Complex Fluid Flow Research Articles

Experimental study of falling film absorption with potassium formate - Water as working pair

As an essential operation in refrigeration and chemical engineering, gas or vapor absorption with falling liquid film is usually coupled with complex fluid flow patterns and heat & mass transfer processes. Experimental studies are necessary for practical application, especially when non-traditional working pairs are adopted. In this paper, KCOOH/Water was used as the working pair to conduct the experimental study of the falling film absorption process. The results showed that waviness increased the mass transfer rate. The waviness intensity (δ/δ‾) and the average mass transfer rate increased first and then decreased with flow rate at Reynolds number ranging from 15 to 95, up to 0.92 and 3.5 g m−2s−1. The heat transfer flux increased with the flow rate in the test range, and absorption rates were sensitive to the cooling water temperature.

Machine-Learning Methods for Complex Flows

We are delighted to introduce this Special Issue focused on novel machine-learning (ML) methods aimed at predicting, modeling, and controlling a variety of complex fluid flow scenarios [...]

Complex Fluid Flow in Microchannels and Heat Pipes with Enhanced Surfaces for Advanced Heat Conversion and Recovery Systems

This paper addresses a multiscale approach for heat recovery systems, used in two distinct applications. In both applications, a microscale approach is used (microchannel heat sinks and heat pipes) for macroscale applications (cooling of a photovoltaic—PV cell), and the thermal energy of exhaust gases of an internal combustion engine is used for thermoelectric generators with variable conductance heat pipes. Several experimental techniques are combined such as visualization, thermography with high spatial and temporal resolution, and the characterization of the flow hydrodynamics, such as the friction losses. The analysis performed evidences the relevance of looking at the physics of the observed phenomena to optimize the heat sink geometry. For instance, the results based on the dissipated heat flux and the convective heat transfer coefficients obtained in the tests of the microchannel-based heat sinks for cooling applications in PV cells show an improvement in the dissipated power at the expense of controlled pumping power, for the best performing geometries. Simple geometries based on these results were then used as inputs in a genetic algorithm to produce the optimized geometries. In both applications, the analysis performed evidences the potential of using two-phase flows. However, instabilities at the microscale must be accurately addressed to take advantage of liquid phase change. In this context, the use of enhanced interfaces may significantly contribute to the resolution of the instability issues as they are able to control bubble dynamics. Such an approach is also addressed here.

A simple and efficient parallel immersed boundary-lattice Boltzmann method for fully resolved simulations of incompressible settling suspensions

This study presents an efficient and parallel fully resolved direct numerical simulation (FR-DNS) of settling suspensions on multiple CPU cores based on the boundary-thickening direct forcing immersed boundary method (BTDF-IBM) and incompressible lattice Boltzmann method (LBM). The simple BTDF-IBM is used to meet the no-slip and no-penetration conditions on particle boundaries, and the incompressible LBM is used to achieve the capability of large pressure fluctuations in suspensions. In addition, a theoretical force model is used to compensate for the unresolved lubrication force between the two approaching particles. A swap strategy for the streaming step is used to reduce the memory storage of the LBM particle density functions to half. A distribution and communication strategy is proposed to handle the IBM computing and complete the immersed boundary (IB) force of the particles residing in the interface region between adjacent subdomains. The developed BTDF-IBM-LBM solver “PFlows” can simulate large particle-laden flows with more than O(106) particles and with a particle volume fraction of up to 0.4. An almost linear parallel speedup and efficiency of higher than 0.8 are obtained by testing three-dimensional (3D) cases (up to 1.0 billion fluid grids and 0.45 million particles) and two-dimensional (2D) cases (up to 1.2 billion fluid grids and 2.39 million particles). Finally, the framework is applied to three large-scale real simulations involving 50,000 particles settling in 2D and 3D bounded and unbounded domains for qualitative and quantitative validations. The particle settling behaviors and disturbed complex fluid flows in the vertical channel are demonstrated. The Boycott effect in the inclined channel is uncovered by a new mechanism that combines particle sliding at the lower sidewall with fluid convection in the upper region. The hindered settling of particles in the 3D periodic domain, which is affected by the strong particle-fluid hydrodynamic interactions and particle-particle many-body interactions at a high solid volume fraction, are analyzed. The complex behaviors and statistical characteristics of the suspensions are preliminarily revealed and analyzed, which demonstrates the prospective capability of the present framework for FR-DNS of large-scale 2D and 3D suspension flows that are relevant to many industrial applications by IB-LBM.

Complex fluid flow in annular space under the effects of mixed convection and rotating wall of the outer enclosure

AbstractThis study aims to investigate the roles of pertinent parameters on the mixed convection of complex liquids in annular devices. The investigated area consists of two circular cylinders with fixed and heat walls. Both cylinders are enclosed within a circular room with a cold wall and rotate regularly. The zone between the inner obstacles and the outer space contains complex power‐law fluids. This investigation is numerically achieved by using the package ANSYS‐CFX, which is based on the finite‐volume method. The parameters studied in this study are the arrangement and size of inner tubes (d/D), the rotational speed of outer space, the rheological nature of fluids (n), and the relative concentration of thermal buoyancy force. These pertinent parameters were quantitatively expressed for the following values:d/D(= 0.1, 0.25, and 0.45); Reynolds number (Re = 1 to 20); flow behavior index (n = 0.6, 1 and 1.6); Richardson number (Ri = 0 to 100), respectively. It was found that increasing the thermal buoyancy value and the rotational speed of the outer container increases the rate of heat transfer of the cylinders in the vertical and horizontal arrangement. For example, for shear‐thinning fluid (n = 0.6), raising the value ofRifrom 0 to 100 increasesNuby 59.67% ford/D = 0.1. Also, the arrangement of the two cylinders differently affects the dynamic behavior of the fluid within the studied space.

A mechanical model of partially liquefied vitreous dynamics induced by saccadic eye movement within a realistic shape of vitreous cavity

The vitreous undergoes physical and biochemical changes with age. The most important of such degenerative changes is vitreous liquefaction or synchysis, in which pockets of liquid known as lacunae form in the vitreous gel. The movement mechanism and characteristics of vitreous liquefaction are quite complex. In this study, the flow dynamics of partial vitreous liquefaction (PVL) as two-phase viscoelastic-Newtonian fluid flow are investigated in the human eye. A reliable three-dimensional (3D) numerical procedure is developed for capturing the interface effects and dynamic characteristics of these two-phase complex fluid flows. In the present work, two different configurations of the PVL including liquefied pocket in the central and the posterior portions of the vitreous cavity are considered. The effects of lens indentation on the flow field and interface deformation of PVL inside the vitreous cavity are investigated. The results show that the curvature of the vitreous cavity due to the lens capsule increases shear and normal stresses in comparison with those for the PVL in a sphere as a simplified model. It is observed that the presence of lens indentation and the location of liquefied region are two factors that can produce conditions of asymmetry inside the vitreous body. In a realistic model of vitreous cavity, although the velocity magnitude inside the liquefied vitreous region increases when the liquefied pocket is in the posterior portion of the vitreous cavity, the stress values and the asymmetric condition of flow field become more significant for the liquefied pocket located close to the posterior lens curvature.

Influence of Complex Fluid Flow on Temperature Distribution in the Rotor Region of Large Hydrogenerator Under the Rotor Rotation

Ventilation cooling design is one of the key technologies during the design of large hydrogenerator. With the increase of hydrogenerator capacity, the overheating problem of rotor region become more and more serious. In this paper, a 250 MW hydrogenerator is analyzed. The transient electromagnetic field of the hydrogenerator is calculated. The losses (heat sources) of rotor components in the rotor region of the hydrogenerator are determined. Three-dimensional fluid and thermal coupled mathematic model of the hydrogenerator rotor region is established. The rotor rotation of the hydrogenerator is considered. The distribution of complex fluid velocity in the rotor region is calculated using the finite volume method. The influence of fluid velocity in the different directions on the temperature of the rotor excitation winding is studied under the different flow rates in the rotor region. The surface heat-transfer coefficient distribution of the rotor components is determined. The temperature distribution of the rotor excitation winding, rotor pole body, rotor press plate, rotor damping bar, and rotor end ring is obtained. The calculated temperature results match well with test values. These provide an important reference for the rotor structural design and optimization of larger hydrogenerator.

DeepPTV: Particle Tracking Velocimetry for Complex Flow Motion via Deep Neural Networks

Particle tracking velocimetry (PTV) is a powerful technique for global and nonintrusive flow field measurement, which shows a great potential to improve the spatial resolution compared to other flow visualization technologies (e.g., correlation-based particle image velocimetry). However, performing PTV under flow conditions with high flow speed and high particle density is still a challenge. In addition, more and more research sacrifices the computational efficiency for high accuracy using complex iterative algorithms. To address these problems, we propose a deep particle tracking network, called deep neural network for PTV (DeepPTV), for learning the complex fluid flow motion from two consecutive particle sets efficiently and accurately. First, the local spatial geometry information from neighboring particles is aggregated for each particle along with robust features (i.e., the relative distance to the neighbors), which help to preserve the properties of fluids. Second, to cope with the problem caused by nonuniform seeding density of particles, the multiscale features are combined together in each hierarchy of the neural network. Furthermore, motivated by the convection flow phenomena, the proposed DeepPTV model adopts a novel network architecture named convection architecture to estimate the flow field in a hierarchical framework, namely, from large-scale motion to small-scale motion. Experimental evaluations on both artificial and laboratory particle images demonstrate that the proposed framework can provide satisfactory accuracy that rivals the state-of-the-art methods. Moreover, the presented high efficiency makes it a promising algorithm for real-time estimation and real-time flow control problems.

The Effect of Groove Shape on Molten Metal Flow Behaviour in Gas Metal Arc Welding.

One of the challenges for development, qualification and optimisation of arc welding processes lies in characterising the complex melt-pool behaviour which exhibits highly non-linear responses to variations of process parameters. The present work presents a computational model to describe the melt-pool behaviour in root-pass gas metal arc welding (GMAW). Three-dimensional numerical simulations have been performed using an enhanced physics-based computational model to unravel the effect of groove shape on complex unsteady heat and fluid flow in GMAW. The influence of surface deformations on the magnitude and distribution of the heat input and the forces applied to the molten material were taken into account. Utilising this model, the complex thermal and fluid flow fields in melt pools were visualised and described for different groove shapes. Additionally, experiments were performed to validate the numerical predictions and the robustness of the present computational model is demonstrated. The model can be used to explore the physical effects of governing fluid flow and melt-pool stability during gas metal arc root welding.

Continuum mechanics modeling of complex fluid systems following Oldroyd's seminal 1950 work

We present a review of some key developments in the continuum mechanics – based macroscopic modeling of complex fluid flows, following the pioneering work of Oldroyd in the 1950s. We start by reviewing the major developments achieved by Oldroyd, namely how his work established rules for consistency in developing continuum stress constitutive models extending the material into objective time derivatives for tensor quantities, with first application the stress tensor in viscoelastic constitutive relationships. We then show how the impact of his work to viscoelastic fluid flows has been amplified from the kinetic theory work of Bird and others who established a firm macromolecular structural connection. The use of objective time derivatives was then extended to include second order conformation tensors and through them the connection was made to internal deformation energy by Marrucci. We then further demonstrate the impact of this work by analyzing the models through the microstructural descriptions offered within the non-equilibrium thermodynamics formalism. We then conclude with a brief mentioning of direct applications of the original Oldroyd-B model (through stability analyses, etc.) towards bettering our understanding of the rheological behaviour of complex fluid systems.

Machine learning for combustion

Combustion science is an interdisciplinary study that involves nonlinear physical and chemical phenomena in time and length scales, including complex chemical reactions and fluid flows. Combustion widely supplies energy for powering vehicles, heating houses, generating electricity, cooking food, etc. The key to study combustion is to improve the combustion efficiency with minimum emission of pollutants. Machine learning facilitates data-driven techniques for handling large amounts of combustion data, either obtained through experiments or simulations under multiple spatiotemporal scales, thereby finding the hidden patterns underlying these data and promoting combustion research. This work presents an overview of studies on the applications of machine learning in combustion science fields over the past several decades. We introduce the fundamentals of machine learning and its usage in aiding chemical reactions, combustion modeling, combustion measurement, engine performance prediction and optimization, and fuel design. The opportunities and limitations of using machine learning in combustion studies are also discussed. This paper aims to provide readers with a portrait of what and how machine learning can be used in combustion research and to inspire researchers in their ongoing studies. Machine learning techniques are rapidly advancing in this era of big data, and there is high potential for exploring the combination between machine learning and combustion research and achieving remarkable results.

Towards High Throughput Structuring of Liquid Foams in Microchannels: Effect of Geometry, Flowrate and Formulation.

This work is part of a study aiming to design a high-throughput foaming microsystem. The main focused field of application is the food industry. With the objective of improving the design of the microdevice, the effects of the geometry and the nature of the liquid base are presently investigated through visualizations of the flow typology of bubbles trains, aiming to expand the knowledge on key parameters that lead to an improved gas breakup. The tested set of conditions is not encountered in traditional microfluidics systems: i.e., throughputs up to 19 L·h−1 for the liquid phase, process velocities around 20 m·s−1 and flow of complex fluids. The behavior of solutions based on xanthan gum (XG) and whey proteins (WPI) is compared to that of solutions containing one of these ingredients or other ones (caseinates, glycerol). The structural and end-used properties of the final foams, namely the bubble diameter and rheological behavior, are evaluated. The incorporation of XG induces bubble shape stabilization even at the highest shear rates (~105 s−1) encountered in the mixing channel. “Controlled” interfacial breakup by tip-streaming or binary breakup are only observed with the WPI/XG biopolymers. This study indubitably highlights the essential role of the process/formulation interaction in the development of structural and functional properties of food foams when using microfluidics at high throughput.

Numerical Simulations of a Dispersive Model Approximating Free-Surface Euler Equations

In some configurations, dispersion effects must be taken into account to improve the simulation of complex fluid flows. A family of free-surface dispersive models has been derived in Fernández-Nieto et al. (Commun Math Sci 16(05):1169–1202, 2018). The hierarchy of models is based on a Galerkin approach and parameterised by the number of discrete layers along the vertical axis. In this paper we propose some numerical schemes designed for these models in a 1D open channel. The cornerstone of this family of models is the Serre – Green-Naghdi model which has been extensively studied in the literature from both theoretical and numerical points of view. More precisely, the goal is to propose a numerical method for the LDNH_2 model that is based on a projection method extended from the one-layer case to any number of layers. To do so, the one-layer case is addressed by means of a projection-correction method applied to a non-standard differential operator. A special attention is paid to boundary conditions. This case is extended to several layers thanks to an original relabelling of the unknowns. In the numerical tests we show the convergence of the method and its accuracy compared to the LDNH_0 model.

Microscale heterogeneous pore occupancy with variable background resistance

Fluid flow through porous media often involves the spontaneous displacement of one immiscible fluid by another. On the level of adjacent channels, a pore doublet model can estimate the relative flow rates in the two channels and the final fluid occupancy of the pair. Pore doublet models nominally capture the dominant roles of capillarity and viscosity, by describing the flow using hydraulic circuit theory. However, this approach neglects the more complex fluid flow in the region where the immiscible fluids meet, and therefore the applicability of this model for low aspect-ratio pores commonly seen in natural media is questionable. We show that for large channel aspect ratios, the numerical results replicate the traditional pore doublet models; however, as the aspect ratio approaches unity, the accuracy of these models break down. We quantify the effect of complex flow on the final fluid occupancy, which we link to the excess energy dissipation rate from the flow near the immiscible interface. Our results indicate that a minimal 1D pore doublet model may be sufficient to model global dynamics, including the fraction of residual oil that remains trapped in a reservoir, where the pore diameter and length are comparable.

Superposition‐based concurrent multiscale approaches for poromechanics

AbstractSuperposition‐based concurrent multiscale approaches for poromechanical problems aimed at resolving localized fluid flow and deformation of a solid skeleton including its possible fracture are developed. The main departure of the proposed formulation is that the primary unknowns in the coupling zone, the solid displacement u and pore pressure p, are discretized by possibly different numerical models. Two discretization schemes are studied: (i) superposition of two or more finite element (FE) discretizations of the Biot's u‐p model of a porous medium, and (ii) superposition of the peridynamics (PD) discretization of the fractured solid phase on the FE discretization of the Biot's u‐p model of a porous medium. In the latter case, the total stress of the fluid–solid mixture in the coupling domain is derived from the effective stress obtained from the combined PD and finite element method solutions while the pore pressure is obtained from the FE solution. The accuracy of the superposition‐based concurrent multiscale method is studied on several benchmark problems including the classical Terzaghi's one‐dimensional consolidation problem, the two‐dimensional strip footing problem, and the pressure‐ and fluid‐driven fracture propagation problem in saturated porous media. The main hydraulic fracture characteristics, including complex crack paths and fluid flow patterns, have been found to be reasonably well reproduced by the proposed method.

Fast estimation of internal flowfields in scramjet intakes via reduced-order modeling and machine learning

The interface between fluid mechanics and machine learning has ushered in a new avenue of scientific inquiry for complex fluid flow problems. This paper presents the development of a reduced-order predictive framework for the fast and accurate estimation of internal flowfields in two classes of scramjet intakes for hypersonic airbreathing propulsion. Proper orthogonal decomposition is employed as a reduced-order model while the moving least squares-based regression model and the multilayer perceptron-based neural network technique are employed. The samples required for the training process are generated using a sampling strategy, such as Latin hypercube sampling, or obtained as an outcome of multi-objective optimization. The study explores the flowfield estimation capability of this framework for the two test cases, each representing a unique type of scramjet intake. The importance of tuning the user-defined parameters as well as the use of multiple reduced-order bases instead of a global basis are highlighted. It is also demonstrated that the bias involved in the generation of input samples in an optimization problem can potentially be utilized to build a reduced-order predictive framework while using only a moderate number of training samples. This offers the potential to significantly reduce the computational time involved in expensive optimization problems, especially those relying on a population-based approach to identify global optimal solutions.

A non‐Gaussian Bayesian filter for sequential data assimilation with non‐intrusive polynomial chaos expansion

AbstractNon‐Gaussian data assimilation is vital for several applications with nonlinear dynamical systems, including geosciences, socio‐economics, infectious disease modeling, and autonomous navigation. Widespread adoption of non‐Gaussian data assimilation requires easy‐to‐implement schemes. We develop, implement, and apply an efficient nonlinear non‐Gaussian data assimilation scheme using non‐intrusive stochastic collocation‐based polynomial chaos expansion (PCE) and Gaussian mixture model (GMM) priors fit to the state's uncertainty. First, we represent the uncertainty in a dynamical system using PCE and propagate it using the stochastic collocation method until an assimilation time. Then, we convert the polynomial basis prior to its equivalent Karhunen–Loeve (KL) form, fit a GMM in the subspace and perform a Bayesian filtering step. Thereafter, the posterior polynomial basis is recovered from the posterior GMM in the KL form, and uncertainty propagation is continued using the stochastic collocation method. The derivation and new equations required for the above conversions are presented. We apply the new scheme to an illustrative population growth dynamics application and a complex fluid flow problem for demonstrating its capabilities. In both cases, our filter accurately captures the non‐Gaussian statistics compared to the polynomial chaos‐ensemble Kalman filter and the polynomial chaos‐error subspace statistical estimation filter.

A Hierarchical Grid Solver for Simulation of Flows of Complex Fluids.

Tree-based grids bring the advantage of using fast Cartesian discretizations, such as finite differences, and the flexibility and accuracy of local mesh refinement. The main challenge is how to adapt the discretization stencil near the interfaces between grid elements of different sizes, which is usually solved by local high-order geometrical interpolations. Most methods usually avoid this by limiting the mesh configuration (usually to graded quadtree/octree grids), reducing the number of cases to be treated locally. In this work, we employ a moving least squares meshless interpolation technique, allowing for more complex mesh configurations, still keeping the overall order of accuracy. This technique was implemented in the HiG-Flow code to simulate Newtonian, generalized Newtonian and viscoelastic fluids flows. Numerical tests and application to viscoelastic fluid flow simulations were performed to illustrate the flexibility and robustness of this new approach.

Application of upscaling methods for fluid flow and mass transport in multi-scale heterogeneous media: A critical review

Physical and biogeochemical heterogeneity dramatically impacts fluid flow and reactive solute transport behaviors in geological formations across scales. From micro pores to regional reservoirs, upscaling has been proven to be a valid approach to estimate large-scale parameters by using data measured at small scales. Upscaling has considerable practical importance in oil and gas production, energy storage, carbon geologic sequestration, contamination remediation, and nuclear waste disposal. This review covers, in a comprehensive manner, the upscaling approaches available in the literature and their applications on various processes, such as advection, dispersion, matrix diffusion, sorption, and chemical reactions. We enclose newly developed approaches and distinguish two main categories of upscaling methodologies, deterministic and stochastic. Volume averaging, one of the deterministic methods, has the advantage of upscaling different kinds of parameters and wide applications by requiring only a few assumptions with improved formulations. Stochastic analytical methods have been extensively developed but have limited impacts in practice due to their requirement for global statistical assumptions. With rapid improvements in computing power, numerical solutions have become more popular for upscaling. In order to tackle complex fluid flow and transport problems, the working principles and limitations of these methods are emphasized. Still, a large gap exists between the approach algorithms and real-world applications. To bridge the gap, an integrated upscaling framework is needed to incorporate in the current upscaling algorithms, uncertainty quantification techniques, data sciences, and artificial intelligence to acquire laboratory and field-scale measurements and validate the upscaled models and parameters with multi-scale observations in future geo-energy research.

Application of non-pressure-based coupled procedures for the solution of heat and mass transfer for the incompressible fluid flow phenomenon

MotivationThe inconvenient treatment of the current velocity-pressure coupling strategies is still a debating issue. Whether the procedures are formed on coupled or segregated solution strategy, the substituted equation for pressure, which is applied instead of the original continuity equation, is known to cause convergence problems for complex fluid flow situations. Challenge and approachThe present study aims to evaluate two fully implicit, non-pressure-based coupled algorithms known as FICS and SICS (Fully/Simplest Implicit Coupled Procedures) that are able to solve the flow equations without utilizing any additional formulations (Poisson-type or else) for pressure. To do so, a numerical code using C++ was developed, and the noted coupled procedures were implemented alongside the well-known SIMPLEC (Semi-Implicit-Pressure-Linked-Equation-Consistent) algorithm, which was utilized as a benchmark procedure. The evaluations of the noted algorithms seek to compare the stability, solution speed, and compatibility to various physical phenomena such as turbulence and heat transfer that are the main subjects used to compare the fluid mechanic procedures. Significant resultsObtained results indicate that coupled procedures are irrefutably stable whether only the laminar equations are solved or other highly influential scalar equations have participated. As an instance, it was observed that FICS-2 achieved convergence at least two times faster than SIMPLEC while applying the least amount of relaxation to amend for both non-linearity and the pressure-velocity coupling. Impact of the study and conclusionAs a result, it is concluded that the primitive form of continuity equation is a more efficient alternative than the standard Poisson-based formulation and could be considered for future developments in commercial CFD purposes.