Turbulent Phenomena Research Articles

The fractional nonlinear Schrödinger equation: Soliton turbulence, modulation instability, and extreme rogue waves.

In this paper, we undertake a systematic exploration of soliton turbulent phenomena and the emergence of extreme rogue waves within the framework of the one-dimensional fractional nonlinear Schrödinger (FNLS) equation, which appears in many fields, such as nonlinear optics, Bose-Einstein condensates, plasma physics, etc. By initiating simulations with a plane wave modulated by small noise, we scrutinized the universal regimes of non-stationary turbulence through various statistical indices. Our analysis elucidates a marked increase in the probability of rogue wave occurrences as the system evolves within a certain range of Lévy index α, which can be ascribed to the broadened modulation instability bandwidth. This heightened probability of extreme rogue waves is corroborated through multiple facets, including wave-action spectrum, fourth-order moments, and probability density functions. However, it is crucial to acknowledge that a decrease in α also results in a reduction in the propagation speed of solitons within the system. Consequently, only high-amplitude solitons with non-zero background are observed, and the occurrence of collisions that could generate higher-amplitude rogue waves is suppressed. This introduces an inverse competitive mechanism: while a lower α expands the bandwidth of modulation instability, it concurrently impairs the mobility of solitons. Our findings contribute to a deeper understanding of the mechanisms driving the formation of rogue waves in nonlinear fractional systems, offering valuable insights for future theoretical and experimental studies.

Theoretical advances in the smagorinsky model for turbulence simulations

This article proposes significant theoretical enhancements to the Smagorinsky model for turbulence simulations, presenting new theorems with complete mathematical proofs to increase the precision and efficiency of these simulations. Acknowledging the limitations of the original model, this work addresses these challenges through a rigorous analysis in Sobolev spaces and the filtered Navier-Stokes equations, which are essential for subgrid-scale simulation development. The study begins by introducing conditions of existence and uniqueness for weak solutions in the modified model, based on methods such as the Galerkin technique, which facilitates the analysis of behavior and stability under small initial perturbations. The application of these techniques enables a detailed verification of the model's accuracy in different turbulent flow scenarios. To validate the theoretical advancements, computational simulations are implemented to compare the performance of the original and modified Smagorinsky models. The results of these simulations demonstrate a significant improvement in both accuracy and computational efficiency, with the enhanced model achieving greater precision with less processing demand. These theoretical and numerical advancements in the Smagorinsky model open new perspectives for the use of turbulence simulations in various fields of engineering and applied sciences, allowing for more detailed analyses and more reliable predictions of complex turbulent phenomena. Thus, this work contributes to advancing the state of the art in turbulence modeling, providing a solid foundation for future research and practical evelopments in the field.

In Situ Calibration of a Tube Passive Sampler in Wastewater Effluent with Adjustable Volumetric Flow for the Assessment of Micropollutants with Fluctuating Concentrations.

We present a versatile flow-through tube passive sampling device (TPS), with a controllable feedwater volumetric flow, that can be calibrated in situ against the feedwater load of organic micropollutants (OMPs). This semipassive approach has the advantage of a determinable water load feeding the sampling device. The design of the TPS allows for new sampling scenarios in closed piping while providing stable and controlled sampling conditions. The calibration referencing an OMP's feedwater load can describe the uptake behavior from wastewater treatment plant effluent with potentially highly fluctuating OMP concentrations. The TPS and its load-dependent calibration under realistic environmental conditions proves possible for a variety of organic trace substances in a challenging matrix. Nine of the 20 monitored representative OMPs could be calibrated load-dependently, leading to a good agreement between the calculated concentration from the TPS and the average concentration of corresponding direct measurements. Due to the simple measuring principle and the membrane-less discs, many influencing factors such as diffusion, turbulence, and lag time phenomena can be neglected. The TPS could support the existing online measurement analytics in a (process-) water treatment plant by delivering integrated water concentrations for discharge monitoring.

Application of machine learning for detecting and tracking turbulent structures in plasma fusion devices using ultra fast imaging

This study explores the application of machine learning techniques for detecting and tracking plasma filaments around the boundary of magnetically confined tokamak plasmas. Plasma filaments, also called blobs, are responsible for enhanced turbulent transport across magnetic field lines, and their accurate characterization is crucial for optimizing the performance of magnetic fusion devices. We present a novel approach that combines machine learning methods applied to data obtained from ultra-fast cameras, including YOLO (You Only Look Once) for object detection, semantic segmentation, and specific tracking methods. This approach enables fast and accurate detection and tracking of filaments while overcoming the limitations of conventional methods, which are time-consuming and prone to human subjectivity. A significant advance in our study lies in the development of a method for automatically labeling a large batch of data, which greatly facilitates the training of supervised machine learning algorithms. Using these techniques, we obtained promising results demonstrating a significant improvement over conventional tracking methods, achieving a detection accuracy of up to 98.8%, while reducing the inference time per frame by 15% to 31% compared to conventional Kalman filter tracking. These results open up new perspectives for investigating turbulent phenomena in tokamaks, and could have important implications for the development of controlled nuclear fusion.

Spectrally decomposed denoising diffusion probabilistic models for generative turbulence super-resolution

We investigate the statistical recovery of missing physics and turbulent phenomena in fluid flows using generative machine learning. Here, we develop and test a two-stage super-resolution method using spectral filtering to restore the high-wavenumber components of two flows: Kolmogorov flow and Rayleigh–Bénard convection. We include a rigorous examination of the generated samples via systematic assessment of the statistical properties of turbulence. The present approach extends prior methods to augment an initial super-resolution with a conditional high-wavenumber generation stage. We demonstrate recovery of fields with statistically accurate turbulence on an 8× upsampling task for both the Kolmogorov flow and the Rayleigh–Bénard convection, significantly increasing the range of recovered wavenumbers from the initial super-resolution.

Air effects on solitary waves impinging and overtopping an impermeable seawall

Considering the presence or absence of air, the solitary waves impinging on an impermeable structure were numerically investigated to discuss solitary wave characteristics such as surface elevation, pressure, vorticity, eddy viscosity, and force on structures under different initial conditions. The volume of fluid (VOF) model (Wu, 2004) was employed to simulate solitary waves impinging an impermeable structure. Besides, the LES turbulent module was utilized to capture the turbulent phenomenon generated by wave-structure interactions, particularly after wave breaking. The present model was verified by comparing the simulation results with the experimental data (Hsiao and Lin, 2010). The findings demonstrated that the model more accurately represents tsunami wave behavior compared to simulations that did not account for air, especially in cases where wave breaking occurs prior to overtopping, entraining more air into the water. Detailed comparisons between simulations with and without air presence reveal that simulations excluding air exhibited delayed wave breaking, a more distant breaking point, and the absence of an air pocket behind the seawall. Despite these differences, the simulations showed excellent agreement with the laboratory results. Moreover, it was shown that the presence of air dissipated part of wave energy. Earlier the stage of waves broke, the more air was entrained, making the effects of air on the waves more noticeable. The highest fluid velocity was observed at the breaking point in front of the structure, while the strongest forces were experienced by the structure at the breaking location behind it.

Scaling Effects of the Weissenberg Number in Electrokinetic Oldroyd-B Fluid Flow Within a Microchannel.

This study attempts to extend previous research on electrokinetic turbulence (EKT) in Oldroyd-B fluid by investigating the relationship between the Weissenberg number ( ) and the second-order velocity structure function ( ) under applied electric fields. Inspired by Sasmal's demonstration in Sasmal (2022) of how heterogeneous zeta potentials induce turbulence above a critical , we develop a mathematical framework linking to turbulent phenomena. Our analysis incorporates recent findings on AC (Zhao & Wang, 2017) and DC (Zhao & Wang 2019) EKT, which have defined scaling laws for velocity and scalar structure functions in the forced cascade region. Our finding shows that and , for a length scale , and , where is a velocity fluctuations quantity and denotes the time relaxation parameter. This work establishes a positive correlation between and turbulent flow phenomena through a rigorous analysis of velocity structure functions, thereby offering a mathematical foundation for building the design and optimization of EKT-based microfluidicdevices.

Neural differentiable modeling with diffusion-based super-resolution for two-dimensional spatiotemporal turbulence

Simulating spatiotemporal turbulence with high fidelity remains a cornerstone challenge in computational fluid dynamics (CFD) due to its intricate multiscale nature and prohibitive computational demands. Traditional approaches typically employ closure models, which attempt to represent small-scale features in an unresolved manner. However, these methods often sacrifice accuracy and lose high-frequency/wavenumber information, especially in scenarios involving complex flow physics. In this paper, we introduce an innovative neural differentiable modeling framework designed to enhance the predictability and efficiency of spatiotemporal turbulence simulations. Our approach features differentiable hybrid modeling techniques that seamlessly integrate deep neural networks with numerical PDE solvers within a differentiable programming framework, synergizing deep learning with physics-based CFD modeling. Specifically, a hybrid differentiable neural solver is constructed on a coarser grid to capture large-scale turbulent phenomena, followed by the application of a Bayesian conditional diffusion model that generates small-scale turbulence conditioned on large-scale flow predictions. Two innovative hybrid architecture designs are studied, and their performance is evaluated through comparative analysis against conventional large eddy simulation techniques with physics-based subgrid-scale closures and purely data-driven neural solvers. The findings underscore the potential of the neural differentiable modeling framework to significantly enhance the accuracy and computational efficiency of turbulence simulations. This study not only demonstrates the efficacy of merging deep learning with physics-based numerical solvers but also sets a new precedent for advanced CFD modeling techniques, highlighting the transformative impact of differentiable programming in scientific computing.

Analysis of hydrodynamics and thermal–hydraulic performance of twisted angle fins within an annular conduit

AbstractThis paper investigated the influence of various twisted angles of fin inserts integrated on the inner heated pipe wall of a double-pipe heat exchanger by analysing the thermal–hydraulic performance through numerical simulations. Results showed twisted angle fin (TAF) induced turbulent fluid flow phenomena, generating transverse and longitudinal vortices, along with swirling flow. This collaboration between the vortices and swirling flow effectively prevents heat trapping and enhances heat transfer from the inner pipe wall through the intensive fluid mixing. Despite longitudinal swirling vortices and turbulence significantly enhance local and global heat transfer performance, they led to increased pressure drop. However, TAF twisting reduces pressure drop by streamlining flow. The performance evaluation criterion (PEC) value is a dimensionless quantity that facilitates the comprehensive evaluation of optimal configurations by comparing the increment in Nusselt number and the increment in friction factor. PEC values greater than 1 indicate that the increase in Nusselt number exceeded the increase in friction factor. Among tested configurations, the twisted fin angles of 60° (TAF60) exhibited the highest improvement in Nusselt number and friction factor, also achieving the highest PEC of 1.59712 at Reynolds number of 1194.71. TAF40 and TAF50 were identified as optimal configurations for enhancing the thermal–hydraulic efficiency, with average PEC values of 1.26893 and 1.27030, respectively. Overall, the study indicated a consistent enhancement trend with increasing twisted angles and emphasizes the significant thermal performance improvement of TAF configurations compared to the smooth conduit. Furthermore, the results showed a converging tendency across all TAF configurations in the percentage improvement in Nusselt number and friction factor, as well as PEC compared to the baseline No fin configuration with increasing Reynolds number, suggesting that future improvements in thermal–hydraulic performance are more dependent on geometric angles than fluid flow velocity.

Estimation of Turbulent Mixing Factor and Study of Turbulent Flow Structures in Pressurized Water Reactor Sub Channel by Direct Numerical Simulation

Abstract Subchannel analysis codes are presently a requirement for design and safety analysis of nuclear reactors. Among the crucial inputs for these codes, the turbulent mixing factor holds particular significance. However, acquiring this factor through experimental means proves to be a challenging endeavor, primarily due to the necessity for precise pressure equilibrium between subchannels. Consequently, this requirement leads to the undertaking of expensive and intricate experiments for each new reactor or in cases where there are modifications in fuel bundle design. The need for direct numerical simulation (DNS) stems from the challenges and costs involved in experimental techniques, and the uncertainties due to empiricism in computational fluid dynamics (CFD) models. In this study, DNS has been conducted across six Reynolds numbers, ranging from 17,640 to 1.176 × 105, in the geometry of a pressurized water reactor (PWR) subchannel. The resulting turbulent flow structures have been computed and their dynamics are examined. Furthermore, this paper presents a methodology for directly calculating the turbulent mixing factor from the fluctuating velocity field obtained from DNS data. The turbulent mixing process has been scrutinized in-depth, and a correlation for the turbulent mixing factor is developed. It is noted that most of the mixing occurs in the near-wall region. The study suggests different mixing factors for mass and momentum mixing. This paper aims to provide a comprehensive insight into the turbulent mixing phenomenon.

Vibration annoyance due to turbulences in an airplane : subjective and physiological assessments

Turbulence phenomena in an aircraft create important vibrations, at frequencies of between 0.5 and 10 Hz. An experimental design was used to assess the influence of different signal parameters (frequency band, vertical and lateral vibration levels), and the task the participant in which the participant was involved (resting, watching a movie on a tablet computer, working by typing and using the trackpad of a computer). Thirty-three participants were subjected to around twenty signals, each lasting 45 s, using a multi-directional excitation device available in Airbus facilities. Physiological parameters (electrodermal activity, heart rate) were measured continuously. After each signal, the participant was asked to assess the discomfort of the situation. The results showed the influence of different signal characteristics or task assigned to the participant. As a general rule, subjective assessments correspond to physiological measurements. The experiment revealed the influences of the signals physical factors and the task performed by the participant. Finally, the ISO2631 standard seems to provide a good representation of the subjective evaluation of discomfort in the different configurations presented.

An improved detached eddy simulation method for cavitation multiphase flow

The evolution of cavitation flow involves intense transient characteristics and complex multi-scale motions, significantly increasing the difficulty and computational cost of solving in separation zones. This study proposes an Improved Detached Eddy Simulation (IDES) method, based on a single-equation eddy-viscosity model, aimed at enhancing the resolution of small-scale cavitation flows. By incorporating the broad-spectrum von Karman scale concept, the method effectively improves the resolution capability for small-scale flows in separated zones. The performance of the IDES model was validated through three computational cases, and the main conclusions are as follows: The results of the triangular cylinder flows show that the IDES model demonstrates a resolution capability for large-scale turbulence comparable to the Large Eddy Simulation (LES) model. The orifice flow results indicate that activating the LES method with insufficient grid resolution is highly discouraged, whereas the IDES model performs more robustly under such conditions. For hydrofoil flows, the IDES model more accurately captures the temporal evolution of cavitation, avoiding the premature cavity shedding predicted by LES under coarse grid conditions. The decomposition results of the vorticity transport equation show that both the dilatation term and viscous term are significant contributors in the vorticity transport process, with their average contributions to vorticity reaching 49.25% and 39.99%, respectively. Vortices can be considered the primary controllers of cavitation dynamics, while the dilatation term and viscous term can be regarded as the main controllers of vorticity. Overall, the energy compensation mechanism of the IDES model, based on local flow information, gives it unique advantages in handling small-scale turbulence and cavitation phenomena, providing both high computational efficiency and accuracy.

Multi-dimensional modeling of solitary wave–structure interaction problems by using a [formula omitted]-LES-SPH model

The interaction mechanisms between waves and marine structures are a popular research topic. This paper applies the weakly compressible smoothed particle hydrodynamics (WCSPH) method to study the dynamics of green water overtopping. To enhance the accuracy of the simulations, the SPH method coupled with the large eddy simulation (LES) model is employed for numerical investigations. Initially, we validate the effectiveness of the model by simulating the generation of solitary waves and irregular waves, as well as numerically reproducing the water surface morphology during the interaction between solitary waves and the deck. Subsequently, the validated model is used to study the dynamic characteristics of different types of waves overtopping, revealing significant variations in their motion. Furthermore, we investigate the effect of deck roughness during the entire green water overtopping process in terms of both protrusions extent and distribution, confirming that a reasonable setting of the protrusions can greatly reduce the wave impact loads on the deck, thereby protecting the structure. Additionally, a three-dimensional model is developed to study the green water problem, and we find that the turbulence phenomenon is more pronounced in the three-dimensional scenario.

Turbulence effects in the topology optimization of compressible subsonic flow

AbstractTurbulence significantly influences fluid flow topology optimization, and this has already been verified under the incompressible flow regime. However, the same cannot be said about the compressible flow regime, in which the density field now affects and couples all of the fluid flow and turbulence equations and makes obtaining the adjoint model, which is necessary for topology optimization, extremely difficult. Up to now, the turbulence phenomenon has still not been considered in compressible flow topology optimization, which is what is being proposed and analyzed here. Rather than being based in the Reynolds‐Averaged Navier–Stokes (RANS) equations which are defined only for incompressible flow, the equations are now based on the Favre‐Averaged Navier–Stokes (FANS) equations, which are the counterpart of the RANS equations for compressible flow and feature different dependencies and terms. The compressible turbulence model being considered is the compressible version of the Spalart–Allmaras model, which differs from the usual Spalart–Allmaras model, since now there are some new spatially varying density and specific heat terms that depend on the primal variables and that act over some of the turbulence terms of the overall model. The adjoint equations are obtained by using an automatic differentiation scheme through a coupled software platform. The optimization algorithm is IPOPT, and some examples are presented to show the effect of turbulence in the compressible flow topology optimization.

Chaos-assisted turbulence in spinor Bose-Einstein condensates

We present a turbulence-sustaining mechanism in a spinor Bose-Einstein condensate, which is based on the chaotic nature of internal spin dynamics. Magnetic driving induces a complete chaotic evolution of the local spin state, thereby continuously randomizing the spin texture of the condensate to maintain the turbulent state. We experimentally demonstrate the onset of turbulence in the driven condensate as the driving frequency changes and show that it is consistent with the regular-to-chaotic transition of the local spin dynamics. This chaos-assisted turbulence establishes the spin-driven spinor condensate as an intriguing platform for exploring quantum chaos and related superfluid turbulence phenomena. Published by the American Physical Society 2024

Turbulence phenomena due to pure wave over the submerged horizontal cylinder

Turbulence phenomena due to pure wave over the submerged horizontal cylinder

The Nature of Pointer States and Their Role in Macroscopic Quantum Coherence

This article begins with an interdisciplinary review of a hydrodynamic approach to understanding the origins and nature of macroscopic quantum phenomena in high-temperature superconductivity, superfluidity, turbulence and biological systems. Building on this review, we consider new theoretical insights into the origin and nature of pointer states and their role in the emergence of quantum systems. The approach includes a theory of quantum coherence underpinned by turbulence, generated by a field of pointer states, which take the form of recirculating, spin-1/2 vortices (toroids), interconnected via a cascade of spin-1 vortices. Decoherence occurs when the bosonic network connecting pointer states is disrupted, leading to their localisation. Building further on this work, we explore how quantum particles (in the form of different vortex structures) could emerge as the product of a causal dynamic process, within a turbulent (fractal) spacetime. The resulting particle structures offer new insights into intrinsic spin, the probabilistic nature of the wave function and how we might consider pointer states within the standard “point source” representation of a quantum particle, which intuitively requires a more complexed description.

Bound Bogoliubov quasiparticles in photon superfluids

Bogoliubov's description of Bose gases relies on the linear dynamics of noninteracting quasiparticles on top of a homogeneous condensate. Here, we theoretically explore the weakly nonlinear regime of a one-dimensional photon superfluid in which phononlike elementary excitations interact via their backreaction on the background flow. The generalized dispersion relation extracted from spatiotemporal intensity spectra reveals additional branches that correspond to Bogoliubov quasiparticles—phase-locked collective excitations originating from nonresonant harmonic generation and wave-mixing processes. These mechanisms are inherent to fluctuation dynamics and highlight nontrivial scattering channels other than resonant interactions that could be relevant in the emergence of dissipative and turbulent phenomena in superfluids. Published by the American Physical Society 2024

Study of dust deposition pattern in the respiratory tract of dust particles less than 10 μm in size

The turbulent disturbances of airflow at different respiratory intensities influence the deposition characteristics of dust. The dust concentration during inhalation is 62.3% higher than that during exhalation. During the respiratory process, the turbulent disturbance phenomenon in the inspiratory phase has a dominant influence on dust deposition. At a respiratory intensity range of 15–45 L/min, the final deposition of particles is mainly influenced by the inhalation airflow, while in the range of 60–90 L/min it is mainly influenced by the exhalation airflow. Particle size affected the deposition characteristics, with the deposition of 7.07-μm dust greatly affected by airflow conditions, with a variation in the deposition rate of 56.3%. As the particle size increased, particles less than 10 μm were more frequently deposited in the right nasal cavity (which has an open spatial structure) than the left nasal cavity, as well as in the thick and short right bronchus.

Evolution mechanism and interaction of the muzzle combustion-gas jets field of underwater dual-barrel synchronized launch

Despite a certain amount of research that has been done on the muzzle combustion–gas jet field of underwater launching in recent years, there are still few reports on the evolution mechanism and interaction of underwater dual-barrel synchronised launch flow fields. To fill this gap, this study aimed to numerically analyse the effects of different barrel intervals on the transient jet field evolution characteristics of the dual-barrel launch. The three-dimensional unsteady multi-phase mathematical model was created and compared with an underwater sealed emission experiment of data for verification. The volume of fluid multi-phase flow model is used to describe the gas–liquid two-phase flow process, and the k–ε turbulence model simulates the turbulent mixing phenomenon in the jet field. On this basis, the user-defined function coupling internal ballistics process was used to determine the transient jet field of a double-barrelled, 30 mm (d = 30) underwater artillery numerically at the barrel intervals of 3d, 4d and 5d. The calculation results indicate that the closer the interval is, the more chaotic the pressure field is, and the Mach disc structure forms later. When the barrel interval is 3d, the Mach disc formation time is ∼ 0.2 ms, while it forms at ∼ 0.15 ms when the barrel interval is 5d. The movement law of projectiles in water is consistent with the change of Mach disc displacement with time, and both satisfy the exponential growth law. The velocity field core is elliptical, and the vortices on both sides of the muzzle continue to grow within 0.4 ms when the launch interval is 3d. As the barrel interval increases, the core of the velocity field is bottle-shaped, the vortex on both sides of the muzzle increases first and then decreases within 0.4 ms, and the maximum temperature of the flow field increases by 15 %.