Turbulent Dynamics Research Articles

Significance of the smaller scales for hypersonic turbulent boundary layers with focused laser differential interferometry

While designed to suppress disturbances located away from its beam foci, focused laser differential interferometry (FLDI) is known to have some integration of signals along its optical axis. This is especially true for longer-wavelength signals, although smaller-scale flow structures also have a non-infinitesimal sensitivity length. This study investigates the performance of FLDI in a hypersonic turbulent boundary layer to better understand its behavior. FLDI simulations were conducted using both full-scale direct numerical simulation (DNS) and spatially averaged DNS inputs to directly assess the influence of smaller flow structures on FLDI measurements. The full-scale FLDI results indicate that integration along the optical axis likely results in lower FLDI amplitudes than for true point measurements. Comparison with the spatially averaged FLDI simulations reveals the significance of small-scale structures in FLDI signal roll-off and root mean square amplitudes. Further, the influence of FLDI setup parameters on the response across the frequency spectrum are analyzed. Circular, Gaussian beams with smaller widths are verified to present increased performance relative to elliptical or uniform-intensity beams. Also, measurements using distinct differentiation directions suggest an experimental way to measure turbulence isotropy scales. These results have notable implications for understanding hypersonic turbulent boundary-layer dynamics and interpreting experimental data. Distribution Statement A: Approved for Public Release; Distribution is Unlimited. PA# AFRL-2024-4678; Cleared 08/23/2024.

Dynamic instabilities and turbulence of merged rotating Bose–Einstein condensates

We present the simulation results of merging harmonically confined rotating Bose–Einstein condensates in two dimensions. Merging of the condensate is triggered by positioning the rotation axis at the trap minima and moving both condensates toward each other while slowly ramping their rotation frequency. We analyze the dynamics of the merged condensate by letting them evolve under a single harmonic trap. We systematically investigate the formation of solitonic and vortex structures in the final, unified condensate, considering both nonrotating and rotating initial states. In both cases, merging leads to the formation of solitons that decay into vortex pairs through snake instability, and subsequently, these pairs annihilate. Soliton formation and decay-induced phase excitations generate sound waves, more pronounced when the merging time is short. We witness no sound wave generation at sufficiently longer merging times that finally leads to the condensate reaching its ground state. With rotation, we notice off-axis merging (where the rotation axes are not aligned), leading to the distortion and weakening of soliton formation. The incompressible kinetic energy spectrum exhibits a Kolmogorov-like cascade [E(k)∼k−5/3] in the initial stage for merging condensates rotating above a critical frequency and a Vinen-like cascade [E(k)∼k−1] at a later time for all cases. Our findings hold potential significance for atomic interferometry, continuous atomic lasers, and quantum sensing applications.

Beam emission spectroscopy diagnostic design and capabilities for two-dimensional turbulence measurements on Wendelstein 7-X

Abstract A beam emission spectroscopy (BES) diagnostic is designed for studying two-dimensional turbulent dynamics by measuring the Doppler-shifted Balmer-Alpha emission (n = 3 → 2) from neutral heating beams on Wendelstein 7-X (W7-X) stellarator. The BES viewing geometry has been determined in the conceptual design previously. However, the small Doppler shifts and small optical throughput compared to a typical BES diagnostic demand dedicated efforts on the optical assemblies and the detector module for the BES system. We present the detailed opto-mechanical design and specifications of BES, including a customized neutral beam viewing optical system, a semi-telecentric optical assembly, and a detector module for electronic amplification. The point spread function is calculated using the pyFIDASIM code with experimental parameters and W7-X magnetic configurations to estimate the BES spatial resolution and beam intensity. The as-manufactured interference filter is applied for the spectral isolated beam radiance calculation. Result shows that the BES system is capable of measuring the ion-scale turbulence for k ⊥ ρ i ≤ 0.4 at r/a = 0.75 with reasonable spatial and wavenumber resolutions. An integrated detector module is fabricated where two 8×4 avalanche photodiode detectors (APD) are embedded into the custom-designed pre-amplifier circuit to gain signals to the desired level. The detector noise measurement is performed and the signal-to-noise ratio (SNR) is evaluated. A detectable fluctuation level can be achieved as low as ñ e /n e ≈ 0.5% at frequency f ≤ 400 kHz with a bandwidth of 1 MHz.

CFD Simulation of Stirling Engines: A Review

Stirling engines (SEs) have long attracted the attention of renewable energy researchers due to their external combustion design and flexibility in operating with various heat sources. The mathematical analysis of these devices is conducted by using a broad range of models ranging from basic zero-order to highly detailed fourth-order models, which are implemented through Computational Fluid Dynamics (CFD) simulations. The unique features of this last approach, combined with the increase in computing power, have promoted the use of CFD as a tool for analyzing SEs in recent years, significantly reducing the costs associated with prototype construction. However, Stirling CFD simulations are sophisticated due to the variety of physical phenomena involved, such as volume change, conjugated heat transfer, turbulent compressible fluid dynamics, and flow through porous media in the regenerator. Furthermore, there is currently no comprehensive review of CFD simulations of SEs in the literature; therefore, this contribution aims to fill that gap. Emphasis has been placed on identifying the type of engine, the physical phenomena modeled, the simplifying assumptions, and specific numerical aspects, such as mesh type, spatial and temporal discretization, and the order of the numerical schemes used. As a result, it has been found that in many cases, CFD numerical reports lack sufficient detail to ensure the reproducibility of the simulations. This work proposes guidelines for reporting CFD studies on Stirling engines to address this issue. Additionally, the need for a sufficiently detailed experimental benchmark database to validate future CFD studies is stressed. Finally, the use of Large Eddy Simulations on coupled key engine components—such as compression and expansion spaces, pistons, displacer, and regenerator—is suggested to provide further insights into the specific flow and heat transfer characteristics in Stirling engines.

Unfolding wall turbulence

We present the project FLARE (Unfolding wall turbulence), funded by the Spanish Ministry of Science and FEDER. The main objective of this project is to contribute to understanding the dynamics of wall-bounded turbulence, exploring two techniques: Lie-Symmetry and Machine Learning. Further, we have compiled several high-quality databases of different flows using Direct Numerical Simulations of the Navier-Stokes equations with the code LISO to use these techniques. This data is available to the turbulence community.

Investigation of the impact of transient pressure gradients on turbulent channel flow dynamics

AbstractThe effect of transient pressure gradients, or transient pumping in turbulent channel flow configuration, is investigated. Employing a cost‐efficient reduced‐order stochastic method known as one‐dimensional turbulence (ODT) modeling, simulations explore different signal shapes for the modulation of the prescribed pressure gradient forcing, including sinusoidal modulation, step‐like modulation, and piecewise sinusoidal beating. Various cycle periods and active pumping times are investigated. The simulations are conducted at a frictional Reynolds number of and a molecular Prandtl number of . The study adopts a passive scalar formulation to investigate heat transfer properties. The study quantifies the effects of transient pressure gradients on heat transfer rate, drag, and pumping power. Preliminary ODT predictions suggest that all transient cases exhibit lower heat transfer rates and a higher pumping power requirement than the constant pressure gradient case, with the step‐like modulation yields superior skin‐friction drag and heat transfer rate reductions relative to other signals.

Stable reproducibility of turbulence dynamics by machine learning

Stable reproducibility of turbulence dynamics by machine learning

Key Issues and Application Prospects in High-Temperature Plasma Physics

High-temperature plasma physics is the core area of research into nuclear fusion energy, and it also has broad application potential in industry and astrophysics. The paper systematically reviews the fundamental definition, the formation mechanism, and research history of high-temperature plasma; analyzes focal problems including energy confinement, plasma instability, radiation cooling, material tolerance, turbulent dynamics; and discusses the technical progress and challenges of magnetic confinement and inertial confinement experimental devices. The comparison of tokamak against laser inertial confinement gives further illustration of the pros and disadvantages of the two fusion routes. Nuclear fusion energy, from an application viewpoint, represents a very ideal energy source for future sustainable development, and high-temperature plasma technology is also very promising in industrial processing, astrophysical experiments, and other fields. In conjunction with relevant recent research, suggestions are also given in this paper regarding high-temperature plasma in the future development direction. All this is done as an effort to offer reference and guidance for future developments in that field.

Robust Edge Flows in Swarming Bacterial Colonies

Understanding if and how the chirality of biomolecules is transferred across scales into larger components and active processes remains elusive. For instance, flagellated bacteria swim in helical trajectories but chirality seems absent from the active turbulence dynamics they display in dense suspensions. We address this question by examining multiscale dynamics in colonies. We find active turbulence without manifest chirality in the bulk, but wide, clockwise (viewed from the air side) circulation all along the tortuous centimeter-scale external boundary, while similar but counterclockwise flows follow internal boundaries. We trace the origin of these robust edge flows to an unexpected asymmetry at the individual level that is amplified by local interactions. We rationalize our findings with a model of noisy self-propelled particles immersed in a Stokes fluid that accounts faithfully for our observations. Our modeling and experimental efforts reveal that local nematic alignment and hydrodynamic interactions amplify the weak chiral bias in individual motion, promoting the formation of strong edge flows. The likely topological protection of these flows provides robust transport mechanism over large scales. Such robust boundary phenomena in weakly chiral active fluids may inspire new control strategies for active and biological matter. Published by the American Physical Society 2024

Numerical Simulation of Fixed-Free End Beam’s Modal Behaviour using Two-Way Coupled Fluid-Structure Interaction Approach

The fluid flow velocity stands as a pivotal parameter with a great influence on the mutual interaction between the fluid domain and structure. This paper focuses on structural deformation, structural velocity, von-Mises stress and frequency response of a fixed-free end beam using two-way coupled fluid-structure interaction within ANSYS Workbench. The parameters such as deformed fluid pressure and velocity were analysed across three diverse flow regimes: laminar, transitional and turbulent – each aligned with distinct fluid velocities. The outcomes show that the total deformation, velocity and von-Mises stress distribution of the fixed-free end beam increase as the inlet fluid velocity increases. As a result, the pressure and velocity distribution in the fluid flow which receiving the resultant or leftover structure deflection also increases as the incoming fluid velocity increases. Furthermore, the analysis probes the frequency response in turbulent flow conditions reveals higher values compared to laminar and transitional flows, albeit within the same natural frequency domain. This observation marks significant vibrational characteristics found in the presence of turbulent flow dynamics.

Optimization of particle–bubble collision dynamics in turbulence via clustering algorithms and microscale vortex enrichment analysis

The interaction dynamics between particles and bubbles in turbulent flow fields are crucial for optimizing multiphase flow systems. In this work, direct numerical simulation is combined with advanced K-means++ clustering algorithms to quantify the spatial distribution and enrichment effects of particle–bubble clusters under different turbulence conditions. The results indicate that the Stokes number increases with particle and bubble size, demonstrating stronger inertial effects, but decreases with higher turbulence intensity. Radial relative velocity and collision frequency also exhibit a positive correlation with size and turbulence intensity. Clustering analysis reveals that larger particles and bubbles form more pronounced clusters, particularly in high turbulence conditions, leading to higher local densities and interaction frequencies. Overlap ratios suggest increased interactions with growing size and turbulence intensity. These findings highlight the importance of optimizing particle and bubble sizes to match specific turbulence conditions, enhancing interaction dynamics in multiphase flow systems. This research provides valuable insights for improving various industrial processes involving particle–bubble interactions.

Posterior comparison of model dynamics in several hybrid turbulence model forms

Hybrid turbulence models that can accurately reproduce unsteady three-dimensional flow physics across the entire range of grid scales and turbulence dynamics from Reynolds-averaged Navier–Stokes (RANS), through large-eddy simulation (LES), down to direct numerical simulations (DNS) are of increasing interest to the turbulence modeling community. However, despite decades of research and development, the basic tasks of eliminating poor-performing hybrid RANS-LES models and accelerating adoption of superior models through well-designed validation and verification have yet to occur. As a step in this direction, in this work we evaluate thirteen different hybrid RANS-LES models via systematic grid refinement of decaying homogeneous isotropic turbulence. We further derive a novel mathematical framework for assessing the energy partitioning dynamics of each Hybrid RANS-LES model, wherein model-to-model variations in energy partitioning can be interpreted as different feedback mechanisms operating on a low-dimensional nonlinear dynamical system. We found that model forms similar to the flow simulation methodology—also often termed very-large eddy simulation—are dynamically inconsistent with DNS at all resolutions. Additionally, we found a strong dynamical similarity in the feedback mechanisms of all models related to detached eddy simulation and partially averaged Navier–Stokes that is inherent to their general model forms.

Influences of blockage ratio and Reynolds number on the spatiotemporal dynamics around a rectangular prism

Particle image velocimetry is used to experimentally investigate the influence of blockage ratio (BR) and Reynolds number (Re) on the turbulent flow around a rectangular prism with depth-to thickness ratio of 3. The prism was selected because it falls within the intermediate regime where the turbulent dynamics is sensitive to the incoming boundary condition. The tested blockage ratios were 2.5%, 5%, and 10% at Reynold numbers of 3000 and 7500. The results are analyzed in terms of the mean flow, turbulent kinetic energy (TKE), frequency spectra, reverse flow area, as well as spectral proper orthogonal decomposition (SPOD). The results indicate that as blockage ratio and/or Reynolds number increase, the tendency of reattachment of the separated shear layer onto the surface of the prism increases while the location of maximum TKE over the prism shifts toward the leading edge, indicating earlier transition of the separated shear layer from laminar to turbulence. For the cases without mean reattachment over the side faces of the prisms, the separated bubble over and downstream of the prism exhibits strong tendency of synchronization in terms of the instantaneous areas of the flow reversal, suggesting a global instability mechanism encompassing the entire prism. In cases with mean flow reattachment, conversely, the low-frequency flapping motion manifests over the prism. SPOD analysis further shows that the relevant shedding dynamics are captured in the first mode and the von Kármán shedding structures have the highest energy.

Application of a non-intrusive reduced order modeling approach to magnetohydrodynamics

Magnetohydrodynamics (MHD) investigates the intricate relationship between electromagnetism and fluid dynamics, offering a complete insight into the behavior of conducting fluids under the influence of magnetic fields. This theory plays a pivotal role in the framework of magnetic confinement fusion, where it can be applied to describe both thermonuclear plasmas confined inside the vacuum vessel and operating fluids, such as liquid metals and molten salts, flowing within the blanket of future tokamaks. Currently, the state-of-the-art numerical modeling of MHD scenarios employs a multi-physics framework to examine the interplay between magnetic fields and thermal hydraulics; however, due to the complexity of the involved physics, detailed models are required, resulting in a significant computational burden. In this regard, reduced order modeling (ROM) techniques may represent a promising solution, as they enable approximating complex systems with lower-dimensional models. Indeed, ROM methodologies can significantly reduce the required computational time while maintaining accuracy in capturing the convoluted physics involved in fusion reactors, especially in the contexts of sensitivity analysis, uncertainty quantification, and control. Despite their potential, ROM methods are relatively under-explored within the MHD framework; this study applies ROM techniques to MHD scenarios, focusing on their capabilities and possible limitations. To this aim, the backward-facing step, which is well suited for exploring the effects of different magnetic fields on turbulent dynamics, is adopted as case study. In particular, this work evaluates the potentialities of the ROM approach in enhancing computational efficiency within the MHD domain. Each of the methods evaluated was effective in precisely reconstructing flow dynamics at any given time and across the full range of magnetic field values tested while significantly reducing computational costs compared to full-order simulations. Practically, this study demonstrates the feasibility to create simplified models that accurately represent the magnetohydrodynamic flows of fluids within the blanket.

Determining the differences in O3-NOx-VOCs sensitivity between sauna and roast days

Temperature is a key meteorological factor that affects tropospheric ozone (O3), with both humid-heat (sauna days) and dry-heat (roast days) conditions leading to O3 exceedances. However, the mechanisms influencing O3 formation and degradation under these two weather conditions remain unclear. Therefore, experiments were conducted in Beijing from 2019-2021 to observe O3, its precursors, and related meteorological elements. A total of 18 days with O3 exceedances were selected, including 10 sauna days and 8 roast days. The results of this study revealed that on roast days, the sensible heat flux was 143.5 W/m2 greater and the wind speed gradient was 0.018 s-1 greater than those on sauna days, indicating more intense thermal and dynamic turbulence. The strong turbulence enhanced the vertical cycle of nitrogen dioxide (NO2) and O3, resulting in a 58.2 μg/(m2·h) increase in NO2 upward transport rate and a 1,034.4 μg/(m2·h) increase in O3 downward transport rate on roast days than sauna days. Subsequently, a box model analysis was used to examine O3 formation under the two types of weather conditions, revealing that the NO2-O3 vertical cycling speed dominated the O3 sensitivity. The O3 sensitivity was synergistically controlled by nitrogen oxides (NOx) and volatile organic compounds on sauna days, while it tended to be NOx-limited on roast days. The aim of this study was to provide a scientific theoretical basis for the control of O3 under different types of high temperature weather conditions.

The Prospective Application of Machine Learning in Turbulence Forecasting over China

Abstract This study analyzes the spatiotemporal distribution of turbulence in China from 2020 to 2022 using pilot reports. Results reveal a higher frequency of moderate-to-severe turbulence during spring and winter, particularly in January. Spatially, the primary regions of turbulence occurrence are eastern China, Xinjiang Province, Sichuan Province, and the Qiongzhou Strait, with a focus on altitudes at or above 6000 m. Machine learning models, especially random forest and extreme gradient boosting (XGBoost), demonstrate high accuracy in turbulence prediction, notably for high-altitude events. The random forest model shows optimal performance in winter, achieving an area under the curve of 0.92. The study highlights the importance of thermally related diagnostics, indicating a significant presence of convectively induced turbulence in high-altitude turbulence events. This research not only deepens the understanding of turbulence dynamics in the China region but also underscores the potential of machine learning in enhancing turbulence forecasting.

Turbulent models of shallow-water equations-based smoothed particle hydrodynamics

The depth-averaged models such as those based on the shallow water equations (SWEs) are commonly used to simulate the large-scale flows with engineering importance. The smoothed particle hydrodynamics (SPH) approach has been documented to solve the SWEs due to its mesh-free superiority in treating the free surfaces and wet-dry boundaries. However, nearly all SWE-SPH models were developed without a turbulent model, which seriously limited the model applications where the flows are complex and where the turbulent parameters are explicitly needed. For the first time, this paper includes a depth-averaged turbulent k̂-ε̂ model in the SWE-SPH solver, making the model more capable of treating the turbulent flows in the practical field. For comparison purpose, a sub-particle-scale turbulent model widely adopted in three-dimensional (3D) SPH was also included in the present SWE-SPH scheme. To evaluate the performance of the two proposed turbulent SWE-SPH models, various open channel flows of increasing complexity were simulated, and the SPH computations were compared with the reported data in the literature. Through the analysis of results for a rough riverbed, L-shaped and sudden expansion channels, it is demonstrated that the present turbulent SWE-SPH models are equipped with good robustness and accuracy in capturing the shallow water turbulent dynamics, with the potential to be used in practical river and coastal flows. In summary, there are two distinct novelties in the proposed work. First, the mesh-free numerical modeling technique SPH is used to solve the shallow water equations, which enable the model to work in large engineering field through simple and effective tracking of free surfaces and wet-dry boundaries. Second, the proposed research expands the shallow water SPH modeling technique by including robust turbulence simulation capacity. The newly developed model can address more challenging engineering scenarios such as the sediment and pollutant transports when the flow turbulence plays an important role and where the turbulent parameters are explicitly required in the relevant transport equations.

Enhancing Savonius Rotor Performance with Zigzag in Concave Surface-CFD Investigation

Savonius, a type of vertical-axis wind turbine (VAWT), is suitable as an appropriate small-scale energy conversion apparatus for regions with relatively low wind speeds, such as Indonesia; however, it exhibits sub-optimal efficiency. One potential approach to improving the efficiency of Savonius turbines is to increase the drag force on the concave surface of the blades. In this case, the dissimilarity in the forces experienced by the two blades can be increased, resulting in a corresponding increase in torque. This investigation aims to assess and compare the power coefficient (Cp), torque and drag coefficient (Cd) of the conventional Savonius rotor with the zigzag pattern implemented in the middle area of the concave surface of the blades at low wind speeds. The efficiency can be achieved by implementing the k-ω shear stress transfer (SST) turbulent model and 3D computational fluid dynamics simulation at tip speed ratio (λ) 0.4-1 with a velocity inlet of 4, 5, and 6 m/s. The study results show that using the zigzag pattern on the concave surface led to an 18.8% boosted in Cp of at λ = 0.8 and an inlet velocity (U) = 5 m/s compared to the standard Savonius rotor model. In this case, the efficiency of the Savonius wind turbine may be enhanced by incorporating a zigzag pattern in the middle of the concave surface of the Savonius rotor.

Whole-brain turbulent dynamics predict responsiveness to pharmacological treatment in major depressive disorder.

Depression is a multifactorial clinical syndrome with a low pharmacological treatment response rate. Therefore, identifying predictors of treatment response capable of providing the basis for future developments of individualized therapies is crucial. Here, we applied model-free and model-based measures of whole-brain turbulent dynamics in resting-state functional magnetic resonance imaging (fMRI) in healthy controls and unmedicated depressed patients. After eight weeks of treatment with selective serotonin reuptake inhibitors (SSRIs), patients were classified as responders and non-responders according to the Hamilton Depression Rating Scale 6 (HAMD6). Using the model-free approach, we found that compared to healthy controls and responder patients, non-responder patients presented disruption of the information transmission across spacetime scales. Furthermore, our results revealed that baseline turbulence level is positively correlated with beneficial pharmacological treatment outcomes. Importantly, our model-free approach enabled prediction of which patients would turn out to be non-responders. Finally, our model-based approach provides mechanistic evidence that non-responder patients are less sensitive to stimulation and, consequently, less prone to respond to treatment. Overall, we demonstrated that different levels of turbulent dynamics are suitable for predicting response to SSRIs treatment in depression.

PIV investigation of the effects of simulated ice blocks on the turbulent flow dynamics around a partially submerged horizontal circular cylinder

This paper presents a novel particle image velocimetry study of the effects of stationary upstream ice blocks on the turbulent flow dynamics around a single, fixed ice boom pontoon. The pontoon was modelled using a half-submerged horizontal circular cylinder. Different lengths, thicknesses, and undersurfaces of the ice blocks were examined. The Reynolds number was maintained at 25,500. The results show that the cylinder encounters an approach flow with lower momentum but higher turbulence intensity when placed behind a long ice block compared to a shorter one, and the presence of undersurface roughness reduces the momentum but enhances the turbulence intensity of the approach flow. The recirculation length, mean velocities, and turbulence levels around the cylinder reduce with increasing ice block length and subsequent roughening of its undersurface. However, a larger recirculation bubble forms from the ice block, and the mean velocities and turbulence levels increase when the ice block thickness increases.