A combined multiscale modeling and experimental study on surface modification of high-volume micro-nanoparticles with atomic accuracy

Surface modification for micro-nanoparticles at the atomic and close-to-atomic scales is of great importance to enhance their performance in various applications,including high-volume battery,persistent luminescence,etc.Fluidized bed atomic layer deposition(FB-ALD)is a promising atomic-scale manufacturing technology that offers ultrathin films on large amounts of particulate materials.Nevertheless,nanoparticles tend to agglomerate due to the strong cohesive forces,which is much unfavorable to the film conformality and also hinders their real applications.In this paper,the particle fluidization process in an ultrasonic vibration-assisted FB-ALD reactor is numerically investigated from micro-scale to macro-scale through the multiscale computational fluid dynamics and discrete element method(CFD-DEM)modeling with experimental verification.Various vibration amplitudes and frequencies are investigated in terms of their effects on the fluid dynamics,distribution of particle velocity and solid volume fraction,as well as the size of agglomerates.Results show that the fluid turbulent kinetic energy,which is the key power source for the particles to obtain the kinetic energy for overcoming the interparticle agglomeration forces,can be strengthened obviously by the ultrasonic vibration.Besides,the application of ultrasonic vibration is found to reduce the mean agglomerate size in the FB.This is bound to facilitate the heat transfer and precursor diffusion in the entire FB-ALD reactor and the agglomerates,which can largely shorten the coating time and improve the film conformality as well as precursor utilization.The simulation results also agree well with our battery experimental results,verifying the validity of the multiscale CFD-DEM model.This work has provided momentous guidance to the mass manufacturing of atomic-scale particle coating from lab-scale to industrial applications.

Dynamic self-adaptive ANP algorithm and its application to electric field simulation of aluminum reduction cell

Region partition(RP) is the key technique to the finite element parallel computing(FEPC),and its performance has a decisive influence on the entire process of analysis and computation.The performance evaluation index of RP method for the three-dimensional finite element model(FEM) has been given.By taking the electric field of aluminum reduction cell(ARC) as the research object,the performance of two classical RP methods,which are Al-NASRA and NGUYEN partition(ANP) algorithm and the multi-level partition(MLP) method,has been analyzed and compared.The comparison results indicate a sound performance of ANP algorithm,but to large-scale models,the computing time of ANP algorithm increases notably.This is because the ANP algorithm determines only one node based on the minimum weight and just adds the elements connected to the node into the sub-region during each iteration.To obtain the satisfied speed and the precision,an improved dynamic self-adaptive ANP(DSA-ANP) algorithm has been proposed.With consideration of model scale,complexity and sub-RP stage,the improved algorithm adaptively determines the number of nodes and selects those nodes with small enough weight,and then dynamically adds these connected elements.The proposed algorithm has been applied to the finite element analysis(FEA) of the electric field simulation of ARC.Compared with the traditional ANP algorithm,the computational efficiency of the proposed algorithm has been shortened approximately from 260 s to 13 s.This proves the superiority of the improved algorithm on computing time performance.

A new computational approach for modeling diffusion tractography in the brain

Computational models provide additional tools for studying the brain,however,many techniques are currently disconnected from each other.There is a need for new computational approaches that span the range of physics operating in the brain.In this review paper,we offer some new perspectives on how the embedded element method can fill this gap and has the potential to connect a myriad of modeling genre.The embedded element method is a mesh superposition technique used within finite element analysis.This method allows for the incorporation of axonal fiber tracts to be explicitly represented.Here,we explore the use of the approach beyond its original goal of predicting axonal strain in brain injury.We explore the potential application of the embedded element method in areas of electrophysiology,neurodegeneration,neuropharmacology and mechanobiology.We conclude that this method has the potential to provide us with an integrated computational framework that can assist in developing improved diagnostic tools and regeneration technologies.

Simulation study on ultrasonic tomography for grouted reinforced concrete by finite element

A finite element reconstruction algorithm for ultrasound tomography based on the Helmholtz equation in frequency domain is presented to monitor the grouting defects in reinforced concrete structures.In this algorithm,a hybrid regularizations-based iterative Newton method is implemented to provide stable inverse solutions.Furthermore,a dual mesh scheme and an adjoint method are adopted to reduce the computation cost and improve the efficiency of reconstruction.Simultaneous reconstruction of both acoustic velocity and attenuation coefficient for a reinforced concrete model is achieved with multiple frequency data.The algorithm is evaluated with numerical simulation under various practical scenarios including varied transmission/receiving modes,different noise levels,different source/detector numbers,and different contrast levels between the heterogeneity and background region.Results obtained suggest that the algorithm is insensitive to noise,and the reconstructions are quantitatively accurate in terms of the location,size and acoustic properties of the target over a range of contrast levels.

Granular collapse in fluids:Dynamics and flow regime identification

The collapse of granular material in fluids is a prevalent phenomenon in both natural and industrial processes,displaying a notable sensitivity to initial configuration of the system.This study is specifically oriented towards falling process of collapsing material under various fluid conditions,employing the computational fluid dynamics-discrete element method(CFD-DEM)to primarily investigate the dynamics and scaling laws of deposit morphology of collapsed material.Through a comprehensive analysis of particle sedimentation in fluids,we introduce a refined inertial characteristic time for granular collapse within the inertial regime.Subsequently,we propose modifications to conventional fluid-particle density ratio and Reynolds number,aiming to enhance the accuracy of depicting collapse dynamics and identifying flow regimes across diverse column heights and fluid conditions.Finally,we construct a phase diagram of flow regimes using modified dimensionless numbers,emphasizing the role of column height in transition between viscous and inertial regimes.These parameters demonstrate enhanced relevance in governing the collapse of immersed granular columns,thereby contributing to a more nuanced understanding of fluid-particle interations in dense granular flows under different regimes.

Parallel computing of discrete element method on multi-core processors

This paper describes parallel simulation techniques for the discrete element method （DEM） on multi-core processors. Recently, multi-core CPU and GPU processors have attracted much attention in accelerating computer simulations in various fields. We propose a new algorithm for multi-thread parallel computation of DEM, which makes effective use of the available memory and accelerates the computation. This study shows that memory usage is drastically reduced by using this algorithm. To show the practical use of DEM in industry, a large-scale powder system is simulated with a complicated drive unit. We compared the performance of the simulation between the latest GPU and CPU processors with optimized programs for each processor. The results show that the difference in performance is not substantial when using either GPUs or CPUs with a multi-thread parallel algorithm. In addition, DEM algorithm is shown to have high scalabilitv in a multi-thread parallel computation on a CPU.

Brief Introduction to and Review on Elements of Computational Statistics

A brief introduction and review of new book about the Elements of Computational Statistics is given.

CFD-DEM modelling of suffusion in multi-layer soils with different fines contents and impermeable zones

Suffusion in broadly graded granular soils is caused by fluid flow and is a typical cause of geo-hazards.Previous studies of it have mainly focused on suffusion in homogeneous soil specimens.In this study,the coupled discrete element method(DEM)and computational fluid dynamics(CFD)approach is adopted to model suffusion in multi-layered soils with different fines contents,and soils with one or more impermeable zones.The parameters of the CFD-DEM model are first calibrated with the classic Ergun test and a good match with experiment is obtained.Then suffusion in multi-layered soils with different fines contents and impermeable zones is simulated and discussed.The simulation results show that,for soils with multiple layers,the cumulative eroded mass is mainly determined by the fines content of the bottom layer.In general,the higher the fines content of the bottom soil layer,the higher the cumulative eroded mass.In addition,suffusion is more severe if the fines content of the layer above is decreased.Impermeable zones inside soil specimens can increase the flow velocity around those zones,facilitating the migration of fine particles and intensifying suffusion.

A hybrid DEM/CFD approach for solid-liquid flows

A hybrid scheme coupling the discrete element method （DEM） with the computational fluid dynamics （CFD） is developed to model solid-liquid flows. Instead of solving the pressure Poisson equation, we use the compressible volume-averaged continuity and momentum equations with an isothermal stiff equation of state for the liquid phase in our CFD scheme. The motion of the solid phase is obtained by using the DEM, in which the particle-particle and particle-wall interactions are modelled by using the theoretical contact mechanics. The two phases are coupled through the Newton＇s third law of motion. To verify the proposed method, the sedi-mentation of a single spherical particle is simulated in water, and the results are compared with experimental results reported in the literature. In addition, the drafting, kissing, and tumbling （DKT） phenomenon between two particles in a liquid is modelled and rea-sonable results are obtained. Finally, the numerical simulation of the density-driven segregation of a binary particulate suspension in-volving 10 000 particles in a closed container is conducted to show that the presented method is potentially powerful to simulate real particulate flows with large number of moving particles.

Investigation into improving the efficiency and accuracy of CFD/DEM simulations

The Euler-Lagrange approach combined with a discrete element method has frequently been applied to elucidate the hydrodynamic behavior of dense fluid-solid flows in fluidized beds. In this work, the efficiency and accuracy of this model are investigated. Parameter studies are performed; in these studies, the stiffness coefficient, the fluid time step and the processor number are varied under conditions with different numbers of particles and different particle diameters. The obtained results are compared with measurements to derive the optimum parameters for CFD/DEM simulations. The results suggest that the application of higher stiffness coefficients slightly improves the simulation accuracy. However, the average computing time increases exponentially. At larger fluid time steps, the results show that the average computation time is independent of the applied fluid time step whereas the simulation accuracy decreases greatly with increasing the fluid time step. The use of smaller time steps leads to negligible improvements in the simulation accuracy but results in an exponential rise in the average computing time. The parallelization accelerates the DEM simulations if the critical number for the domain decomposition is not reached. Above this number, the performance is no longer proportional to the number of processors. The critical number for the domain decomposition depends on the number of particles. An increase in solid contents results in a shift of the critical decomposition number to higher numbers of CPUs.

Accelerating CFD–DEM simulation of processes with wide particle size distributions

Sizereduction systems have been extensively used in industry for many years. Nevertheless, reliable engi neering tools to be used to predict the comminution of particles are scarce. Computational fluid dynamics （CFD）discrete element model （DEM） numerical simulation may be used to predict such a complex phe nomenon and therefore establish a proper design and optimization model for comminution systems, They may also be used to predict attrition in systems where particle attrition is significant. Therefore, empirical comminution functions （which are applicable for any attrition/comminution process）, such as： strength distribution, selection, equivalence, breakage, and fatigue, have been integrated into the three dimensional CFDDEM simulation tool. The main drawback of such a design tool is the long computational time required owing to the large number of particles and the minute timestep required to maintain a steady solution while simulating the flow of particulate materials with very fine particles. The present study developed several methods to accelerate CFDDEM simulations： reducing the num ber of operations carried out at the singleparticle level, constructing a DEM grid detached from the CFD grid enabling a no binary search, generating a subgrid within the DEM grid to enable a no binary search for fine particles, and increasing the computational timestep and eliminating the finest particles in the simulation while still tracking their contribution to the process. The total speedup of the simulation process without the elimination of the finest particles was a factor of about 17. The elimination of the finest particles gave additional speedup of a factor of at least 18. Therefore, the simulation of a grinding process can run at least 300 times faster than the conventional method in which a standard no binary search is employed and the smallest particles are tracked.

Investigation of particle-wall interaction in a pseudo-2D fluidized bed using CFD-DEM simulations

We report on discrete element method simulations of a pseudo-two-dimensional （pseudo-2D） fluidized bed to investigate particle-wall interactions. Detailed information on macroscopic flow field variables, including solids pressure, granular temperature, and normal and tangential wall stresses are analyzed. The normal wall stress differs from the solids pressure because of the strong anisotropic flow behavior in the pseudo-2D system. A simple linear relationship exists between normal wall stress and solids pressure. In addition, an effective friction coefficient can be derived to characterize particle-wall flow interaction after evaluating the normal and tangential wall stresses. The effects of inter-particle and particle-wall friction coefficients are evaluated. Strong anisotropic flow behavior in the pseudo-2D system needs to be considered to validate the two-fluid model where the boundary condition is usually developed based on an isotropic assumption. The conclusion has been confirmed by simulation with different particle stiffnesses. Assumptions in the newly developed model for 2D simulation are further examined against the discrete element method simulation.

Eulerian-Lagrangian simulation of distinct clustering phenomena and RTDs in riser and downer

Numerical simulation of fully developed hydrodynamics of a riser and a downer was carried out using an Eulerian-Lagrangian model, where the particles are modeled by the discrete element method （DEM） and the gas by the Navier-Stokes equations. Periodic flow domain with two side walls was adopted to simulate the fully developed dynamics in a 2D channel of 10 cm in width. All the simulations were carried out under the same superficial gas velocity and solids holdup in the domain, starting with a homogenous state for both gas and solids, and followed by the evolution of the dynamics to the heterogeneous state with distinct clustering in the riser and the downer. In the riser, particle clusters move slowly, tending to suspend along the wall or to flow downwards, which causes wide residence time distribution of the particles. In the downer, clusters still exist, but they have faster velocities than the discrete particles. Loosely collected particles in the clusters move in the same direction as the bulk flow, resulting in plug flow in the downer. The residence time distribution （RTD） of solids was computed by tracking the displacements of all particles in the flow direction. The results show a rather wide RTD for the solids in the riser hut a sharp peak RTD in the downer, much in agreement with the experimental findings in the literature. The ensemble average of transient dynamics also shows reasonable profiles of solids volume fraction and solids velocity, and their dependence on particle density.

Analysis of gas-solid flow and shaft-injected gas distribution in an oxygen blast furnace using a discrete element method and computational fluid dynamics coupled model

lronmaking using an oxygen blast furnace is an attractive approach for reducing energy consumption in the iron and steel industry. This paper presents a numerical study of gas-solid flow in an oxygen blast fur- nace by coupling the discrete element method with computational fluid dynamics. The model reliability was verified by previous experimental results. The influences of particle diameter, shaft tuyere size, and specific ratio （X） of shaft-injected gas （51G） flowrate to total gas flowrate on the SIC penetration behavior and pressure field in the furnace were investigated. The results showed that gas penetration capacity in the furnace gradually decreased as the particle diameter decreased from 100 to 40 mm. Decreasing particle diameter and increasing shaft tuyere size both slightly increased the SIG concentration near the furnace wall but decreased it at the furnace center. The value of X has a significant impact on the SIG distribution. According to the pressure fields obtained under different conditions, the key factor affecting SIG penetration depth is the pressure difference between the upper and lower levels of the shaft tuyere. If the pressure difference is small, the SIG can easily penetrate to the furnace center.

Modeling and simulation of chemically reacting flows in gas-solid catalytic and non-catalytic processes

This paper gives an overview of the recent development of modeling and simulation of chemically react- ing flows in gas-solid catalytic and non-catalytic processes. General methodology has been focused on the Eulerian-Lagrangian description of particulate flows, where the particles behave as the catalysts or the reactant materials. For the strong interaction between the transport phenomena （i.e., momentum, heat and mass transfer） and the chemical reactions at the particle scale, a cross-scale modeling approach, i.e., CFD-DEM or CFD-DPM, is established for describing a wide variety of complex reacting flows in multiphase reactors, Representative processes, including fluid catalytic cracking （FCC）, catalytic conversion of syngas to methane, and coal pyrolysis to acetylene in thermal plasma, are chosen as case studies to demonstrate the unique advantages of the theoretical scheme based on the integrated particle-scale information with clear physical meanings, This type of modeling approach provides a solid basis for understanding the multiphase reacting flow problems in general.

Selection of PCEs' location in multi-domain optical networks

Path computation elements （PCEs） are employed to compute end-to-end paths across multi-domain optical networks due to the advantages of powerful computation capability. However, PCEs＇ location selection is still an open problem which is closely related to the communication overhead. This paper mainly focuses on the problem of PCEs＇ location selection to minimize the overall communication overhead in the control plane. The problem is formulated as a quadratic integer programming （QIP） model, and an optimal decision rule is gained from the solution of the QIP model. Then based on the decision rule, a distributed heuristic algorithm is proposed for dynamic network scenario. Simulation results demonstrate the benefit and the effectiveness of our proposed approach by comparing it with random selection policy.

Simulation and computational heat transfer in the human eye with Dirichlet–Neumann domain decomposition approximation

In this paper,a bioheat model of temperature distribution in the human eye is studied,the mathematical formulation of this model is described using adequate mathematical tools.The existence and the uniqueness of the solution of this problem is proven and four algorithms based on finite element method approximation and domain decomposition methods are presented in details.The validation of all algorithm is done using a numerical application for an example where the analytical solution is known.The properties and parameters reported in the open literature for the human eye are used to approximate numerically the temperature for bioheat model by finite element approximation and nonoverlapping domain decomposition method.The obtained results that are verified using the experimental results recorded in the literature revealed a better accuracy by the use of algorithm proposed.

3D image reconstruction with a controllable overlapping number of elemental images in computational integral imaging

In this Letter, we propose a three-dimensional （3D） image reconstruction method with a controllable overlapping number of elemental images in computational integral imaging. The proposed method can control the overlap- ping number of pixels coming from the elemental images by using the subpixel distance based on ray optics between a 3D object and an image sensor. The use of a controllable overlapping number enables us to provide an improved 3D image visualization by controlling the inter-pixel interference within the reconstructed pixels. To find the optimal overlapping number, we simulate the pickup and reconstruction processes and utilize the numerical reconstruction results using a peak signal-to-noise ratio （PSNR） metric. To demonstrate the feasibility of our work in optical experiments, we carry out the preliminary experiments and present the results.

AN IMPROVED EFFICIENT SEMI-IMPLICIT FINITE ELEMENT SCHEME FOR TWO-DIMENSIONAL TIDAL FLOW COMPUTATIONS

In a recent paper, an efficient semi-implicit finite element scheme for 2-dimensional tidal flow computations is proposed. In that scheme, each term of the governing equations, rather than each dependent variable, is ex- panded in terms of the unknown nodal values. Simpson's rule ix used for numerical integration to make the mass matrix diagonal. The friction terms are represented semi-implicitly to improve stability, but no additional compu- tational effort is required. The shortcomings of this scheme are that the time-stepping scheme is only first-order ae- curate and artificial smoothing is required to control the numerical noise. In this paper, the previous scheme is im- proved by including the eddy viscosity terms in the governing equations to replace artificial smoothing in noise con- trol and the time-stepping scheme is modified to make it second-order accurate. These improvements can be achieved with only a slight increase in computational effort. The test cases used previously to validate the former scheme are again employed to test the present scheme.

THE COMPUTATION OF SEEPAGE FORCE ON MARINE STRUCTURES WITH FINITE ELEMENT METHOD

The wave-induced seepage force is investigated on marine structures resting on or buried in the seabed.The bed is modelled as a poroelastic medium containing a nearly saturated water.The governing equations are solved with Finite Element Method.For a pipeline buried in the seabed,agreement between the present numerical results and that of Cheng H.D.(1986)is quite satisfactory.