Flow Field Problem Research Articles

Advancing particle forces and motion dynamics in centrifugal concentrator based on flow field simulation

ABSTRACT The forces and motion state of particles within the fluid domain of the Knelson concentrator have long been a focal point for researchers. Presently, Stokes’ flow laws are commonly employed as the basis for theoretical calculations. However, this approach somewhat deviates from reality due to challenges in determining the Reynolds number of particles in the centrifugal force field during practical work. Additionally, the relationship between the Reynolds number and the drag coefficient remains undetermined in certain ranges. This study presents a high predictive relationship curve, obtained using fitting software, to supplement and rectify the limitations in the existing relationship. Leveraging fluid simulation software, this research determines the Reynolds number of particles of different sizes and densities within the fluid, offering a methodological reference for similar flow field problems. A new drag coefficient function is proposed and validated for the Reynolds number range of 1 to 20, addressing a gap in existing theoretical models. The simulation results indicate that under the suitable separation conditions of −0.074 + 0.02 mm particles, the concentrate particles overcome the flushing effect of the reverse washing water and move in the opposite direction to the fluid. This advancement not only improves the theoretical framework but also offers significant academic and practical value by enhancing the efficiency of particle separation in the Knelson concentrator.

Rapid prediction of indoor airflow field using operator neural network with small dataset

Indoor airflow is one of the most critical factors affecting room comfort. The accurate prediction of indoor airflow fields is essential for efficient environmental control. However, representative methods for calculating indoor airflow organization, such as computational fluid dynamics (CFD), are complex and time consuming. Therefore, this study proposes a machine learning approach that can rapidly reconstruct indoor airflow fields. This method employs an improved deep operator network (DeepONet) and a Fourier neural operator (FNO) neural network to learn a set of solutions to a problem resembling a flow field and then realizes an accuracy-preserving prediction of an unseen domain. First, we decompose the computational domain into subdomains and then reconstruct the flow field for the subdomains. Subsequently, the subdomains are stitched into the original computational domain. Using data enhancement techniques along with a small dataset, this method achieves satisfactory training results. The results indicate that for a two-dimensional isothermal flow field problem, both the improved DeepONet and FNO models accurately reconstruct the flow field. The mean squared errors are 0.28% and 1.89% for the improved DeepONet and FNO models, respectively, with both requiring less than 0.01s. This method does not require repeated training under different operating conditions, which significantly reduces the computation time. Compared with conventional CFD technology, the proposed method improves the speed by up to three to six orders of magnitude.

Thermal radiation influence on non-Newtonian nanofluid flow along a stretchable surface with Newton boundary condition

This article focuses on the heat transfer on a mixed convection flow of nanoparticles suspended non-Newtonian nanofluid past a stretching surface under Newtonian boundary conditions. The leading boundary layer equations are changed to a non-linear boundary value problem by using suitable similarity variables. BVP4c with MATLAB is used to elucidate the resultant system. The controlled parameters involved in the flow field problem and its impact on the flow components as well as the interested engineering quantities are examined via graphs and tables. Our study results are in good agreement with the existing literature. It is noticed that the presence of radiation increases the heat inside the fluid, which leads to an increase in the thickness of the energy boundary layer and an increase in the temperature of the fluid. The temperature of the fluid decreases for higher values of the Brownian motion parameter and increases for variations in thermophoresis.

Study and management of flow and concentration field problems in 600 MW SCR unit

With the increasingly stringent national requirements for environmental protection, the control of pollutants in coal-fired power plants has been gradually strengthened. In order to meet the NOx emission standard, some coal-fired units achieve ultra-low emissions by excessive ammonia injection, which seriously affects the unit operation economy. This paper takes the SCR denitrification unit of a 600 MW coal-fired unit with a Π-type furnace in China as the research object and studies the distribution of flow and concentration fields inside the unit under a 60% load section by means of CFD numerical simulation. It points out the problems of flow and concentration fields at local locations under current operating conditions and proposes the rectification of the corresponding area of the inflow equipment and the idea of a zonal ammonia injection optimization method. It provides a certain reference value for the optimized management of the denitrification system of coal-fired units in the future.

An Efficient Approach for Solving the HVDC ion Flow Field Problem Using the PDE Constrained Optimization Scheme

An Efficient Approach for Solving the HVDC ion Flow Field Problem Using the PDE Constrained Optimization Scheme

The Meshless Direct Simulation Monte Carlo method

A new numerical simulation method called the Meshless Direct Simulation Monte Carlo (DSMC) Method is presented in this article for solving a rarefied flow field problem. It uses a discrete points group instead of using a conventional mesh to discretize the computational domain. The meshless theory is used to solve the governing equations of the rarefied flow field. Numerical challenges related to mesh distortion and low accuracy encountered in conventional mesh technology are eliminated. The meshless technology used in the DSMC method constructs the molecular cloud structure and the virtual volume to establish the methodology of molecular fast search, molecular collision pair number calculation, and molecular cloud sampling. The numerical results of a two-dimensional flow around a cylinder, a nozzle flow, a three-dimensional flow around a sphere, and a Mars probe re-entry flow are presented to demonstrate the feasibility, accuracy, and robustness of the Meshless DSMC method. This study provides the basis for meshless technology development in the field of rarefied flow.

Data-driven methods for low-dimensional representation and state identification for the spatiotemporal structure of cavitation flow fields

Computational Fluid Dynamics (CFD) generates high-dimensional spatiotemporal data. The data-driven method approach to extracting physical information from CFD has attracted widespread concern in fluid mechanics. While good results have been obtained for some benchmark problems, the performance on complex flow field problems has not been extensively studied. In this paper, we use a dimensionality reduction approach to preserve the main features of the flow field. Based on this, we perform unsupervised identification of flow field states using a clustering approach that applies data-driven analysis to the spatiotemporal structure of complex three-dimensional unsteady cavitation flows. The result shows that the data-driven method can effectively represent the changes in the spatial structure of the unsteady flow field over time and to visualize changes in the quasi-periodic state of the flow. Furthermore, we demonstrate that the combination of principal component analysis and Toeplitz inverse covariance-based clustering can identify different states of the cavitated flow field with high accuracy. This suggests that the method has great potential for application in complex flow phenomena.

Research on simulation of gun muzzle flow field empowered by artificial intelligence

Artificial intelligence technology is introduced into the simulation of muzzle flow field to improve its simulation efficiency in this paper. A data-physical fusion driven framework is proposed. First, the known flow field data is used to initialize the model parameters, so that the parameters to be trained are close to the optimal value. Then physical prior knowledge is introduced into the training process so that the prediction results not only meet the known flow field information but also meet the physical conservation laws. Through two examples, it is proved that the model under the fusion driven framework can solve the strongly nonlinear flow field problems, and has stronger generalization and expansion. The proposed model is used to solve a muzzle flow field, and the safety clearance behind the barrel side is divided. It is pointed out that the shape of the safety clearance under different launch speeds is roughly the same, and the pressure disturbance in the area within 9.2 m behind the muzzle section exceeds the safety threshold, which is a dangerous area. Comparison with the CFD results shows that the calculation efficiency of the proposed model is greatly improved under the condition of the same calculation accuracy. The proposed model can quickly and accurately simulate the muzzle flow field under various launch conditions.

An efficient AMG based composite solver for the fully coupled solution of the large scale ion flow field problem

• The authors provide more details for the mathematical description of the ion flow field problem and explain the irregularity introduced by the Kapzov hypothesis. • The comparison of the iteration costs under the unipolar and the bipolar cases are present to verify the efficiency of the present method. • The misleading statement about the scalability is rephrased. • The capitalization problems and other typos are revised according to the reviewers’ comments. As the configuration of the HVDC transmission line model becomes more complex, the size of the discretized ion flow field problem grows up to an extremely large degree and the computational time needed for solving the linear system is unacceptable. The algebraic multigrid method(AMG) is a well-known preconditioner for its theoretically optimal performance in solving the elliptic equation. In the present work, the Poisson equation is pre-processed by the classical AMG method and the transport part is preconditioned by the Petrov-Galerkin AMG. These two preconditioners are applied to approximate the ideal preconditioner of the Poisson-Continuity coupled system derived from the block LU factorization. The composite preconditioner significantly improves the convergence of the Krylov iterative solver and the ion flow field problem with million degrees of freedom is solved in less than 20 min. The present work brings a novel and general scheme to improve the efficiency of the traditional algorithm for the multi-physics problems.

Reconstruction of hydrofoil cavitation flow based on the chain-style physics-informed neural network

Cavitation flow is a typical complex flow phenomenon, which involves many flow mechanisms. At present, the main approach to reconstruct the cavitation flow field based on the experimental results is numerical simulation, which has the defects of low computational efficiency and is difficult to effectively use the experimental data. In this paper, a chain-style physics-informed neural network (chain-style PINN) is developed to solve the reconstruction problem of cavitation flow field. On the basis of decoupling the governing equations, our method solves the physical quantities of interest serially by introducing multiple serial PINNs. A physics-informed loss function is defined to realize the assimilation of experimental data and physical mechanism. The prediction for a 3D NACA66 hydrofoil case is validated by comparing with Direct Numerical Simulation (DNS), which demonstrates that the calculation time is reduced by about 70% while the relative L2 errors of pressure and liquid volume fraction fields are only 0.0030 and 0.0035. While comparing with the existing method Hidden Fluid Mechanics (i.e., baseline PINN), the results show the validity of our method. To the best of our knowledge, this is the first theoretical work that applies PINN to cavitation flow.

Parallel Scheme for Multi-Layer Refinement Non-Uniform Grid Lattice Boltzmann Method Based on Load Balancing

The large-scale numerical simulation of complex flows has been an important research area in scientific and engineering computing. The lattice Boltzmann method (LBM) as a mesoscopic method for solving flow field problems has become a relatively new research direction in computational fluid dynamics. The multi-layer grid-refinement strategy deals with different-level of computing complexity through multi-scale grids, which can be used to solve the complex flow field of the non-uniform grid LBM without destroying the parallelism of the standard LBM. It also avoids the inefficiencies and waste of computational resources associated with standard LBMs using uniform and homogeneous Cartesian grids. This paper proposed a multi-layer grid-refinement strategy for LBM and implemented the corresponding parallel algorithm with load balancing. Taking a parallel scheme for two-dimensional non-uniform meshes as an example, this method presented the implementation details of the proposed parallel algorithm, including a partitioning scheme for evaluating the load in a one-dimensional direction and an interpolation scheme based on buffer optimization. Simply by expanding the necessary data transfer of distribution functions and macroscopic quantities for non-uniform grids in different parallel domains, our method could be used to conduct numerical simulations of the flow field problems with complex geometry and achieved good load-balancing results. Among them, the weak scalability performance could be as high as 88.90% in a 16-threaded environment, while the numerical simulation with a specific grid structure still had a parallel efficiency of 77.4% when the parallel domain was expanded to 16 threads.

A high performance approach for solving the high voltage direct current ion flow field problem by tensor‐structured finite element method

A high performance approach for solving the high voltage direct current ion flow field problem by tensor‐structured finite element method

The Particle Element Method to Obtain Parameter Distributions of Two-phase Reactive Flow in a Propulsion Combustion System

ABSTRACT Large-particle porous propellant has good surface-enhancing combustion performance and may improve the muzzle velocity of combustion propulsion system effectively. The proposed particle element method is further refined to investigate particle motion characteristics and flow field distribution in a large-particle charge combustion system with moving boundary. The particle element parameter aggregation is established to describe particle parameter distribution in the system, and the motion is controlled by particle motion equations during combustion and propulsion, so that the particle element is stretched and coupled with the gas phase. The particle element method accurately describes the distribution of the particle movement process and the evolution of the flow field in the chamber, and the numerical simulation results are in good agreement with the AGARD code. In particular, the overall efficiency of the entire calculating procedure is improved by 21.7%. The research results will effectively solve the flow field problem in the large-particle charge combustion system.

Applications of degenerate kernels to potential flow across circular, elliptical cylinders and a thin airfoil

In this paper, we employ the boundary integral equation (BIE) to analytically derive the solution of potential flow across a circular cylinder, an elliptical cylinder and a thin airfoil. It is found that the symmetric or antisymmetric potential flow problem can be solved by using the UT or the LM equation alone. Both analytical and numerical approaches were considered. The key tool is using the degenerate kernel instead of the closed-form fundamental solution. A closed-form fundamental solution is expressed in terms of degenerate kernel by using polar and elliptical coordinates for a circular cylinder and an elliptical cylinder, respectively. The role of the dual BEM is also examined by showing the singular vectors of influence matrix. Besides, either the singular or the hypersingular BIE are respectively employed alone to solve the problem of symmetric and anti-symmetric flow field. Analytical derivation as well as the BEM is demonstrated. The orientation of the ellipse, as well as the angle of attack for the thin airfoil, is considered. The result shows that the degenerate kernel can be an alternative tool for solving some BVPs, although the complex variable is always employed. Once the degenerate kernel for the closed-form fundamental solution is available, the BIE is nothing more than the linear algebra and an analytical study is possible. The extension to 3-D object is promising once the degenerate kernel is available.

A Novel and General Approach for Solving the Ion-Flow Field Problem by a Regularization Technique

In order to have a better convergence and accuracy for solving the ion-flow field problem, a novel and general numerical approach is proposed. In the past, the framework of the traditional mesh based method has a dilemma that the Kapzov boundary condition can be imposed properly, and it must have two loops: the “well-posed” problem is solved in the inner loop and the secant based method is applied to impose the Kapzov assumption in the outer loop. In contrast, the proposed method solves the ion flow field problem from the perspective of the inverse problem. The original boundary value problem is transformed into a regularized optimization problem based on the prior information about the smooth ion distribution on the conductors. The objective function is separated into two parts and minimized by the alternating direction iterative method. In contrast to the traditional methods, the proposed method has removed the redundant iterations and the contentious simplifications. Numerical experiments show that the performance of the proposed method is superior to the traditional method and the results obtained by the proposed method agree better with the physical law than the traditional method. The new method presents a general and rigorous way to analysis the ion-flow field problem.

Study of new accurate supplementary energy modeling with multi-components based on newly developed high resolution scheme

In this work, we developed a code of finite volume method for 1D unsteady Euler equations to carry out the flow field problem due to moving contact discontinuity interface between two different species on both sides of the shock tube. The derived additional energy conservation equation would produce a non-conservative term. It is important to reduce the non-physical numerical oscillation problem and improve the capturing-shock ability and computing accuracy of high resolution problem. This study focuses on the following two parts. The first part, we expanded the energy equation of unsteady Euler equations into the form of i species. Further, we verified the feasibility and reliability of the new numerical energy model under the dual-species condition, and then we executed a series of systematic research to carry out the some experimental verification. Moreover, we adopted the most suitable numerical scheme for new Model B3 and validated with the old energy model. Second, we developed 9 new models of flux limiter and validated these limiters through the condition of dual species.For the validated results, the new energy Model B3 can effectively improve the numerical oscillations and capture phenomenon quite well, which just adopt the lower-order difference method. The validated results of new developed limiter models show that their capturing effects of some limiters are very well.

Research on the combined electrochemical machining and electrical discharge machining technology for closed integer impeller

In order to improve the machining efficiency of engine closed integral impeller, the electrochemical machining (ECM) and electrical discharge machining (EDM) combined technology was proposed. ECM was used to remove the large machining allowance with high efficiency, and then the precision processing was accomplished by EDM. Because the two ends of the vortex channel are large and the middle is narrow, so the special-shaped vortex channel was divided into internal and external flow channels. First of all, based on the problem of flow field diverge and non-uniform in ECM S-03 special stainless steel material, the method of reverse flow ECM external flow channel was proposed. The ECM fixture design of internal and external flow channels was carried out, and the composite electrolyte composition of 5%NaCl+16%NaNO3+4%NaClO3 was obtained. Secondly, the EDM rough and precision machining electrodes were designed and the EDM experiment has done. Finally, the combined ECM and EDM experiment was finished. The experiment result showed that the combined method is feasible for machining closed integral impeller; the machining efficiency is 30% higher than that of EDM alone.

Development of the Snapshot Method for Six Degree-of-Freedom Flight Dynamics Simulation of a High Aspect Ratio Wing Aircraft

The purpose of this paper is to develop a six degree-of-freedom flight simulation while considering the flexibility of an aircraft with high aspect ratio wings using by new quasi-steady temporal coupling scheme named ‘snapshot method’. The simulation was based on the quasi-steady temporal coupling scheme for the flow field, elastic structure, and rigid body motion problem. A full three-dimensional finite-element model of unmanned aerial vehicles was used. The object aircraft has main wings with an aspect ratio over 20 and a flight for long endurance in high altitude. To consider the flexibility of these aircraft, the present snapshot method was developed that combines ‘aerodynamic—structural dynamics—flight dynamics’ to analyze dynamic response. By applying this method, MATLAB/SIMULINK, which analyzes the rigid body motion, and MSC FlightLoads, which is responsible for aeroelastic trim analysis, was tightly linked into the present simulation framework. Using the present simulation, aircraft response under various maneuver conditions was simulated. First, the trim analysis for the level cruise was performed. Trim parameters, stability derivative coefficients, and the moment of inertia were also determined. Based on these results, the flight dynamics of the aircraft was simulated according to the operation of the rudder and the aileron control surface. The effect of the rigid and flexible body assumptions was also confirmed. In addition, these results were compared with other existing simulation results based on the multibody dynamics under the same conditions. To predict the response of the aircraft under the gust, the simulation was performed by applying the two-dimensional 1-cosine discrete gust profile. The important aspects, such as numerical prediction methods during stages of the highly flexible aircraft design process for a countermeasure to various challenging problems, were shown.

Integrated improvement of the elasticity-based mesh deformation method based on robust parameters and mesh quality

Highly robust mesh deformation methods are key techniques for solving unsteady flow field problems with moving or deforming boundaries. Because it is imperative to reduce the remeshing times, these methods are important in engineering applications, especially for complex geometric boundaries and large displacements. We introduce three classical elasticity-based mesh deformation methods and determine the limitations of the two nonlinear classical methods. Two steps were taken to achieve an integrated improvement: first, the robust power parameters a and b and the weighted parameter x are introduced to enhance the robustness of the basic elasticity equation. Second, a mesh quality parameter is implemented to prevent the large distortion of the poor elements and this parameter is added to the elasticity equation as a constraint. To validate the validity of the integrated improvement approach, several test cases of a moving or deforming two-dimensional flat plate are used. Additionally, two simulated engineering examples are used to demonstrate the application of the integrated improvement for practical problems, including the pitching oscillation of a National Advisory Committee for Aeronautics (NACA) 0012 airfoil and the ONERA M6 wing. The results show that the integrated improvement approach does not only allow for the selection of suitable robust parameters to achieve more robust deformed meshes but also reduces the distortion of the poor elements near the moving boundary, even when the deformation is severe.

Comparisons of FV-MHMM with Other Finite Volume Multiscale Methods

Upscaling and multiscale methods in reservoir engineering remain a complicated task especially when dealing with heterogeneities. In this study, we focus on flow field problem with a Darcy’s equation considered at the fine scale. The main difficulty is then to obtain an accurate description of the flow behavior by using multiscale methods available in petroleum engineering. We cross-compare three of the main finite volume formulations: multiscale finite volume method (MsFv), multiscale restriction smoothed (MsRSB) and a new finite volume method, FV-MHMM. Comparisons are done in terms of accuracy to reproduce the fine scale behavior.