High-resolution Direct Numerical Simulations Research Articles

Settling velocity characteristics of inertial particles in turbulent and wave-induced environments

In the present study, a theoretical model is proposed to calculate the settling velocity of solid particles in turbulence generated by both oscillatory and nearly horizontal flow motions. In contrast to other previous models that typically compartmentalize two flow conditions in their studies, this study takes a more comprehensive approach by considering the combined effects of both conditions. Taking into account the influence of drag nonlinearity, virtual mass and Basset history forces, the new theoretical model is formulated. The proposed model is obtained by solving the particle motion in fluid flow under some reasonable assumptions. Accordingly, we obtain a new dimensionless term to better take into account the effect of turbulence anisotropy on the settling velocity and the role of the sediment damping coefficient. Application of this term for other conditions is discussed in the paper. The present model shows satisfactory agreement with a wide range of experimental and numerical data and with different flow conditions found in the existing literature. These data include homogeneous isotropic turbulence with high resolution direct numerical simulations (DNS), turbulent open channel and vertical oscillation.

Low-Order Moments of Velocity Gradient Tensors in Two-Dimensional Isotropic Turbulence

In isotropic turbulence, symmetry of different directions can reduce the number of independent components for velocity gradient tensors. In three-dimensional isotropic turbulence, the independent components under either incompressible or compressible conditions have already been analyzed in the literature. However, for two-dimensional isotropic turbulence, they are still unclear. We derive rigorously the independent components for velocity gradient tensors of two-dimensional isotropic turbulence and give physical explanations. These theoretical results are validated using high-resolution direct numerical simulations (DNSs) of two-dimensional compressible turbulence. Results show that the present DNS setup is still not sufficient to capture the isotropy of third-order moments, suggesting that more investigations on determining the smallest scale and improving the numerical schemes for two-dimensional compressible turbulence are required.

Turbulent mixing in the vertical magnetic Rayleigh–Taylor instability

The presence of a mean magnetic field aligned with the direction of the acceleration greatly modifies the development of the Rayleigh–Taylor instability (RTI). High resolution direct numerical simulations of the Boussinesq–Navier–Stokes equations under the magnetohydrodynamics approximation reveal that, after an initial damping of the perturbations at the interface between the two miscible fluids, a rapid increase of the mixing layer is observed. Structures are significantly stretched in the vertical direction because magnetic tension prevents small-scale shear instabilities. When the vertical turbulent velocity exceeds the Alfvén velocity, the flow transitions to turbulence, structures break and an enhanced mixing occurs with strong dissipation. Afterwards, the mixing zone slows down and its growth rate is decreased compared to the hydrodynamic case. For larger magnitudes of the mean magnetic field, a strong anisotropy persists, and an increased fraction of potential energy injected into the system is lost into turbulent magnetic energy: as a consequence, the mixing zone growth rate is decreased even more. This phenomenology is embedded in a general buoyancy-drag equation, derived from simplified equations that reflect the large-scale dynamics, in which the drag coefficient is increased by the presence of turbulent magnetic energy.

Modeling Kelvin Helmholtz Instability Tube and Knot Dynamics and Their Impact on Mixing in the Lower Thermosphere

AbstractWe present modeling results of tube and knot (T&K) dynamics accompanying thermospheric Kelvin Helmholtz Instabilities (KHI) in an event captured by the 2018 Super Soaker campaign (R. L. Mesquita et al., 2020, https://doi.org/10.1029/2020JA027972). Chemical tracers released by a rocketsonde on 26 January 2018 showed coherent KHI in the lower thermosphere that rapidly deteriorated within 45–90 s. Using wind and temperature data from the event, we conducted high resolution direct numerical simulations (DNS) employing both wide and narrow spanwise domains to facilitate (wide domain case) and prohibit (narrow domain case) the axial deformation of KH billows that allows tubes and knots to form. KHI T&K dynamics are shown to produce accelerated instability evolution consistent with the observations, achieving peak dissipation rates nearly two times larger and 1.8 buoyancy periods faster than axially uniform KHI generated by the same initial conditions. Rapidly evolving twist waves are revealed to drive the transition to turbulence; their evolution precludes the formation of secondary convective instabilities and secondary KHI seen to dominate the turbulence evolution in artificially constrained laboratory and simulation environments. T&K dynamics extract more kinetic energy from the background environment and yield greater irreversible energy exchange and entropy production, yet they do so with weaker mixing efficiency due to greater energy dissipation. The results suggest that enhanced mixing from thermospheric KHI T&K events could account for the discrepancy between modeled and observed mixing in the lower thermosphere (Garcia et al., 2014, https://doi.org/10.1002/2013JD021208; Liu, 2021, https://doi.org/10.1029/2020GL091474) and merits further study.

Validation of RANS-Based Turbulence Models Against High-Resolution Experiments and DNS for Buoyancy-Driven Flow with Stratified Fronts

To provide computational fluid dynamics (CFD)–grade experimental data for studying stratification, measurements on the High-Resolution Jet (HiRJet) facility at the University of Michigan have been conducted with density differences of 1.5 % and − 1.5 % , respectively. Fluid with a density different from the fluid initially present in the HiRJet tank was injected, and the propagation of the time-dependent density stratification was captured on a two-dimensional plane with the aid of the wire-mesh sensor technique for Reynolds numbers near 5000 and Richardson numbers near 0.29. Direct numerical simulations (DNSs) of the two cases have also been conducted to expand the multifidelity database. The novel experimental and DNS data were then used to assess the predictive capabilities of the Standard k − ε (SKE) model and the Reynolds Stress Transport (RST) model. In particular, the propagation speed and thickness of the stratification fronts were assessed by comparing the CFD results against the experimental and DNS data. It was found that the general trends of the stratified density fronts were well predicted by the CFD simulations; however, slight overprediction of the thickness of the stratification layer was found with the SKE model while the RST model gave a larger overprediction of the mixing. Examination of the turbulent statistics showed that the turbulent viscosity was largely overpredicted by the RST model compared to the SKE model.

Collisions of localized patterns in a nonvariational Swift-Hohenberg equation.

The cubic-quintic Swift-Hohenberg equation(SH35) has been proposed as an order parameter description of several convective systems with reflection symmetry in the layer midplane, including binary fluid convection. We use numerical continuation, together with extensive direct numerical simulations (DNSs), to study SH35 with an additional nonvariational quadratic term to model the effects of breaking the midplane reflection symmetry. The nonvariational structure of the model leads to the propagation of asymmetric spatially localized structures (LSs). An asymptotic prediction for the drift velocity of such structures, derived in the limit of weak symmetry breaking, is validated numerically. Next, we present an extensive study of possible collision scenarios between identical and nonidentical traveling structures, varying a temperaturelike control parameter. These collisions are inelastic and result in stationary or traveling structures. Depending on system parameters and the types of structures colliding, the final state may be a simple bound state of the initial LSs, but it can also be longer or shorter than the sum of the two initial states as a result of nonlinear interactions. The Maxwell point of the variational system, where the free energy of the global pattern state equals that of the trivial state, is shown to have no bearing on which of these scenarios is realized. Instead, we argue that the stability properties of bound states are key. While individual LSs lie on a modified snakes-and-ladders structure in the nonvariational SH35, the multipulse bound states resulting from collisions lie on isolas in parameter space, disconnected from the trivial solution. In the gradient SH35, such isolas are always of figure-eight shape, but in the present nongradient case they are generically more complex, although the figure-eight shape is preserved in a small subset of cases. Some of these complex isolas are shown to terminate in T-point bifurcations. A reduced model is proposed to describe the interactions between the tails of the LSs. The model consists of two coupled ordinary differential equations (ODEs) capturing the oscillatory nature of SH35 profiles at the linear level. It contains three parameters: two interaction amplitudes and a phase, whose values are deduced from high-resolution DNSs using gradient descent optimization. For collisions leading to the formation of simple bound states, the reduced model reproduces the trajectories of LSs with high quantitative accuracy. When nonlinear interactions lead to the creation or deletion of wavelengths, the model performs less well. Finally, we propose an effective signature of a given interaction in terms of net attraction or repulsion relative to free propagation. It is found that interactions can be attractive or repulsive in the net, irrespective of whether the two closest interacting extrema are of the same or opposite signs. Our findings highlight the rich temporal dynamics described by this bistable nonvariational SH35, and show that the interactions in this system can be quantitatively captured, to a significant extent, by a highly reduced ODE model.

Contribution of direct numerical simulations to the budget and modelling of the transport equations for passive scalar turbulent fields with wall scalar fluctuations

We perform direct numerical simulations (DNS) of the fully developed turbulent channel flow with a passive scalar subjected to constant time-averaged scalar fluxes at the wall. The first case (case I) considers a constant time-averaged scalar flux $\left \langle q_w \right \rangle$ along with the specific condition of a non-fluctuating scalar $\theta _w$ imposed at the wall implying zero wall scalar fluctuation $\theta '_w=0$ and zero variance (isoscalar boundary condition) whereas the second case (case II) accounts for a constant instantaneous scalar flux $q_w$ in time and space leading to zero gradient of scalar fluctuation along the normal to the wall $(\partial \theta '/ \partial x_n)_w = 0$ (isoflux boundary condition) implying a non-zero variance. The friction Reynolds number takes on the value $R_\tau =395$ and the molecular Prandtl numbers considered are $P_r=0.01$ , 0.1, 1 and 10. The purpose is to investigate the effect of the wall scalar fluctuations on the scalar field. Emphasis is put on the mean passive scalar $\left \langle \theta \right \rangle$ , the half-scalar variance $k_\theta$ , the turbulent scalar fluxes $\tau _{i \theta }$ , the correlation coefficients $R_{i \theta }$ , the passive scalar to dynamic time-scale ratio $\mathcal {R}$ , the turbulent Prandtl number $Pr_t$ and higher-order scalar statistics. Systematic comparisons between these two scalar fields are undertaken. As a result of interest, it is found that the mean scalar remains almost the same whatever the type of the boundary layer condition but not the scalar variance. The budgets of transport equations for the half-scalar variance and turbulent fluxes reveal that some scalar quantities such as the dissipation-rate and the molecular diffusion terms are highly modified in the near-wall region but not really the production, diffusion and the scalar-pressure gradient correlation terms in a first approximation. Visualization of the instantaneous scalar fields indicates that the topology of the structures is strongly modified as the Prandtl number increases from $P_r=0.01$ up to $10$ . Finally, it is shown how to use this DNS database to devise and calibrate scalar flux equation models in the framework of both first and second moment closures. This study suggests that accounting for wall scalar fluctuations should be considered in the simulation of turbulent flows involving fluid and solid combinations at the interface and provides a useful high resolution DNS database.

PARC: Physics-aware recurrent convolutional neural networks to assimilate meso scale reactive mechanics of energetic materials.

The thermo-mechanical response of shock-initiated energetic materials (EMs) is highly influenced by their microstructures, presenting an opportunity to engineer EM microstructures in a "materials-by-design" framework. However, the current design practice is limited, as a large ensemble of simulations is required to construct the complex EM structure-property-performance linkages. We present the physics-aware recurrent convolutional (PARC) neural network, a deep learning algorithm capable of learning the mesoscale thermo-mechanics of EM from a modest number of high-resolution direct numerical simulations (DNS). Validation results demonstrated that PARC could predict the themo-mechanical response of shocked EMs with comparable accuracy to DNS but with notably less computation time. The physics-awareness of PARC enhances its modeling capabilities and generalizability, especially when challenged in unseen prediction scenarios. We also demonstrate that visualizing the artificial neurons at PARC can shed light on important aspects of EM thermos-mechanics and provide an additional lens for conceptualizing EM.

Dynamics of flames in tubes with no-slip walls and the mechanism of tulip flame formation1

ABSTRACT A hydrogen/air flame propagation and the development of tulip-shaped flame in 2D tubes of different aspect ratios with both closed ends and in a half-open rectangular channel were studied using high resolution direct numerical simulations of the fully compressible Navier – Stokes equations coupled with a detailed chemistry. Flame propagation in a 3D rectangular channel was studied using large eddy simulations and compared with the results of direct numerical simulations of flame propagation in a 2D rectangular channel with the same aspect ratio. It is shown that the interaction of the rarefaction wave generated by the flame at the deceleration stage with the “positive” flow of unburned gas generated by the flame at the previous accelerating stage leads to a significant decrease of the velocity of the unburned gas flow in the near field zone ahead of the flame front. As a result, the thickness of the boundary layer in the near-field zone ahead of the flame increases significantly, and the profile of the axial velocity of the unburned gas in the near-field zone ahead of the flame front takes the form of a tulip or an inverted tulip, which leads to corresponding changes in the velocities of different parts of the flame front, the flame front inversion, and the formation of a tulip-shaped flame.

Growth rate of the turbulent magnetic Rayleigh-Taylor instability.

The Rayleigh-Taylor instability is strongly modified in the presence of a vertical mean magnetic field. Perturbations are first stretched in the vertical direction with no mixing due to the inhibition of small-scale shear instabilities. Then smooth elongated fingers eventually break after transition to turbulence, and a strong anisotropy persists. For increasing Alfvèn velocities, the growth rate of the mixing zone in the fully turbulent regime is decreased due to the conversion of potential energy into turbulent magnetic energy. A new theoretical prediction for the growth rate based on turbulent quantities is proposed and assessed with high-resolution direct numerical simulations of the Boussinesq-Navier-Stokes equationsunder the magnetohydrodynamics approximation.

Explicit Incorporation of Discrete Fractures Into Pore Network Models

AbstractFractured porous media exist widely in reservoir rocks and fractures play a critical role in fluid flow processes. High resolution direct numerical simulations of fluid flow can provide important insight into pore‐scale processes and flow mechanisms in fractured permeable media, however, the tremendous computational costs prevent these methods from being applied into larger scale models. Pore network modeling is an alternative solution to this problem, but currently it can only be used in porous media without fractures. This work is concerned with incorporating discrete fractures into pore network modeling to represent fractured porous media. A new fracture matrix pore network model (FM‐PNM) is developed to efficiently simulate the fluid flow properties in fractures associated with the pore matrix. Discrete fractures are transformed into a fracture pipe network and integrated with the pore matrix that is represented by a network of pore bodies and pore throats. These two networks are coupled together to create a single nested network which is topologically equivalent to the fractured porous medium. This method extends the scope of applications of pore network modeling to fractured porous media. The permeability of the coupled network (FM‐PNM) is benchmarked by Lattice Boltzmann simulation for various structures of pore matrix and discrete fracture networks.

Direct numerical simulation of compressible turbulence accelerated by graphics processing unit: An open-access database of high-resolution direct numerical simulation

In the author’s previous work, we introduced an open-source accelerated computational fluid dynamics code for scientific computations using a graphics processing unit system (OpenCFD-SCU). This code offers significantly improved computation speed and can be applied to challenging direct numerical simulation (DNS) problems. This paper presents several high-resolution cases using OpenCFD-SCU: (1) a 24° compression ramp at Mach 2.9, where the length of the ramp is 200 mm and the mesh number is 7.68 × 109; (2) a 34° compression ramp at Mach 6 with a mesh number of 9.3 × 109; (3) a cold-wall flat plate at Mach 10 with a friction Reynolds number of 1550 and mesh number of 4.5 × 109; (4) a blunt cone with a 1 mm head radius and 0° attack angle at Mach 10, where the mesh number is 24 × 109; and (5) a lifting-body model at Mach 6 with a mesh number of 11.1 × 109. Compared with DNS studies of compressible wall-bound turbulent flow under similar conditions, these cases have larger computational domains, finer resolutions, or higher Reynolds numbers, demonstrating the simulation capability of OpenCFD-SCU and broadening the scope of DNS applications. We have conducted preliminary analyses of these cases and have established an open-access database to store these data. The source code of OpenCFD-SCU can be accessed at http://developer.hpccube.com/codes/danggl/opencfd-scu.git; this website also contains detailed database descriptions and data acquisition methods.

Deep learning method for the super-resolution reconstruction of small-scale motions in large-eddy simulation

A super-resolution reconstruction model for the subgrid scale (SGS) turbulent flow field in large-eddy simulation (LES) is proposed, and it is called the meta-learning deep convolutional neural network (MLDCNN). Direct numerical simulation (DNS) data of isotropic turbulence are used as the dataset of the model. The MLDCNN is an unsupervised learning model, which only includes high-resolution DNS data without manually inputting preprocessed low-resolution data. In this model, the training process adopts the meta-learning method. First, in the a priori test, the SGS turbulent flow motions in the filtered DNS (FDNS) flow field are reconstructed, and the energy spectrum and probability density function of the velocity gradient of the DNS flow field are reconstructed with high accuracy. Then, in the a posteriori test, the super-resolution reconstruction of the LES flow field is carried out. The difficulty of LES flow field reconstruction is that it contains filtering loss and subgrid model errors relative to the DNS flow field. The super-resolution reconstruction of the LES flow field achieves good results through this unsupervised learning model. The proposed model makes a good prediction of small-scale motions in the LES flow field. This work improves the prediction accuracy of LES, which is crucial for the phenomena dominated by small-scale motions, such as relative motions of particles suspended in turbulent flows.

Turbulent wakes in a non-uniformly stratified environment

This study explores the behavior of turbulent wakes generated by a sphere propagating with constant speed in a non-uniformly stratified fluid. The investigation is based on a series of high-resolution direct numerical simulations in which the background stratification is systematically varied. We consider one linear and three nonlinear density profiles and discover that even modest, spatially localized non-uniformities of stratification can profoundly influence the wake dynamics, structure, and evolution. The analysis of microstructure signatures shows that wakes in non-uniformly stratified fluids tend to be more spread horizontally, and internal waves are much stronger than in linear stratification. Simulations performed with Gaussian perturbations are characterized by a vertically asymmetric energy distribution, which is attributed to internal wave reflections from low-gradient regions. Using microstructure decay rates, we estimate the effective persistence period of wakes, showing that it substantially increases with the increasing Froude number. We also find that wakes persist much longer in high-gradient profiles, whereas weak local gradients can substantially reduce the wake longevity.

Some new insights for inferring diapycnal (irreversible) diffusivity in stably stratified turbulence

New insight for inferring diapycnal diffusivity in stably stratified turbulent flows is obtained based on physical scaling arguments and tested using high-resolution direct numerical simulation data. It is shown that the irreversible diapycnal diffusivity can be decomposed into a diapycnal length scale that represents an inner scale of turbulence and a diapycnal velocity scale. Furthermore, it is shown that the diapycnal length scale and velocity scale can be related to the measurable Ellison length scale (LE) that represents outer scale of turbulence and vertical turbulent velocity scale (w′) through a turbulent Froude number scaling analysis. The turbulent Froude number is defined as Fr=ε/Nk, where ε is the rate of dissipation of turbulent kinetic energy, N is the buoyancy frequency, and k is the turbulent kinetic energy. The scaling analysis suggests that the diapycnal diffusivity Kρ∼w′LE in the weakly stratified regime (Fr >1) and Kρ∼(w′LE)×Fr for the strongly stratified regime (Fr <1).

Features of far-downstream asymptotic velocity fluctuations in a round jet: A one-dimensional turbulence study

An accurate prediction of the turbulent jet noise is usually only possible with direct numerical simulation (DNS) or high-resolution large-eddy simulation (LES) of the turbulent sources in the acoustic near field. The required level of fidelity comes at the price of high numerical resolution requirements, a severe restriction of the accessible parameter space, and high computational costs in general. These limitations can be partially mitigated by reduced-order models. In the present work, the stochastic one-dimensional turbulence (ODT) model is utilized as a stand-alone tool in order to study turbulent fluctuations in the far downstream region of turbulent round jets with finite co-flow velocity. ODT is a dimensionally reduced turbulence model that aims to resolve flow-field over a broad range of scales and, thus, the turbulent noise sources at all relevant scales, but only for a single, radially oriented, physical coordinate that is advected downstream with the flow during a simulation run. Here, unheated round jets with nozzle diameter D, nominal Mach number Ma = 0.9 but Reynolds number ReD∈{9×104,2×105,4×105} are studied as a canonical problem. An ensemble of ODT realizations is used to obtain flow statistics from a detailed representation of fluctuations that may be used to estimate turbulent noise by small-scale resolved sources in the near future. As the first step in this direction, we analyze the model representation of the flow field and the participating flow scales in detail. This is done even far downstream of the nozzle, which is not possible with high-resolution LES or DNS. The present ODT results agree well with the available reference data. The model accurately reproduces the asymptotic mean and fluctuating velocity behavior, and radial turbulence spectra of the jet that approximately obey large-scale jet similarity but are modified by axially decreasing the turbulence intensity. Based on these results, an outlook on the model application for turbulent jet noise prediction is given.

Extreme vorticity events in turbulent Rayleigh-Bénard convection from stereoscopic measurements and reservoir computing

High-amplitude events of the out-of-plane vorticity component ${\ensuremath{\omega}}_{z}$ are analyzed by stereoscopic particle image velocimetry (PIV) in the bulk region of turbulent Rayleigh-B\'enard convection in air. The Rayleigh numbers $\mathrm{Ra}$ vary from $1.7\ifmmode\times\else\texttimes\fi{}{10}^{4}$ to $5.1\ifmmode\times\else\texttimes\fi{}{10}^{5}$. The experimental investigation is connected with a comprehensive statistical analysis of long-term time series of ${\ensuremath{\omega}}_{z}$ and individual velocity derivatives $\ensuremath{\partial}{u}_{i}/\ensuremath{\partial}{x}_{j}$. A statistical convergence for derivative moments up to an order of 6 is demonstrated. Our results are found to agree well with existing high-resolution direct numerical simulation data in the same range of parameters, including the extreme vorticity events that appear in the far exponential tails of the corresponding probability density functions. The transition from Gaussian to non-Gaussian velocity derivative statistics in the bulk of a convection flow is confirmed experimentally. The experimental data are used to train a reservoir computing model, one implementation of a recurrent neural network, to reproduce highly intermittent experimental time series of the vorticity and thus reconstruct extreme out-of-plane vorticity events. After training the model with high-resolution PIV data, the machine learning model is run with sparsely seeded, continually available, and unseen measurement data in the reconstruction phase. The dependence of the reconstruction quality on the sparsity of the partial observations is also documented. Our latter result paves the way to machine-learning-assisted experimental analyses of small-scale turbulence for which time series of missing velocity derivatives can be provided by generative algorithms.

Subgrid modeling of the filtered equation of state with application to real-fluid turbulent mixing at supercritical pressures

Simulation of turbulent mixing and combustion at supercritical pressures requires the use of a real-fluid equation of state (EOS) to represent the nonideal, nonlinear thermodynamic behavior of fluids under these conditions. The simplified representation of the filtered EOS in the large eddy simulation methodology introduces inconsistencies in the computed filtered thermodynamic state. This study investigates these inconsistencies and novel subgrid modeling approaches to address these issues, using high-resolution direct numerical simulation of a transcritical mixing layer. Errors incurred by not accounting for subgrid effects in the EOS are quantified, and fundamental insights are drawn regarding the nature of these effects. Then, different modeling approaches are proposed and investigated to obtain a more accurate representation of the filtered EOS. The evaluation of the filtered EOS in terms of the Reynolds-filtered state variables is considered instead of the conventional Favre-filtered variables. A dynamic gradient model is formulated by building upon the ideas of dynamic modeling to render a functional form for the subgrid EOS expressed in terms of the resolved flow gradients. A scale-similarity model formulation for the subgrid EOS is also constructed and examined. Finally, a model for the filtered EOS is derived using a presumed filtered density function that accounts for the effect of subgrid-scale fluctuations. The performance of each model is evaluated using various metrics, and the relative accuracy of each modeling approach is compared and contrasted at different filter sizes.

Hot spot ignition and growth from tandem micro-scale simulations and experiments on plastic-bonded explosives

Head-to-head comparisons of multiple experimental observations and numerical simulations on a deconstructed plastic-bonded explosive consisting of an octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine crystal embedded in a polymeric binder with a 4 ns duration 20 GPa input shock are presented. Hot spots observed in high-resolution direct numerical simulations are compared with micro-scale shock-induced reactions visualized using nanosecond microscope imaging and optical pyrometry. Despite the challenges and limitations of both the experimental and simulation techniques, an agreement is obtained on many of the observed features of hot spot evolution, e.g., (1) the magnitude and time variation of temperatures in the hot spots, (2) the time to fully consume the crystals (∼100 ns) of size (100–300 μm) employed in this study, and (3) the locations of hot spot initiation and growth. Three different mechanisms of hot spot formation are indicated by simulations: (1) high-temperature hot spots formed by pore collapse, (2) lower temperature hot spots initiated at the polymer–crystal interface near corners and asperities, and (3) high-temperature reaction waves leading to fast consumption of the energetic crystal. This first attempt at a head-to-head comparison between experiments and simulations not only provides new insight but also highlights efforts needed to bring models and experiments into closer alignment, in particular, highlighting the importance of distinctly three-dimensional and multiple mechanisms of the hot spot ignition and growth.

Numerical investigation of turbulent features past different mechanical aortic valves

Flow through mechanical aortic valves (MAVs) has been constantly associated to higher haemolysis and platelet activation levels with respect to native valves, due to non-physiologic haemodynamic features. Both computational and experimental investigations have correlated the blood damage to augmented levels of turbulent stress downstream of MAVs. This study provides a computational estimation, drawn from high-resolution direct numerical simulations, of turbulent and fluctuating viscous stresses in three different MAV configurations, at subsequent stages of the cardiac cycle. The configurations comprise a St. Judes Medical Regent valve (SJMV), a Lapeyre-Triflo FURTIVA valve (LTFV) with three leaflets, and a SJMV with vortex generators (VGs). Non-standard configurations are expected to mitigate the mean stress level on blood constituents reducing the turbulent production. Computations are carried out by means of a finite-difference flow solver with a direct-forcing immersed boundary technique to handle fixed and moving bodies. The VGs are found to provide instabilities which corrupt the Kármán-like vortex shedding downstream of the leaflets, reducing the intensity of turbulent kinetic energy at the peak flow rate, thus lowering the local Reynolds shear stress. Conversely, the LTFV configuration provides comparable haemodynamic performance at peak flow rate but further reduced stress level in the deceleration phase. These interpretations are supported by probability density distributions from three-dimensional fields, and further corroborated by a pointwise mapping of the Taylor length scale and local energy spectra. The outcomes of this study might potentially be exploited to improve the design of new-generation MAVs, with the aim of decreasing the risk of thromboembolic complications.