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The objective of this study was to explore the higher-order turbulence statistics of flow and turbulent length scales around a complex pier (CP) and compare the results with those for a simple pier (SP). The velocity data were recorded in a laboratory flume using particle image velocimetry (PIV). The PIV data were analysed to estimate the velocity fluctuations of third order, turbulence production and dissipation rates, turbulent length scales and the contributions of burst–sweep events to the total Reynolds shear stress around the piers mounted on a rigid flat surface. The skewness and advection coefficients indicated a more asymmetric distribution of velocity fluctuations for the SP than for the CP. Ejection and sweep events illustrated the dominance of similar strengths for an extended period, downstream of the piers. The upstream turbulent kinetic energy production was similar for both piers, while the upstream dissipation rate was higher for the CP. The length scales were greater at the upstream for the case of the SP while, downstream, they were greater for the CP. The findings of this work demonstrate the importance of a pile cap in restricting downward-moving flow by showing a lower magnitude of scour-inducing turbulence parameters for the CP as compared with the SP. [ABSTRACT FROM AUTHOR]

The turbulent jet plays an important role in fluid mechanics since it is a prototype of free turbulent flow which presents many unsolved problems, among which the absence of closure of the governing equations. Despite the chaotic nature of turbulence, it is characterized by the existence of many universal structures, in particular dimensionless invariants such as its opening angle or the correlation coefficient of velocities. After having given new exact solutions of the Reynolds Averaged Navier–Stokes equations (RANS), we suggest a solution to this puzzle in the scale-relativity framework. In this theory, the time derivative of the Navier–Stokes equations is integrated in terms of a macroscopic Schrödinger equation acting in velocity-space. This equation involves a constant ℏ v which can be identified with the energy dissipation rate, while the pressure gradient manifests itself as a quantum harmonic oscillator (QHO) potential. The squared modulus of its solutions yields the probability density function (PDF) of velocities. The Reynolds stresses can then be derived from this PDF, so that the closure problem is solved in this case. This allows us to obtain a theoretical prediction for the turbulent intensity radial profile (and therefore for the pressure) which agrees with the experimental data. The ratio of axial over radial velocity fluctuations is found to be R = 1.3 – 1.4 from QHO properties, in good agreement with its experimental values; we theoretically predict a jet opening angle α = 1 / 2 R 3 accounting for its universal value ≈ 1 / 5 ; the mean ratio of turbulent intensity amplitudes over jet centerline axial velocity is predicted to be X = 19 / 80 , in good agreement with its universally measured value ≈ 1 / 4 ; from these parameters we derive possible values of the radial turbulent intensity amplitude μ = 0.19 – 0.22 consistent with experiments; finally, we find a correlation coefficient of velocities ρ = 1 / R 3 = 2 α , suggesting an explanation for the universal value ≈ 0.4 observed for the turbulent jet and for all free shear flows. [ABSTRACT FROM AUTHOR]

An unstable density stratification between two fluids mixes spontaneously under the effect of gravity, a phenomenon known as Rayleigh--Taylor (RT) turbulence. If the two fluids are immiscible, for example, oil and water, surface tension prevents intermixing at the molecular level. However, turbulence fragments one fluid into the other, generating an emulsion in which the typical droplet size decreases over time as a result of the competition between the rising kinetic energy and the surface energy density. Even though the first phenomenological theory describing this emulsification process was derived many years ago, it has remained elusive to experimental verification, hampering our ability to predict the fate of oil in applications such as deep-water spills. Here, we provide the first experimental and numerical verification of the immiscible RT turbulence theory, unveiling a unique turbulent state that originates at the oil--water interface due to the interaction of multiple capillary waves. We show that a single, non-dimensional, and time-independent parameter controls the range of validity of the theory. Our findings have wide-ranging implications for the understanding of the mixing of immiscible fluids. This includes in particular oil spills, where our work enables the prediction of the oil--water interface dynamics that ultimately determine the rate of oil biodegradation by marine bacteria. [ABSTRACT FROM AUTHOR]

In the field of fluid mechanics, traditional turbulence models such as those based on Reynolds-averaged Navier–Stokes (RANS) equations play a crucial role in solving numerous problems. However, their accuracy in complex scenarios is often limited due to inherent assumptions and approximations, as well as imprecise coefficients in the turbulence model equations. Addressing these challenges, our research introduces an innovative approach employing physics-informed neural networks (PINNs) to optimize the parameters of the standard k − ω turbulence model. PINNs integrate physical loss functions into the model, enabling the adaptation of all coefficients in the standard k − ω model as trainable parameters. This novel methodology significantly enhances the accuracy and efficiency of turbulent flow simulations, as demonstrated by our application to the flow over periodic hills. The two coefficients that have been modified considerably are σ ω and α, which correspond to the diffusion and production terms in the specific dissipation rate equation. The results indicate that the RANS simulation with PINNs coefficients (k − ω − PINNs simulation) improves the prediction of separation in the near-wall region and mitigates the overestimation of turbulent kinetic energy compared to the base RANS simulation. This research marks a significant advancement in turbulence modeling, showcasing the potential of PINNs in parameter identification and optimization in fluid mechanics. [ABSTRACT FROM AUTHOR]

The current revolution in the field of machine learning is leading to many interesting developments in a wide range of areas, including fluid mechanics. Fluid mechanics, and more concretely turbulence, is an ubiquitous problem in science and engineering. Being able to understand and predict the evolution of turbulent flows can have a critical impact on our possibilities to tackle a wide range of sustainability problems (including the current climate emergency) and industrial applications. Here, we review recent and emerging possibilities in the context of predictions, simulations, and control of fluid flows, focusing on wall-bounded turbulence. When it comes to flow control, we refer to the active manipulation of the fluid flow to improve the efficiency of processes such as reduced drag in vehicles, increased mixing in industrial processes, enhanced heat transfer in heat exchangers, and pollution reduction in urban environments. A number of important areas are benefiting from ML, and it is important to identify the synergies with the existing pillars of scientific discovery, i.e., theory, experiments, and simulations. Finally, I would like to encourage a balanced approach as a community in order to harness all the positive potential of these novel methods. [ABSTRACT FROM AUTHOR]

Due to costs and practical constraints, field campaigns in the atmospheric boundary layer typically only measure a fraction of the atmospheric volume of interest. Machine learning techniques have previously successfully reconstructed unobserved regions of flow in canonical fluid mechanics problems and two-dimensional geophysical flows, but these techniques have not yet been demonstrated in the three-dimensional atmospheric boundary layer. Here, we conduct a numerical analogue of a field campaign with spatially limited measurements using large-eddy simulation. We pose flow reconstruction as an inpainting problem, and reconstruct realistic samples of turbulent, three-dimensional flow with the use of a latent diffusion model. The diffusion model generates physically plausible turbulent structures on larger spatial scales, even when input observations cover less than 1% of the volume. Through a combination of qualitative visualization and quantitative assessment, we demonstrate that the diffusion model generates meaningfully diverse samples when conditioned on just one observation. These samples successfully serve as initial conditions for a large-eddy simulation code. We find that diffusion models show promise and potential for other applications for other turbulent flow reconstruction problems. [ABSTRACT FROM AUTHOR]

Various fluid mechanics software, due to inherent factors such as algorithms and boundary conditions, cannot quickly simulate 3D flow fields in batches, and the calculation of each model still takes a lot of time.In order to realize the rapid prediction of the three-dimensional flow field around the airfoil, this paper uses a new SDF geometric expression to describe the shape of the airfoil, and combines the prediction accuracy of the velocity and pressure channels, and proposes a two-stage Unet3d convolution prediction model based on the SDF expression, which greatly improves the prediction accuracy of the pressure channel.In addition, the introduced two-stage convolutional network is optimized by combining lightweight network and attention mechanism. On the premise of ensuring the accuracy of the network, it can effectively reduce the parameters of the network model and improve the operating efficiency of the network. The two-stage method was tested on the Naca0012 and RAE2822 three-dimensional datasets, and the average accuracy rates were 95.44% and 98.22% respectively, which were 2 to 3 percentage points higher than the original method. [ABSTRACT FROM AUTHOR]

Obtaining reliable flow data is essential for the fluid mechanics analysis and control, and various measurement techniques have been proposed to achieve this goal. However, imperfect data can occur in experimental scenarios, particularly in the particle image velocimetry technique, resulting in insufficient flow data for accurate analysis. To address this issue, a novel machine learning-based multi-scale autoencoder (MS-AE) framework is proposed to reconstruct missing flow fields from imperfect turbulent flows. The framework includes two missing flow reconstruction strategies: complementary flow reconstruction and non-complementary flow reconstruction. The former requires two independent measurements of complementary paired flow fields, posing challenges for real-world implementation, whereas the latter requires only a single measurement, offering greater flexibility. A benchmark case study of channel flow with ordinary missing configuration is used to assess the performance of the MS-AE framework. The results demonstrate that the MS-AE framework outperforms the traditional fused proper orthogonal decomposition method in reconstructing missing turbulent flow, irrespective of the availability of complementary paired faulty flow fields. Furthermore, the robustness of the proposed MS-AE approach is assessed by exploring its sensitivity to various factors, such as latent size, overlap proportion, reconstruction efficiency, and suitability for multiscale turbulent flow structures. The new method has the potential to contribute to more effective flow control in the future, thanks to its characteristic that eliminates the requirement for complementary flow fields. [ABSTRACT FROM AUTHOR]

Physics-informed neural networks (PINNs) are widely used to solve forward and inverse problems in fluid mechanics. However, the current PINNs framework faces notable challenges when presented with problems that involve large spatiotemporal domains or high Reynolds numbers, leading to hyper-parameter tuning difficulties and excessively long training times. To overcome these issues and enhance PINNs' efficacy in solving inverse problems, this paper proposes a spatiotemporal parallel physics-informed neural networks (STPINNs) framework that can be deployed simultaneously to multi-central processing units. The STPINNs framework is specially designed for the inverse problems of fluid mechanics by utilizing an overlapping domain decomposition strategy and incorporating Reynolds-averaged Navier–Stokes equations, with eddy viscosity in the output layer of neural networks. The performance of the proposed STPINNs is evaluated on three turbulent cases: the wake flow of a two-dimensional cylinder, homogeneous isotropic decaying turbulence, and the average wake flow of a three-dimensional cylinder. All three turbulent flow cases are successfully reconstructed with sparse observations. The quantitative results along with strong and weak scaling analyses demonstrate that STPINNs can accurately and efficiently solve turbulent flows with comparatively high Reynolds numbers. [ABSTRACT FROM AUTHOR]

An elementary observation of a laminar cylindrical Poiseuille–Couette flow profile reveals no distinction in the parabolic streamwise profile, from one without a cross-stream flow, in whatever reference frame the observation is made. This is because the laminar flow is in solid-body rotation and there is no fluid intrinsic rotation. Hence, the main streamwise Poiseuille flow is unaffected. On the contrary, in turbulent (unsteady) cylindrical axial-Couette flow, the rotational reference frame must be considered, and any observation from an external inertial reference frame can give outright incorrect results. However, even in axial turbulent pipe flow with axial rotation, the resultant effect of azimuthal velocity on the flow profile is still usually too low. Hence, the importance of consideration in the rotational frame is often overlooked. A common misconception in the study of fluid mechanics is that the position of the observer does not matter. In this direct numerical simulation study, firstly turbulent flow in a pipe with axial rotation is established. Then turbulent flow in the concentric pipe, with inner wall rotation, is used to show how tilted wall streak direction is oriented by the rotational reference frame and not the inertial reference frame. [ABSTRACT FROM AUTHOR]

Physics-informed machine-learning (PIML) enables the integration of domain knowledge with machine learning (ML) algorithms, which results in higher data efficiency and more stable predictions. This provides opportunities for augmenting—and even replacing—high-fidelity numerical simulations of complex turbulent flows, which are often expensive due to the requirement of high temporal and spatial resolution. In this review, we (i) provide an introduction and historical perspective of ML methods, in particular neural networks (NN), (ii) examine existing PIML applications to fluid mechanics problems, especially in complex high Reynolds number flows, (iii) demonstrate the utility of PIML techniques through a case study, and (iv) discuss the challenges and opportunities of developing PIML for fluid mechanics. [ABSTRACT FROM AUTHOR]

Transcatheter aortic valve replacements (TAVRs) are an increasingly common treatment for aortic valve disease due to their minimally invasive delivery. As TAVR designs require thinner leaflets to facilitate catheter-based delivery, they experience greater leaflet operational stresses and potentially greater durability issues than conventional surgical valves. Yet, our understanding of TAVR durability remains largely unexplored. Currently, preclinical TAVR durability is evaluated within an ISO:5840 compliant accelerated wear tester (AWT) up to a required 200 × 106 cycles, corresponding to approximately five years in vivo. While AWTs use high cycle frequencies (10-20 Hz) to achieve realistic timeframes, the resulting valve loading behaviors and fluid dynamics are not representative of the in vivo environment and thus may not accurately predict failure mechanisms. Despite the importance of fatigue and failure predictions for replacement heart valves, surprisingly, little quantitative information exists on the dynamic AWT environment. To better understand this environment, we examined frequency and diastolic period effects for the first time using high-speed enface imaging and particle image velocimetry to quantify valve motion and flow, respectively, using a Durapulse™ AWT at frequencies of 10, 15, and 20 Hz. Regardless of operating condition, no waveform achieved a physiologically relevant transvalvular loading pressure, despite having an ISO compliant geometric orifice area (GOA) and waveform. General fluid mechanics were consistent with in vivo but the AWT geometry developed secondary flow structures, which could impact mechanical loading. Therefore, the nonphysiologic loading and variability induced by changes in operating condition must be carefully regulated to ensure physiologically relevant fatigue. [ABSTRACT FROM AUTHOR]

Physics-informed neural networks (PINNs) are becoming popular in solving fluid mechanics problems forwardly and inversely. However, under limited observations, the application of PINNs was found to be difficult in solving the inverse problems of three-dimensional Reynolds-averaged Navier–Stokes (RANS) equations. In this study, the classical turbulent case of jet in crossflow was representatively adopted into the investigation. The dataset was obtained from a high-fidelity large-eddy simulation. The tensor-basis eddy viscosity (t-EV) model was imported first into the structure of PINNs as prior knowledge. Observations of five measured planes were preliminarily used to reconstruct the time-averaged turbulent flow field. After embedding the t-EV model, the highest absolute error and the relative L2 error of streamwise velocity were reduced by 11.1% and 31.4%, respectively. To cut down the volume of limited observations, a more effective training dataset containing only two planes and two pairs of lines was determined based on the flow characteristics (e.g., shear layer and counter-rotating vortex pair). Compared with those of five planes, the highest absolute error and the relative L2 error of streamwise velocity were further reduced by 30.0% and 6.4%, respectively. The investigation in this study provided an alternative to resolve the inverse problems of three-dimensional RANS equations with limited observations, which extended the deep learning application in fluid mechanics. [ABSTRACT FROM AUTHOR]

Direct numerical simulation is used to determine the turbulent Prandtl number P r t above cold (isothermal) and hot (adiabatic) walls in a family of low-supersonic channel flows. A range of mean temperature/density variations, corresponding to effective/edge Mach numbers between 1.1 to 2.2, and wall-variable-based Reynolds number R e τ w from 73 to 3800, is considered. The adiabatic condition is a new feature of special interest. The value of P r t away from the wall approaches 0.85 above both the isothermal and adiabatic walls. The variations of the near-wall P r t profiles in both the present and previous, passive-scalar simulations collapse as a function of the semilocal y w ∗ wall scaling proposed in 1995 by [Huang, P. G., G. N. Coleman, and P. Bradshaw. 1995. "Compressible Turbulent Channel Flows: DNS Results and Modelling." Journal of Fluid Mechanics 305: 185–218. doi:.], with only a weak dependence on R e τ w . This leads to a rather simple proposal for a model of heat transfer, attached to an eddy-viscosity model. [ABSTRACT FROM AUTHOR]

Air–water mixing associated with high turbulence is a common hydraulic phenomenon, where the transport of entrained air bubbles and the dissipation of turbulent energy are key processes affecting the air–water mass transfer. Herein hydraulic jumps were selected as a seminal case of self-air-entrainment in transitional water flow, and the air–water flow properties were investigated at high Froude numbers from 10.5 to 13.5. The analysis of air concentration distributions and bubble size spectra enabled deviation of the rates of bubble diffusion and turbulence dissipation. The study was facilitated with re-analyses of earlier experimental data for smaller Froude numbers between 3.8 and 10. The spatial evolution of the diffusion and dissipation rates suggested that the diffusion of air bubbles and dissipation of turbulent structures were not independent processes, and, at high Froude numbers, the mix of air and water was subject to re-aeration of the turbulent shear layer by the roller. [ABSTRACT FROM AUTHOR]

In 1959 Batchelor predicted that the stationary statistics of passive scalars advected in fluids with small diffusivity k should display a k−1 power spectrum along an inertial range contained in the viscous‐convective range of the fluid model. This prediction has been extensively tested, both experimentally and numerically, and is a core prediction of passive scalar turbulence. In this article we provide a rigorous proof of a version of Batchelor's prediction in the κ→0 limit when the scalar is subjected to a spatially smooth, white‐in‐time stochastic source and is advected by the 2D Navier‐Stokes equations or 3D hyperviscous Navier‐Stokes equations in Td forced by sufficiently regular, nondegenerate stochastic forcing. Although our results hold for fluids at arbitrary Reynolds number, this value is fixed throughout. Our results rely on the quantitative understanding of Lagrangian chaos and passive scalar mixing established in our recent works. Additionally, in the κ→0 limit, we obtain statistically stationary, weak solutions in H−ϵ to the stochastically forced advection problem without diffusivity. These solutions are almost‐surely not locally integrable distributions with nonvanishing average anomalous flux and satisfy the Batchelor spectrum at all sufficiently small scales. We also prove an Onsager‐type criticality result that shows that no such dissipative, weak solutions with a little more regularity can exist. © 2021 Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

We examine the two-dimensional Euler equations including the local energy (in)equality as a differential inclusion and show that the associated relaxation essentially reduces to the known relaxation for the Euler equations considered without local energy (im)balance. Concerning bounded solutions we provide a sufficient criterion for a globally dissipative subsolution to induce infinitely many globally dissipative solutions having the same initial data, pressure, and dissipation measure as the subsolution. The criterion can easily be verified in the case of a flat vortex sheet giving rise to the Kelvin--Helmholtz instability. As another application we show that there exists initial data for which associated globally dissipative solutions realize every dissipation measure from an open set in C0 (T² × [0, T]). In fact the set of such initial data is dense in the space of solenoidal L² (T²; R²) vector fields. [ABSTRACT FROM AUTHOR]

This study achieved three goals to clarify the impact of a vegetation patch on flow adjustment and velocity. First, a valid equation for the interior adjustment distance (Ld) inside a model patch was developed for a wide range of velocities and flow depths. Second, the minimum distance inside a patch beyond which the resuspension of fine sediment is suppressed (Lmin) was found to be related to the position at which the local velocity decreases to the threshold for generating stem-scale turbulence. Lmin primarily depends on the flow blockage (Cdab) and the stem diameter (d): a shorter Lmin is a result of a larger Cdab and a smaller d. An equation was formulated for estimating Lmin. Third, for the fully developed flow region inside a patch (L > x > Ld), an equation was developed to estimate the increase in the mean velocity in the bare channel relative to the overall mean channel velocity. For Cdab < 2, this fraction is controlled by both the patch density (ad) and the patch blockage (b/B) whereas, for Cdab > 2, this fraction is controlled by only b/B. A suggestion for choosing the patch size in future flow and sediment research projects is presented. [ABSTRACT FROM AUTHOR]

In this study, the most widely used Rushton turbine in the industry was discussed, and the effect of different blade angles on the mixture was investigated numerically. As a standard model, 6 bladed propellers were used and 4 baffles were placed in the stirred tank. The selected tank model is in the form of a flat bottom cylindrical container. Flow characteristics were obtained by giving angles (10°, 20°, 30°, 40°, 50°, 60°) to the propeller blades used in the straight model. The obtained results were compared with each other. In addition, analyzes were repeated at different rotation speeds (600 rpm, 750 rpm, 1000 rpm) for each model at each angle. ANSYS Fluent 18 commercial software, which is the most preferred CFD program in the literature, was used for this numerical study. The analyzes were provided in the standard k-epsilon (ε) turbulence model. The Multiple Reference Frame (MRF) approach was used to simulate impeller rotation. The velocity profiles obtained from the simulations have been shown to be in consistent with the experimental estimates and the results of previous studies. As a result, it has been revealed that the best mixing balance is provided by the impeller blade at 40 and 50 degrees. [ABSTRACT FROM AUTHOR]

This is an idiosyncratic survey of statistical fluid mechanics centering on the Hopf functional differential equation. Using the Burgers equation for illustration, we review several functional integration approaches to the theory of turbulence. We note in particular that some important contributions have been brought about by researchers working on wave propagation in random media, among which Uriel Frisch is not an exception.We also discuss a particular finite-dimensional approximation for the Burgers equation. This article is part of the theme issue ''Scaling the turbulence edifice (part 1)'. [ABSTRACT FROM AUTHOR]

Shock wave–boundary layer interaction (SWBLI) is one of the most prevalent challenges in the field of fluid mechanics. Excessive interaction may lead to strong flow separation, which is an important factor causing the deterioration of aircraft performance. Reynolds averaged Navier–Stokes (RANS) models remain the primary methods for predicting flow separation for engineering applications. RANS simulation results typically have uncertainty owing to the drawbacks of the model structure and the variability of the parameters. Therefore, evaluation of a turbulence model based on nominal predictions may be insufficient for reflecting its actual simulation capabilities. In this study, the Bayesian method is employed to re-evaluate the simulation capabilities of three k–ω models for hypersonic SWBLI flows: the original k–ω model and two k–ω models with compressibility corrections (Wilcox's and Zeman's corrections). This is achieved by perturbing the model parameters and combining with experimental data. Bayesian model evaluation based on different datasets is performed using the embedded model error method, and the three turbulence models are compared from three aspects: posterior mean of the quantities of interests, model error, and Bayesian evidence. The results show that the Bayesian calibration can effectively improve the predictive abilities of the three models for wall pressure and wall heat flux. Different from the large differences in the nominal results, the performance of the two calibrated k–ω models with compressibility corrections are very close and superior to that of the original model. Moreover, the evaluation results of this study are also proven to be applicable to other similar flows. • The Bayesian method is employed to re-evaluate three k–ω models. • The embedded model error method is used to estimate the model error. • Turbulence models are compared from three aspects: posterior mean, model error, and Bayesian evidence. • The applicability of evaluation results is investigated. [ABSTRACT FROM AUTHOR]

Gaining and understanding flow dynamics have much importance in a wide range of disciplines, e.g., astrophysics, geophysics, biology, mechanical engineering, and biomedical engineering. For turbulent flows, local flow information such as velocity and its statistics, can be measured experimentally. Due to the poor fidelity or experimental limitations, some information may not be resolved in a region of interest. On the other hand, detailed flow features are described by the governing equations, e.g., the Navier–Stokes equations for viscous fluid, and can be resolved numerically, which is heavily dependent on the capability of either computing resources or modeling. Alternatively, we address this problem by employing the physics-informed deep learning and treat the governing equations as a parameterized constraint to recover the missing flow dynamics. We demonstrate that with limited data, no matter from experiment or others, the flow dynamics in the region where the required data are missing or not measured, can be reconstructed with the parameterized governing equations. Meanwhile, a richer dataset, with spatial distribution of the control parameter (e.g., eddy viscosity of turbulence modelings), can be obtained. The method provided in this paper may shed light on the data-driven scale-adaptive turbulent structure recovering and understanding of complex fluid physics and can be extended to other parameterized governing systems beyond fluid mechanics. [ABSTRACT FROM AUTHOR]

In recent works, we proposed a hypothesis that the turbulence in gases could be produced by particles interacting via a potential and examined the proposed mechanics of turbulence formation in a simple model of two particles for a variety of different potentials. In this work, we use the same hypothesis to develop new fluid mechanics equations that model turbulent gas flow on a macroscopic scale. The main difference between our approach and the conventional formalism is that we avoid replacing the potential interaction between particles with the Boltzmann collision integral. Due to this difference, the velocity moment closure, which we implement for the shear stress and heat flux, relies upon the high Reynolds number condition rather than the Newton law of viscosity and the Fourier law of heat conduction. The resulting system of equations of fluid mechanics differs considerably from the standard Euler and Navier–Stokes equations. A numerical simulation of our system shows that a laminar Bernoulli jet of an argon-like hard sphere gas in a straight pipe rapidly becomes a turbulent flow. The time-averaged Fourier spectra of the kinetic energy of this flow exhibit Kolmogorov's negative five-thirds power decay rate. [ABSTRACT FROM AUTHOR]

The primary objective of this research study was to develop a strategy to examine a key topic of fluid mechanics for undergraduate education by using a theoretical-experimental-computational approach. The key topic examined covered topics from Bernoulli's extended equation, specifically, for calculating head losses in pipelines under turbulent flow conditions. The contribution of the computational approach was appropriate due to the observable reduction in both tedious calculations and optimization time for educational laboratory purposes. The most relevant result was the verification, in a university environment, of trends predicted by theory and experimental results. They correlated in a modified Moody diagram: the Reynolds number, relative roughness, and the Darcy friction factor. In conclusion, the test series showed the advantages and disadvantages of conducting real observations and controlled measurements while performing theoretical analyses. [ABSTRACT FROM AUTHOR]

The dissipation theorem is applied to fully developed turbulent flow past a flat plate. Most of the velocity profile occurs in a thin layer near the surface, but a layer of turbulence (represented by the eddy viscosity) extends substantially farther into the fluid. [ABSTRACT FROM AUTHOR]

This paper presents a low-communication-overhead parallel method for direct numerical simulations of the 3D incompressible wall turbulence. A fully explicit projection method with second-order space-time accuracy is adopted. Combined with fast Fourier transforms, the parallel diagonal dominant (PDD) algorithm for the tridiagonal system is employed to solve the pressure Poisson equation. The number of all-to-all communications is decreased to only two, in a 2D pencil-like domain decomposition. The resulting MPI/OpenMP hybrid parallel code shows excellent strong scalability up to 104 cores and small wall-clock time per timestep. Numerical simulations of turbulent channel flow at different friction Reynolds numbers ( R e τ = 550 , 1000 , 2000) have been conducted and the statistics are in good agreement with the reference data and the recent scaling theories [Chen, X. and K. R. Sreenivasan. 2021. "Reynolds Number Scaling of the Peak Turbulence Intensity in Wall Flows." Journal of Fluid Mechanics 908: R3. doi:10.1017/jfm.2020.991]. [ABSTRACT FROM AUTHOR]

In fluid mechanics, fountains take place when a source fluid is driven by its own momentum into a surrounding ambient fluid, and it is counterbalanced by buoyancy. These phenomena are largely encountered in nature and human activities. Despite the numerous studies on the subject, few experimental data are available about the internal structure of turbulent fountains. Here, we present a set of laboratory experiments with the aim to (i) get direct velocity and density measurements of fountains in a controlled environment and (ii) obtain insights about the basic physics of the phenomenon. The results concern the characteristics of the mean and turbulent flow: we report the analysis of the turbulent kinetic energy, the velocity skewness, and the Reynolds stresses, including a quadrant analysis of the fluctuating velocities. For some tests, the correlation between density and vertical velocity is investigated for both mean and fluctuating values. We have quantified the momentum transport, which is mainly out-downward at the nozzle axis with peaks at the mean rise height, where also maximum levels of the buoyancy and mass fluxes are present. The ability of acoustic Doppler current profilers to identify the rise height of the fountain and to measure the velocity field is also discussed. [ABSTRACT FROM AUTHOR]

This paper presents the results of flow and turbulence characteristics measured by a down-looking 16 MHz micro acoustic Doppler velocimeter around partially submerged spur dyke founded in a clay–gravel sediment mixture. Velocity and turbulence data were collected at various cross-sections at the wake and upstream sides of the spur dyke within and outside of the scour hole. The longitudinal velocity, turbulence intensities and Reynolds stresses were measured and quantitative analysis was carried out. Very small values of the longitudinal velocity component (negative) were obtained within the scour hole whereas larger values were obtained beyond the scour hole region. Turbulence intensities and Reynolds stresses were larger within the scour hole in the wake zone of the spur dyke. Bursting events, including outward interaction, ejection, inward interaction and sweep, were also analysed around the spur dyke. Quadrant analysis of the velocimeter data showed that the values of outward and inward interaction were higher within the scour hole around the spur dyke compared with the values of ejection and sweep events, while outside of the scour hole, the values of ejection and sweep events were higher than the values of outward and inward interaction events. [ABSTRACT FROM AUTHOR]

The shear-stress cospectrum and the horizontal and vertical temperature-flux cospectra in the convective boundary layer (CBL) are predicted using the multi-point Monin–Obukhov similarity (MMO theory). MMO theory was recently proposed and then derived from first principles by Tong and Nguyen (Journal of the Atmospheric Sciences, 2015, Vol. 72, 4337 – 4348) and Tong and Ding (Journal of Fluid Mechanics, 2019, Vol. 864, 640 – 669) to address the issue of the incomplete similarity in the Monin–Obukhov similarity theory. According to MMO theory, the CBL has a two-layer structure: the convective layer ( z ≫ - L ) and the convective–dynamic layer ( z ≪ - L ). The former consists of the convective range ( k ≪ - 1 / L ) and the inertial range ( k ≫ 1 / z ), while the latter consists of the convective range, the dynamic range ( - 1 / L ≪ k ≪ 1 / z ), and the inertial range, where z, k, and L are the height from the ground, the horizontal wavenumber, and the Obukhov length, respectively. We use MMO theory to predict the cospectra for the convective range and the dynamic range. They have the same scaling in the convective range for both z ≪ - L and z ≫ - L . The shear-stress cospectrum and the vertical temperature-flux cospectrum have k 0 scaling in both the convective and dynamic ranges. The horizontal temperature-flux cospectrum has k - 1 / 3 and k - 1 scaling in the convective and dynamic ranges respectively. The predicted scaling exponents are in general agreement with high-resolution large-eddy-simulation results. However, the horizontal temperature-flux cospectrum is found to change sign from the dynamic range (negative) to the convective range (positive), which is shown to be caused by the temperature–pressure-gradient interaction. [ABSTRACT FROM AUTHOR]

• • The concept of hydraulic radius can be reinterpreted as a measure of large-scale turbulent flow structure. • • Hydraulic radius as proxy for large-scale eddies enables new framework for bed shear stress model and unified scaling of scour depth. • • Hydraulic radius formulation provides insight into characterizing large-scale flow structure by geometrical boundary conditions. Hydraulic radius has long been customarily used as a characteristic length to assess the cross-sectional geometry and efficiency of channels and conduits. This review paper revisits the concept of the hydraulic radius in light of its extensive applications in recent studies, with the aim of piecing together a state-of-the-art understanding of its physical underpinnings. The original definition of the hydraulic radius is presented as the ratio of cross-sectional flow area to wetted parameter, which inherently integrates the properties of the flow domain and the contacting surface. The use of hydraulic radius as a versatile characteristic length in classical Manning's formula and the Reynolds number underscores its significance in relation to flow resistance. Through a thorough review of its diverse applications, this paper provides a unified understanding of the physical meaning of hydraulic radius, highlighting its interpretation as a measure of large-scale eddies within a given flow domain. This new insight can be justified beyond uniform flows, as evidenced by its use in addressing sediment transport issues in complex vegetated flows, based on turbulence phenomenological theory. Furthermore, the original formulation of the hydraulic radius provides insights into how large-scale flow structure can be quantified with geometrical boundary characteristics, leading to a promising framework for scour prediction based on large-scale vortex size. This paper highlights the versatility and utility of hydraulic radius across various fields of fluid mechanics and sediment transport research, and proposes its potential for future studies as a proxy for large-scale flow structures. [ABSTRACT FROM AUTHOR]

The accumulation of insulator surface contamination is closely related to the distribution of flow field around the insulator. In order to study the unevenness of the insulator surface contamination, a three‐unit lxy‐160 insulator is selected. Based on the principle of fluid mechanics, the fluid movement state on the insulator surface is determined by the calculation of Reynolds number and boundary layer, then the flow field distribution around the insulator is obtained. On this basis, the artificial contamination test and numerical simulation are carried out to study the characteristics of contamination uneven distribution on the insulator surface. The results show that when the wind speed is 3–7 m/s and the particle diameter is 1–60 µm, there is obvious boundary layer separation phenomenon, and the flow state before the separation point is laminar, while the flow state behind the separation point is turbulent. From top to bottom, the degree of accumulation on each insulator is different, and the contamination on the windward and leeward sides are unevenly distributed in a fan shape. The increment of wind speed as well as particle diameter will aggravate the unevenness of the contamination. [ABSTRACT FROM AUTHOR]

We have demonstrated the effectiveness of reinforcement learning (RL) in bluff body flow control problems both in experiments and simulations by automatically discovering active control strategies for drag reduction in turbulent flow. Specifically, we aimed to maximize the power gain efficiency by properly selecting the rotational speed of two small cylinders, located parallel to and downstream of the main cylinder. By properly defining rewards and designing noise reduction techniques, and after an automatic sequence of tens of towing experiments, the RL agent was shown to discover a control strategy that is comparable to the optimal strategy found through lengthy systematically planned control experiments. Subsequently, these results were verified by simulations that enabled us to gain insight into the physical mechanisms of the drag reduction process. While RL has been used effectively previously in idealized computer flow simulation studies, this study demonstrates its effectiveness in experimental fluid mechanics and verifies it by simulations, potentially paving the way for efficient exploration of additional active flow control strategies in other complex fluid mechanics applications. [ABSTRACT FROM AUTHOR]

We survey temperature patterns and heat transport in convective atmospheric boundary layers (CBLs). We use the word "plumes" to describe the emergent temperature patterns, in much the same way that "eddies" describe patterns of motion in turbulent flows. We introduce a two-temperature (2T) toy model to connect the cross-sectional areas of plumes to the scaling properties of temperature gradients, temperature spectra, and heat transport. We find that the half power law (z−1/2, where z is the height above the surface) form of the temperature profile reflects the change in plume cross-sectional area with height and that this is consistent with the mixed length scale required to collapse the peak regions of temperature spectra above the surface friction layer (SFL). We introduce new scaling results for temperature spectra and heat flux cospectra that extend this relationship to most of the SFLs. The spectral properties change in the bottom tenth of the SFL, where the temperature profile becomes logarithmic and temperature fluctuations increasingly display Gaussian statistics. At such small heights, the self-similarity property of the plumes reflects their randomness rather than self-similarity in the order observed above. We conclude with a general discussion, contrasting our interpretation of the role of buoyancy, as being associated with the largest structures in CBL flows, with that of Richardson [Proc. R. Soc. A 87, 354–373 (1920)], who neglected large structures and assumed that it acts locally, on the small eddies. Richardson's ideas still inform the currently accepted, statistical fluid mechanics model of boundary-layer flows. [ABSTRACT FROM AUTHOR]

The article examines the possibilities of numerical solution of chimney load from the effect of wind. The shear‐stress transport (SST) k‐ω turbulence model in ANSYS Fluent software is used to evaluate the task of the flow around the circumference of the rough cylinder. Calculations are performed on two different meshes that lead to the solution using wall function and near wall modeling. These two solution approaches in terms of defining wall roughness are presented in the paper by evaluating of the time dependence of the mean pressure coefficient distribution at the circumference, drag coefficient, and lift coefficient. The accuracy of the calculations is verified with parameters determined according to valid standards. [ABSTRACT FROM AUTHOR]

Two deep learning (DL) models addressing the super-resolution (SR) reconstruction of turbulent flows from low-resolution coarse flow field data are developed. One is the static convolutional neural network (SCNN), and the other is the novel multiple temporal paths convolutional neural network (MTPC). The SCNN model takes instantaneous snapshots as an input, while the MTPC model takes a time series of velocity fields as an input, and it includes spatial and temporal information simultaneously. Three temporal paths are designed in the MTPC to fully capture features in different time ranges. A weight path is added to generate pixel-level weight maps of each temporal path. These models were first applied to forced isotropic turbulence. The corresponding high-resolution flow fields were reconstructed with high accuracy. The MTPC seems to be able to reproduce many important features as well, such as kinetic energy spectra and the joint probability density function of the second and third invariants of the velocity gradient tensor. As a further evaluation, the SR reconstruction of anisotropic channel flow with the DL models was performed. The SCNN and MTPC remarkably improve the spatial resolution in various wall regions and potentially grasp all the anisotropic turbulent properties. It is also shown that the MTPC supplements more under-resolved details than the SCNN. The success is attributed to the fact that the MTPC can extract extra temporal information from consecutive fluid fields. The present work may contribute to the development of the subgrid-scale model in computational fluid dynamics and enrich the application of SR technology in fluid mechanics. [ABSTRACT FROM AUTHOR]

The article offers information on small-scale universality in the spectral structure of transitional pipe flows. Topics include the importance of “small-scale universality” with turbulence theory; and the study which informs that the small-scale universality governs the spectral structure of a class of flows with no apparent ties to the idealized flows that is transitional pipe flows.

Fricative consonants are known to be pronounced by controlling turbulent flow inside a vocal tract. In this study, a simplified vocal tract model was proposed to investigate the characteristics of flow and sound during production of the fricative [s] in a word context. By controlling the inlet flow rate and tongue speed, the acoustic characteristics of [s] were reproduced by the model. The measurements with a microphone and a hot-wire anemometer showed that the flow velocity at the teeth gap and far-field sound pressure started oscillating before the tongue reached the /s/ position, and continued during tongue descent. This behaviour was not affected by the changes of the tongue speed. These results indicate that there is a time shift between source generation and tongue movement. This time shift can be a physical constraint in the articulation of words which include /s/. With the proposed model, we could investigate the effects of tongue speed on the flow and sound generation in a parametric way. The proposed methodology is applicable for other phonemes to further explore the aeroacoustics of phonation. [ABSTRACT FROM AUTHOR]

The capture precision of the free surface of an open-channel with a water-air interface directly affects the calculation precision of flow field characteristics and general characteristics of the flow. Significant research effort has been devoted to Level Set since its creation, although the relevant research is mainly limited to bubble or droplet movement. In this paper, Level Set method is applied to a two-dimensional numerical simulation of open-channel turbulence, while a new numerical model is proposed and multispot synchronized experimental data are applied to the validation of numerical model. In addition, the model is used to study the flow field characteristics and general characteristics of open-channel flow, which have a water-level lowering curve. The study shows that (1) a semilogarithm zone of vertical distribution of longitudinal velocity is still present amid the transition of flow from nonuniform to uniform, and the depth-averaged velocity and wall shear stress increase along the flowing path. (2) both the energy loss coefficient and roughness coefficient of the flow at nonuniform flow region are greater than the respective values at uniform flow region, and the magnitude of the deviation is relevant to the magnitude of the flow deviation from uniform flow stage. [ABSTRACT FROM AUTHOR]

In this study we attempted to determine the effect of various feeding methods (bottom and surface feeding) used in the hatchery, on the survival and growth rates of hatchery-reared sea trout (Salmo trutta trutta L.) in the wild. Rearing was performed in two variants: a bottom-fed group (BFG) and a surface-fed group (SFG). At the end of the rearing time, we observed that BFG fish gathered at the bottom of tank, as opposed to SFG fish, which swam in the whole water column. After 4 weeks of rearing, the fish were released into two similar streams. After about 2 months the fish were captured and the foodbase of the streams were examined. 30 fish from each group have been randomly selected for stomach contents analysis. In the shallow stream the growth rates were better for the BFG fish than the SFG and also a significantly higher number of typical benthic taxa was found in stomachs of the BFG fish than the SFG fish. In the deeper stream more food was found in the stomachs of the SFG fish than in the BFG fish. The analyzed results showed that factors such as stream depth, current velocity, and turbulence can also affect the rearing success of juvenile salmonids in hatchery streams. Bottom feeding fish during rearing has a positive impact only on the fish in shallow watercourses, where there is no turbulence, and the food is not carried by the current drift or washed out from the bottom into the drift. [ABSTRACT FROM AUTHOR]

Impact of barge movement on phytoplankton abundance and biomass was assessed in the lower stretch of river Ganga, popularly known as Bhagirathi-Hooghly river, during April 2016 to March, 2017. Based on the magnitude of tide, intensity of shipping and boating activities, the stretch from Baranagar to Lalbag (278 km), located at latitude (22°38'33.41"N to 24°10'59.75"N) and longitude (88°21'21.29"E to 88°16'5.65"E) was divided into three zones viz. zone—I (Baranagar to Barrackpore), zone II (Triveni to Balagarh) and zone III (Nabadweep to Lalbag). Water samples were collected randomly from six stations covering 22 barge movements at their passage at three different time intervals viz., 30 minutes before ‘barge movement’, during ‘barge movement’ and 30 minutes after ‘barge movement’. Analysis revealed the presence of 52 phytoplankton taxa belonged to 5 phylum during the study period. The abundance of phytoplankton was highest in zone—I followed by zone III and the zone II. A 44% decrease (1,997 ±1,510 ul-1) in phytoplankton abundance was observed during ‘barge movement’ with respect to normal condition (3,513 ± 2,239 ul-1) which could be due to propeller turbulence in the passage. Cell damage study revealed 21% damage in phytoplankton cell structure in ‘during barge’ followed by ‘after barge’ (10%) condition compared to natural state (6%). Study revealed that phytoplankton biomass (Chlorophyll a) was influenced by ‘barge movement’ in the sampling stretches and the impact was assessed by one way ANOVA. The effect was found significant at Barrackpore (p <0.01), Triveni (p <0.01), Balagarh (p <0.01) and Lalbag (p <0.01) where as it was insignificant at Baranagar and Nabadweep, which may be due to continuous and existing boat trafficking at Baranagar and Nabadweep. Two way ANOVA computed using ‘barge movement’ and sampling stations showed significant (p<0.01) effect on magnitude of Chl a concentrations in the sampling locations. Thus, the ‘barge movement’ influenced phytoplankton abundance and biomass, it had a detrimental effect on phytoplankton cell architecture also. The data set of this work serves as foundation information to understand the ecological implications augmented barge induced environmental disturbances in waterways. This is the first such study which depicts the impact of ‘barge movement’ on aquatic food chain linkages in Bhagirathi- Hooghly river. [ABSTRACT FROM AUTHOR]

This paper is an attempt to introduce methods and concepts of the Riemann–Cartan geometry largely used in such physical theories as general relativity, gauge theories, solid dynamics to fluid dynamics in general and to studying and modeling turbulence in particular. Thus, in order to account for the rotational degrees of freedom of the irregular dynamics of small-scale vortexes, we further generalize our unified first-order hyperbolic formulation of continuum fluid and solid mechanics which treats the flowing medium as a Riemann–Cartan manifold with zero curvature but non-vanishing torsion. We associate the rotational degrees of freedom of the main field of our theory, the distortion field, to the dynamics of microscopic (unresolved) vortexes. The distortion field characterizes the deformation and rotation of the material elements and can be viewed as anholonomic basis triad with non-vanishing torsion. The torsion tensor is then used to characterize distortion's spin and is treated as an independent field with its own time evolution equation. This new governing equation has essentially the structure of the nonlinear electrodynamics in a moving medium and can be viewed as a Yang–Mills-type gauge theory. The system is closed by providing an example of the total energy potential. The extended system describes not only irreversible dynamics (which raises the entropy) due to the viscosity or plasticity effect, but it also has dispersive features which are due to the reversible energy exchange (which conserves the entropy) between micro- and macroscales. Both the irreversible and dispersive processes are represented by relaxation-type algebraic source terms so that the overall system remains first-order hyperbolic. The turbulent state is then treated as an excitation of the equilibrium (laminar) state due to the nonlinear interplay between dissipation and dispersion. [ABSTRACT FROM AUTHOR]

Propagule dispersal is an integral part of the life cycle of seagrasses; important for colonising unvegetated areas and increasing their spatial distribution. However, to understand recruitment success, seed dispersal and survival in habitats of different complexity remains to be quantified. We tested the single and synergistic effects of three commonly distributed ecosystem engineers—eelgrass (Zostera marina), oysters (Magellana gigas) and blue mussels (Mytilus edulis)—on trapping of Z. marina seeds in a hydraulic flume under currents. Our results suggest that seed retention increases with habitat complexity and further reveal insights into the underlying mechanisms. In eelgrass canopy, trapping occurred mostly through direct blocking of a seed’s pathway, while trapping in bivalve patches was mainly related to altered hydrodynamics in the lee side, i.e. behind each specimen. With increasing flow velocity (24–30 cm s-1 in eelgrass canopy, 18–30 cm s-1 in bivalve patches), modifications of the sediment surface through increased turbulence and erosive processes became more important and resulted in high seed trapping rates. Furthermore, we show that while monospecific patches of seagrass and bivalves had different trapping optima depending on flow velocities, intermixing resulted in consistently high trapping rates throughout the investigated hydrodynamic gradient. Our results highlight the importance of positive interactions among ecosystem engineers for seed retention and patch emergence in eelgrass. [ABSTRACT FROM AUTHOR]

Experimental and numerical analyses performed on a scaled-down model of a 1900TEU container-ship are reported herein. Wind-tunnel and towing-tank experiments along with computational-fluid-dynamic simulations were performed to obtain (1) wind-load coefficients for superstructure of container ship at different wind angles under full-load operating conditions; (2) wave resistance of the model sans the superstructure under different wave conditions; and (3) combined wind–wave resistance of the model in the head waves coupled with a fluctuating wind. Wind-tunnel experiments were first performed to determine wind-load coefficients concerning of the superstructure at different wind angles. Subsequently, the obtained wind-load coefficients from the wind tunnel test were compared against numerical and empirically obtained results to validate the applicability of the applied numerical methods. Next, the wave-induced resistance to ship motion was investigated via a series of towing-tank experiments and numerical simulations to analyze the resistance and motion of ship under wavy conditions. Finally, characteristics of the added resistance to ship motion under conditions of combined wind–wave load were analyzed, and the coupling between ship motion and combined wind–wave load was used to investigate the changes in added resistance under different load scenarios. The results reveal that combined wind–wave load causes the resistance to ship motion to exceed the algebraic sum of the corresponding resistances under standalone wind- and wave-load conditions. The additional resistance was observed to be a combined manifestation of resistances induced by ship motion and wave-parameter alterations. [ABSTRACT FROM AUTHOR]

Environmental changes can modify the phenotypic characteristics of populations, which in turn can influence their evolutionary trajectories. In ectotherms like fishes, temperature is a particularly important environmental variable that is known to have significant impacts on the phenotype. Here, we raised specimens of the surface ecomorph of Astyanax mexicanus at temperatures of 20°C, 23°C, 25°C, and 28°C to examine how temperature influenced vertebral number and body shape. To increase biological realism, specimens were also subjected to two water turbulence regimes. Vertebral number was counted from x-rays and body shape variation was analysed using geometric morphometric methods. Temperature significantly impacted mean total vertebral number, which increased at the lowest and highest temperatures. Fish reared at lower temperatures had relatively more precaudal vertebrae while fish reared at higher temperatures had relatively more caudal vertebrae. Vertebral anomalies, especially vertebral fusions, were most frequent at the extreme temperature treatments. Temperature significantly impacted body shape as well, with fish reared at 20°C being particularly divergent. Water turbulence also impacted body shape in a generally predictable manner, with specimens reared in high turbulence environments being more streamlined and having extended dorsal and anal fin bases. Variation in environmental variables thus resulted in significant changes in morphological traits known to impact fish fitness, indicating that A. mexicanus has the capacity to exhibit a range of phenotypic plasticity when challenged by environmental change. Understanding the biochemical mechanisms underlying this plasticity and whether adaptive plasticity has influenced the evolutionary radiation of the Characidae, are major directions for future research. [ABSTRACT FROM AUTHOR]

Jameson cell is a flotation device that has unique characteristics for fine grained particles, and thus, it has more than three hundred applications in worldwide. On the contrary, the flotation performance of the cell decreases by coarser feeding, which limits the application of the Jameson cell. It has been figured out that the main reason for the performance decrease for coarse particle is turbulence which occurs at the outlet of the downcomer in the Jameson cell. Therefore, the aim of this study was to prevent the performance decrease in the Jameson cell by modifying the downcomer which was implemented by taking into account the fluid mechanics law and mathematical modelling. The modified downcomer, which can be called as diffuser, can provide better aggregate stability and less turbulence at the end of the downcomer. Thus, theoretically the better performance was obtained by the use of the new form of downcomer. In addition, a series of experiments were carried out to verify the success of the modified downcomer. According to the results, velocity gradient (G) decreased to 640 s−1 from 671 s−1 by using the modified downcomer, and the maximum floatable particle size increased to 255 µm from 225 µm. [ABSTRACT FROM AUTHOR]

Hydrodynamic properties of a turbulent two-phase flow (water droplets in the air) produced by a mechanical jet sprayer were studied experimentally and the drag force on the droplets was found to be anomalously weak; the drag coefficient is four to seven times smaller than predicted by standard expressions. Several hypotheses are suggested in this article and discussed in an attempt to explain the phenomenon. A two-dimensional model of the flow with the drag anomaly is proposed, which provides excellent agreement between the numerical and experimental results. Taking the drag anomaly into account allows an explanation of a number of features of the two-phase flow that are hard to explain otherwise, in particular, the fact that only about one-half of the initial water jet momentum was transferred to the gas during the experiment. [ABSTRACT FROM AUTHOR]

The laminar-turbulent transition has always been a hot topic of fluid mechanics. Receptivity is the initial stage and plays a crucial role in the entire transition process. The previous studies of receptivity focus on external disturbances such as sound waves and vortices in the free stream, whereas those on the leading-edge receptivity to the three-dimensional free-stream turbulence (FST), which is more general in the nature, are rarely reported. In consideration of this, this work is devoted to investigating the receptivity process of three-dimensional Tollmien-Schlichting (T-S) wave packets excited by the three-dimensional FST in a flat-plate boundary layer numerically. The relations between the leading-edge receptivity and the turbulence intensity are established, and the influence of the FST directions on the propagation directions and group velocities of the excited T-S wave packets is studied. Moreover, the leading-edge receptivity to the anisotropic FST is also studied. This parametric investigation can contribute to the prediction of laminar-turbulent transition. [ABSTRACT FROM AUTHOR]

A theory for turbulent particle pair diffusion in the inertial subrange [Malik NA, PLoS ONE 13(10):e0202940 (2018)] is investigated numerically using a Lagrangian diffusion model, Kinematic Simulations [Kraichnan RH, Phys. Fluids 13:22 (1970); Malik NA, PLoS ONE 12(12):e0189917 (2017)]. All predictions of the theory are observed in flow fields with generalised energy spectra of the type, E(k) ∼ k− p. Most importantly, two non-Richardson regimes are observed: for short inertial subrange of size 102 the simulations yield quasi-local regimes for the pair diffusion coefficient, ; and for asymptotically infinite inertial subrange the simulations yield non-local regimes , with γ intermediate between the purely local scaling γl = (1 + p)/2 and the purely non-local scaling γnl = 2. For intermittent turbulence spectra, E(k) ∼ k−1.72, the simulations yield , in agreement with the revised 1926 dataset [Richardson LF, Proc. Roy. Soc. Lond. A 100:709 (1926); Malik NA, PLoS ONE 13(10):e0202940 (2018)]. These results lend support to the physical picture proposed in the new theory that turbulent diffusion in the inertial subrange is governed by both local and non-local diffusion transport processes. [ABSTRACT FROM AUTHOR]