Application Of Fluid Dynamics Research Articles

Prospects of federated machine learning in fluid dynamics

Physics-based models have been mainstream in fluid dynamics for developing predictive models. In recent years, machine learning has offered a renaissance to the fluid community due to the rapid developments in data science, processing units, neural network based technologies, and sensor adaptations. So far in many applications in fluid dynamics, machine learning approaches have been mostly focused on a standard process that requires centralizing the training data on a designated machine or in a data center. In this article, we present a federated machine learning approach that enables localized clients to collaboratively learn an aggregated and shared predictive model while keeping all the training data on each edge device. We demonstrate the feasibility and prospects of such a decentralized learning approach with an effort to forge a deep learning surrogate model for reconstructing spatiotemporal fields. Our results indicate that federated machine learning might be a viable tool for designing highly accurate predictive decentralized digital twins relevant to fluid dynamics.

Flow in oscillatory boundary layers over permeable beds

In fluid dynamics applications that involve flow adjacent to a porous medium, there exists some ambiguity in how to model the interface. Despite different developments, there is no agreed upon boundary condition that should be applied at the interface. We present a new analytical solution for laminar boundary layers over permeable beds driven by oscillatory free stream motion where flow in the permeable region follows Darcy's law. We study the fluid boundary layer for two different boundary conditions at the interface between the fluid and a permeable bed that was first introduced in the context of steady flows: a mixed boundary condition proposed by Beavers and Joseph [“Boundary conditions at a naturally permeable bed,” J. Fluid Mech. 30, 197–207 (1967)] and the velocity continuity condition proposed by Le Bars and Worster [“Interfacial conditions between a pure fluid and a porous medium: Implications for binary alloy solidification,” J. Fluid Mech. 550, 149–173 (2006)]. Our analytical solution based on the velocity continuity condition agrees very well with numerical results using the mixed boundary condition, suggesting that the simpler velocity boundary condition is able to accurately capture the flow physics near the interface. Furthermore, we compare our solution against experimental data in an oscillatory boundary layer generated by water waves propagating over a permeable bed and find good agreement. Our results show the existence of a transition zone below the interface, where the boundary layer flow still dominates. The depth of this transition zone scales with the grain diameter of the porous medium and is proportional to an empirical parameter that we fit to the available data.

A comprehensive assessment of accuracy of adaptive integration of cut cells for laminar fluid-structure interaction problems

Finite element methods based on cut-cells are becoming increasingly popular because of their advantages over formulations based on body-fitted meshes for problems with moving interfaces. In such methods, the cells (or elements) which are cut by the interface between two different domains need to be integrated using special techniques in order to obtain optimal convergence rates and accurate fluxes across the interface. The adaptive integration technique in which the cells are recursively subdivided is one of the popular techniques for the numerical integration of cut-cells due to its advantages over tessellation, particularly for problems involving complex geometries in three dimensions. Although adaptive integration does not impose any limitations on the representation of the geometry of immersed solids as it requires only point location algorithms, it becomes computationally expensive for recovering optimal convergence rates. This paper presents a comprehensive assessment of the adaptive integration of cut-cells for applications in computational fluid dynamics and fluid-structure interaction. We assess the effect of the accuracy of integration of cut cells on convergence rates in velocity and pressure fields, and then on forces and displacements for fluid-structure interaction problems by studying several examples in two and three dimensions. By taking the computational cost and the accuracy of forces and displacements into account, we demonstrate that numerical results of acceptable accuracy for FSI problems involving laminar flows can be obtained with only fewer levels of refinement. In particular, we show that three levels of adaptive refinement are sufficient for obtaining force and displacement values of acceptable accuracy for laminar fluid-structure interaction problems.

Computational Fluid Dynamic Applications for Solar Stills Efficiency Assessment: A Review

Even though water is a renewable resource, the majority of the available water on the planet is unfit for human use. Moreover, the drinkable water demand is ever-increasing as a result of rising population, urbanization, and life standards, which makes the needs for sustainable, economic, and environment-friendly treatment alternatives of utmost importance. Seawater desalination using solar stills has been proposed as a promising alternative that may help to solve drinkable water scarcity issues. In the past decades, many studies have been conducted to assess the performance of different types of solar stills aiming to enhance their productivity. Computational fluid dynamic (CFD) numerical simulation is one of the approaches that have been used recently to assess the performance of solar stills. The present study performed a systematic review and bibliometric analysis to provide a comprehensive overview of CFD numerical simulation uses as a tool to assess solar stills performance. A total of 486 publications were collected initially from different databases for the period between 2012 and 2022. The collected publications were filtered through several stages reaching 43 publications of highest significance. The collected data were analyzed descriptively, and the bibliometric mapping was presented. Furthermore, the basics and principles of CFD numerical simulation of solar stills efficiency were described and discussed. Later, the previous studies were analyzed to understand the algorithms, methods, and still types used. Finally, future research scopes and conclusions were stated. The presented knowledge in this study can help to provide a deep overview of using CFD in studying the efficiency of solar stills and inspire researchers to identify future research ways and gaps.

Numerical simulation of bubble dynamics and segregation in binary heptane/dodecane mixtures

A mathematical model for the simulation of spherical bubble dynamics in binary alkane mixtures is presented. Detailed heat and mass transfer and phase transition are resolved, and air absorption and desorption are considered. As example mixtures, high-volatile heptane and low-volatile dodecane are investigated. The low-volatile component shows a convective counter-intuitive mass transport opposite to the diffusion flux. A staggered mass flux of heptane and dodecane is associated with a local segregation of mixture components in the surrounding liquid and a distinctive species distribution within the bubble. A comparative study with a pseudo-fluid where alkane species interdiffusion is absent and whose components cannot segregate reveals that for an oscillating bubble, the local segregation hardly affects bubble dynamics, while for a continuously growing bubble in a superheated liquid, the growth rate is considerably affected, particularly for a low heptane mixture percentage. This study demonstrates limitations of treating mixtures by a single-component surrogate fluid and may serve as a starting point for the development of multi-component cavitation models for computational fluid dynamics applications in real fluid mixtures as, e.g. fuels or hydraulic oils.

An improved immersed boundary method by coupling of the multi-direct forcing and Fourier pseudo-spectral methods

The present paper aims to report an improve on the development of the IMERSPEC methodology, which is a methodology that couples the Fourier pseudo-spectral and immersed boundary methods, which can now solve flows over complex geometries. In the present work, the Lagrangian mesh that represents the immersed body inside the flow does not have to coincide with the Eulerian mesh. Furthermore, a high accuracy for the resultant methodology is achieved. These two important improvements arise from the development of the multi-direct forcing method and used to calculate the force field of the immersed boundary method. In order to verify the IMERSPEC methodology, a manufactured solution technique was used. The results of a refined mesh were employed, and different distribution and interpolation functions were used and analysed. Finally, flows over a backward-facing step geometry were simulated in two dimensions. This type of flow presents several physical features, for example, detachment and reattachment of the boundary layer and vortex generation, which are difficult to capture using numerical solutions. A comparison with the experimental data is presented and shows that the IMERSPEC methodology is promising for computational fluid dynamics applications and its analysis.

Application of computational fluid dynamics for detection of high risk region in middle cerebral artery (MCA) aneurysm

In the recent decades, the main reason for the high death rate is related to cardiovascular disease and stroke. In this paper, numerical studies have been done to investigate the hemodynamic effects on the rupture of middle cerebral artery (MCA) in different working conditions. In this work, the effects of the blood viscosity and velocity on the pressure distribution and average wall shear stress (AWSS) are fully investigated. Also, the flow pattern inside the aneurysm is investigated to obtain the high-risk regions for the rupture of the aneurysm. Our findings show that the wall shear stress increases with increasing the blood flow velocity. Meanwhile, the risk of aneurysm rupture is considerably increased when the AWSS increases more than 0.6. In fact, the blood flow with high viscosity expands the high-risk region on the wall of the aneurysm. Blood flow indicates that the angle of the incoming bloodstream is substantially effective in the high-risk region on the aneurysm wall. The augmentation of the blood velocity and vortices considerably increases the risk of hemorrhage of the aneurysm.

High-Fidelity Digital Twin Data Models by Randomized Dynamic Mode Decomposition and Deep Learning with Applications in Fluid Dynamics

The purpose of this paper is the identification of high-fidelity digital twin data models from numerical code outputs by non-intrusive techniques (i.e., not requiring Galerkin projection of the governing equations onto the reduced modes basis). In this paper the author defines the concept of the digital twin data model (DTM) as a model of reduced complexity that has the main feature of mirroring the original process behavior. The significant advantage of a DTM is to reproduce the dynamics with high accuracy and reduced costs in CPU time and hardware for settings difficult to explore because of the complexity of the dynamics over time. This paper introduces a new framework for creating efficient digital twin data models by combining two state-of-the-art tools: randomized dynamic mode decomposition and deep learning artificial intelligence. It is shown that the outputs are consistent with the original source data with the advantage of reduced complexity. The DTMs are investigated in the numerical simulation of three shock wave phenomena with increasing complexity. The author performs a thorough assessment of the performance of the new digital twin data models in terms of numerical accuracy and computational efficiency.

Applications of Computational Fluid Dynamics in the E-Cigarettes Industry

An advanced pod E-cigarette, launched by Shenzhen Woody Vapes Technology Co., Ltd., was researched and analysed in this paper with the help of computational fluid dynamics (CFD) simulation. The standard k-ε turbulent model was introduced to simulate the flow of air, the Broadband Noise Source model adapted to measure the noise and the Discrete Phase Model (DPM) used to calculate the trajectories of the aerosols. The pressure, velocity and noise fields, the trajectories of the aerosols, obtained by Reynolds-Averaged Navier-Stokes (RANS) simulation, were analysed to optimize the structure design of this pod system. Several related experiments were performed and significant improvement was also confirmed.

Periodic Flow Through Regenerator Fillers Made from Packed Spherical Microparticles

Periodic flow of gases at cryogenic temperatures through microporous structures occur in the regenerators of Stirling-type cryocoolers. For computational fluid dynamics simulation of such flows using the Darcy–Brinkman–Forchheimer model, permeability and inertial coefficients are needed. Experimental pore-level characterization of such regenerators is difficult due to their microporous structure, and the occurrence of near-zero instantaneous flow rates and extraction of these parameters from experimental data can involve significant uncertainty. In this work, by three-dimensional direct simulation, the hydrodynamic parameters are found for flow through a metallic fill powder common to some recent cryocooler regenerators that operate at very low temperatures. The intrinsic permeability and the Forchheimer coefficients are found for parameter ranges of interest to pulse-tube cryocoolers and are compared with reported extracted experimental values. The permeability and Forchheimer coefficients are correlated to be suitable for application in computational fluid dynamics codes.

Numerical simulation of gas-dynamic processes in the centrifugal radial fan of seeding machines

Improving the efficiency of crop production, where a significant place belongs to row crops (such as corn, sunflower, soybean, sorghum, sugar beet, etc.), is inextricably linked with the introduction of energy- and resource-saving technologies to ensure quality and timely implementation of production processes. Sowing is an important technological process. To increase the speed, as a consequence, productivity and, most importantly, quality of field works, at present, precision seeding seeders with pneumatic systems with improved characteristics of vacuum generators are used. In this case, the vacuum systems of such seeders are most often based on the use of a radial centrifugal fan. Therefore, an important task is to design the fan, taking into account the matching of its parameters with the parameters of the seeder as a whole, which requires a large number of tests and checks. The use of natural models (test tables) requires considerable time and resource expenses. On the basis of numerical simulation of gas-dynamic processes there is an opportunity to significantly reduce the number of full-scale experiments, and more accurately determine the rational form of the centrifugal radial fan. The purpose of this paper is to consider the method of numerical simulation of gas dynamic processes in a centrifugal centrifugal radial fan using computer-aided design (CAD) packages. The application of computational fluid dynamics (CFD) methods to discretize the solutions of differential equations taking into account the Euler and Navier-Stokes equations. Numerical modeling of turbulence based on k-ε models, k-ω models, and shear stress transfer (SST) models. The results of calculation of three-dimensional field of velocities and pressures in the fan working zone are presented, the rational geometrical characteristics and aerodynamic characteristics (dependence of pressure drop on the air consumption) are determined. Such approach to centrifugal fan design allows to unify significantly its parameters at the stage of development and to reduce the terms of new projects.

Application of Computational Fluid Dynamics with Multiphase Flow in Water Treatment

Application of Computational Fluid Dynamics with Multiphase Flow in Water Treatment

An enhanced CLSVOF method with an algebraic second-reconstruction step for simulating incompressible two-phase flows

The CLSVOF (coupled level set method and volume of fluid) method is a widely-used approach for capturing interfaces in engineering applications of computational fluid dynamics (CFD) due to its accurate interface computation, small mass error and ease of extension to 3D (three-dimensional) simulations. To further enhance this method, a second-reconstruction CLSVOF method is used to simulate incompressible two-phase flows issues with high surface tension effects or not. In the proposed improved method, an algebraic second-reconstruction step is introduced and will be performed after the re-initialization step of the standard CLSVOF process, aiming at obtaining accurate two-phase flow interface parameters. The proposed method introduces a new interface function by means of a sigmoid formula, based on the ultimate LS function calculated by the standard CLSVOF steps. In order to evaluate the superiority of the proposed method compared to existing methods, several benchmark tests are carried out, including two-dimensional rising bubble, three-dimensional rising bubble, two-dimensional dam-break flow with a wet bed, and three-dimensional dam-break flow with an obstacle. The results show that the proposed method is more accurate than existing methods, while guaranteeing almost no mass error. In addition, the simulated results of the air-water interface agree well with those in previous experiments data.

Modeling of Lateral Flow in CFD for Subchannel Analysis

This paper is aimed at the application of computational fluid dynamics (CFD) calculations for lateral flow modeling in rod bundles of Russian-type pressurized water reactors with hexagonal fuel rod lattice by subchannel analysis under a constant temperature. The subchannel code SUBCAL and CFD code ANSYS Fluent with the Reynolds stress turbulence model, which is capable of solving the anisotropic flow present in rod bundles, are used. Both methods are compared in terms of calculations in rod bundles. The literature review of available experiments of rod bundles suitable for CFD calculation validation follows. This paper describes the created CFD models on a triangular lattice, which are subsequently validated on selected experimental data in a wide range of Reynolds numbers and geometry (pitch-to–rod diameter ratio) together with mesh sensitivity analysis. The main part of this work is to develop a new equation for the lateral flow resistance coefficient for the subchannel code based on CFD calculations. Within these calculations, the turbulent mixing coefficient β for hydraulically smooth rod bundles, which is related to the geometry, and the momentum-energy transfer analogy correction factor ε are also evaluated and for which the equation is subsequently proposed.

Prediction Method for Condensation Heat Transfer in the Presence of Noncondensable Gas for Computational Fluid Dynamics Applications

Abstract The objective of this study was to present a prediction method for condensation heat transfer in the presence of noncondensable gas (air or nitrogen) for computational fluid dynamics (CFD) analyses, where physical quantities in the computational cells in contact with the structural wall are generally used. First, using existing temperature distributions T(y) in the turbulent boundary layer along a flat plate as functions of the distance y from the condensation surface, we evaluated the distribution of condensation heat flux qc,pre(y) from the gradient of steam concentration, we derived a modification factor η(y+) as a function of the dimensionless distance y+ to obtain a good agreement with qc,cal calculated by the qc correlation defined by using the bulk quantities; and we obtained qc,mod(y)/qc,cal = 0.90–1.10 for the region of y+ > 17. Second, we modified the local Sherwood number Sh(x) for flat plates for the boundary layer thickness δ and obtained the function Sh(δ). An existing qc correlation for flat plates as a function of Sh(δ) was applied to predict the distribution of the local value qc,pre(y), and qc,pre(y)/qc,cal = 0.95–1.15 in the best case was obtained for the region of y+ > 30. Finally, a correlation of the local Sherwood number Sh(y) was derived from the temperature distributions T(y) as a function of the local Reynolds number Re(y).

Optimization under Rare Chance Constraints

Chance constraints provide a principled framework to mitigate the risk of high-impact extreme events by modifying the controllable properties of a system. The low probability and rare occurrence of such events, however, impose severe sampling and computational requirements on classical solution methods that render them impractical. This work proposes a novel sampling-free method for solving rare chance constrained optimization problems affected by uncertainties that follow general Gaussian mixture distributions. By integrating modern developments in large deviation theory with tools from convex analysis and bilevel optimization, we propose tractable formulations that can be solved by off-the-shelf solvers. Our formulations enjoy several advantages compared to classical methods: their size and complexity is independent of event rarity, they do not require linearity or convexity assumptions on system constraints, and under easily verifiable conditions, serve as safe conservative approximations or asymptotically exact reformulations of the true problem. Computational experiments on linear, nonlinear and PDE-constrained problems from applications in portfolio management, structural engineering and fluid dynamics illustrate the broad applicability of our method and its advantages over classical sampling-based approaches in terms of both accuracy and efficiency.

A non-invasive model based on the virtual portal pressure gradient to predict the first variceal hemorrhage in cirrhotic patients.

This study aimed to establish a non-invasive model based on the virtual portal pressure gradient (vPPG) to predict the first variceal hemorrhage (VH) in patients with cirrhosis. This single-center study prospectively enrolled cirrhotic patients as the training and validation cohorts during different time periods. The PPG-detection software (PPGS 1.0) was used to perform vPPG calculation, which involves 2 steps including three-dimensional (3D) reconstruction of portal vein tree and subsequent application of computational fluid dynamics. All patients were given standard primary prophylaxis against VH and followed up for 2years. Data from the training cohort were assessed using univariate and multivariate Cox regression and Kaplan-Meier analyses, by which a nomogram with its dynamic form was developed to estimate the probability of VH. In the training cohort (n = 128), 37 (28.9%) experienced VH during 2-year follow-up. Four variables including vPPG ≥ 10.5mmHg (p < 0.001), PLT < 56 × 109/L (p = 0.048), albumin < 32g/L (p < 0.001) and INR ≥ 1.2 (p = 0.022) were identified as independent risk factors of VH, among which vPPG showed the best diagnostic performance (AUC 0.875). Subsequently, these predictors were incorporated into the nomogram, of which C-indexes were 0.891 and 0.926 for the training and validation cohorts, respectively. Calibration curves demonstrated a great calibration ability of the model. At the threshold probabilities of 0.1-0.6 (1year) and 0.1-1.0 (2years), this nomogram could offer more net benefits in decision curve analysis. The vPPG-based nomogram could be used for risk stratification of the first VH in patients with cirrhosis.

Uncertainty quantification (UQ) for CFD simulation of OECD-NEA cold leg mixing benchmark

An uncertainty quantification (UQ) analysis was conducted for the unsteady Reynolds Average Navier Stokes Simulation (URANS) of the OECD-NEA cold leg mixing benchmark. The methodology is based on the American Society of Mechanical Engineers Verification and Validation (ASME V&V) standard for UQ in Computational Fluid Dynamics (CFD) applications. The numerical, input and experimental uncertainties were calculated to determine the validation uncertainty for the open test (T1). Furthermore, based on validation uncertainty, model uncertainty was calculated. Finally, on the basis of open test (T1) the symmetric and asymmetric uncertainty band was achieved for the blind test (T2). The validation uncertainty closely covers the PIV data in the cold leg. Besides, the simulation results of the blind test, together with the uncertainty band, closely bound the PIV data of the mean velocity in the cold leg. However, a large simulation uncertainty band was obtained in the downcomer due to a large validation error.

Analytical Solution for the MHD Flow of Non-Newtonian Fluids between Two Coaxial Cylinders

This paper deals with the MHD peristaltic flow of Williamson fluids through a porous medium between two joint cylinders. The fluid flow was considered to be that of a non-Newtonian fluid, i.e., a Williamson fluid. The inner tube was uniform, while the flexible outer tube had a Sine wave moving down its wall. The analytical solutions for velocity and temperature were obtained as functions (Bessell functions of the first and second types). The solution for velocity profile, temperature, and concentration distribution were obtained as functions of the physical parameters of the problem (Darcy number, magnetic parameter, Grasoff thermal number, Reynolds number, Prantl number, and Schmidt number) along with other physical parameters. The effect of the physical parameters was discussed graphically. A comparison with previously published graphical results was also carried out. The ambition of the present paper is to contribute to practical applications in geographical and physiological fluid dynamics, such as on sandstone, in the human lungs, on beach sand, on limestone, and in the bile duct. This study is based on theoretical research and can be helpful in the fields of fluid mechanics and mathematics.

Computational Fluid Dynamics on Solar Dish in a Concentrated Solar Power: A Bibliometric Review

Concentrated solar power is an alternative renewable energy technology that converts solar energy into electrical energy by using a solar concentrator and a solar receiver. Computational fluid dynamics have been used to numerically design concentrated solar power. This is a powerful numerical analysis approach that is widely used in energy and environmental engineering applications. In this paper, we review previous work on the applications of computational fluid dynamics in the design of concentrated solar power technology. We performed a bibliometric analysis of journal articles relevant to applications to analyze the current trend of utilization of computational fluid dynamics in these technologies. Then, we conducted a comprehensive analysis focused on the design of solar dish technology using computational fluid dynamics. Furthermore, we reviewed in detail the optical modeling of solar concentrators and solar receivers. Of the 83 retrieved publications from Scopus database, 80 were journal articles, and only three were review papers. Among these 80 journal articles, only 54 were relevant to this study, and 23 were relevant to solar dish technology. The documents were analyzed according to their number of citations, journal sources, and keyword evolution and network map. The information presented in this paper is useful to further recognize the contributions of computational fluid dynamics to the development of concentrated solar power, particularly to solar dish technology. In addition, we also discuss the challenges and future research directions to make solar energy a more sustainable source of renewable energy.