Turbulent Energy Research Articles

Real-time adaptive optics for high-power laser beam correction in the strong turbulence

A combined adaptive optical system designed to correct the wavefront of light radiation distorted by the influence of strong atmospheric turbulence is presented. The system consists of a beam position stabilizer and a fast adaptive optical system operating in real time. Stabilization of the beam position is carried out by two electronically controlled tilt mirrors. The control loop includes two quadrant sensors and an FPGA (field-programmable gate array) that closes the feedback loop. Using information received from Shack-Hartmann wavefront sensor, a bimorph-based adaptive mirror, controlled by another FPGA, is able to compensate for wavefront aberrations for up to 23-th Zernike polynomial in real time. The system was tested under the laboratory turbulence conditions created by a fan heater. The bandwidth of the artificial turbulence in the experiments did not exceed 100 Hz, which corresponds to the average statistical state of the real atmosphere. Results of the correction of the wave front distorted by the artificial turbulence are presented. It is shown that when only a bimorph corrector is used, the value of wavefront tilt angles increases. This presents a certain problem, since a significant part of the turbulence energy falls on the wave front tilts. To address this problem, it is proposed additionally using a system for stabilizing the position of the light beam.

The effects of finite electron inertia on helicity-barrier-mediated turbulence

Understanding the partitioning of turbulent energy between ions and electrons in weakly collisional plasmas is crucial for the accurate interpretation of observations and modelling of various astrophysical phenomena. Many such plasmas are ‘imbalanced’, wherein the large-scale energy input is dominated by Alfvénic fluctuations propagating in a single direction. In this paper, we demonstrate that when strongly-magnetised plasma turbulence is imbalanced, nonlinear conservation laws imply the existence of a critical value of the electron plasma beta (the ratio of the thermal to magnetic pressures) that separates two dramatically different types of turbulence in parameter space. For betas below the critical value, the free energy injected on the largest scales is able to undergo a familiar Kolmogorov-type cascade to small scales where it is dissipated, heating electrons. For betas above the critical value, the system forms a ‘helicity barrier’ that prevents the cascade from proceeding past the ion Larmor radius, causing the majority of the injected free energy to be deposited into ion heating. Physically, the helicity barrier results from the inability of the system to adjust to the disparity between the perpendicular-wavenumber scalings of the free energy and generalised helicity below the ion Larmor radius; restoring finite electron inertia can annul, or even reverse, this disparity, giving rise to the aforementioned critical beta. We relate this physics to the ‘dynamic phase alignment’ mechanism (that operates under yet lower beta conditions and in pair plasmas), and characterise various other important features of the helicity barrier, including the nature of the nonlinear wavenumber-space fluxes, dissipation rates, and energy spectra. The existence of such a critical beta has important implications for heating, as it suggests that the dominant recipient of the turbulent energy, ions or electrons, can depend sensitively on the characteristics of the plasma at large scales.

An artificial neural network model for recovering small-scale velocity in large-eddy simulation of isotropic turbulent flows

Small-scale motions in turbulent flows play a significant role in various small-scale processes, such as particle relative dispersion and collision, bubble or droplet deformation, and orientation dynamics of non-sphere particles. Recovering the small-scale flows that cannot be resolved in large eddy simulation (LES) is of great importance for such processes sensitive to the small-scale motions in turbulent flows. This study proposes a subgrid-scale model for recovering the small-scale turbulent velocity field based on the artificial neural network (ANN). The governing equations of small-scale turbulent velocity are linearized, and the pressure gradient and the nonlinear convection term are modeled with the aid of the ANN. Direct numerical simulation (DNS) and filtered direct numerical simulation (FDNS) provide the data required for training and validating the ANN. The large-scale velocity and velocity gradient tensor are selected as inputs for the ANN model. The linearized governing equations of small-scale turbulent velocity are numerically solved by coupling the large-scale flow field information. The results indicate that the model established by the ANN can accurately recover the small-scale velocity lost in FDNS due to filtering operation. With the ANN model, the flow fields at different Reynolds numbers agree well with the DNS results regarding velocity field statistics, flow field structures, turbulent energy spectra, and two-point, two-time Lagrangian correlation functions. This study demonstrates that the proposed ANN model can be applied to recovering the small-scale velocity field in the LES of isotropic turbulent flows at different Reynolds numbers.

Gyrokinetic simulations of the kinetic electron effects on the electrostatic instabilities on the ITER baseline scenario

The linear and nonlinear simulations are carried out using the gyrokinetic code NLT for the electrostatic instabilities in the core region of a deuterium plasma based on the International Thermonuclear Experimental Reactor (ITER) baseline scenario. The kinetic electron effects on the linear frequency and nonlinear transport are studied by adopting the adiabatic electron model and the fully drift-kinetic electron model in the NLT code, respectively. The linear simulations focus on the dependence of linear frequency on the plasma parameters, such as the ion and electron temperature gradients , the density gradient and the ion–electron temperature ratio . Here, is the major radius, and and denote the electron and ion temperatures, respectively. is the gradient scale length, with denoting the density, the ion and electron temperatures, respectively. In the kinetic electron model, the ion temperature gradient (ITG) instability and the trapped electron mode (TEM) dominate in the small and large region, respectively, where is the poloidal wavenumber. The TEM-dominant region becomes wider by increasing (decreasing) ( ) or by decreasing . For the nominal parameters of the ITER baseline scenario, the maximum growth rate of dominant ITG instability in the kinetic electron model is about three times larger than that in the adiabatic electron model. The normalized linear frequency depends on the value of , rather than the value of or , in both the adiabatic and kinetic electron models. The nonlinear simulation results show that the ion heat diffusivity in the kinetic electron model is quite a lot larger than that in the adiabatic electron model, the radial structure is finer and the time oscillation is more rapid. In addition, the magnitude of the fluctuated potential at the saturated stage peaks in the ITG-dominated region, and contributions from the TEM (dominating in the higher region) to the nonlinear transport can be neglected. In the adiabatic electron model, the zonal radial electric field is found to be mainly driven by the turbulent energy flux, and the contribution of turbulent poloidal Reynolds stress is quite small due to the toroidal shielding effect. However, in the kinetic electron model, the turbulent energy flux is not strong enough to drive the zonal radial electric field in the nonlinear saturated stage. The kinetic electron effects on the mechanism of the turbulence-driven zonal radial electric field should be further investigated.

Numerical simulation of hydraulic characteristics and pollutant transport in the channels with different ice coverages

ABSTRACT In winter, rivers at high latitudes often freeze and an ice cover emerges at the free surface of the river. According to the coverage degree of the ice cover, rivers can be divided into free-flowing, partially frozen, and completely frozen. The presence of ice cover can greatly alter the hydraulic conditions of rivers, complicating the transport of pollutants in river channels. The distribution of pollutants in rivers with different ice coverages was simulated using the Detached Eddy Simulation (DES) model in this paper. The velocity distribution, the pollutant diffusion coefficient distribution, the turbulent kinetic energy distribution, and the vortex distribution with different ice coverages were analyzed. The velocity in the ice cover zone is at a lower rate than in the open flow zone. With the increase of the ice coverage, the turbulent kinetic energy of the ice cover area in partially frozen conditions gradually increases, which makes the water flow turbulence increase. The diffusion coefficient of pollutants in the ice cover area is greater than that in the open flow area, so pollutants disperse more quickly in the ice cover area. The turbulence energy and the diffusion coefficient have similar distribution characteristics beneath the ice cover. The presence of the ice cover promotes the movement of the vortex from the open flow area to the ice cover area, which may be the reason for the larger turbulence energy and the diffusion coefficient. The simulation results can provide a reference for ice disasters and water quality remediation.

Correction method for a shipborne ultrasonic anemometer in measuring the refractive index structure constant in a marine environment

The atmospheric refractive index structure constant (C n 2) was measured in a coastal region using a shipborne three-dimensional ultrasonic anemometer and a micro-thermometer. The results showed that the C n 2 measurements from both instruments were generally consistent but deviated in some cases, especially as the wind speed increased. Careful examination of the data revealed that this was due to noise introduced by wind-induced high-frequency oscillations of the extended arm carrying the ultrasonic probes, which also resulted in higher energy levels in the high-frequency region of the temperature spectrum. To address these issues, an attempt was made to filter the temperature data using a first-order low-pass filtering (LPF) algorithm. For our case, the corrected temperature spectrum reflects a reasonable distribution of turbulent energy at different frequencies, making it obey the −5/3 power law of Kolmogorov turbulence within the inertial subrange. In addition, the C n 2 values estimated from the corrected temperature data showed excellent agreement with the micro-thermometer measurements. The findings of this study provide experience and guidance for the measurement of optical turbulence in the marine environment.

Spatially resolved properties of extraplanar diffuse ionized gas in NGC 3511 and NGC 3513

ABSTRACT Gaseous, disc–halo interfaces are shaped by processes that are critical to galaxy evolution, including gas accretion and outflows. Extraplanar diffuse ionized gas (eDIG) layers are characterized by scale heights that largely exceed those predicted by their temperature, suggesting the presence of turbulent energy injection from star-formation feedback. However, the origin of this large-scale height remains uncertain. To explore the connection between eDIG and star-forming discs, we present a spatially resolved case study of a nearby pair of sub-$L_*$, intermediately inclined disc galaxies NGC 3511/3513. We decompose optical nebular lines observed using long-slit spectroscopy into narrow and broad velocity components. In NGC 3511, the broad component has three distinctive characteristics in comparison to the narrow component: (1) significantly higher velocity dispersions (a median $\langle \sigma \rangle _{\text{Broad}} = 24$ km s$^{-1}$compared to $\langle \sigma \rangle _{\text{Narrow}} = 13$ km s$^{-1}$), (2) elevated [N ii]$\lambda$6583/H$\alpha$ and [S ii]$\lambda$6716/H$\alpha$ line ratios, and (3) a rotational velocity lag. These characteristics support the origin of the broad component in an extraplanar, gaseous disc. In NGC 3513, the broad component reveals disc–halo circulation via localized outflows at radius $\lesssim 1$ kpc. For NGC 3511, we test a vertical hydrostatic equilibrium model with pressure support supplied by thermal and turbulent motions. Under this assumption, the eDIG velocity dispersion corresponds to a scale height $h_{z} \gtrsim 0.2 - 0.4$ kpc at $R = 3 - 5$ kpc, a factor of a few above the thermal scale height ($h_{z} \lesssim 0.1$ kpc). This highlights the importance of turbulent motions to the vertical structure of the gaseous, disc–halo interface.

Lagrangian Irreversibility and Energy Exchanges in Rotating-Stratified Turbulent Flows.

Turbulence in stratified and rotating turbulent flows is characterized by an interplay between waves and eddies, resulting in continuous exchanges between potential and kinetic energy. Here, we study how these processes affect the turbulent energy cascade from large to small scales, which manifests itself by an irreversible evolution of the relative kinetic energy between two tracer particles. We find that when r_{0}, the separation between particles, is below a characteristic length ℓ_{t}, potential energy is on average transferred to kinetic energy, reducing time irreversibility, and conversely when r_{0}>ℓ_{t}. Our Letter reveals that the scale ℓ_{t} coincides with the buoyancy length scale L_{B} over a broad range of configurations until a transition to a wave-dominated regime is reached.

Genetically-Based Active Flow Control And PIV Measurements Of A Circular Cylinder Wake

In the field of flow manipulation, considerable attention is devoted to controlling the wake of bluff bodies, which are characterized by the phenomenon of vortex shedding. Specifically, the control of the wake behind a single circular cylinder has garnered substantial research interest due to its engineering applications, such as reducing aerodynamic drag in the automotive and aerospace industries. Therefore, in the current work, through the application of the planar PIV technique, the fluid dynamic behavior of a circular cylinder wake controlled via synthetic jets (SJ) and Machine Learning (ML) methods is analyzed and discussed. ML algorithms are used to determine the optimal voltage signal for the loudspeaker, which effectively minimizes the aerodynamic drag of the cylinder. This approach overcomes the limitations associated with the a priori assumption of a parametric waveshape. In particular, the gradient-enriched machine learning control (gMLC) algorithm is chosen as optimization tool to search the best open-loop control policy for aerodynamic drag reduction. The cost function for this problem has been defined considering both the drag reduction contribution and the electrical power spent for the actuation. Initial optimization tests are performed by minimizing a cost function considering only the reduction in aerodynamic drag. Subsequently, a term related to the electrical power consumption for actuation is incorporated into the cost function. Once obtained the optimal control policies for these cases (hereinafter renamed CC1 and CC2, respectively), the physical mechanism responsible for reducing the aerodynamic drag is investigated more closely by analyzing the effect of the control laws on the turbulent flow statistics. Figure 1 reports a comparative assessment of the CC1 and CC2 with the baseline configuration and the configuration controlled by a sinusoidal law (CCS). The baseline configuration is characterized by an extended region of localized turbulent fluctuations in the far wake, where the time-averaged signature of von Kármán vortices is found. In contrast, all the controlled configurations show a global reduction in wake turbulence, with a peak of turbulent energy at the rear stagnation point due to the momentum injection from the SJ actuator. Notably, the CCS and CC2 configurations share similar flow field morphologies, while the CC1 configuration shows a greater reduction in turbulent fluctuations compared to the other controlled cases. This control law also achieves the largest drag reduction among all configurations studied reporting a 9.7% of drag reduction, compared to CCS and CC2, which exhibit similar reductions of 8.4% and 8.5%, respectively. Therefore, the optimization procedure has proven the capability of finding control policies able to outperform the traditional sinusoidal control widely studied in literature.

Analysis of informativeness of features of classification of dangerous weather events based on radar observation results

One of the crucial factors affecting the safety and regularity of state and civil aviation flights is the meteorological situation. The European territory of Russia is most characterized by dangerous meteorological phenomena associated with cumulonimbus clouds: shower, thunderstorms, hail, accompanied by high atmospheric turbulence. Currently, meteorological radar stations are an indispensable source of information about the weather situation for air transport. The criteria for the classification of meteorological phenomena used in modern radar stations are formed for each event separately and are based on knowledge only about the altitude distribution of radar reflectivity and air temperature, despite the fact that radar data assess the wind characteristics of the atmosphere. It is shown that optimization of the classification criteria for the mentioned meteorological phenomena should be realized by generalization of the criteria and their construction in accordance with the theory of statistical hypothesis distinction, as well as by additional use of information on atmospheric turbulence. Based on the analysis of radar signals reflected from the meteorological events of shower, thunderstorm, and hail, probability distributions of reflectivity and specific dissipation rate of turbulent energy were obtained. Statistical analysis of probability distribution densities was carried out for: the maximum value of reflectivity Zmax, its dependence on height H(Zmax), as well as the maximum specific dissipation rate of turbulent energy EDRmax and the value H(EDRmax). The classification criterion based on the maximum probability functional was chosen to determine the structure of classification algorithms and decision rules. At the same time under the acceptable confidence is accepted the value of the probability of correct classification not lower than 0.8. For the accepted criterion the decision thresholds are constructed and the complete matrices of classification probabilities are calculated. The results of calculations showed that the worst informativeness in the classification of dangerous meteorological events of cumulonimbus cloudiness have parameters H(Zmax), H(EDRmax). Parameters Zmax, EDRmax have greater separating ability, but even for them the confidence of classification is unacceptable. In the article to increase the confidence of classification the joint use of features in the form of multivariate probability distribution densities of information parameters was applied. The best results are achieved when three p(Zmax,H(Zmax),EDRmax) and four p(Zmax,H(Zmax),EDRmax,H(EDRmax)) features are used. In the probability matrices for these cases, the maximum and acceptable at 0.8 level of probabilities of correct classification are achieved. Thus, the expansion of the feature space due to atmospheric turbulence is justified in the problem under consideration. These results will be refined with increasing observation time and will vary for different climatic zones. In general, the decision thresholds for classifying dangerous meteorological events of cumulonimbus cloudiness should be adaptive.

The co-benefits of offshore wind under the UK Renewable Obligation scheme: Integrating sustainability in energy policy evaluation

Offshore wind energy is a key technology for decarbonising the UK electricity system. It also delivers significant socio-environmental co-benefits. Assessing these co-benefits is essential for energy policy under turbulent energy market conditions emerging in the wake of geopolitical unrest. This study focuses on assessing the co-benefits and costs associated with offshore wind electricity generation for the Renewable Obligation scheme in the UK, which although being phased out, currently supports more offshore wind generation in 2023 than its Contracts-for-Difference replacement scheme. Comparing offshore wind co-benefits with support scheme costs provides an objective evaluation of the scheme's success. Results indicate that reduced energy imports contribute to co-benefits of £5.9 ± 0.3bn and £4.9 ± 0.3bn in simple and flexible scenarios respectively. Emissions reductions lead to £4.4 ± 0.9bn in simple and £3.9 ± 0.8bn in flexible scenario. The employment benefits amounted £1 ± 0.2bn. The cost of the Renewable Obligation scheme amounted to £18.8 ± 3.8bn, indicating that the co-benefits can cover 60% and 52% of the policy costs, in simple and flexible scenarios, respectively. This analysis supports a case for monetising the wider co-benefits of energy technology implementation to support institutions and policy makers in the integration and evaluation of sustainability in energy policy in a way that goes beyond the electricity price.

Spatial and Temporal Variability of Turbulent Mixing in the Deep Northwestern Pacific

AbstractSmall‐scale turbulent mixing supplies potential energy for the upwelling of deep waters in the abyssal ocean, a key component of the global overturning circulation. This process is particularly significant in critical regions such as the Northwestern Pacific where the upwelling structure of deep waters remains poorly understood due to limited knowledge of deep ocean mixing. Here, we investigate the full‐depth spatiotemporal variability of turbulent mixing in the deep Northwestern Pacific based on hydrographic data collected over repeated surveys. Nineteen‐year‐average diapycnal diffusivity of 1.42 × 10−4 m2 s−1 is reveled in the deep Philippine Sea, indicating significantly stronger mixing compared to the stratified ocean interior. Spatially, turbulent mixing strengthens toward the bottom and intensifies westward from the open Pacific to the Philippine Sea due to rough topography. At certain mixing hotspots, enhanced mixing can penetrate up to 2,500 m above the bottom, suggesting a substantial potential for upwelling. Below 2,000 m, turbulent mixing exhibits pronounced seasonal variation that deep mixing is more intense in summer (winter) than in winter (summer) in the West Caroline Basin (the Parece Vela Basin). This spatially varying seasonality may be attributed to the inhomogeneous internal tidal energy dissipation in the Northwestern Pacific. Our study will serve to clarify the modulation of turbulent mixing to deep‐water mass transformation and circulation in the Northwestern Pacific.

Kelvin–Helmholtz Instability “Tube” and “Knot” Dynamics. Part III: Extension of Elevated Turbulence and Energy Dissipation into Increasingly Viscous Flows

Abstract A companion paper by Fritts et al. reviews extensive evidence for Kelvin–Helmholtz instability (KHI) “tube” and “knot” (T&K) dynamics at multiple altitudes in the atmosphere and in the oceans that reveal these dynamics to be widespread. A second companion paper by Fritts and Wang reveals KHI T&K events at larger and smaller scales to arise on multiple highly stratified sheets in a direct numerical simulation (DNS) of idealized, multiscale gravity wave–fine structure interactions. These studies reveal the diverse environments in which KHI T&K dynamics arise and suggest their potentially ubiquitous occurrence throughout the atmosphere and oceans. This paper describes a DNS of multiple KHI evolutions in wide and narrow domains enabling and excluding T&K dynamics. These DNSs employ common initial conditions but are performed for decreasing Reynolds numbers (Re) to explore whether T&K dynamics enable enhanced KHI-induced turbulence where it would be weaker or not otherwise occur. The major results are that KHI T&K dynamics extend elevated turbulence intensities and energy dissipation rates ε to smaller Re. We expect these results to have important implications for improving parameterizations of KHI-induced turbulence in the atmosphere and oceans. Significance Statement Turbulence due to small-scale shear flows plays important roles in the structure and variability of the atmosphere and oceans extending to large spatial and temporal scales. New modeling reveals that enhanced turbulence accompanies Kelvin–Helmholtz instabilities (KHIs) that arise on unstable shear layers and exhibit what were initially described as “tubes” and “knots” (T&K) when they were first observed in early laboratory experiments. We perform new modeling to explore two further aspects of these dynamics: 1) can KHI T&K dynamics increase turbulence intensities compared to KHI without T&K dynamics for the same initial fields and 2) can KHI T&K dynamics enable elevated turbulence and energy dissipation extending to more viscous flows? We show here that the answer to both questions is yes.

Effect of variable conditions on transient flow in a solid–liquid two-phase centrifugal pump

To investigate the influence of altering operational parameters on the transient flow characteristics within the flow channel of a solid–liquid two-phase centrifugal pump, this study employs a particle model based on the Euler–Euler method. Utilizing the standard k–e model, flow field simulations are conducted using the ANSYS-CFX software. Specifically, the study focuses on throttle regulation scenarios, monitoring and comparing the external and internal flow parameters of the solid–liquid two-phase pump with those of a clear water medium centrifugal pump. The results indicate notable modifications in head, efficiency, and shaft power due to the presence of solid particles in the two-phase flow. Decreasing flow rates during throttle regulation lead to fluctuations in pressure and turbulence energy distribution. Furthermore, under identical operational conditions, the variable working conditions of the solid–liquid pump result in increased flow rates of solid-phase particles near the impeller's outer edge, with particles shifting toward the middle and tail of the vane suction surface. This phenomenon exacerbates wear on the vane tail of the suction surface. Moreover, the study identifies that changing operational conditions in the solid–liquid dual-flow centrifugal pump contribute to increased axial forces, consequently leading to pump vibrations. Overall, this research elucidates the transient flow characteristics within the flow channel of solid–liquid two-phase centrifugal pumps under varied operational conditions, serving as a foundational reference for assessing the stability of such pumps.

Evaluation of seedless wavelet-based optical flow velocimetry for schlieren images

In harsh flow environments, traditional particle-based velocimetry methods face challenges. This study explores the use of seedless schlieren images for velocimetry through a novel algorithm, namely, wavelet-based optical flow velocimetry (wOFV). Various data term constraints for wOFV were examined. It is found that the data term derived from the integrated continuity equation (ICE) outperformed the conventional displaced frame difference constraint and the schlieren-tailored constraints (SE and SSE). Evaluation based on the root mean square error (RMSE) and turbulence energy spectrum (TES) reveals that the choice of wavelet becomes insignificant for the optimal estimated velocity field when the wavelet support length is sufficiently long. In addition, the implementation of a proper truncation in wOFV shows little dependence of the RMSE on the weighting coefficient, therefore alleviating the uncertainty associated with selecting an appropriate weighting coefficient. It is found that the retrieved flow field from schlieren images approximates a down-sampled result based on available structural scales in images. Considering the prevalence of under-resolved velocity field in practical applications, schlieren-based wOFV offers a reasonable alternative to particle-based velocimetry, particularly in harsh flow environments.

Numerical analyses of water swirls in aquaculture tanks

Water swirls were observed in both model and prototype aquaculture tanks with bottom drains. This phenomenon was seldom replicated in studies of flow fields of water in aquaculture tanks with computational fluid dynamics. A commonality of these studies is that the linear eddy-viscosity turbulence models were employed. This study delves into the water swirls from the aspect of the generation of the turbulence kinetic energy; both the linear and nonlinear eddy-viscosity turbulence models are used, as well as a Reynolds stress turbulence model. A novel identification method is utilized to pinpoint vortex structures. Numerical results affirm the outstanding performance of the Reynolds stress model to estimate the flow fields of water in aquaculture tanks. Both the linear and nonlinear eddy-viscosity models overestimate the kinetic turbulence energy in the stagnation zone of swirls. The overestimation can be restrained by including the effect of the streamline curvature correction (SCC) to the turbulence production term. Even so, the SCC does not help to improve the estimating accuracy between the Reynolds stress tensor and the mean rate-of-strain tensor. While the nonlinear model offers some improvements, the Reynolds stress model provides a more effectvie solution. After that, we calculate the flow fields of water in aquaculture tanks with different inlet–outlet configurations with the Reynolds stress turbulence model. Both the vertical and horizontal scales of water swirls increase with inlet velocities and Froude numbers, where the Froude number is based on the bottom draining velocity and the water depth above the bottom drain. The vertical distributions of the water residence time in aquaculture tanks are shown to improve the design of tanks.

Sign-Indefinite Invariants Shape Turbulent Cascades.

We highlight a noncanonical yet natural choice of variables for an efficient derivation of a kinetic equation for the energy density in nonisotropic systems, including internal gravity waves on a vertical plane, inertial, and Rossby waves. The existence of a second quadratic invariant simplifies the kinetic equation and leads to extra conservation laws for resonant interactions. We analytically determine the scaling of the radial turbulent energy spectrum. Our findings suggest the existence of an inverse energy cascade of internal gravity waves, from small to large scales, in practically relevant scenarios.

Turbulent blood flow in a cerebral artery with an aneurysm

Unruptured intracranial aneurysms are common in the general population, and many uncertainties remain when predicting rupture risks and treatment outcomes. One of the cutting-edge tools used to investigate this condition is computational fluid dynamics (CFD). However, CFD is not yet mature enough to guide the clinical management of this disease. In addition, recent studies have reported significant flow instabilities when refined numerical methods are used. Questions remain as to how to properly simulate and evaluate this flow, and whether these instabilities are really turbulence. The purpose of the present study is to evaluate the impact of the simulation setup on the results and investigate the occurrence of turbulence in a cerebral artery with an aneurysm. For this purpose, direct numerical simulations were performed with up to 200 cardiac cycles and with data sampling rates of up to 100,000 times per cardiac cycle. Through phase-averaging or triple decomposition, the contributions of turbulence and of laminar pulsatile waves to the velocity, pressure and wall shear stress fluctuations were distinguished. For example, the commonly used oscillatory shear index was found to be closely related to the laminar waves introduced at the inlet, rather than turbulence. The turbulence energy cascade was evaluated through energy spectrum estimates, revealing that, despite the low flow rates and Reynolds number, the flow is turbulent near the aneurysm. Phase-averaging was shown to be an approach that can help researchers better understand this flow, although the results are highly dependent on simulation setup and post-processing choices.

The Origin of the Slow-to-Alfvén Wave Cascade Power Ratio and Its Implications for Particle Heating in Accretion Flows

The partition of turbulent heating between ions and electrons in radiatively inefficient accretion flows plays a crucial role in determining the observational appearance of accreting black holes. Modeling this partition is, however, a challenging problem because of the large scale-separation between the macroscopic scales at which energy is injected by turbulence and the microscopic ones at which it is dissipated into heat. Recent studies of particle heating from collisionless damping of turbulent energy have shown that the partition of energy between ions and electrons is dictated by the ratio of the energy injected into the slow and Alfvén wave cascades as well as the plasma β parameter. In this paper, we study the mechanism of the injection of turbulent energy into slow- and Alfvén-wave cascades in magnetized shear flows. We show that this ratio depends on the particular (r ϕ) components of the Maxwell and Reynolds stress tensors that cause the transport of angular momentum, the shearing rate, and the orientation of the mean magnetic field with respect to the shear. We then use numerical magnetohydrodynamic shearing-box simulations with background conditions relevant to black hole accretion disks to compute the magnitudes of the stress tensors for turbulence driven by the magneto-rotational instability and derive the injection power ratio between slow and Alfvén wave cascades. We use these results to formulate a local subgrid model for the ion-to-electron heating ratio that depends on the macroscopic characteristics of the accretion flow.

Thermal convection of viscoelastic fluids in concentric rotating cylinders: Elastic turbulence and kinetic energy budget analysis

Thermal convection of viscoelastic fluids in concentric rotating cylinders: Elastic turbulence and kinetic energy budget analysis