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The problem of the geodynamo is simple to formulate (Why does the Earth possess a magnetic field?), yet it proves surprisingly hard to address. As with most geophysical flows, the fluid flow of molten iron in the Earth's core is strongly influenced by the Coriolis effect. Because the liquid is electrically conducting, it is also strongly influenced by the Lorentz force. The balance is unusual in that, whereas each of these effects considered separately tends to impede the flow, the magnetic field in the Earth's core relaxes the effect of the rapid rotation and allows the development of a large-scale flow in the core that in turn regenerates the field. This review covers some recent developments regarding the interplay between rotation and magnetic fields and how it affects the flow in the Earth's core.
This review provides a comprehensive analysis of the literature on vortex-induced vibration (VIV) of flexible circular cylinders in cross-flow. It delves into the details of the underlying physics governing the VIV dynamics of cylinders characterized by low mass damping and high aspect ratio, subject to both uniform and shear flows. It compiles decades of experimental investigations, modeling efforts, and numerical simulations and describes the fundamental findings in the field. Key focal points include but are not limited to amplitude–frequency response behavior, the relationship between the distributed loading acting on the cylinder and the trajectories and the near wake structures around the cylinder, the existence of traveling waves, the identification of power-in/power-out regions, and the modal overlapping and mode competition phenomena.
Turbulence is often studied by tracking its spatiotemporal evolution and analyzing the dynamics of its different scales. The dual to this perspective is that of an observer who starts from measurements, or observations, of turbulence and attempts to identify their back-in-time origin, which is the foundation of data assimilation. This back-in-time search must contend with the action of chaos, which obfuscates the interpretation of the observations. When the available measurements satisfy a critical resolution threshold, the influence of chaos can be entirely mitigated and turbulence can be synchronized to the exact state–space trajectory that generated the observations. The critical threshold offers a new interpretation of the Taylor microscale, one that underscores its causal influence. Below the critical threshold, the origin of measurements becomes less definitive in regions where the flow is inconsequential to the observations. In contrast, flow events that influence the measurements, or are within their domain of dependence, are accurately captured. The implications for our understanding of wall turbulence are explored, starting with the highest density of measurements that entirely tame chaos and proceeding all the way to an isolated measurement of wall stress. The article concludes with a discussion of future opportunities and a call to action.
Chemical gradients, the spatial variations in chemical concentrations and components, are omnipresent in environments ranging from biological and environmental systems to industrial processes. These thermodynamic forces often play a central role in driving transport processes taking place in such systems. This review focuses on diffusiophoresis, a phoretic transport phenomenon driven by chemical gradients. We begin by revisiting the fundamental physicochemical hydrodynamics governing the transport. Then we discuss diffusiophoresis arising in flow systems found in natural and artificial settings. By exploring various scenarios where chemical gradients are encountered and exploited, we aim to demonstrate the significance of diffusiophoresis and its state-of-the-art development in technological applications.
Ice structures such as accretion on airplanes, wires, or roadways; ice falls; ice stalactites; frozen rivers; and aufeis are formed by the freezing of capillary flows (drops, rivulets, and films). To understand these phenomena, a detailed exploration of the complex coupling between capillary flow and solidification is necessary. Among the many scientific questions that remain open in order to understand these problems are the confinement of the thermal boundary layer by the free surface, the interaction between a freezing front and a free surface, the effect of freezing on the contact line motion, etc. This review focuses mainly on water and ice, discussing the theoretical framework and recent developments in the main areas of the freezing–capillarity interaction. The text deeply explores the freezing of a moving drop or a rivulet and the fundamental problem of wetting water on ice. Additionally, it highlights some of the main open questions on the subject.
The environmental setting of the Dead Sea combines several aspects whose interplay creates flow phenomena and transport processes that cannot be observed anywhere else on Earth. As a terminal lake with a rapidly declining surface level, the Dead Sea has a salinity that is close to saturation, so that the buoyancy-driven flows common in lakes are coupled to precipitation and dissolution, and large amounts of salt are being deposited year-round. The Dead Sea is the only hypersaline lake deep enough to form a thermohaline stratification during the summer, which gives rise to descending supersaturated dissolved-salt fingers that precipitate halite particles. In contrast, during the winter the entire supersaturated, well-mixed water column produces halite. The rapid lake level decline of O(1 m/year) exposes vast areas of newly formed beach every year, which exhibit deep incisions from streams. Taken together, these phenomena provide insight into the enigmatic salt giants observed in the Earth's geological record and offer lessons regarding the stability, erosion, and protection of arid coastlines under sea level change.
By imploding fuel of hydrogen isotopes, inertial confinement fusion (ICF) aims to create conditions that mimic those in the Sun's core. This is fluid dynamics in an extreme regime, with the ultimate goal of making nuclear fusion a viable clean energy source. The fuel must be reliably and symmetrically compressed to temperatures exceeding 100 million degrees Celsius. After the best part of a century of research, the foremost fusion milestone was reached in 2021, when ICF became the first technology to achieve an igniting fusion fuel (thermonuclear instability), and then in 2022 scientific energy breakeven was attained. A key trade-off of the ICF platform is that greater fuel compression leads to higher burn efficiency, but at the expense of amplified Rayleigh–Taylor and Richtmyer–Meshkov instabilities and kinetic-energy-wasting asymmetries. In extreme cases, these three-dimensional instabilities can completely break up the implosion. Even in the highest-yielding 2022 scientific breakeven experiment, high-atomic-number (high-Z) contaminants were unintentionally injected into the fuel. Here we review the pivotal role that fluid dynamics plays in the construction of a stable implosion and the decades of improved understanding and isolated experiments that have contributed to fusion ignition.
Our understanding of respiratory flow phenomena has been consolidated over decades with the exploration of in vitro and in silico canonical models that underscore the multiscale fluid mechanics spanning the vast airway complex. In recent years, there has been growing recognition of the significant intersubject variability characterizing the human lung morphometry that modulates underlying canonical flows across subjects. Despite outstanding challenges in modeling and validation approaches, exemplified foremost in capturing chronic respiratory diseases, the field is swiftly moving toward hybrid in silico whole-lung simulations that combine various model classes to resolve airflow and aerosol transport spanning the entire respiratory tract over cumulative breathing cycles. In the years to come, the prospect of accessible, community-curated datasets, in conjunction with the use of machine learning tools, could pave the way for in silico population-based studies to uncover unrecognized trends at the population level and deliver new respiratory diagnostic and pulmonary drug delivery endpoints.
Lagrangian averaging theories, most notably the generalized Lagrangian mean (GLM) theory of Andrews and McIntyre, have been primarily developed in Euclidean space and Cartesian coordinates. We reinterpret these theories using a geometric, coordinate-free formulation. This gives central roles to the flow map, its decomposition into mean and perturbation maps, and the momentum 1-form dual to the velocity vector. In this interpretation, the Lagrangian mean of any tensorial quantity is obtained by averaging its pull-back to the mean configuration. Crucially, the mean velocity is not a Lagrangian mean in this sense. It can be defined in a variety of ways, leading to alternative Lagrangian mean formulations that include GLM and Soward and Roberts's volume-preserving version. These formulations share key features that the geometric approach uncovers. We derive governing equations both for the mean flow and for wave activities constraining the dynamics of the perturbations. The presentation focuses on the Boussinesq model for inviscid rotating stratified flows and reviews the necessary tools of differential geometry.
When flowing through narrow channels or constrictions, many-body systems exhibit various flowing patterns, yet they can also get stuck. In many of these systems, the flowing elements remain as individuals (they do not aggregate or merge), sharing strong analogies among each other. This is the case for systems as contrasting as grains in a silo and pedestrians passing through tight spaces. Interestingly, when these entities flow within a fluid medium, numerous similarities persist. However, the fluid dynamics aspects of such clogging events, such as interstitial flow, liquid pressure, and hydrodynamic interactions, has only recently begun to be explored. In this review, we describe parallels with dry granular clogging and extensively analyze phenomena emerging when particles coexist with fluid in the system. We discuss the influence of diverse flow drive, particle propulsion mechanisms, and particle characteristics, and we conclude with examples from nature.
Publication date: 15 December 2024
Source: Computers & Fluids, Volume 285
Author(s): Abdelkader Hammouti, Fatna Oukaili, Damien Pham Van Bang
Publication date: 15 December 2024
Source: Computers & Fluids, Volume 285
Author(s): Andrei I. Tolstykh, Dmitrii A. Shirobokov
Publication date: 15 December 2024
Source: Computers & Fluids, Volume 285
Author(s): Swapnil Tupkari, Hrishikesh Gadgil, Vineeth Nair
Publication date: 15 December 2024
Source: Computers & Fluids, Volume 285
Author(s): Chunyuan Xu, Zhijun Shen, Qinghong Zeng
Publication date: 15 December 2024
Source: Computers & Fluids, Volume 285
Author(s): Jose Luis Cercos-Pita, Daniel Duque, Pablo Eleazar Merino-Alonso, Javier Calderon-Sanchez
Publication date: 15 December 2024
Source: Computers & Fluids, Volume 285
Author(s): Philippe Hergibo, Timothy N. Phillips, Zhihua Xie
Publication date: 15 December 2024
Source: Computers & Fluids, Volume 285
Author(s): Sanghun Kim, Eunji Jun
Publication date: 15 December 2024
Source: Computers & Fluids, Volume 285
Author(s): Chengzhi Zhang, Supei Zheng, Jianhu Feng, Shasha Liu
Publication date: 15 December 2024
Source: Computers & Fluids, Volume 285
Author(s): Xin Li, Zhiwen Deng, Rui Feng, Ziyang Liu, Renkun Han, Hongsheng Liu, Gang Chen
Publication date: Available online 17 November 2024
Source: Computers & Fluids
Author(s): Yiqiu Jin, Yiqing Shen, Guowei Yang, Guannan Zheng
In this study, we introduce a time-space dual adaptive uncoupled method for Supersonic Combustion. This method realizes adaptive coordination for the advection and reaction time steps in accordance with the non-uniform feature of stiffness in the space and time dimensions. It can advance by a small time step in strong stiffness while with a large one in weak stiffness through the “prediction-correction-recovery” strategy. It improved the computation efficiency and widened the error tolerance of the initial time step.
High computational complexity due to rapidly increasing numerical stiffness is a difficult problem for simulating a supersonic reactive flow by using the uncoupled method. On the basis of our previous work, this paper proposes a dual adaptive method to ensure high calculation efficiency and good robustness in simulating stiff cases. The principle of this method is to realize adaptive coordination for the advection and reaction time steps in accordance with the non-uniform feature of stiffness in the space and time dimensions. The proposed method can advance by a small time step in strong stiffness while with a large one in weak stiffness through the “prediction-correction-recovery” strategy. Some classical problems are chosen to verify the performance of the proposed method. The proposed method improved the computation efficiency by at least 30%$$ 30\% $$ comparing with the previous method [1] and widened the error tolerance of the initial time step.
When simulating fluid–structure interaction, the update of the fluid domain typically requires frequent mesh updates. Rather than updating the mesh, we propose to generate higher-order meshes in every time step, utilizing a block-structure and transfinite maps. This approach leads to high-quality meshes throughout the whole simulation, thereby preventing the mesh from becoming invalid and aborting the simulation.
In fluid–structure interaction (FSI), a fluid flow and a deforming solid are coupled along a time-dependent and moving interface. The change in the fluid domain requires an update of the related mesh. Herein, we propose to use a higher-order block-structured mesh generation approach, where a new mesh is generated (rather than updated) in every time step, taking the deformed FSI-interface into account. The mesh generation is based on a block-structure, consisting of coarse, linear quads, and transfinite maps to generate sub-meshes inside the block-structure, of any desired number and order of elements. The approach presented herein enables high-quality meshes throughout the simulation. The selection of the block-structure is crucial and leads to a very robust method. The performance of the mesh generation approach is confirmed through numerical results.
Practical applications often involve variable flow rates, posing significant challenges for physical informed neural networks (PINNs) to converge and find stable solutions. This paper proposes a new model named Simulation Net (Sim-net), which is designed to simulate and solve seepage equations without the need for retraining. Numerical experiments demonstrate that Sim-net efficiently solves seepage equations under unsteady boundaries, promising practical advancements in real-world applications.
The seepage equation plays a crucial role in fields such as groundwater management, petroleum engineering, and civil engineering. Currently, physical-informed neural networks (PINNs) have become an effective tool for solving seepage equations. However, practical applications often involve variable flow rates, which pose significant challenges for using neural networks to find solutions. Inspired by Deep Operator Network (DeepONet), this paper proposes a new model named Simulation Net (Sim-net) to deal with unsteady sources or sinks problems. Sim-net is designed to simulate and solve seepage equations without the need for retraining. This model integrates potential spatial and temporal features based on spatial pressure distribution and well bottom–hole pressure, respectively, which serve as additional signposts to guide neural networks in approximating seepage equations. Sim-net exhibits transfer learning capabilities, enabling it to handle variable flow rate problems without retraining for new flow conditions. Numerical experiments demonstrate that the trained model can directly solve seepage equations without the need for retraining, indicating its superior applicability compared to existing PINNs-based methods. Additionally, in comparison to the DeepONet, Sim-net achieves higher accuracy.
In order to reflect the actual cavitation erosion potential more accurately, we propose a new erosion indicator based on comprehensive cavitation erosion power density formulation. The new erosion indicator characterizes the cavitation erosion power density as complete as possible. In addition, the coupling effect of vapor volume fraction, velocity, and pressure gradient distribution is considered, so that the erosion indicator takes into account the cavitation-related factors and reflects the influence of the cavitation erosion state in a better way.
Cavitation erosion would degrade the performance of the fluid machinery. To improve the reliability and prolong the life span of fluid machinery, it is necessary to study the mechanism of cavitation erosion and predict the possibility of erosion. Since the erosion power to be measured and calculated is closer to the actual state of cavitation, a new cavitation erosion indicator epp model based on erosion power is proposed, which can reflect the size and region of the erosion generated by cavitation more precisely. Concerning the cases of the axisymmetric nozzle and venturi tube, the prediction of cavitation erosion based on the newly proposed indicator is illustrated. It is found that cavitation erosion mainly occurs near the maximum margin of the cavitation region. This research indicates the possible erosion state of fluid machinery in a cavitation environment and provides a new approach to estimate the state of cavitation erosion.
The study focuses on combining Alumina-Engine oil-based nanofluid flow subject to an electro-magnetohydrodynamic, porous medium, and a stretching surface with an impermeable structure under the convective conditions at the boundary. A simulation model is also proposed using a multilayer perceptron artificial neural network model.
The inspiration for this study originates from a recognized research gap within the broader collection of studies on nanofluids, with a specific focus on their interactions with different surfaces and boundary conditions (BCs). The primary purpose of this research is to use an artificial neural network to examine the combination of Alumina-Engine oil-based nanofluid flow subject to electro-magnetohydrodynamic effects, within a porous medium, and over a stretching surface with an impermeable structure under convective BCs. The flow model incorporates Thermophoresis and Brownian motion directly from Buongiorno's model. Accounting for the porous medium's effect, the model integrates the Forchheimer number (depicting local inertia) and the porosity factor developed in response to the presence of the porous medium. The conversion of governing equations into non-linear ordinary differential systems is achieved by implementing transformations. A highly non-linear ordinary differential system's final system is solved using a numerical scheme (Runge–Kutta fourth-order). Findings indicate that the porosity factor positively impacts the skin friction and the momentum boundary layer. The influence suggests an increment in the frictional force and a decline in the velocity profile. The volume fraction, Prandtl number, and magnetic number significantly impact the flow profiles. The skin friction data is tabulated with some physical justifications.
The geometric model can maintain a fixed contact angle throughout contact line motion, while the surface-energy one predicts a changeable contact angle, with a fluctuation of about 5°. In the oblique drop impact, contact angle hysteresis was captured even if a static contact angle was applied in the surface-energy formulation.
In phase field methods based on a second-order Allen-Cahn (AC) equation, contact angles are prescribed mostly via a geometric formulation. However, it is of great interest to utilize the surface-energy formulation, which is often employed in the Cahn-Hilliard (CH) phase field method, in the AC phase field method. This article thus put forward a surface-energy formulation of contact angles. The model was compared with the geometric one in a number of impact problems, including both normal and oblique impacts. The governing equations were discretized using a finite difference method on a half-staggered grid. The Navier–Stokes equation was tackled using an explicit projection method. The major findings are as follows. First, the geometric model can maintain a fixed contact angle throughout contact line motion, while the surface-energy one predicts a changeable contact angle, with a fluctuation of about 5°. In the oblique drop impact, contact angle hysteresis was captured even if a static contact angle was applied in the surface-energy formulation.
In this paper, the Intrusive Polynomial Chaos Method (IPCM) is used to compute the mean and variance of the model output. These values are then employed to determine the confidence intervals for the model output. This figure, compares the confidence intervals for (ux), ( uy), and (p) computed using the IPCM (in blue) and the Monte Carlo (MC) method (in hatched red) on the horizontal cross section (y = 0.2). For this test case, the IPCM results, obtained with only two simulations, are highly accurate and comparable to those of the Monte Carlo method, which requires 1300 simulations.
This work presents a comprehensive framework for the sensitivity analysis of the Navier–Stokes equations, with an emphasis on the stability estimate of the discretized first-order sensitivity of the Navier–Stokes equations. The first-order sensitivity of the Navier–Stokes equations is defined using the polynomial chaos method, and a finite element-volume numerical scheme for the Navier–Stokes equations is suggested. This numerical method is integrated into the open-source industrial code TrioCFD developed by the CEA. The finite element-volume discretization is extended to the first-order sensitivity Navier–Stokes equations, and the most significant and original point is the discretization of the nonlinear term. A stability estimate for continuous and discrete Navier–Stokes equations is established. Finally, numerical tests are presented to evaluate the polynomial chaos method and to compare it to the Monte Carlo and Taylor expansion methods.
The numerical study of flow around the multiple spheres is investigated by using a direct-forcing immersed boundary method. It conducted numerical analyses of flow past single sphere, tandem arrangements of two spheres, and a uniform array of nine spheres, under various flow conditions. An important characteristic of flow over the multiple spheres is devised by comparing with the drag, transverse and lift coefficients, as well as vortex shedding.
The numerical study of flow around a pair of spheres and a square array of spheres is investigated by using a direct-forcing immersed boundary method. Using high resolution three-dimensional computations, we analyzed the flow around several configurations: a sphere, a pair of spheres in a tandem arrangement with center-to-center streamwise ratio L/D ranging from 1 to 6, and a square array with 9 spheres in a uniform arrangement. In the latter case, we explore the ratio of array diameter (D G) to sphere diameter (D) at 4, 5, 6 and 7. The center-to-center streamwise and transverse pitch is the same, varied from L/D = 1.5, 2, 2.5 to 3, and they were arranged in a square periodic array to allow uniform distribution within the array. Based on the effective direct-forcing immersed boundary projection method, the fractional time marching methodology is applied for solving four field variables involving three velocities and one pressure component. The pressure Poisson equation is advanced in space by using the fast Fourier transform (FFT) and a tridiagonal matrix algorithm (TDMA), effectively solving for the diagonally dominant tridiagonal matrix equations. A direct-forcing immersed boundary method is involved to treat the interfacial terms by adding the appropriate sources as force function at the boundary, separating the phases. Geometries featuring the stationary solid obstacles in the flow are embedded in the Cartesian grid with special discretizations near the embedded boundary using a discrete Dirac delta function to ensure the accuracy of the solution in the cut cells. An important characteristic of flow over the multiple spheres is devised by comparing with the drag and lift coefficients, as well as vortex shedding.
We have developed an arbitrary Lagrangian–Eulerian (ALE) technique-based monolithic solver for analyzing fully coupled fluid-structure-electrostatic interactions in micro-electro-mechanical systems (MEMS). Numerical investigations show that fluid compressibility plays a significant role in the dynamics of MEMS actuators, in the cases of constrained flow geometries and high frequency electrostatic actuation. Comparative studies show that the nonlinear compressible Reynolds equation is not always a good approximation to the compressible Navier–Stokes equation, especially at low pressure and high viscosity values.
This work presents a monolithic finite element strategy for the accurate solution of strongly-coupled fluid-structure-electrostatics interaction problems involving a compressible fluid. The complete set of equations for a compressible fluid is employed within the framework of the arbitrary Lagrangian–Eulerian (ALE) fluid formulation on the reference configuration. The proposed numerical approach incorporates geometric nonlinearities of both the structural and fluid domains, and can thus be used for investigating dynamic pull-in phenomena and squeeze film damping in high aspect-ratio micro-electro-mechanical systems (MEMS) structures immersed in a compressible fluid. Through various illustrative examples, we demonstrate the significant influence of fluid compressibility on the dynamics of MEMS devices subjected to constrained geometry and/or high-frequency electrostatic actuation. Moreover, we compare the proposed formulation with the nonlinear compressible Reynolds equation and highlight that, particularly at low pressures and high fluid viscosity, the Reynolds equation fails to provide a reliable approximation to the complete set of equations utilized in our proposed formulation.
A rigid-perfectly plastic Bingham model is presented, and its implementation into an FV-VoF procedure is validated for cohesive and noncohesive materials featuring different angles of repose. A close agreement of the predicted soil surface with experimental data is obtained for noncohesive material, and the failure lines, calculated from the introduced Euler–Almansi strain measure, coincide well with the experimental data. To verify the applicability to realistic problems, the current procedure is successfully verified in large-scale dimensions against SPH simulations that use a more sophisticated material model.
Granular flow problems characterized by large deformations are widespread in various applications, including coastal and geotechnical engineering. The paper deals with the application of a rigid-perfectly plastic two-phase model extended by the Drucker–Prager yield criterion to simulate granular media with a finite volume flow solver (FV). The model refers to the combination of a Bingham fluid and an Eulerian strain measure to assess the failure region of granular dam slides. A monolithic volume-of-fluid (VoF) method is used to distinguish between the air and granular phases, both governed by the incompressible Navier–Stokes equations. The numerical framework enables modeling of large displacements and arbitrary shapes for large-scale applications. The displayed validation and verification focuses on the rigid-perfectly plastic material model for noncohesive and cohesive materials with varying angles of repose. Results indicate a good agreement of the predicted soil surface and strain results with experimental and numerical data.
Publication date: Available online 19 November 2024
Source: Journal of Computational Physics
Author(s): Maxime Jonval, Ibtihel Ben Gharbia, Clément Cancès, Thibault Faney, Quang-Huy Tran
Publication date: Available online 17 November 2024
Source: Journal of Computational Physics
Author(s): Xiaojian Yang, Yajun Zhu, Chang Liu, Kun Xu
Publication date: Available online 19 November 2024
Source: Journal of Computational Physics
Author(s): Luke Triplett, Jianfeng Lu
Publication date: Available online 19 November 2024
Source: Journal of Computational Physics
Author(s): Shinya Maeyama, Tomo-Hiko Watanabe, Motoki Nakata, Masanori Nunami, Yuuichi Asahi, Akihiro Ishizawa
Publication date: Available online 20 November 2024
Source: Journal of Computational Physics
Author(s): Jianguo Huang, Yue Qiu
Publication date: Available online 19 November 2024
Source: Journal of Computational Physics
Author(s): Xuelian Bao, Chun Liu, Yiwei Wang
Publication date: Available online 17 November 2024
Source: Journal of Computational Physics
Author(s): Mahmoud Shaqfa, Gary P.T. Choi, Guillaume Anciaux, Katrin Beyer
Publication date: Available online 17 November 2024
Source: Journal of Computational Physics
Author(s): Benoît Cossart, Jean-Philippe Braeunig, Raphaël Loubère
Publication date: Available online 14 November 2024
Source: Journal of Computational Physics
Author(s): Deniz A. Bezgin, Aaron B. Buhendwa, Steffen J. Schmidt, Nikolaus A. Adams
Publication date: Available online 13 November 2024
Source: Journal of Computational Physics
Author(s): Jonathan Palafoutas, David A. Velasco Romero, Romain Teyssier
The use of heaving and pitching fins for underwater propulsion of engineering devices poses an attractive outlook given the efficiency and adaptability of natural fish. However, significant knowledge gaps need to be bridged before biologically inspired propulsion is able to operate at competitive performances in a practical setting. One of these relates to the design of structures that can leverage passive deformation and active morphing in order to achieve optimal hydrodynamic performance. To provide insights into the performance improvements associated with passive and active fin deformations, we provide here a systematic numerical investigation in the thrust, power, and efficiency of 2D heaving and pitching fins with imposed curvature variations. The results show that for a given chordline kinematics, the use of curvature can improve thrust by 70% or efficiency by 35% over a rigid fin. Maximum thrust is achieved when the camber variations are synchronized with the maximum heave velocity, increasing the overall magnitude of the force vector while increasing efficiency as well. Maximum efficiency is achieved when camber is applied during the first half of the stroke, tilting the force vector to create thrust earlier in the cycle than a comparable rigid fin. Overall, our results demonstrate that curving fins are consistently able to significantly outperform rigid fins with the same chord line kinematics on both thrust and hydrodynamic efficiency.
The aerodynamic and aeroacoustic performance of a low-aspect-ratio ( \(\hbox {AR}=0.2\) ) pitching foil during dynamic stall are investigated numerically with focus on the effects of trailing edge serrations. A hybrid method coupling an immersed boundary method for incompressible flows with the Ffowcs Williams–Hawkings acoustic analogy is employed. Large eddy simulation and turbulent boundary layer equation wall model are also employed to capture the turbulent effects. A modified NACA0012 foil with a rectangular trailing edge flap attached to the trailing edge (baseline case) undergoing pitching motion is considered. Trailing edge serrations are applied to the trailing edge flap and their effects on the aerodynamic and aeroacoustic performance of the oscillating airfoil are considered by varying the wave amplitude ( \(2h^*= 0.05, 0.1\) , and 0.2) at a Reynolds number of 100,000 and a Mach number of 0.05. It is found that the reduction of the sound pressure level at the dimensionless frequency band \(St_{b}\in [1.25,4]\) can be over 4 dB with the presence of the trailing edge serrations ( \(2h^*=0.1\) ), while the aerodynamic performance and its fluctuations are not significantly altered except a reduction around 10% in the negative moment coefficient and it fluctuations. This is due to the reduction of the average spanwise coherence function and the average surface pressure with respect to that of the baseline case, suggesting the reduction of the spanwise coherence and the noise source may result in the noise reduction. Analysis of the topology of the near wake coherent structure for \(2h^*=0.1\) reveals that the alignment of the streamwise-oriented vortex with the serration edge may reduce the surface pressure fluctuation.
Cluster and void formations are key processes in the dynamics of particle-laden turbulence. In this work, we assess the performance of various neural network models for synthesizing preferential concentration fields of particles in turbulence. A database of direct numerical simulations of homogeneous isotropic two-dimensional turbulence with one-way coupled inertial point particles, is used to train the models using vorticity as the input to predict the particle number density fields. We compare encoder–decoder, U-Net, generative adversarial network (GAN), and diffusion model approaches, and assess the statistical properties of the generated particle number density fields. We find that the GANs are superior in predicting clusters and voids, and therefore result in the best performance. Additionally, we explore a concept of “supersampling”, where neural networks can be used to predict full particle data using only the information of few particles, which yields promising perspectives for reducing the computational cost of expensive DNS computations by avoiding the tracking of millions of particles. We also explore the inverse problem of synthesizing the absolute values of the vorticity fields using the particle number density distribution as the input at different Stokes numbers. Hence, our study also indicates the potential use of neural networks to predict turbulent flow statistics using experimental measurements of inertial particles.
In this paper we present a numerical scheme based on spectral collocation methods to investigate the flow of a piezo-viscous fluid, i.e., a fluid in which the rheological parameters depend on the pressure. In particular, we consider an incompressible Navier–Stokes fluid with pressure dependent viscosity flowing in: (i) a two-dimensional non-symmetric planar channel; (ii) a three-dimensional axisymmetric non-straight conduit. For both cases we impose the Navier slip boundary conditions that can be reduced to the classical no-slip condition for a proper choice of the slip parameter. We assume that the dependence of the viscosity on the pressure is of exponential type (Barus law), even though the model can be replaced by any other viscosity function. We write the mathematical problem (stress based formulation) and discretize the governing equations through a spectral collocation scheme. The advantage of this numerical procedure, which to the authors’ knowledge has never been used before for this class of fluids, lies in in the ease of implementation and in the accuracy of the solution. To validate our model we compare the numerical solution with the one that can be obtained in the case of small aspect ratio, i.e., the leading order lubrication solution. We perform some numerical simulation to investigate the effects of the pressure-dependent viscosity on the flow. We consider different wall functions to gain insight also on the role played by the channel/duct geometry. In both cases (i), (ii) we find that the increase of the coefficient appearing in the viscosity function results in a global reduction of the flow, as physically expected.
Different transition to turbulence routes for the flow around blunt bodies are possible. Non-modal amplification of perturbations via the lift-up effect has recently been explored to explain transition near the stagnation point in axisymmetric bodies. However, only perturbations already present in the boundary layer can be amplified, and the mechanisms by which free-stream perturbations enter the boundary layer have not yet been fully explored. In this study, we present an investigation of how disturbances enter the boundary layer via the stagnation point. This linear mechanism is expected to dominate over non-linear mechanisms previously identified on the formation of boundary layer perturbations at low turbulence intensity levels. A parametric investigation is presented, revealing trends with Reynolds and Mach numbers.
We propose a technique for performing spectral (in time) analysis of spatially-resolved flowfield data, without needing any temporal resolution or information. This is achieved by combining projection-based reduced-order modeling with spectral proper orthogonal decomposition. In this method, space-only proper orthogonal decomposition is first performed on velocity data to identify a subspace onto which the known equations of motion are projected, following standard Galerkin projection techniques. The resulting reduced-order model is then utilized to generate time-resolved trajectories of data. Spectral proper orthogonal decomposition (SPOD) is then applied to this model-generated data to obtain a prediction of the spectral content of the system, while predicted SPOD modes can be obtained by lifting back to the original velocity field domain. This method is first demonstrated on a forced, randomly generated linear system, before being applied to study and reconstruct the spectral content of two-dimensional flow over two collinear flat plates perpendicular to an oncoming flow. At the range of Reynolds numbers considered, this configuration features an unsteady wake characterized by the formation and interaction of vortical structures in the wake. Depending on the Reynolds number, the wake can be periodic or feature broadband behavior, making it an insightful test case to assess the performance of the proposed method. In particular, we show that this method can accurately recover the spectral content of periodic, quasi-periodic, and broadband flows without utilizing any temporal information in the original data. To emphasize that temporal resolution is not required, we show that the predictive accuracy of the proposed method is robust to using temporally-subsampled data.
A low-order physics-based model to simulate the unsteady flow response to airfoils undergoing large-amplitude variations of the camber is presented in this paper. Potential-flow theory adapted for unsteady airfoils and numerical methods using discrete-vortex elements are combined to obtain rapid predictions of flow behavior and force evolution. To elude the inherent restriction of thin-airfoil theory to small flow disturbances, a time-varying chord line is proposed in this work over which to satisfy the appropriate boundary condition, enabling large deformations of the camber line to be modeled. Computational fluid dynamics simulations are performed to assess the accuracy of the low-order model for a wide range of dynamic trailing-edge flap deflections. By allowing the chord line to rotate with trailing-edge deflections, aerodynamic loads predictions are greatly enhanced as compared to the classical approach where the chord line is fixed. This is especially evident for large-amplitude deformations.
The generation mechanism of wall heat flux is one of the fundamental problems in supersonic/hypersonic turbulent boundary layers. A novel heat decomposition formula under the curvilinear coordinate was proposed in this paper. The new formula has wider application scope and can be applied in the configurations with grid deformed. The new formula analyzes the wall heat flux of an interaction between a shock wave and a turbulent boundary layer over a compression corner. The results indicated good performance of the formula in the complex interaction region. The contributions of different energy transport processes were obtained. While the processes by the mean profiles such as molecular stresses and heat conduction, can be ignored, the contributions by the turbulent fluctuations, such as Reynolds stresses and turbulent transfer of heat flux, were greatly increased. Additionally, the pressure work is another factor that affects the wall heat flux. The pressure work in the wall-normal direction is concentrated close to the reattachment point, while the pressure work in the streamwise direction acts primarily in the shear layer and the reattachment point.
An inviscid vortex shedding model is numerically extended to simulate falling flat plates. The body and vortices separated from the edge of the body are described by vortex sheets. The vortex shedding model has computational limitations when the angle of incidence is small and the free vortex sheet approaches the body closely. These problems are overcome by using numerical procedures such as a method for a near-singular integral and the suppression of vortex shedding at the plate edge. The model is applied to a falling plate of flow regimes of various Froude numbers. For \(\text {Fr}=0.5\) , the plate develops large-scale side-to-side oscillations. In the case of \(\text {Fr}=1\) , the plate motion is a combination of side-to-side oscillations and tumbling and is identified as a chaotic type. For \(\text {Fr}=1.5\) , the plate develops to autorotating motion. Comparisons with previous experimental results show good agreement for the falling pattern. The dependence of change in the vortex structure on the Froude number and its relation with the plate motion is also examined.
This paper presents an overlay-based one-way coupled Eulerian–Lagrangian computational approach designed to investigate the dynamics of particulate phases in extreme high-speed, high-altitude flight conditions characterized by very low particulate mass loading. Utilizing the Direct Simulation Monte Carlo method to generate accurate gas flow fields, this study explores two canonical hypersonic flow systems. First we focus on the hypersonic flow over a sphere-cone, revealing the formation of dust-free zones for small particulate diameters and describing the particulate interaction with gas shocks. As particulate diameter and flight speed increase, the characteristics of the particulate phase evolve, leading to the emergence of distinctive features such as high particulate concentration bands or regions void of particulates. Subsequently, the investigation considers flow over a double-cone, emphasizing the behavior of particulate phases in separated vortex-dominated systems where particulate-inertia-driven interactions with vortices result in unique particulate-free zones in the vicinity of the primary and secondary vortices. Additionally, the paper addresses the importance of using realistic fractal-like particulate shapes and demonstrates that the shape effect tends to decelerate the fractal aggregates and trap them along the boundaries of the primary vortex. This research contributes to a deeper understanding of particulate phase dynamics in extreme flight conditions, offering insights relevant to aerospace and aerodynamic applications.
