscillations. Last but not the least, a water saturation balance requirement between the GDL and GC is observed. In terms of varying fiber diameter, a larger fiber diameter would result in less water saturation in the GDL but more water in the GC, in addition to faster water movement throughout the total domain.

Lattice Boltzmann method simulation of two-phase flow in horizontal channel

Immiscible two-phase flow exists in many fields such as the chemical engineering, energy engineering, and geography. It is of great significance in enhancing the oil recovery and geological carbon dioxide storage. Relative permeability is a comprehensive reflection of the effects of various factors including the saturation, contact angle, viscosity ratio, and capillary number of immiscible two-phase flow, and it is a key parameter describing such a flow and thus can directly reflect the flow capacity of each phase. As a new fluid numerical calculation method, the lattice Boltzmann method (LBM) has its own unique advantage in simulating various flows because it does not need to capture the phase interface, and thus has been widely used in recent years. In this research, the multi-relaxation time multi-component pseudopotential lattice Boltzmann method is improved to make it possible to solve the two-phase relative permeability under high viscosity ratios. It is known that the LBM is a particle-based hydrodynamic method, with the spontaneous diffusion of components in multi-component system inevitably causing a mixing between components, leading to distortion of the velocity of two-phase flow with a high viscosity ratio. The color gradient model is introduced into the pseudopotential model for the treatment of mixing, the multiple relaxation time is employed to improve the numerical stability and viscosity ratio range, and the numerical distortion caused by mixing is therefore resolved. The resulting model is validated by the use of the two-phase layered flow in a 2D infinite channel, and accurate numerical results are obtained even if the viscosity ratio reaches 1000. Based on the improved model, the two-phase flow in a two-dimensional horizontal channel is analyzed and the effects of saturation, viscosity ratio, wettability and capillary number on relative permeability and phase permeation curves are investigated. The results show that the relative permeability of the high-viscosity phase increases with the increase of the viscosity ratio, and the saturation range for maintaining high flow capacity broadens with the increase of the low-viscosity phase. There is a limit for the influence of viscous coupling effect on the relative permeability of two phases: at a certain saturation, the relative permeability of the small viscosity phase has a minimum value while that of the large viscosity phase has a maximum value, the viscous coupling effect will never make the relative permeability of the small viscosity phase to be lower than the minimum value and that of the large viscosity phase to be higher than the maximum value. Non-wetting condition plays a role in increasing the flow capacity and relative permeability of the high-viscosity phase, while the wetting condition can weaken the flow capability, relative permeability of the high-viscosity phase. When the high-viscosity phase is a non-wetting phase, the decrease of the contact area with the solid wall increases its proportion in the middle flow passage, which enables it to maintain a strong flow capability in a wide saturation range. Wall wetting tends to inhibit fluid flow and consequently reduce the relative permeability. The increase of the capillary number may cause a more obvious contact angle hysteresis effect, which reduces the relative permeability of two phases.

Numerical simulation of turbulent channel flow with particle-adhered riblet surfaces

Numerical simulation of turbulent channel flow with particle-adhered riblet surfaces

Dissipation-optimized proper orthogonal decomposition

We present a formalism for dissipation-optimized decomposition of the strain rate tensor (SRT) of turbulent flow data using Proper Orthogonal Decomposition (POD). The formalism includes a novel inverse spectral SRT operator allowing the mapping of the resulting SRT modes to corresponding velocity fields, which enables a complete dissipation-optimized reconstruction of the velocity field. Flow data snapshots are obtained from a direct numerical simulation of a turbulent channel flow with friction Reynolds number Reτ=390. The lowest dissipation-optimized POD (d-POD) modes are compared to the lowest conventional turbulent kinetic energy (TKE)-optimized POD (e-POD) modes. The lowest d-POD modes show a richer small-scale structure, along with traces of the large-scale structure characteristic of e-POD modes, indicating that the former captures structures across a wider range of spatial scales. Profiles of both TKE and dissipation are reconstructed using both decompositions, and reconstruction convergences are compared in all cases. Both TKE and dissipation are reconstructed more efficiently in the dissipation-rich near-wall region using d-POD modes, and in the TKE-rich bulk using e-POD modes. Lower modes of either decomposition tend to contribute more to either reconstructed quantity. Separating each term into eigenvalues and factors relating to the inherent structures in each mode reveals that higher e-POD modes tend to encode more dissipative structures, whereas the structures encoded by d-POD modes have roughly constant inherent TKE content, supporting the hypothesis that structures encoded by d-POD modes tend to span a wide range of spatial scales.