Three-dimensional Turbulent Flow Research Articles

Interplay between advective, diffusive and active barriers in (rotating) Rayleigh–Bénard flow

Our understanding of the material organization of complex fluid flows has benefited recently from mathematical developments in the theory of objective coherent structures. These methods have provided a wealth of approaches that identify transport barriers in three-dimensional (3-D) turbulent flows. Specifically, theoretical advances have been incorporated into numerical algorithms that extract the most influential advective, diffusive and active barriers to transport from data sets in a frame-indifferent fashion. To date, however, there has been very limited investigation into these objectively defined transport barriers in 3-D unsteady flows with complicated spatiotemporal dynamics. Similarly, no systematic comparison of advective, diffusive and active barriers has been carried out in a 3-D flow with both thermally driven and mechanically modified structures. In our study, we utilize simulations of turbulent rotating Rayleigh–Bénard convection to uncover the interplay between advective transport barriers (Lagrangian coherent structures), material barriers to diffusive heat transport, and objective Eulerian barriers to momentum transport. For a range of (inverse) Rossby numbers, we identify each type of barrier and find intriguing relationships between momentum and heat transport that can be related to changes in the relative influence of mechanical and thermal forces. Further connections between bulk behaviours and structure-specific behaviours are also developed.

A massively parallel implicit 3D unstructured grid solver for computing turbulent flows on latest distributed memory computational architectures

An implicit unstructured grid density-based solver–PRAVAHA based on a parallel variant of the lower upper symmetric Gauss-Seidel (LUSGS) method is developed to compute large-scale engineering problems. A four-layered parallel algorithm is designed to efficiently compute three-dimensional turbulent flows on massively parallel modern multiple instruction multiple data-stream (MIMD) computational hardware. This data parallel approach achieves multiple layers of parallelism including continuity of flow solution, transfer of solution gradients, and calculation of drag/lift/solution residuals, right up to the innermost implicit LUSGS solver sub-routine, which is relatively less explored in the literature. Domain decomposition is performed using the METIS software based on multi-level graph partitioning algorithms. Non-blocking message-passing interface library functions are used to manage inter-processor communication through explicit message passing, efficiently. Super-linear scalability of the parallel solver is established on the current state-of-the-art supercomputing facility, the 838 teraflops PARAM seva on up to 6144 cores. Linear or even super-linear speedup on problems of significant size is observed even on ad-hoc parallel computing platforms like workstations and multi-node clusters, for turbulent flow simulations.

Flow time history representation and reconstruction based on machine learning

Based on deep learning technology, a new spatiotemporal flow data representation and reconstruction scheme is proposed by using flow time history (FTH) data instead of flow snapshots. First, the high-dimensional nonlinear flow system is reduced to a low-dimensional representation latent code using the FTH autoencoder model. Second, the mapping from physical space to latent code space is built using mathematical and machine-learning schemes. Finally, FTH at unavailable positions in physical space is generated by the FTH generator. The proposed scheme is validated by three case studies: (i) representing and recovering the FTH data of periodic laminar flow around a circular cylinder at Re = 200 and generating high-resolution laminar flow data; (ii) reconstructing complex FTH of flow past cylinder at Re = 3900 which including laminar and turbulent flow region and generating three-dimensional high-resolution turbulent flow data, respectively; (iii) representing and generating multi-variable turbulent flow data simultaneously using the multi-channel model. The results show that the proposed scheme is an effective low-dimensional representation for complex flow time variant features, which is suitable for both laminar and turbulent FTH data to generate spatiotemporal high-resolution FTH data in three-dimensional space.

Investigation on aerodynamic noise for leading edge erosion of wind turbine blade

Wind turbine blade is extremely prone to leading edge erosion under complicated operation conditions. This decreases the aerodynamic performance and power generation efficiency of wind turbine. Currently acoustic-based erosion detection of the blade still faces a significant challenge. Consequently, this paper presents aerodynamic noise mechanism of the eroded blade using the computational fluid dynamics method. The Zonal Detached Delay Eddy Simulation turbulence model is applied to obtain the three-dimensional instantaneous turbulent flow field. Then the far-field aerodynamic noise is carried out using the Ffowcs Williams and Hawkings approach. Simulations are performed for the erosion condition that determined by the length and depth at leading edge of 5-MW National Renewable Laboratory wind turbine. Results indicate that erosion leads to unsteady pressure pulsation near the leading edge, decrease of surface pressure difference in tip area, increase of airflow separation region and forward movement of separation point. Furthermore, the eroded blade achieves higher acoustic level than that of the normal one. From the noise directivity of wind turbine blade, erosion causes obvious asymmetry of noise pattern in the upwind and downwind directions.

Heavy and light inertial particle aggregates in homogeneous isotropic turbulence: A study on breakup and stress statistics

The breakup of inertial, solid aggregates in an incompressible, homogeneous and isotropic three-dimensional turbulent flow is studied by means of a direct numerical simulation, and by a Lagrangian tracking of the aggregates at varying Stokes number and fluid-to-particle density ratio. Within the point-particle approximation of the Maxey–Riley–Gatignol equations of motion, we analyze the statistics of the time series of shear and drag stresses, which are here both deemed as responsible for aggregate breakup. We observe that, regardless of the Stokes number, the shear stresses produced by the turbulent velocity gradients similarly impact the breakup statistics of inertial and neutrally buoyant aggregates, and dictate the breakup rate of loose aggregates. When the density ratio is different from unity, drag stresses become dominant and are seen to be able to cause to breakup of also the most resistant aggregates. A transition from a shear-dominated to a drag-dominated breakup regime is observed, and a power-law is seen to well describe the breakup rate of loose aggregates regardless of their inertia. The present work assesses the role of shear and drag stresses on aggregate breakup and computes breakup rates to be possibly used in population balance models.

Mean flow and fluctuations in the three-dimensional turbulent cellular flow

Theoretical and numerical turbulent flow studies either consider turbulence as generated by fluid-solid interactions or focus on intrinsic, bulk properties. There is another group of flows for which homogeneity and isotropy are broken by the body force that sustains the flow, not by physical boundaries. In this class we consider the cellular flow produced by a two-dimensional spatially periodic forcing whose laminar state corresponds to a regular array of counter-rotating vortices. We find that, despite the developed turbulence recovering isotropic features at small scales, the signature of forcing remains in the mean flow, allowing us to quantify the efficiency of the work done by the force.

A positivity-preserving and conservative high-order flux reconstruction method for the polyatomic Boltzmann–BGK equation

In this work, we present a positivity-preserving high-order flux reconstruction method for the polyatomic Boltzmann–BGK equation augmented with a discrete velocity model that ensures the scheme is discretely conservative. Through modeling the internal degrees of freedom, the approach is further extended to polyatomic molecules and can encompass arbitrary constitutive laws. The approach is validated on a series of large-scale complex numerical experiments, ranging from shock-dominated flows computed on unstructured grids to direct numerical simulation of three-dimensional compressible turbulent flows, the latter of which is the first instance of such a flow computed by directly solving the Boltzmann equation. The results show the ability of the scheme to directly resolve shock structures without any ad hoc numerical shock capturing method and correctly approximate turbulent flow phenomena in a consistent manner with the hydrodynamic equations.

The effect of short pin fin aspect ratio on thermal characteristics of intermittent impinging jet; An experimental and numerical study

BackgroundPin fins are secondary surfaces extending from an object to enhance the heat transfer rate. Pin fin is one of the most effective practical techniques used in many industrial applications and thermal treatments especially for cooling electronic devices. Also, Pulsating flow is extremely used in the machinery industry and it can improve the heat transfer. Therefore, pulsating flow is combined with an extended surface to enhance the heat transfer efficiency. MethodsThe current paper investigates numerically and experimentally the intermittent impingement flow and consequence heat transfer characteristics in the presence of a pin-fin array over a flat plate. The RNG k − ɛ model is employed to simulate unsteady three-dimensional turbulent flow using CFD software. The influences of jet Reynolds number, pulsation frequency, jet-to-surface distance, and aspect ratio on the distribution of the area-time averaged Nusselt number are studied. 36 elliptical pin-fins considered at three rows on the surface, placed at r/ D = 3, 5, and 7 (36, 60, and 84 mm) from the central point of the jet. Considering the influence of the aspect ratio on the streamline and temperature patterns of the flow, numerical simulations were conducted in various pin-fin diameters of 4–12 mm. Significant findingsFrom the experimental data, the results indicated that there is a specific frequency that the heat transfer increases for Reynolds numbers in the range of 10,000–20,000. The results illustrated that the rate of heat transfer is reduced with rising the diameter of the pin fin for AR>1, whereas it is enhanced for AR<1. The area-time averaged Nusselt number is enhanced with rising aspect ratio at various pin fin heights. For Re=10,000, the heat transfer rate decreases with increasing the jet-to-surface distance in steady state while it increases for pulsating flow. Also, the maximum value of turbulent kinetic energy appears nearby the pin-fin owing to the formation of a horseshoe vortex. The vortex structures are strengthened and grow downstream, as the frequency increases.

Reconstruction of three-dimensional turbulent flow structures using surface measurements for free-surface flows based on a convolutional neural network

A model based on a convolutional neural network (CNN) is designed to reconstruct the three-dimensional turbulent flows beneath a free surface using surface measurements, including the surface elevation and surface velocity. Trained on datasets obtained from the direct numerical simulation of turbulent open-channel flows with a deformable free surface, the proposed model can accurately reconstruct the near-surface flow field and capture the characteristic large-scale flow structures away from the surface. The reconstruction performance of the model, measured by metrics such as the normalised mean squared reconstruction errors and scale-specific errors, is considerably better than that of the traditional linear stochastic estimation (LSE) method. We further analyse the saliency maps of the CNN model and the kernels of the LSE model and obtain insights into how the two models utilise surface features to reconstruct subsurface flows. The importance of different surface variables is analysed based on the saliency map of the CNN, which reveals knowledge about the surface–subsurface relations. The CNN is also shown to have a good generalisation capability with respect to the Froude number if a model trained for a flow with a high Froude number is applied to predict flows with lower Froude numbers. The results presented in this work indicate that the CNN is effective regarding the detection of subsurface flow structures and by interpreting the surface–subsurface relations underlying the reconstruction model, the CNN can be a promising tool for assisting with the physical understanding of free-surface turbulence.

In vitro-in silico correlation of three-dimensional turbulent flows in an idealized mouth-throat model.

There exists an ongoing need to improve the validity and accuracy of computational fluid dynamics (CFD) simulations of turbulent airflows in the extra-thoracic and upper airways. Yet, a knowledge gap remains in providing experimentally-resolved 3D flow benchmarks with sufficient data density and completeness for useful comparison with widely-employed numerical schemes. Motivated by such shortcomings, the present work details to the best of our knowledge the first attempt to deliver in vitro-in silico correlations of 3D respiratory airflows in a generalized mouth-throat model and thereby assess the performance of Large Eddy Simulations (LES) and Reynolds-Averaged Numerical Simulations (RANS). Numerical predictions are compared against 3D volumetric flow measurements using Tomographic Particle Image Velocimetry (TPIV) at three steady inhalation flowrates varying from shallow to deep inhalation conditions. We find that a RANS k-ω SST model adequately predicts velocity flow patterns for Reynolds numbers spanning 1'500 to 7'000, supporting results in close proximity to a more computationally-expensive LES model. Yet, RANS significantly underestimates turbulent kinetic energy (TKE), thus underlining the advantages of LES as a higher-order turbulence modeling scheme. In an effort to bridge future endevours across respiratory research disciplines, we provide end users with the present in vitro-in silico correlation data for improved predictive CFD models towards inhalation therapy and therapeutic or toxic dosimetry endpoints.

Numerical simulation of three-dimensional turbulent flows based on the mathematical model of wave processes

Numerical simulation of three-dimensional turbulent flows based on the mathematical model of wave processes

Three-dimensional ESRGAN for super-resolution reconstruction of turbulent flows with tricubic interpolation-based transfer learning

Turbulence is a complicated phenomenon because of its chaotic behavior with multiple spatiotemporal scales. Turbulence also has irregularity and diffusivity, making predicting and reconstructing turbulence more challenging. This study proposes a deep-learning approach to reconstruct three-dimensional (3D) high-resolution turbulent flows from spatially limited data using a 3D enhanced super-resolution generative adversarial networks (3D-ESRGAN). In addition, a novel transfer-learning method based on tricubic interpolation is employed. Turbulent channel flow data at friction Reynolds numbers Reτ = 180 and Reτ = 500 were generated by direct numerical simulation (DNS) and used to estimate the performance of the deep-learning model as well as that of tricubic interpolation-based transfer learning. The results, including instantaneous velocity fields and turbulence statistics, show that the reconstructed high-resolution data agree well with the reference DNS data. The findings also indicate that the proposed 3D-ESRGAN can reconstruct 3D high-resolution turbulent flows even with limited training data.

Three-Dimensional Turbulent Flow Characteristics Near the Leading Edge of a Longitudinal Structure in the Presence of an Inclined Channel Bank

The present work investigates turbulent flow structures and behavior near the leading edge of a longitudinal flow obstruction in an open channel with an inclined bank. A volumetric particle image velocimetry (VPIV) was employed to collect velocity data. The results indicate that a relatively moderate channel bank angle (θ=28∘) does not prevent the formation of a junction vortex (JV) system. Indeed, it is found that the JV system develops over the channel bank and extends to the leading edge of the flow obstruction. It is demonstrated that the main factor that strengthens the primary junction vortex (JV1) at the tip of the protrusion is the pronounced downward flow. The probability density functions (pdfs) of the velocity fluctuations specify that the JV1 oscillates aperiodically between the so-called zero-flow and back flow modes. This explains the amplification of TKE at its core. It is shown that the velocity difference between the peaks of the pdf increases from over the channel bank towards the tip of the flow obstruction. The aperiodic behavior of the JV1 is confirmed via the proper orthogonal decomposition (POD) technique. Specifically, it is demonstrated that the leading POD modes, associated with the JV system, contain lower energy content compared to periodic flows. The time-averaged vertical vorticity field verifies the presence of a tornado like vortex structure near the upstream face of the retaining wall. Finally, the results suggest that the largest bed shear stress values in the mean flow are located near the tip of the protrusion.

Computational Fluid Dynamics Simulation on Thermal Performance of Al/Al2O3/SWCNT Nanocoolants for Turning Operations.

The objective of this study is to numerically investigate the thermal performance of cutting fluids dispersed with nanoparticles for effective heat removal during turning operations. The simulations are performed using Ansys Fluent software, and the problem is modelled as a three-dimensional turbulent incompressible single-phase flow. The computational domain consists of a heated cutting tool and work piece, and nanocoolants are sprayed from a nozzle located above the machining zone. The nanocoolants are prepared by mixing mineral oil with nanoparticles of Al2O3 (Aluminium Oxide), Al (Aluminium) and SWCNT (Single Walled Carbon Nanotube). The heat transfer performances of different nanocoolants are compared by varying the nanoparticle volume fraction (φ) and coolant velocity (Uc) in the range of 2% ≤ φ ≤ 8% and 1 m/s ≤ Uc ≤ 15 m/s, respectively. The results indicated a drastic drop in the cutting tool temperature with an increase in the volume fraction of dispersed nanoparticles and coolant velocity. The increase in volume fraction decreases the average cutting tool temperature by 25.65% and also enhances the average heat transfer rate by 25.43%. It is additionally observed that SWCNT nanocoolants exhibited a superior thermal performance and heat removal rate compared with Al and Al2O3 nanocoolants. The analysed numerical results are validated and are in good accordance with the benchmark results validated from literature.

АНАЛІЗ КОНСТРУКТИВНИХ ЗАХОДІВ З УКРІПЛЕННЯ НИЖНІХ Б’ЄФІВ ГІДРОТЕХНІЧНИХ СПОРУД У ТРАНСПОРТНОМУ БУДІВНИЦТВІ З ДОРОЖНІХ ВОДОПРОПУСКНИХ ТРУБ

Introduction. Road culverts are one of the most massive hydraulic structures of transport construction in Ukraine. The bottom beef of such structures works in difficult operating conditions: with significant unevenness of the distribution of specific costs; high kinetics of the discharge flow and its saturation with sediments, floating garbage; small flooding of the diversion channel, etc. The main difficulty of the problem lies in the fact that a two-dimensional flow takes place in the area of free spreading, and in the area of quenching of excess kinetic energy, this two-dimensional flow turns into a three-dimensional turbulent flow, which makes it practically impossible to obtain a theoretical solution for the movement of water in the lower bay of hydrotechnical structures . The need to improve the structures of the lower bief of hydraulic structures of transport construction from road culverts is urgent, taking into account that the existing approaches do not lead to the desired positive results. Problems. From the literature analysis, it was established that the strengthening of the lower biefs of hydraulic structures of transport construction from road culverts is an important component for the durability of the structure itself and its proper functioning. Goal. It consists in the analysis of constructive measures to strengthen the lower banks of hydraulic structures of transport construction from road corrugated metal culverts. The results. An analysis of the main approaches to strengthening the lower beams of hydraulic structures of transport construction from road culverts was carried out. The analysis of the calculation of the structural elements of active type energy extinguishers was performed. Conclusions. To date, there are two most common approaches to the solution of the problem of fixing the lower biefs of hydraulic structures of transport construction from road culverts: complete rejection of the arrangement of energy extinguishing structures, which causes a significant shift of the erosion gap from the road embankment; or the use of jet-type energy quenchers (of the water well type formed by a ledge or wall), breakers or dispersants of various types. However, both approaches do not completely solve the problem of extinguishing the energy of the water flow behind the structures of road culverts. The method of hydraulic calculations of ordinary concrete (conditionally smooth) pipes and metal corrugated pipes (with increased roughness of the inner surface) is performed according to the same method, the difference is only in the constants used in the calculation: roughness coefficient, friction slope, depth at the entrance to the pipe, etc. d., which in turn indicates the need for additional calculations and experimental studies. In addition, the existing methods of calculation for the optimization of the structures of energy quenchers in the lower biefs need experimental clarification.

3D MODELING OF TURBULENT FLOWS USING LES AND RANS APPROACHES BASED ON FILTERED EXPEDITION DATA

The article describes the developed software that made it possible to process a large amount of data from observations of the movement and parameters of the aquatic environment in the Sea of Azov, which was obtained during expeditionary research using the ADCP hydrophysical probe, using the filtration procedure. The filtering procedure significantly reduces the spread of data and the amplitude of fluctuations, which, in turn, makes it possible to more adequately evaluate the information obtained during field experiments. For different filter widths, a box filter, a Gauss filter and a Fourier filter were used. In these calculations, the filter width was set based on the size of the hydrodynamics problem to be solved and the grid scale corresponding to this size. The obtained data are planned to be used for numerical simulation of three-dimensional turbulent flows using the LES approach and comparison with the results of averaging by RANS.

Turbulence tracks recurrent solutions

Despite a long and rich history of scientific investigation, fluid turbulence remains one of the most challenging problems in science and engineering. One of the key outstanding questions concerns the role of coherent structures that describe frequently observed patterns embedded in turbulence. It has been suggested, but not proved, that coherent structures correspond to unstable, recurrent solutions of the governing equation of fluid dynamics. Here, we present experimental and numerical evidence that three-dimensional turbulent flow tracks, episodically but repeatedly, the spatial and temporal structure of multiple such solutions. Our results provide compelling evidence that coherent structures, grounded in the governing equations, can be harnessed to predict how turbulent flows evolve.

Direct numerical simulations of turbulent flow over misaligned traveling waves

Direct numerical simulations of turbulent flow over prescribed traveling waves in a half-channel flow setup subject to a combined streamwise and spanwise pressure gradient are performed at a friction Reynolds number of 180. The simulations undertaken in this study consider both flow-aligned (including opposing and following) and misaligned waves as we attempt to quantify the effect of wave misalignment on turbulence statistics, the pressure drag force, and the wave attenuation rate. For the simulations, we consider three characteristic wave age values corresponding to slow-, intermediate-, and fast-moving waves. Wave misalignment is taken into account by applying a spanwise pressure gradient vertical to the traveling waves, which results in a three-dimensional turbulent flow field above the moving waves. Key flow quantities such as the mean velocity, velocity variances, and momentum fluxes are found to vary with the wave parameters, confirming the findings of previous studies. In addition, our analysis shows that the mean velocity vector deviates from the applied pressure gradient with larger discrepancies being found when fast-moving waves run in an obtuse angle of 135° relative to the applied pressure gradient vector. Additionally, large deviation angles (up to 50°) between the applied pressure gradient and the shear-stress vector were found to exhibit their peak within the buffer layer in ζ+<10, whereas they rapidly reduce for ζ+>10, where ζ+ is the vertical coordinate in wall units. Finally, with the help of triple decomposition we show the dependence of the spanwise wave-coherent velocity on the dynamics of the vertical component and highlight important differences between flow-following and flow-opposing waves.

Aerothermal analysis of pulsed jet impinging on a flat surface with different pin configurations

In this work, the effect of a pin as a secondary surface mounted on hydrothermal behavior of impinging jet over a flat plate investigated numerically and experimentally. The transient three-dimensional turbulent flow is simulated by the Renormalization Group (RNG) k − ɛ model. The injection air is pulsed by square waves. In a radial arrangement, several differently shaped pins (i.e., circular, elliptical, and square) with the same cross-sectional areas are compared. Three Reynolds numbers (10,000, 15,000 and 20,000) and four pin-to-injection point distances (r = 2D, r = 3D, r = 4D and r = 5D) are considered. Within the experimental range, the results indicated that the use of a pulsating jet in the frequency range of 50–100 Hz enhances the rate of heat transfer. The rate of heat transfer of the square pin is less than that of the smooth surface. Based on specific performance parameters, the elliptical pin is found to be a favorable alternative configuration to a circular pin. Also, the results showed that the appropriate position to mount the pin on a flat surface at a radial distance is three times the diameter of the jet (r = 3D) for elliptical and circular pins.

Scalable in situ compression of transient simulation data using time-dependent bases

Large-scale simulations of time-dependent problems generate a massive amount of data and with the explosive increase in computational resources the size of the data generated by these simulations has increased significantly. This has imposed severe limitations on the amount of data that can be stored and has elevated the issue of input/output (I/O) into one of the major bottlenecks of high-performance computing. In this work, we present an in situ compression technique to reduce the size of the data storage by orders of magnitude. This methodology is based on time-dependent subspaces and it extracts low-rank structures from multidimensional streaming data by decomposing the data into a set of time-dependent bases and a core tensor. We derive closed-form evolution equations for the core tensor as well as the time-dependent bases. The presented methodology does not require the data history and the computational cost of its extractions scales linearly with the size of data — making it suitable for large-scale streaming datasets. To control the compression error, we present an adaptive strategy to add/remove modes to maintain the reconstruction error below a given threshold. We present four demonstration cases: (i) analytical example, (ii) incompressible unsteady reactive flow, (iii) stochastic turbulent reactive flow, and (iv) three-dimensional turbulent channel flow.