Turbulent Field Research Articles

Rotary-wing drone-induced flow – comparison of simulations with lidar measurements

Abstract. Ultrasonic anemometers mounted on rotary-wing drones have the potential to provide a cost-efficient alternative to the classical meteorological mast-mounted counterpart for atmospheric boundary layer research. However, the propeller-induced flow may degrade the accuracy of free-stream wind velocity measurements by wind sensors mounted on drones – a fact that needs to be investigated for optimal sensor placement. Computational fluid dynamics (CFD) simulations are an alternative to experiments for studying characteristics of the propeller-induced flow but require validation. Therefore, we performed an experiment using three short-range continuous-wave Doppler lidars (light detection and ranging; DTU WindScanners) to measure the complex and turbulent three-dimensional wind field around a hovering drone at low ambient wind speeds. Good agreement is found between experimental results and those obtained using CFD simulations under similar conditions. Both methods conclude that the disturbance zone (defined as a relative deviation from the mean free-stream velocity by more than 1 %) on a horizontal plane located at 1 D (rotor diameter D of 0.71 m) below the drone extends about 2.8 D upstream from the drone center for the horizontal wind velocity and more than 7 D for the vertical wind velocity. By comparing wind velocities along horizontal lines in the upstream direction, we find that the velocity difference between the two methods is ≤ 0.1 m s−1 (less than a 4 % difference relative to the free-stream velocity) in most cases. Both the plane and line scan results validate the reliability of the simulations. Furthermore, simulations of flow patterns in a vertical plane at the ambient speed of 1.3 m s−1 indicate that it is difficult to accurately measure the vertical wind component with less than a 1 % distortion using drone-mounted sonic anemometers.

A multiscale and multicriteria generative adversarial network to synthesize 1-dimensional turbulent fields

This article introduces a new neural network stochastic model to generate a 1-dimensional stochastic field with turbulent velocity statistics. Both the model architecture and training procedure ground on the Kolmogorov and Obukhov statistical theories of fully developed turbulence, so guaranteeing descriptions of (1) energy distribution, (2) energy cascade and (3) intermittency across scales in agreement with experimental observations. The model is a generative adversarial network (GAN) with multiple multiscale optimization criteria. First, we use three physics-based criteria: the variance, skewness and flatness of the increments of the generated field, that retrieve respectively the turbulent energy distribution, energy cascade and intermittency across scales. Second, the GAN criterion, based on reproducing statistical distributions, is used on segments of different length of the generated field. Furthermore, to mimic multiscale decompositions frequently used in turbulence’s studies, the model architecture is fully convolutional with kernel sizes varying along the multiple layers of the model. To train our model, we use turbulent velocity signals from grid turbulence at Modane wind tunnel.

Modelling urban canopy with object-based porosity model

We present a novel approach to modelling urban canopies based on the porosity model. The impact of objects in the canopy layer is implicitly accounted for by applying a high-value drag force in the parts of the canopy layer that objects would occupy. This effectively halts fluid flow in the defined space of the objects, mimicking the impact of solid objects in the canopy layer. The model addresses two common issues in urban canopy modelling: the definition of the drag coefficient and the loss of canopy morphology, which significantly affect flow and turbulence fields. The model is assessed for three cases: two idealised urban-like canopies with realistic urban flow conditions and one benchmark case based on the measurements of Hilderman and Chong (2007). The benchmark results, where the explicitly modelled objects are reduced from 109 to 9, show that the new model exhibits a level of accuracy similar to explicit modelling. We also computed the commonly used zone-based porosity and roughness models for the two idealised urban-like canopies. The new model produced results comparable to the results of explicit modelling and superior to those of the alternative approaches. All cases were computed in unsteady mode using a hybrid RANS/LES model based on elliptic-relaxation eddy-viscosity RANS and the dynamic Smagorinsky model. The simulations were performed using the open-source computational fluid dynamics code T-Flows, available on Github.

Theory of the momentum source method for synthetic turbulence

The interaction between turbulence and blade leading edges is known to have a significant impact on the aerodynamic and aeroacoustic performance of propellers. In addition to directly simulating turbulence, synthetic turbulence, such as the momentum source method, has been developed as a popular method for studying this interaction process in computational fluid dynamics and computational aeroacoustics. However, it is found that for non-periodic disturbances, although the induced velocity field is divergence-free, spurious noise may be generated in the source region and contaminate simulation results. To address this issue, the present work proposes adding a correction term so that the divergence-free condition is satisfied globally and the unwanted acoustic waves are suppressed, as an extension to our previous work for time-periodic gusts [H. Jiang, Phys. Fluids 35, 096115 (2023)]. The strength of the proposed approach lies in its simplicity, flexibility, and generality. First, it derives explicit source terms, which are straightforward for numerical implementations, to generate unsteady flow fluctuations. Second, the sources can be added inside the computational domain, saving computational costs for turbulence convection and being compatible with most existing boundary conditions. Third, the proposed method can obtain analytical expressions for the needed momentum source of the Navier–Stokes equation subject to any desired isotropic or anisotropic divergence-free turbulence fields. The method has been verified by examples of synthesizing harmonic gusts, Gaussian eddies, and random turbulence. The synthetic velocity results characterized by different spectral components are directly compared to target velocity fields, verifying the proposed approach and showing its capability. Parameters that influence the distribution of added sources are systematically investigated to identify an optimal combination for different scenarios. Finally, the model is employed to evaluate the aerodynamic interaction between an incoming turbulence and a thin airfoil. The obtained results exhibit good correspondence with analytical solutions.

A Comparison of Different Biomass Combustion Mechanisms in the Transient State

Different combustion reaction process models were used to numerically study the behavior of the temperature, velocity, and turbulence fields, as well as to gain a better understanding of the differences between the reaction products obtained with each model. Transient-state simulations were conducted for a gasifier under specific operating conditions. The standard K-epsilon (2eq) turbulence model was utilized, along with the incorporation of species transport, volumetric responses, and eddy dissipation. In this study, the impacts of one-, two-, and four-step reaction mechanisms on the mass fraction of the products of the reactions, as well as the maximum values of velocity, turbulence, and temperature, were examined. The findings demonstrated that for all mechanisms, the greater maximum values of velocity and turbulence are attained at early time steps and decrease with subsequent time steps. The temperature rises as much in the early time steps and nearly stays the same in the late time steps. In all situations examined, the species’ fraction mass varies slightly in the early time steps but becomes nearly constant in the latter time stages. Similar species mass fraction values were found for both one-step and four-step methods. The results also suggest that the lower half of the gasifier is where the highest mass fraction values are found.

Large eddy simulation of a turbulent channel flow using dynamic Smagorinsky subgrid scale model and differential equation wall model

A large eddy simulation (LES) is conducted in a plane channel flow which is turbulent. For understanding the mechanism of the turbulent motion more efficiently, the present study is an attempt to conduct the LES using a Dynamic Smagorinsky Model (DSM) and a Differential Equation Wall Model (DEWM). DSM is a subgrid-scale model and DEWM is for approximating the near wall layer. The simulation is performed in a domain of 2 π δ × 2 δ × π δwhich is discretized by 32 × 20 × 32grid points where δ is the channel half width. The discretization techniques have been used in the simulation, are the 3rd order low storage R-K method in time and 2nd order finite difference formulation in space. To assess the performance of the LES with DSM and DEWM, the simulation results are compared with direct numerical simulation (DNS) data and LES data using Standard Smagorinsky Model (SSM). Comparing the results in the essential turbulence statistical field it has been found that DSM performs better than SSM in most of the cases and shows better agreement with the DNS results. Flow structures in the turbulent flow field are compared in isosurfaces and contour plots, and found that tube-like vortical structures are randomly distributed over the entire flow field, and the number of the vortical structures are more for the DSM case than that of SSM.

A new probability-distribution scale synthetic eddy method for large eddy simulation of wind loads

The accurate generation of inflow turbulence in large eddy simulation (LES) plays a crucial role in assessing the wind loads on buildings. To faithfully recreate turbulent flow fields, the inflow turbulence must accurately replicate vortex structures. In this study, we propose a novel method for generating turbulent inflow called the probability-distribution scale synthetic eddy method (PDSSEM). PDSSEM utilizes a random generation of eddy positions, with the length of each eddy scale determined by its probability density function (PDF). This approach ensures that PDSSEM maintains consistency in the mean wind speed profile, turbulence integral length, turbulence intensity profile, and wind speed spectra of the atmospheric boundary layer (ABL). The PDSSEM method can be more easily applied compared with multi-scale synthetic eddy method (MSSEM), making it highly versatile and adaptable. The self-sustaining characteristics of the flow field generated by PDSSEM are validated, revealing abundant vortex structures and good agreement with targeted values for turbulence flow characteristics. Furthermore, comparing the wind pressures of a tall building with the experimental data, the accuracy and feasibility of PDSSEM are comprehensively demonstrated. Thus, it indicates the great potential of the proposed method for broader computational wind engineering applications, including wind load evaluation and flow pattern investigation.

Propagation and fluxes of ultra-high energy cosmic rays in f(R)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\varvec{f(R)}$$\\end{document} gravity theory

In this work, we study the effect of diffusion of ultra-high energy cosmic ray (UHECR) protons in the presence of turbulent magnetic fields (TMFs) in the light of the f(R) theory of gravity. The f(R) theory of gravity is a successful modified theory of gravity in explaining the various aspects of the observable Universe including its current state of expansion. For this work, we consider two most studied f(R) gravity models, viz., the power-law model and the Starobinsky model. With these two models, we study the diffusive character of the propagation of UHECR protons in terms of their density enhancement. The density enhancement is a measure of how the density of CRs changes due to their diffusion in the intergalactic medium and interaction with the cosmic microwave background (CMB) radiation. Ankle, instep and Greisen–Zatsepin–Kuzmin (GZK) cutoff are all spectrum characteristics that extragalactic UHECRs acquire when they propagate through the CMB. We analyse all these characteristics through the diffusive flux as well as its modification factor. Model dependence of the modification factor is minimal compared to the diffusive flux. We compare the UHECR proton spectra calculated for the considered f(R) gravity models with the available data of the Telescope Array (TA) and Pierre Auger Observatory (PAO). We see that both models of f(R) gravity predict energy spectra of UHECRs with all experimentally observed features, which lay well within the range of combined data of both experiments throughout the energy range of concern. It is to be noted that our present work is only to investigate the possible effects of f(R) gravity theory on the UHECRs propagation, using pure proton composition as a simplified case study since protons are least affected by magnetic fields. Hence, at this stage, our results cannot be used to favor or disfavor f(R) cosmology over Λ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Lambda $$\\end{document}CDM cosmology as more work is needed in this regard.

What role of gravity, turbulence and magnetic fields in high-mass star formation clouds?

Abstract To explore the potential role of gravity, turbulence and magnetic fields in high- mass star formation in molecular clouds, this study revisits the velocity dispersion–size (σ–L) and density–size (ρ–L) scalings and the associated turbulent energy spectrum using an extensive data sample. The sample includes various hierarchical density structures in high-mass star formation clouds, across scales of 0.01 to 100 pc. We observe σ ∝ L0.26 and ρ ∝ L−1.54 scalings, converging toward a virial equilibrium state. A nearly flat virial parameter–mass (αvir−M) distribution is seen across all density scales, with αvir values centered around unity, suggesting a global equilibrium maintained by the interplay between gravity and turbulence across multiple scales. Our turbulent energy spectrum (E(k)) analysis, based on the σ–L and ρ–L scalings, yields a characteristic E(k) ∝ k−1.52. These findings indicate the potential significance of gravity, turbulence, and possibly magnetic fields all in regulating dynamics of molecular clouds and high-mass star formation therein.

Ion Kinetics and Neutron Generation Associated with Electromagnetic Turbulence in Laboratory-Scale Counterstreaming Plasmas.

Electromagnetic turbulence and ion kinetics in counterstreaming plasmas hold great significance in laboratory astrophysics, such as turbulence field amplification and particle energization. Here, we quantitatively demonstrate for the first time how electromagnetic turbulence affects ion kinetics under achievable laboratory conditions (millimeter-scale interpenetrating plasmas with initial velocity of 2000  km/s, density of 4×10^{19}  cm^{-3}, and temperature of 100eV) utilizing a recently developed high-order implicit particle-in-cell code without scaling transformation. It is found that the electromagnetic turbulence is driven by ion two-stream and filamentation instabilities. For the magnetized scenarios where an applied magnetic field of tens of Tesla is perpendicular to plasma flows, the growth rates of instabilities increase with the strengthening of applied magnetic field, which therefore leads to a significant enhancement of turbulence fields. Under the competition between the stochastic acceleration due to electromagnetic turbulence and collisional thermalization, ion distribution function shows a distinct super-Gaussian shape, and the ion kinetics are manifested in neutron yields and spectra. Our results have well explained the recent unmagnetized experimental observations, and the findings of magnetized scenario can be verified by current astrophysical experiments.

Cygnus OB2 as a test case for particle acceleration in young massive star clusters

In this paper, we focus on the scientific case of Cygnus OB2, a young massive star cluster (YMSC) located in the northern sky towards the Cygnus X star-forming complex. We consider a model that assumes cosmic-ray acceleration occurring only at the termination shock of the collective wind of the YMSC and address the question of whether or not, and under what hypotheses, hadronic emission by the accelerated particles can account for the observations of Cygnus OB2 obtained by Fermi-LAT, HAWC, and LHAASO. To this end, we carefully review the available information on this source, also confronting different estimates of the relevant parameters with ad hoc developed simulations. Once other model parameters are fixed, the spectral and spatial properties of the emission are found to be very sensitive to the unknown properties of the turbulent magnetic field. Comparison with the data shows that our suggested scenario is incompatible with Kolmogorov turbulence. Assuming Kraichnan- or Bohm-type turbulence spectra, the model accounts well for the very high energy (VHE) data, but fails to reproduce the centrally peaked morphology observed by Fermi-LAT, suggesting that additional effects might be important for lower energy gamma -ray emission. We discuss how additional progress can be made with more detailed and extended knowledge of the spectral and morphological properties of the emission.

Time-Averaged Parameters of the Circular Synthetic Jet for Different Dimensionless Stroke Length

Abstract The circular synthetic jet (SJ) for different dimensionless stroke lengths and at Reynolds number Re=5000 was investigated in this paper. Particle image velocimetry was used. The flow was measured at a distance of 240 mm from the orifice and this area was divided into two fields of view (FOV). The parameter fields were created by the injunction of these two FOVs. The time-averaged velocity, turbulent kinetic energy (TKE), turbulence intensity, vorticity field, centreline, and profiles of SJ were presented and discussed. Additionally, the jet half-width of SJ was investigated. The data discontinuity at a line of the FOVs was discussed. The impact of the dimensionless stroke lengths on the parameters of SJ at Re=5000 was discussed.

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.