Turbulent Field Research Articles (Page 5)

Abstract Turbulent magnetic field fluctuations observed in the solar wind often maintain a constant-magnitude magnetic field accompanied by spherically polarized velocity fluctuations; these signatures are characteristic of large-amplitude Alfvén waves. Nonlinear energy transfer in Alfvénic turbulence is typically considered in the small-amplitude limit where the constant-magnitude condition may be neglected; in contrast, nonlinear energy transfer of large-amplitude fluctuations remains relatively unstudied. We develop a method to analyze large-amplitude turbulence through studying fluctuations as constant-magnitude rotations in the de Hoffmann–Teller frame, in which the convected electric field of the fluctuations vanishes such that the frame and fluctuations are copropagating. Our analysis reveals signatures of large-amplitude effects deep into the inertial range. While the dominant fluctuations are consistent with spherically polarized large-amplitude Alfvén waves, the subdominant fluctuations are relatively compressible. Signatures of nonlinear interaction between the large-amplitude spherically polarized mode with the subdominant population reveal highly aligned transverse components. In many theoretical models of Alfvénic turbulence, alignment is thought to reduce nonlinearity; our observations suggest that the observed alignment is sufficient to either reduce shear nonlinearity such that non-Alfvénic interactions may be responsible for energy transfer in spherically polarized states, or alternatively that counterpropagating fluctuations maintain anomalous coherence, a predicted signature of reflection-driven turbulence.

Abstract Kinetic helicity is a fundamental characteristic of astrophysical turbulent flows. It is not only responsible for the generation of large-scale magnetic fields in the Sun, stars, and spiral galaxies, but it also affects turbulent diffusion, resulting in the dissipation of large-scale magnetic fields. Using the path integral approach for random helical velocity fields with a finite correlation time and large Reynolds numbers, we show that turbulent magnetic diffusion is reduced by the kinetic helicity, while the turbulent diffusivity of a passive scalar is enhanced by the helicity. The latter can explain the results of recent numerical simulations for forced helical turbulence. One of the crucial reasons for the difference between the kinetic helicity effect on magnetic and scalar fields is related to the helicity dependence of the correlation time of a turbulent velocity field.

The dynamic response of pump valve motion directly influences the volumetric efficiency of drilling pumps and serves as a critical factor in performance enhancement. This study presents a coupled fluid–structure interaction (FSI) analysis of a novel secondary cushioned pump valve for drilling systems. A validated 3D transient numerical model, integrating piston–valve kinematic coupling and clearance threshold modeling, was developed to resolve the dynamic interactions between reciprocating mechanisms and turbulent flow fields. The methodology addresses critical limitations in conventional valve closure simulations by incorporating a geometrically adaptive mesh refinement strategy while maintaining computational stability. Transient velocity profiles confirm complete sealing integrity with near-zero leakage (<0.01 m/s), while a 39.3 MPa inter-pipeline pressure differential induces 16% higher jet velocities in suction valves compared to discharge counterparts. The secondary cushioned valve design reduces closure hysteresis by 22%, enhancing volumetric efficiency under rated conditions. Parametric studies reveal structural dominance, with increases in cylindrical spring stiffness lowering discharge valve lift by 7.2% and velocity amplitude by 2.74%, while wave spring optimization (24% stiffness enhancement) eliminates pressure decay and reduces perturbations by 90%. Operational sensitivity analysis demonstrates stroke frequency as a critical failure determinant: elevating speed from 90 to 120 rpm amplifies suction valve peak velocity by 59.87% and initial closing shock by 129.07%. Transient flow simulations validate configuration-dependent performance, showing 6.3 ± 0.1% flow rate deviations from theoretical predictions (Qt_max = 40.0316 kg/s) due to kinematic hysteresis. This study establishes spring parameter modulation as a key strategy for balancing flow stability and mitigating cushioning-induced oscillations. These findings provide actionable insights for optimizing high-pressure pump systems through hysteresis control and parametric adaptation.

Planar entropy waves are commonly assumed for predicting indirect combustion noise. However, the non-planar and turbulent nature of flows found in most practical combustors challenges this assumption. In the present paper, we examine the indirect noise generated by non-planar and turbulent entropy fields through subsonic nozzles. Firstly, we introduce a new transfer function framework that accounts for the contribution of non-planar Fourier modes of the entropy field to the indirect noise spectra. When applied to a turbulent flow field, this method demonstrates a significant improvement in spectral predictions compared with a conventional approach that only considers the planar mode. Secondly, simulations show that non-planar Fourier modes become significant above a threshold frequency $f_{thresh}$ , found in the mid- to high-frequency range. This contribution of non-planar modes is explained by two-dimensional shear effects that distort the entropy waves. A scaling relation that uses residence times along streamlines is developed for $f_{thresh}$ , showing good agreement with simulation results. Finally, we show that the indirect noise from non-planar entropy modes found in aviation combustors can be significant at frequencies below 1 kHz, which might be relevant in situations of thermo-acoustic instabilities coupled to indirect noise.

ABSTRACT The formation of circumstellar discs is a critical step in the formation of stars and planets. Magnetic fields can strongly affect the evolution of angular momentum during prestellar core collapse, potentially leading to the failure of protostellar disc formation. This phenomenon, known as the magnetic braking catastrophe, has been observed in ideal-magentohydrodynamics (MHD) simulations. In this work, we present results from ideal-MHD simulations of circumstellar disc formation from realistic initial conditions of strongly magnetized, massive cores with masses between $30$ and $300 ~{\rm M}_\odot$ resolved by zooming into giant molecular clouds (GMCs) with masses $\sim 10^4 \ {\rm M}_\odot$ and initial mass-to-flux ratios $0.6 \le \mu _0 \le 3$. Due to the large turbulence in the gas, the dominant vertical support of discs is turbulent motion, while magnetic and turbulent pressures contribute equally in the outer toroid. We find that large Keplerian discs can form even in magnetically critical or near-critical cores due to the suppression of magnetic braking by highly turbulent and incoherent magnetic field topologies. Only cores in GMCs with $\mu _0 < 1$ fail to form discs. Instead, they collapse into a sheet-like structure and produce numerous low-mass stars. We also discuss a universal $B{\small --}\rho$ relation valid over a large range of scales from the GMC to massive cores, irrespective of the GMC magnetization. This study differs from the vast literature on this topic which typically focus on smaller mass discs with idealized initial and boundary conditions, therefore providing insights into the initial conditions of massive prestellar core collapse and disc formation.

This article studies an anti-collision control method for the trajectory tracking problem of an unmanned aerial vehicle for aircraft skin inspection under complex wind disturbance. To guarantee the safety of the aircraft during the inspection, the anti-collision control under wind disturbance is described by the maximum position offset constraint of the unmanned aerial vehicles (UAVs). Then, an exponential nonlinear integral super-twisting sliding mode (ENISTSM) position controller is designed, and incorporated with the prescribed performance control(PPC) to ensure that the position error is consistently constrained within specified bounds. Subsequently, the attitude and angular velocity cascaded control law is investigated based on the modified Rodrigues parameters (MRPs) attitude representation using the exponential super-twisting sliding mode (ESTSM) method. The proposed method achieves fast tracking of relatively large variable angles and is robust to wind disturbance. In addition, the stability of the controllers is proven via Lyapunov analysis. Finally, the simulation results are included by considering the turbulent wind field to demonstrate the effectiveness and the advantages.

Simulation of nonstationary and nonhomogeneous turbulent wind fields with probability information is essential to conduct wind reliability analysis on complex structures. The stochastic wave-based spectral representation method (SWSRM) is a wind field simulation method applicable to multiple simulation points. However, SWSRM cannot determine the probability information of simulated samples and exhibits low efficiency when simulating nonstationary and nonhomogeneous wind fields. To this end, the dimension-reduced non-uniform fast Fourier transform (NUFFT)-enhanced SWSRM (DR-N-SWSRM) is proposed. The method utilizes NUFFT to reduce the time and space complexity, while leveraging random functions and number-theoretic method (NTM) to ensure clear probability information for each sample. Numerical experiments demonstrate the effectiveness of the proposed method. Results indicate the proposed method greatly reduces the memory consumption during the simulation compared to the classical methods, thereby alleviating the high computational requirements of SWSRM. Simultaneously, the consuming time for a single simulation is also compared with other methods, demonstrating the high efficiency of the proposed method. Moreover, the random functions and NTM not only result in a substantial reduction in the random variables, but also provide explicit probability information for each sample. This capability allows the simulated sample set to facilitate probability density evolution method (PDEM)-based structural reliability analysis.

Abstract We analyzed environmental fields for moderate clear air turbulence (CAT) reported above 400 hPa over Japan between 2010 and 2017. We divided the year into five periods, with June separate from summer. In June, a stagnant front called the Baiu front is often present over Japan, making meteorological conditions different from summer. Using reanalysis data, we analyzed environmental fields for each period. It is shown that the environmental fields of aviation turbulence around Japan differ depending on altitude and period. In winter, CAT tends to occur on the west side of the trough of the jet stream axis. The jet stream is often weak when CAT occurred. CAT is likely to occur around trough in spring and fall, suggesting that the trough‐enhanced deformation and strengthened vertical wind shear caused the CAT. CAT likely occurs in a field with cyclonic circulation and active convection in the lower levels in summer. In June, it is suggested that it tends to occur north of the Baiu front and around troughs associated with the jet stream. The jet stream to the north of the Baiu front suggests that the Baiu front is related to the onset of CAT.

3D self-supportive structures of micro/nanofiber assemblies constructed in situ in air turbulent flow fields for thermal protection at extreme conditions

The turbulent wake dynamics over hilly terrain with typical topographic shapes and slopes under different oncoming flow conditions are numerically investigated using large-eddy simulations, followed by proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD) analysis. First, the effects of terrain shape, slope and inflow turbulence on the statistical and spectral characteristics of wake turbulence over hilly terrain are clarified. Then, the dominant flow patterns in the topographic wake are identified by POD and DMD, respectively. Finally, the turbulent wake flow fields over typical hilly terrain are reconstructed using DMD. The results show that the peak spectral frequencies at half topography elevation decrease as the terrain shape transitions from three-dimensional to two-dimensional but increase with decreasing terrain slope and oncoming turbulence intensity. From POD and DMD analyses, it is demonstrated that the wake dynamics over steep terrain under turbulent inflow conditions are predominantly governed by the separated shear layer shed from the hillside and hilltop on the horizontal and vertical planes, respectively. Some discrepancies are observed in the higher-order modes extracted from POD and DMD, indicating strong interactions among multi-frequency eddy motions in the topographic wake. Moreover, the wake fields over typical hilly terrain under different incoming flow conditions can be effectively reconstructed using only 30% of DMD modes with reasonable accuracy. The reconstruction errors are primarily concentrated within the separated shear layer due to the strong flow nonlinearity in this region.

The wind field in forested areas is strongly influenced by complex terrain and dense vegetation cover, resulting in substantial spatial heterogeneity and temporal variability in wind characteristics. These factors are critical to the safety of transportation infrastructure and the efficiency of wind energy development in forested areas. However, systematic observational studies in such environments remain limited. This study comprehensively analyzed the spatiotemporal evolution of wind speed, wind direction, and turbulence characteristics in forested areas based on long-term observational data obtained from a flux tower and light detection and ranging at the Mao'er Mountain Forest Ecosystem National Field Science Observation and Research Station. The vertical distribution of wind speed and its seasonal variation were also examined. The results show that the probability density function of turbulence intensity follows a lognormal distribution with fitting accuracy improving with height. Significant discrepancies were identified between the observed wind characteristics and the values recommended by current standards. In summer, the gust factor exhibited greater variability with increasing wind speed and was generally higher than in winter at similar altitudes. Moreover, the von Kármán spectrum showed the best agreement with the measured wind speed power spectra in the longitudinal, lateral, and vertical directions, outperforming the Simiu and Panofsky models. These findings enhance the understanding of wind dynamics in forested areas and provide a valuable scientific basis for wind disaster risk assessment, wind-resistant infrastructure design, and strategic planning of wind energy resources in mountainous forested areas.

The aerodynamic performance of fractal geometries is a critical concern in engineering, such as urban trees, whose multi-scale wake structures warrant detailed examination. Identifying the contributions from multiple sub-scale tree geometries to wake dynamics requires decomposition and recognition of characteristic wake scales, which can encounter scale mixing in conventional methods such as the fast-fourier transform (FFT) and bare empirical mode decomposition (EMD). This study analyzes the wake characteristics behind fractal trees with varying crown porosities using the Hilbert–Huang transform (HHT). HHT decomposes the wake by EMD into intrinsic mode functions (IMFs) first, then determines each IMF's instantaneous frequency and amplitude by Hilbert spectral analysis. The statistical peaked frequency, which is calculated via the marginal Hilbert spectrum, reveals a similar major scale but a different spatial energy distribution compared with the FFT. The statistical joint probability density function (JPDF) of the instantaneous frequency and amplitude denotes consistent high-occurrence peaks at Sth = 0.2, 0.6, and 1.2, recommending including 1, 0.33, and 0.17 h into urban greening parameterization. The reconstructed peaked turbulence field exhibits specific spatial distribution patterns. This finding validates the bond between sub-scale geometries and JPDF peaks. The interaction of different peak scales is investigated to look into scale coherence. The central frequency and oval-like distribution slope offer a novel perspective on wake instability assessment. Additionally, the momentum fluxes driven by different peaked scales are examined, elucidating the contributions of sub-scale tree geometries to wake dynamics and pollutant transport, providing valuable guidance for optimizing urban greening design.

Abstract The Dynamic Wake Meandering model is becoming a de facto standard for cost-efficient simulation of non-stationary wind power plant (WPP) flow fields to be used as input for aeroelastic WPP design computations. The fundamental conjecture behind this model is to address the massive modeling challenge – caused by the wide range of flow scales represented in WPP flow fields – by introducing a simplifying ‘binary’ split of flow scales, and consider wake deficits as passive tracers driven by large scale turbulence structures. This split in scales is in the original paper formulated in terms of a spatial wake scale dictated flow average, which in turn, adopting Taylor’s hypothesis, is re-casted into a low-pass filter with a cut-off frequency, f c , equal to U ∞/(2D w ), where U ∞ is the undisturbed ambient mean wind speed, and D w is the wake diameter. Proper determination of f c is crucial to obtain reliable predictions of both production- and load simulations of WPP turbines, since the modeling of wake meandering energy is directly associated with f c . Various attempts have been performed to validate or reject the originally conjectured value of f c , which essentially represents an upper limit value of f c potentially allowing all parts of a wake organized flow structure to be displaced in the same direction by any eddy size of the large scale turbulence field. Using a full-scale test campaign, combining Lidar observations of near-wake flow field dynamics with an advanced adaptive wake tracking procedure based on extended Kalman filtering, a remarkably good agreement between the originally conjectured cut-off frequency and the measured (dominating) scales contributing to wake meandering is demonstrated.

The conversion of CMB photons to axions (or axion-like particles (ALPs)) can lead to a unique spectral distortion in the temperature and polarization sky which can be explored in upcoming CMB experiments. In this work we have developed a numerical simulation-based technique of photons to ALPs conversion in the galaxy clusters and show for the first time that this physical process can lead to large non-Gaussian signal in the temperature and polarization field, which is impacted by the presence of inhomogeneities and turbulence in the electron density and magnetic field. Our simulation-based technique can simulate the theoretical signal for different scenarios of cluster electron density and magnetic field turbulence and provides testable predictions to discover ALPs from galaxy clusters using spatially non-Gaussian and anisotropic spectral distortion of the microwave sky. We show that the presence of turbulence in the magnetic field and electron density can impact the Gaussian part of the signal captured in terms of the angular power spectra of the signal by more than an order of magnitude. Also, the presence of turbulence in different clusters will lead the temperature and polarization fluctuations around the cluster region to have varying non-Gaussian distribution, with peaks and tails different from the Gaussian statistics of the CMB anisotropy. This new numerical technique has made it possible to calculate also the non-Gaussian signals and can be used in future CMB analysis in synergy with X-ray and radio observations to unveil ALPs coupling with photons in the currently unexplored ranges, for the masses between about 10-14 eV–10-11 eV.

Abstract Turbulent flows are known to produce enhanced effective magnetic and passive scalar diffusivities, which can fairly accurately be determined with numerical methods. It is now known that, if the flow is also helical, the effective magnetic diffusivity is reduced relative to the nonhelical value. Neither the usual second-order correlation approximation nor the various τ approaches have been able to capture this. Here we show that the helicity effect on the turbulent passive scalar diffusivity works in the opposite sense and leads to an enhancement. We have also demonstrated that the correlation time of the turbulent velocity field increases with the kinetic helicity. This is a key point in the theoretical interpretation of the obtained numerical results. Simulations in which helicity is being produced self-consistently by stratified rotating turbulence resulted in a turbulent passive scalar diffusivity that was found to be decreasing with increasing rotation rate.

Abstract. The atmosphere contains aerosol particles, some of which are hygroscopic in nature. These particles have direct and indirect effects on weather and climate. Furthermore, turbulence causes fluctuations in temperature, water vapor content, and relative humidity (RH). Turbulent humidity fluctuations may influence, among others, the phase state of specific hygroscopic particles. One process of particular interest in that context is particle deliquescence, which is the phase transition of solid particles to solution droplets. It occurs at a certain RH, the so-called deliquescence relative humidity (DRH), which in turn depends on, e.g., the particle substance. This study investigates the deliquescence behavior of sodium chloride particles in a turbulent humidity field, in particular addressing the questions of whether and how turbulent relative humidity fluctuations affect the number and number fraction of deliquesced particles. The turbulent moist-air wind tunnel LACIS-T (Turbulent Leipzig Aerosol Cloud Interaction Simulator) is used for this study. The results show that the number of deliquesced particles is influenced by turbulent RH fluctuations. On the one hand, particle deliquescence can be observed although the mean RH is smaller than the DRH. On the other hand, there are cases for which non-deliquesced particles are present even though the mean RH is larger than the DRH. In general, the number fraction of deliquesced particles depends on a combination of mean relative humidity, strength of humidity fluctuations, and residence time of the particles in the turbulent humidity field. The study concludes that relying solely on the mean relative humidity is inadequate for determining the phase state of deliquescent particle species in the atmosphere. It is necessary to additionally consider both the humidity fluctuations and the particle history.

The scaling inertial-range behavior of the single-time two-point correlation functions of the weak magnetic field, passively advected by the turbulent velocity field driven by the stochastic Navier-Stokes equation, is investigated in the framework of the field-theoretic renormalization group approach in the second order of the corresponding perturbative expansion (in the two-loop approximation in the language of quantum field theory). The explicit two-loop expressions for the corresponding scaling exponents are found and compared to those obtained in the Kazantsev-Kraichnan model of the kinematic magnetohydrodynamics with the simple Gaussian statistics of the turbulent velocity field. It is shown that, in general, the presence of higher correlations of the velocity field in the turbulent kinematic magnetohydrodynamics leads to more pronounced anomalous scaling behavior of the magnetic correlations deep inside the inertial interval. Moreover, the analysis of the asymptotic behavior of dimensionless ratios of the single-time two-point correlation functions of the magnetic field shows that even the persistence of anisotropy deep inside the inertial range is more pronounced in the genuine kinematic magnetohydrodynamics with the Navier-Stokes turbulent velocity field than in the Kazantsev-Kraichnan model of the kinematic magnetohydrodynamics with the complete absence of higher correlations of the turbulent velocity field.

This paper aims at investigating the impact of changing the number of blades on the thrust force and efficiency at turbulent flows to improve the propeller design. The propeller performance is important in many applications, such as aviation and marine propulsion systems, where efficiency and thrust force are important. A CFD approach was used to study the flow field and thrust and torque characteristics of propellers with two, three, and four blades. These simulations were based on the velocity and pressure distributions, thrust force, and aerodynamic efficiency, all of which were maintained at optimal levels of operation. Quantitative analysis revealed a clear trend: greater numbers of blades increased the thrust force and efficiency of the system. In particular, the thrust force increased three times when comparing the blade numbers of two and three, changing from 0.3556 N to -1.2766 N. The same trend was observed for the thrust force, which increased from 1.4966 N for the three blades to 2.9818 N for the four blades. This shows that the addition of blades does increase efficiency, but the degree to which this increases efficiency decreases as the number of blades increases: an example of a nonlinear relationship. The thrust coefficient also increased with the number of blades, suggesting better aerodynamics. Additional information was obtained from the velocity and pressure contours. For the two-blade configuration, the flow separation resulted in high pressure around the rotation domain and low pressure in the static domain for the thrust force. The three- and four-blade designs showed that the flow was smoother, the flow separation was less pronounced, and the pressure differences were higher, which contributed to higher thrust and efficiency. The results of this research advance the understanding of propeller behavior in turbulent flow fields. This paper proposes a mathematical model that establishes the correlation between the blade count and aerodynamic performance, which will be useful for future propeller design in aviation, marine, and other forms of transport. More studies should be conducted to understand higher blade geometries and materials to enhance efficiency.

Abstract Semi‐empirical coefficients for electron transport in Alfvénic turbulence are used to drive the global evolution of energetic electron distributions through Earth's outer radiation belt. It is shown how these turbulent fields facilitate radial transport and pitch‐angle scattering that drive losses through the magnetopause, into the plasma sheet, through the plasmapause and to the atmosphere. Butterfly distributions are formed due to pitch‐angle scattering and the combined effect of the loss processes. For the observed spectrum of oscillations, it is estimated that Alfvénic turbulence drives order of magnitude depletions of outer radiation belt electron fluxes at relativistic energies over a period of a few hours. On the other hand, at lower energies, energization in transverse Alfvénic electric fields leads to enhancements of the electron spectrum to provide a source population for subsequent acceleration to higher energies and, in concert with the loss processes, provides exponential spectral form as a function of energy.

Self-similarity is a property of an object or process wherein a part is similar to the whole. Mathematically, it can often be expressed as a power-law scaling of the quantity of interest. Extended self-similarity is a concept widely used in the field of turbulence and refers to the power-law scaling of the longitudinal structure functions of the velocity field expressed through the structure functions of different orders, rather than distance. Originally discovered by [R. Benzi et al., Phys. Rev. E 48, R29 (1993)1063-651X10.1103/PhysRevE.48.R29] in fully developed turbulence, it was later found to hold in other situations and systems as well. In this paper, we show that in an active-matter system, extended self-similarity is possible even without the presence of respective power-law scaling in the underlying structure functions of distance. The active-matter system used in this study was a single-layer suspension of active Janus particles in a plasma. Janus particles are polymer microspheres with hemispherical metal coating. When dispersed in a plasma, they acquire self-propulsion and act as microswimmers. Extended self-similarity was also observed in the velocity field of a single-layer suspension of laser-heated regular (passive) particles, where the underlying structure functions displayed a hint of the power-law scaling near the mean interparticle distance. Therefore, it appears to be an inherent characteristic of complex plasmas.