Turbulent Field Research Articles

Turbulent Magnetic Reconnection as an Acceleration Mechanism in Earth’s Magnetotail

Using electric and magnetic fields measured by the Magnetospheric Multiscale (MMS) mission, we construct a test-particle simulation of a turbulent magnetic reconnection region to investigate observed ion acceleration. We identify three types of energized ions: (1) ion jets, (2) Speiser-like energized ions—both of which carry significant energy but do not produce a strong energetic (>80 keV) tail in the ion distribution—and (3) a separate but sizable population of ions that are accelerated to significantly higher energies (>80 keV) by the turbulent fields. The majority of ions that undergo energization by the turbulent fields cross the magnetic null plane multiple times. By preferentially energizing these particles, the turbulence creates a separate population of ions that mostly exits in the dawn direction of the magnetotail and forms a high-energy power-law tail in the ion flux-energy distribution. We also find that the highest acceleration energies are limited by the size of the turbulent region (with respect to ion gyroradii). Since turbulence is widespread in astrophysical plasmas and has no a priori limit on scale size, the MMS observations suggest turbulence may have a significant role in particle acceleration.

Review of recent analytical advances in the spectroscopy of hydrogenic lines in plasmas

Abstract Broadening of hydrogenic spectral lines is an important tool in spectroscopic diagnostics of various laboratory and astrophysical plasmas. We review recent analytical advances in three areas. First, we review the analytical solution for the splitting of hydrogenic lines under the combination of a circularly polarized electromagnetic wave with a strong magnetic field. Practical applications of this solution relate to the spectroscopic diagnostic of the electron cyclotron waves and to the relativistic laser–plasma interactions. Second, we review analytical results concerning the Stark–Zeeman broadening of the Lyman-alpha (Ly-alpha) line in plasmas. These results allow for the Stark width of the Ly-alpha π-component to be used for the experimental determination of the ion density or of the root-mean-square field of a low-frequency electrostatic plasma turbulence in the situation where the Zeeman effect dominates over the Stark effects. Third, we review recent analytical advances in the area of the intra-Stark spectroscopy: three different new methods, based on the emergent phenomenon of the Langmuir-wave-caused structures (“L-dips”) in the line profiles, for measuring super-strong magnetic fields of the GigaGauss range developing during relativistic laser–plasma interactions. We also review the rich physics behind the L-dips phenomenon – because there was a confusion in the literature in this regard.

Universal relative scaling of longitudinal structure functions in shear-dominated turbulence

Shear significantly influences turbulence in the energy-containing range of shear-dominated flows, and the longitudinal structure functions do not have a universal form as they do in homogeneous isotropic turbulence. Despite this, the relative scaling of structure functions exhibits universal sub-Gaussian behaviour in shear-dominated flows, in particular for turbulent boundary layers, channels and Taylor–Couette flows. Our investigation of a turbulent vertical buoyancy layer at $Pr = 0.71$ using direct numerical simulation shows this universality even in moderate-Reynolds-number buoyancy-driven but shear-dominated boundary layers. It is demonstrated that the universality is related to the energy density of the eddies, which attains a hierarchical equilibrium in the energy-containing range of shear-dominated turbulence. We conjecture that the universal sub-Gaussian behaviour of the energy density of the energy-containing range, which was considered to be non-trivial in prior studies, is related to the universal anomalous scaling exponents of the inertial subrange turbulence. Based on this conjecture, we propose a hypothesis that relates large-scale eddies and the intermittent dissipation field in shear-dominated turbulence, highlighting a relationship between large and small scales. A phenomenological model is also developed to predict the scaling, which is verified using data from a turbulent boundary layer, half-channel and vertical buoyancy layer at friction Reynolds numbers spanning four orders of magnitude. Excellent agreement is observed.

On the Effect of Nonlinear Damping Sources in Output-Only Identification Methods Applied to Floating Wind Turbines

Output-only methods for modal identification are only strictly valid if a set of requirements are fulfilled regarding both structural and environmental conditions. A particularly challenging effect in wind turbine dynamics is the significant presence of nonlinear damping sources coming from aerodynamic forces and, in offshore applications, hydrodynamic forces on the substructure. In this work, the impact of these terms is firstly discussed in analytical terms, and then the corresponding effect on the performance of the covariance-driven stochastic subspace identification is evaluated on a single-degree-of-freedom model. The analysis is then extended to a full hydro-aeroelastic simulation of a 5 MW floating wind turbine using the open source software OpenFAST, mimicking the structural response in free decay tests and in parked conditions with turbulent wind fields. The results show that output-only identification methods are applicable in these challenging scenarios, but the results obtained must be carefully interpreted, since their dependence on the environmental conditions and motion amplitude imply that they are not directly translated into the structure properties, although still closely related to them.

Boundary fluid constraints during electrochemical jet machining of large size emerging titanium alloy aerospace parts in gas–liquid flows: Experimental and numerical simulation

Large size titanium alloy parts are widely used in aerospace. However, they are difficult to manufacture using mechanical cutting technology because of severe tool wear. Electrochemical jet machining is a promising technology to achieve high efficiency, because it has high machining flexibility and no machining tool wear. However, reports on the macro electrochemical jet machining of large size titanium alloy parts are very scarce, because it is difficult to achieve effective constraint of the flow field in macro electrochemical jet machining. In addition, titanium alloy is very sensitive to fluctuation of the flow field, and a turbulent flow field would lead to serious stray corrosion. This paper reports a series of investigations of the electrochemical jet machining of titanium alloy parts. Based on the flow analysis and experiments, the machining flow field was effectively constrained. TB6 titanium alloy part with a perimeter of one meter was machined. The machined surface was smooth with no obvious machining defects. The machining process was particularly stable with no obvious spark discharge. The research provides a reference for the application of electrochemical jet machining technology to achieve large allowance material removal in the machining of large titanium alloy parts.

Parallel Diffusion Coefficient of Energetic Charged Particles in the Inner Heliosphere from the Turbulent Magnetic Fields Measured by Parker Solar Probe

Diffusion coefficients of energetic charged particles in turbulent magnetic fields are a fundamental aspect of diffusive transport theory but remain incompletely understood. In this work, we use quasi-linear theory to evaluate the spatial variation of the parallel diffusion coefficient κ ∥ from the measured magnetic turbulence power spectra in the inner heliosphere. We consider the magnetic field and plasma velocity measurements from Parker Solar Probe made during Orbits 5–13. The parallel diffusion coefficient is calculated as a function of radial distance from 0.062 to 0.8 au, and the particle energy from 100 keV to 1 GeV. We find that κ ∥ increases exponentially with both heliocentric distance and energy of particles. The fluctuations in κ ∥ are related to the episodes of large-scale magnetic structures in the solar wind. By fitting the results, we also provide an empirical formula of κ ∥ = (5.16 ± 1.22) × 1018 r 1.17±0.08 E 0.71±0.02 (cm2 s−1) in the inner heliosphere, which can be used as a reference in studying the transport and acceleration of solar energetic particles as well as the modulation of cosmic rays.

A Combined Model of Diffusion Model and Enhanced Residual Network for Super-Resolution Reconstruction of Turbulent Flows

In this study, we introduce a novel model, the Combined Model, composed of a conditional denoising diffusion model (SR3) and an enhanced residual network (EResNet), for reconstructing high-resolution turbulent flow fields from low-resolution flow data. The SR3 model is adept at learning the distribution of flow fields. The EResNet architecture incorporates a long skip connection extending from the input directly to the output. This modification ensures the preservation of essential features learned by the SR3, while simultaneously enhancing the accuracy of the flow field. Additionally, we incorporated physical gradient constraints into the loss function of EResNet to ensure that the flow fields reconstructed by the Combined Model are consistent with the direct numerical simulation (DNS) data. Consequently, the high-resolution flow fields reconstructed by the Combined Model exhibit high conformity with the DNS results in terms of flow distribution, details, and accuracy. To validate the effectiveness of the model, experiments were conducted on two-dimensional flow around a square cylinder at a Reynolds number (Re) of 100 and turbulent channel flow at Re = 4000. The results demonstrate that the Combined Model can reconstruct both high-resolution laminar and turbulent flow fields from low-resolution data. Comparisons with a super-resolution convolutional neural network (SRCNN) and an enhanced super-resolution generative adversarial network (ESRGAN) demonstrate that while all three models perform admirably in reconstructing laminar flows, the Combined Model excels in capturing more details in turbulent flows, aligning the statistical outcomes more closely with the DNS results. Furthermore, in terms of L2 norm error, the Combined Model achieves an order of magnitude lower error compared to SRCNN and ESRGAN. Experimentation also revealed that SR3 possesses the capability to learn the distribution of flow fields. This work opens new avenues for high-fidelity flow field reconstruction using deep learning methods.

The Mechanism of Dust Transportation Based on Wind Tunnel Experiments and Numerical Simulations

The process of dust transportation is widespread, leading to the formation of regions such as the Loess Plateau. In order to understand the mechanisms of dust particle transportation, this study conducted wind tunnel experiments to simulate natural wind-driven dust transport processes. Theoretical derivations were carried out to establish the relationship between particle size and transportation distance, which was then validated through numerical simulations. The following conclusions were drawn: (1) wind tunnel experiments, theoretical derivations, and numerical simulations yielded consistent results, indicating the effectiveness of the wind tunnel experiments; (2) Under the influence of wind forces, the ideal transportation distance of particles is inversely proportional to the square of their size; (3) turbulent wind fields have a minor impact on dust transport, while particle roundness has a significant effect on transport; (4) clay particles and dust particles in loess regions share the same source areas and transport pathways.

Laser-induced emission from iron oxide nanoparticles in spray-flame synthesis: in situ high-speed microscopy

Spray-flame synthesis uses low-cost precursors dissolved in organic solvents to produce functional metaloxide nanoparticles. In the spray flame, the precursor-laden droplets show frequent and intense thermally-induced disruption, so-called puffing and micro-explosion. This process is often correlated with high uniformity of particle sizes. Whether puffing and micro-explosion are also directly associated with the formation or release of iron oxide nanoparticles is not clear. Also, the spatiotemporal evolution of nanoparticles in the turbulent flow field of the flame is largely unknown from experiments. We performed simultaneous high-speed microscopic imaging of droplet shadowgraphs at 360 kHz as well as elastic light scattering (ELS) and laser-induced emission (LIE) of nanoparticles at 40 kHz. Comparing ELS and LIE images allows distinguishing signals from droplets, flame, and nanoparticles, as only the nanoparticles will appear in images from both methods. ELS and LIE show nanoparticles as thin narrow filaments, presumably following the local flow. Nanoparticle filaments are found at a height of 50 mm and more above the burner in the spray flame. The filaments show increasing LIE signal and higher confinement with increasing height above the burner. The appearance of LIE and thus nanoparticles does not directly correlate with the presence of droplets or their disruption.

Analysis of Confined Jet Impingement in Converging Annular Microchannel Heat Sinks

Jet impingement cooling is deemed an excellent choice for the thermal management of high-power electronics. However, high-pressure drop penalties and low local heat transfer coefficients in regions far from the jet zone are its drawbacks. Although it is reported that recirculation areas appear because of the entrainment, the effects of recirculation size on thermal behavior are not understood well enough. Here, jet impingement heat sinks with converging annular channels are employed in a numerical investigation to minimize the adverse cooling effects associated with an impinging jet in a microchannel. The realizable k−ε turbulent model is used for modeling thermal and turbulent flow fields (Re=5,000 to 25,000). It was found that the different flow recirculation zones in small scales are responsible for the enhanced heat transfer rate. While the thermal performance of a converging wall jet impingement heat sink is higher than its flat wall counterpart at low Re numbers, the thermal performance results are in favor of the flat wall jet impingement heat sink at high Re numbers. The flow recirculation area shrinks in converging channels at high Re numbers, thereby deteriorating the thermal performance of the converging channel compared with a flat wall jet heat sink. Also, it was found that employing steeper converging channels shrinks the flow recirculation region, resulting in up to 59% lower pressure drops at Re=25,000. The present study examines the role of flow recirculation at different Re numbers on the thermohydraulic performance of jet impingement converging annular heat sinks.

Effect of network architecture on physics-informed deep learning of the Reynolds-averaged turbulent flow field around cylinders without training data

Unsupervised physics-informed deep learning can be used to solve computational physics problems by training neural networks to satisfy the underlying equations and boundary conditions without labeled data. Parameters such as network architecture and training method determine the training success. However, the best choice is unknown a priori as it is case specific. Here, we investigated network shapes, sizes, and types for unsupervised physics-informed deep learning of the two-dimensional Reynolds-averaged flow around cylinders. We trained mixed-variable networks and compared them to traditional models. Several network architectures with different shape factors and sizes were evaluated. The models were trained to solve the Reynolds-averaged Navier-Stokes equations incorporating Prandtl’s mixing length turbulence model. No training data were deployed to train the models. The superiority of the mixed-variable approach was confirmed for the investigated high Reynolds number flow. The mixed-variable models were sensitive to the network shape. For the two cylinders, differently deep networks showed superior performance. The best fitting models were able to capture important flow phenomena such as stagnation regions, boundary layers, flow separation, and recirculation. We also encountered difficulties when predicting high Reynolds number flows without training data.

The Thermophysical Aspects of the Transformation of Porous Structures in Versatile Nanostructured Materials

The technology of obtaining porous nanostructures is based on ecological organosilicon materials and their uses in some spheres of human life, for example, for medical preparations, for thermal insulation of building structures and industrial equipment, and for cleaning. The purpose of this study was to establish correlations between various experimental parameters (shear stress, speed pulsations, temperature, viscosity, and processing time) and the rheological characteristics of suspensions obtained by the method of liquid-phase dispersion; it was a study of hydrodynamic effects and the processes of heat and mass exchange in liquid systems during the liquid-phase dispersion of hydrogel monoliths by means of discrete-pulse activation in a special rotary apparatus. The dehydration of hydrogels was carried out by two methods: convective drying in a layer and spraying in the coolant flow. Experiments have shown that the key parameters for obtaining stable homogeneous suspensions are a synergistic combination of concentration factors and processing time. To obtain adsorbents in the form of pastes with specified adsorption properties and a monolith size of up to 300 μm, the optimal parameters were a hydrogel concentration of 70% and a processing time in the double-recirculation mode. Xerogels obtained by convective drying are a polydisperse mixture of strong monoliths and fragile aggregates. In contrast, xerogel monoliths obtained by spray drying show great homogeneity in terms of dispersion and strength characteristics. The rheological parameters of the hydrogel dispersions, which depend on the concentration and hydrodynamic treatment modes, are the dominant factors affecting the moisture extraction during drying. This study marks the first investigation into the resilience of porous organosilicon structures against the influence of intense turbulence fields and mechanical stresses experienced within the rotor apparatus during suspension production.

Numerical study on the sensitivity of photovoltaic panels to wind load on array layout

Offshore floating photovoltaics began to gradually enter people's vision due to the limitation of inland land resources. However, the offshore environment is harsh, and wind load is an essential factor in floating photovoltaic design. At the same time, the photovoltaic panel will be subjected to a large wind load in strong typhoon weather, which may cause a drag-driven or lift-driven instability for offshore floating photovoltaics. In this work, the effects of wind loads on six PV array structure configurations installed on offshore floating PV platforms at high Reynolds numbers are investigated by using the computational fluid dynamics numerical method. The differences in wind load on photovoltaic panels under different layout structures are analyzed and explained, including analysis of velocity and pressure distribution, turbulence field, and lift and drag coefficient of photovoltaic panels. The results showed array b with symmetrically staggered has less sensitivity to wind direction, less lifting torque, and relatively small pressure on the surface of the photovoltaic panel, which is a potential arrangement.

Secondary flows in a flat diffuser and their significance for the formation of a turbulence field

Secondary flows in a flat diffuser and their significance for the formation of a turbulence field

Stochastic subgrid-scale modeling for particles dispersion and deposition for a filtered DNS channel flow field

The effect of subgrid-scale velocity fluctuations on the deposition and dispersion of solid particles in a filtered DNS turbulent channel flow at Reτ=180, and for particles with Stokes numbers of St = 1, 2, 5, 24 was studied. First, the turbulent flow field was simulated using the DNS on a high-resolution grid. Then, the filtered DNS flow fields were generated using several low-resolution grids. Particle tracking was performed for the DNS and filtered DNS channel flow fields, and the effects of filtering on particle deposition and concentration were studied. It was shown that filtering significantly decreases the particle deposition velocities at lower Stokes numbers (St = 1, 2, 5). However, at higher Stokes numbers (St = 24), the deposition velocity was less affected. Next, the ability of a stochastic model to generate the correct particle deposition velocities and concentration profiles was studied. A Langevin stochastic equation for modeling the subgrid-scale (SGS) fluid velocity fluctuations as seen by particles was developed and tested. The two input parameters of the stochastic model are the variance of SGS fluctuations in the wall-normal direction and the Lagrangian SGS time-scale. It was seen that the model prediction is sensitive to the SGS time scale used in the Langevin equation. The model was capable of predicting the correct deposition velocities and concentration profiles of lower inertia particles when the proper time-scale was used. For higher inertia particles and when a larger amount of energy was removed by filtering, the model was unable to predict the deposition velocities.

Application of a new DES model based on Wray-Agarwal turbulence model in flow simulation of a mixed-flow pump

In recent years, it has been demonstrated for many two- and three-dimensional external and internal turbulent flows that the one-equation Wray-Agarwal turbulence model can compute the complex turbulent flow fields with high computational accuracy, excellent computational convergence and efficiency. In this paper, Wray-Agarwal (WA) turbulence model is employed as part of a detached eddy simulation (DES) method to predict the performance of a mixed-flow pump. By comparing the computations with the experimental results, the differences and similarities between the WA-DES model and the Shear Stress Transfer (SST) k-ω model in predicting the internal and external flow characteristics of the pump are analyzed. The results show that both the SST k-ω model and the WA-DES model can reasonably predict the performance of the pump between 0.6 Q and 1.2 Q, where Q is the design flow rate; however, they have their own merits and deficiencies in predicting head and efficiency of the pump at low and high flow rates. For the velocity field in the rotor-stator interaction region, the WA-DES model shows better prediction accuracy since it can accurately predict the large-scale recirculating vortex structure at the inlet of the guide vane. The SST k-ω model over-predicts the separated flow region, which leads to the emergence of a small vortex structure before the backflow region of the pump. Although the turbulent eddy viscosity predicted by the WA-DES model is higher than that of the SST k-ω model and there is small difference in the results for the scale of the tip leakage vortex (TLV) between the two models, the overall simulation results of the WA-DES model for the high turbulent viscosity region and the pressure increase in the impeller are consistent with the SST k-ω model results. The results of this paper demonstrate the potential of WA-DES model for prediction of flows in pumps.

Effects of grain magnetic properties and grain growth on synthetic dust polarization of MHD simulations of low-mass Class 0/I YSOs

ABSTRACT Thermal dust polarization is a powerful tool to probe magnetic fields ($\boldsymbol{B}$) and grain properties. However, a systematic study of the dependence of dust polarization on grain properties in protostellar environments is not yet available. In this paper, we post-process a non-ideal MHD simulation of a collapsing protostellar core with our updated POLARIS code to study in detail the effects of iron inclusions and grain growth on thermal dust polarization. We found that superparamagnetic (SPM) grains can produce high polarization degree of $p \sim 10\!-\!40~{{\ \rm per\ cent}}$ beyond ∼500 au from the protostar because of their efficient alignment by magnetically enhanced radiative torque mechanism. The magnetic field turbulence in the envelope causes the decrease in p with increasing emission intensity I as p ∝ Iα with the slope α ∼ −0.3. But within 500 au, SPM grains tend to have inefficient internal alignment and be aligned with $\boldsymbol{B}$ by RATs only, producing lower $p \sim 1~{{\ \rm per\ cent}}$ and a steeper slope of α ∼ −0.6. For paramagnetic (PM) grains, the alignment loss of grains above $1\, {\mu \rm {m}}$ in the inner ∼200 au produces $p \lt \lt 1~{{\ \rm per\ cent}}$ and the polarization hole with α ∼ −0.9. Grain growth can increase p in the envelope for SPM grains, but cause stronger depolarization for SPM grains in the inner ∼500 au and for PM grains in the entire protostellar core. Finally, we found the increase of polarization angle dispersion function S with iron inclusions and grain growth, implying the dependence of B-field strength measured using the David–Chandrasekhar–Fermi technique on grain alignment and grain properties.

Research on enhancing separation of ultra‐fine droplets using turbulators between adjacent demister plates in WFGD systems

AbstractTo enhance the performance of demister applied in wet flue gas desulphurization systems, flow turbulators are equipped between adjacent plates to reconstruct flow field. Both experimental and numerical approaches are employed to investigate the influence of various kinds of turbulator configurations upon removal of droplets within the range of 5–50 μm obeying Rosin‐Rammler distribution. Turbulators including spoiler, square column, concave groove, perforated concave groove, and triangular and cylinder columns are compared, among which spoiler provided the highest overall efficiency while square column yields the best graded efficiency for 5 μm droplets group. Furthermore, moving the spoiler towards the core region of the demister ducts received better performance due to augmented interaction between spoiler and drainage channels, which performed an essential role in droplets collection. Based on this knowledge, spoilers are optimized by changing their angle of attack and size; the result is positive since overall separation efficiency can be improved to 100%, along with graded efficiencies for 10 and 5 μm groups achieving 95.97% and 27.26%, respectively, much higher than those of baseline demister without turbulators. This study indicates that inertial‐based demisters have great potential in separating ultra‐fine droplets through reorganizing turbulence field, thus extra system loss can be avoided by abandoning additional filter components.

Experimental and numerical research on the coupled mechanisms of cavitation effect in a Venturi-type bubble generator

Venturi type bubble generator has a broad application in various fields and its bubble performance is closely related to the strong turbulent flow field. The interaction between bubble breakup and cavitation flow is not fully explained. In present work, the influence of cavitation on the suction performance and gas-phase transport pattern of a Venturi-type bubble generator is investigated by experiments and numerical simulations. The results show that the pressure ratio of 0.58 is the critical cavitation condition and the suction of the Venturi type bubble generator reaches the limiting value. The Venturi type bubble generator almost lost its suction capacity at the pressure ratio decreased to 0.27. However, the cavitation effect has a suppressive effect on the suction volume. The quasi-periodicity of the air inlet velocity pulsation and cavity development is highly consistent. Further research found that the blocking effect formed by return jets and pressure waves from cavity collapse is the main factor in reduced suction volume. The mechanisms of cavity shedding and collapse have a similar evolutionary model to the bubble breakup mechanisms in the Venturi-type generator.

Measurement-driven large-eddy simulations of a diurnal cycle during a wake-steering field campaign

Abstract. High-fidelity flow modeling with data assimilation enables accurate representation of the wind farm operating environment under realistic, nonstationary atmospheric conditions. Capturing the temporal evolution of the turbulent atmospheric boundary layer is critical to understanding the behavior of wind turbines under operating conditions with simultaneously varying inflow and control inputs. This paper has three parts: the identification of a case study during a field evaluation of wake steering; the development of a tailored mesoscale-to-microscale coupling strategy that resolved local flow conditions within a large-eddy simulation (LES), using observations that did not completely capture the wind and temperature fields throughout the simulation domain; and the application of this coupling strategy to validate high-fidelity aeroelastic predictions of turbine performance and wake interactions with and without wake steering. The case study spans 4.5 h after midnight local time, during which wake steering was toggled on and off five times, achieving yaw offset angles ranging from 0 to 17°. To resolve nonstationary nighttime conditions that exhibited shear instabilities, the turbulence field was evolved starting from the diurnal cycle of the previous day. These background conditions were then used to drive wind farm simulations with two different models: an LES with actuator disk turbines and a steady-state engineering wake model. Subsequent analysis identified two representative periods during which the up- and downstream turbines were most nearly aligned with the mean wind direction and had observed yaw offsets of 0 and 15°. Both periods corresponded to partial waking on the downstream turbine, which had errors in the LES-predicted power of 4 % and 6 %, with and without wake steering. The LES was also able to capture conditions during which an upstream turbine wake induced a speedup at a downstream turbine and increased power production by up to 13 %.