Mesoscopic Method Research Articles

Multifractal characterization of gangue particle size distribution structure during ball milling process

This study is focused on the fractal characteristics of gangue particle size distribution(PSD) during ball milling process, taking mudstone, sandstone , and limestone gangue as the research object with multifractal theory, laser scattering-based particle size analysis , scanning electron microscopy (SEM), X-ray diffractometry (XRD) and other mesoscopic methods. The multifractal characteristic parameters of gangue PSD under different milling time and their correlation with the mesostructure are analyzed. The results show that the PSD of three gangues have different fractal characteristics and the multifractal parameters have stage distribution characteristics with time. The multifractal characteristic parameters of gangue, such as D(0) D (2), Δα 、 Δf , initially increase and then decrease with the increase of ball milling time, and reach the maximum value in 10-20 min. The heterogeneity of gangue PSD and the microscopic mechanism of multifractal parameter changes are revealed by examining the correlation between multifractal parameters and gangue morphology in fragmentation form. The change of gangue morphology is consistent with the change of multifractal parameters of PSD structure during ball milling process. • Particle size distribution multifractal characteristics of gangue have phased characteristics during ball milling. • Shape coefficient is highly consistent with the multifractal parameter of particle size distribution . • Particle breakage form is the main factor of particle size distribution and meso-structure change. • With an increase in milling time, the main forms of crushing transition from impact to extrusion and friction.

A macroscopic and mesoscopic model of Newtonian and non-Newtonian nanofluids with a two-energy equation method

We present an updated comprehensive macroscopic model of nanofluids, considering a revisited local thermal non-equilibrium (LTNE) condition to study the temperature difference between carrier fluid and nanoparticles. A new relation for thermal conductivity of solid and liquid phases in the LTNE condition is introduced which considers the possible particle aggregation. This model is thermodynamically consistent and covers the non-Newtonian models of nanofluids, including power-law and viscoplastic ones. A mesoscopic scheme based on the lattice Boltzmann method (LBM) which satisfies the presented macroscopic equations is introduced and derived. This investigation is a further development of our recent studies[G. H. R. Kefayati and A. Bassom, “A lattice Boltzmann method for single and two phase models of nanofluids: Newtonian and non-Newtonian nanofluids,” Phys. Fluids 33, 102008 (2021); G. H. R. Kefayati, “A two- and three-dimensional mesoscopic method for an updated non-homogeneous model of Newtonian and non-Newtonian nanofluids,” Phys. Fluids 34, 032003 (2022).] for simulating and analyzing nanofluids by a two-phase model. To assess the present numerical method, it is studied for a benchmark problem of natural convection in a cavity. The dimensional and non-dimensional macroscopic equations for the mentioned benchmark are defined and the implemented non-dimensional relations of LBM are shown. The present approach is verified with the obtained results of the mixture approach and a previous two-phase model, which demonstrated the accuracy of the presented method. The results including the temperature distributions of the solid and fluid phases, the nanoparticles distributions, and fluid flow behavior as well as the yielded/unyielded sections for the viscoplastic nanofluids are shown and discussed for the defined non-dimensional parameters. It was also demonstrated that the previous proposed thermal conductivity model of nanofluids in the LTNE approach generates a significantly different value compared to experimental results, and the current suggested model produces reliable results to the experimental ones.

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.

Consistent and Transferable Force Fields for Statistical Copolymer Systems at the Mesoscale.

The statistical trajectory matching (STM) method was applied successfully to derive coarse grain (CG) models for bulk properties of homopolymers. The extension of the methodology for building CG models for statistical copolymer systems is much more challenging. We present here the strategy for developing CG models for styrene-butadiene-rubber, and we compare the quality of the resulting CG force fields on the structure and thermodynamics at different chemical compositions. The CG models are used through the use of a genuine mesoscopic method called the dissipative particle dynamics method and compared to high-resolution molecular dynamics simulations. We conclude that the STM method is able to produce coarse-grained potentials that are transferable in composition by using only a few reference systems. Additionally, this methodology can be applied on any copolymer system.

Cross-scale identification for friction and wear boundaries of tooth flank of high-feed milling cutter

In the milling process, under the high-efficiency and intermittent cutting loads, the instantaneous posture of the milling cutter and the instantaneous cutter-workpiece engagement are in an unstable state. It is difficult to accurately identify the friction and wear boundary of the cutter tooth flank. It has become an urgent problem to be solved in the life evaluation of milling cutters. The characteristics of the instantaneous posture variation of the milling cutter and the distribution of the thermal-stress mechanical coupling field of the flank of cutter tooth under the vibration were studied. Using the cross-scale load transfer method, the cross-scale relationship between the macro and micro friction loads on the cutter tooth flank was realized. The number of broken valence bonds, the sudden change of potential energy and the attenuation of elastic modulus of the super-cell on the flank of cutter tooth were studied. The mesoscopic scale identification method of the friction and wear boundary feature points of the tooth flank was proposed. The instantaneous and cumulative boundary distribution of friction and wear on the flank of cutter tooth were obtained, and verified by experiments.

Unit conversion in pseudopotential lattice Boltzmann method for liquid–vapor phase change simulations

Pseudopotential lattice Boltzmann (LB) model is an effective mesoscopic method for liquid–vapor phase change simulations. In LB methods, calculations are often carried out in lattice units. Thus, a correct mapping from the lattice unit system to the physical unit system is crucial for accurate simulations of practical problems. The unit conversion for liquid–vapor phase change problems is more complicated than single-phase problems, because an equation of state (EOS) for a nonideal fluid is introduced in the pseudopotential two-phase model. In this work, a novel unit conversion method for the pseudopotential LB model is proposed. The basic strategy is to obtain the conversion relations of fundamental units by mapping the surface tension and EOS parameters related to fluid properties, and thus, the unit conversion relations of other quantities are deduced. Numerical simulations of benchmark problems including the film evaporation and the bubble heterogeneous nucleation from a V-shaped cavity are carried out, and the simulation results are converted to the physical unit system by the proposed method. The numerical results demonstrate that the proposed method is able to recover the physical-unit latent heat of the fluid in the film evaporation problem. In the bubble nucleation from a V-shaped cavity problem, the conventional unit conversion method cannot derive the correct superheat temperature in the physical unit, whereas the proposed method based on the fundamental units recovers the critical superheat temperature which is consistent with the analytical result.

Cranial window for longitudinal and multimodal imaging of the whole mouse cortex.

.SignificanceAll functional brain imaging methods have technical drawbacks and specific spatial and temporal resolution limitations. Unraveling brain function requires bridging the data acquired with cellular and mesoscopic functional imaging. This imposes the access to animal preparations, allowing longitudinal and multiscale investigations of brain function in anesthetized and awake animals. Such preparations are optimal to study normal and pathological brain functions while reducing the number of animals used.AimTo fulfill these needs, we developed a chronic and stable preparation for a broad set of imaging modalities and experimental design.ApproachWe describe the detailed protocol for a chronic cranial window, transparent to light and ultrasound, devoid of BOLD functional magnetic resonance imaging (fMRI) artifact and allowing stable and longitudinal multimodal imaging of the entire mouse cortex.ResultsThe inexpensive, transparent, and curved polymethylpentene cranial window preparation gives access to the entire mouse cortex. It is compatible with standard microscopic and mesoscopic neuroimaging methods. We present examples of data on the neurovascular unit and its activation using two-photon, functional ultrasound imaging, and BOLD fMRI.ConclusionThis preparation is ideal for multimodal imaging in the same animal.

Study on the optimal parameter range of droplet-wrapped respirable dust in spray dustfall by mesoscopic method.

Coal miners on the fringes of cities are often exposed to respirable dust hazards. Spray is one of the most effective dust reduction measures. When studying the coupling and collision behavior of droplets and dust particles, it is helpful to optimize the parameter range of the droplets to capture dust particles at the mesoscopic level, to determine the effect of the spray field on the dust particles at the macroscopic level. In this study, the volume of fluid (VOF) method was used to track the interface of multiphase flow. A numerical simulation of 13 working conditions was carried out using the control variable method. Based on the numerical simulation results, we obtained the optimal parameter range for dust to be encapsulated by droplets. To confirm the reliability of the simulation, we independently developed an experimental system and conducted experiments. The simulation results obtained were measured using the experimental system, and an optimal droplet parameter range of 7 μm to settle dust in a coal mining face was determined. Numerical simulation using a mesoscopic method to study dust–spray coupling produced reliable results, which can be used in the practical application of spray dust reduction and has wider relevance for practical engineering.

Mesoscopic simulations of inertial drag enhancement and polymer migration in viscoelastic solutions flowing around a confined array of cylinders

We study the flow around a periodic array of cylinders using a mesoscopic viscoelastic fluid that mimics polymeric solutions. We model our fluid employing a novel mesoscopic method based on Smoothed Dissipative Particle Dynamics and FENE springs. We characterize the static and dynamic properties of our model solutions and compare the results with theoretical predictions based on the Zimm model. After rheological characterization of the modeled solutions, we simulate the flow around a confined array of cylinders. The balance between inertia and elasticity in our simulations is studied using a wide range of Reynolds (Re) and Weissenberg (Wi) numbers. We find that increasing the flow rate reduces the drag coefficient on the cylinder up to a critical Re corresponding to a minimum. Thereafter, inertia becomes dominant and we encounter drag enhancement for all the solutions studied, including the Newtonian solvent. With the use of simple model for the viscous and inertial contributions to drag, we conclude that inertial effects are driving the increase in the drag experienced by the cylinder. In our simulations, we also observe migration of polymer chains away from the channel walls and in the wake of the cylinder. We conclude that stress gradients induced by the curvature of streamlines and convection of the depleted layers at the walls as the principal mechanisms driving the migration of chains. We find the extent of the migration correlates well with the viscoelastic Mach number (Ma = Re Wi ) suggesting that both elastic and inertial effects play a role in this phenomenon. • A mesoscopic model fluid with viscoelastic behavior is presented. • The drag on a confined array of periodically spaced cylinders is investigated. • Drag enhancement is explained with a simple model combining inertial and viscous drag. • Polymeric migration at the walls and the wake of the cylinders is investigated.

Mesoscopic analysis of heat and moisture coupled transfer in concrete considering phase change under frost action

Freeze-thaw damage in cold areas often decreases the performance and service life of concrete structures. This work presents a mesoscopic numerical method to investigate the heat and moisture coupled transfer of concrete subjected to frost action at the meso-scale while accounting for phase change kinetics. In this method, a new multiphase hydrothermal coupled model is established to describe the coupling effects of heat exchange, moisture migration, ice formation, and vapor condensation in concrete exposed to freeze-thaw cycles. To consider its meso-structural characteristics, a meso-structure of concrete consisting of mortar, interfacial transition zones (ITZs) and aggregates is generated and employed to conduct some numerical simulations. Results indicate that the proposed mesoscopic method is capable of predicting hydrothermal behaviors of concrete at the meso-scale. The hysteresis of the evolution of relative humidity with temperature becomes more pronounced as aggregate content increases from 20% to 50%, owing to the role of phase change. In particular, the relative humidity of concrete containing 50% aggregates rises to 91% and then swiftly reduces to 85% as the temperature decreases. Furthermore, when the permeability ratio of the ITZ to mortar is reduced from 10 to 1, the ITZ diffusivity only affects the relative humidity during the thawing process.

Compressive stress-strain relationships of concrete exposed to elevated temperatures based on mesoscopic damage method

Damage evolution in concrete after high temperature is a complicated procedure, in which the pre-peak strain hardening behaviour, the post-peak strain softening behaviour and the impact of high temperature play key roles. Uniaxial and biaxial compression damage models of concrete considering high temperature degradation effect are proposed based on damage theory and experimental phenomena. They consider that the destruction of concrete is actually the cumulative evolution course of the two meso-damage modes, rupture and yield. High temperature changes the mechanical performance in microstructure of concrete and the generation and propagation of microcracks. It could be described by adjusting the probability distributions which characterize the mesoscopic damage evolution. The damage constitutive model is employed to determine the stress-strain behaviour of concrete under uniaxial compression, and the calculated results are compared with the experimental results under different high temperature levels. Results indicate that the proposed model can not only predict the stress-strain behaviour with acceptable accuracy in macroscopic scale, but also reveal the damage evolution mechanism in mesoscopic scale. Finally, the constitutive behaviour under biaxial compression is also simulated to investigate the influence of high temperature on biaxial stress-strain behavior and strength envelope.

Macro- and Mesoscopic Design for Cabin Door Pretightened Fabric Rubber Seal Structure

The aviation fabric reinforced rubber seal structure is the key component of aircraft cabin seal and load transfer mechanism, and its performance directly determines the safety and reliability of high-performance aircraft. The inner and surface fabric rubber layers of the cladding are characterized by a macroscopic nonorthogonal anisotropic constitutive model and a representative volume element based on mesostructure, respectively. Compared with the conventional single/ring belt seal, this novel cladding/core type of seal involves the strong anisotropy; the pretightened assembly process; and the interaction of cladding/core, cladding/fixture, and core/fixture. The effectiveness of the macro- and mesoscopic analysis method is verified by experiments and numerical simulation. In addition, the effects of friction coefficients, pretightened displacement, and material orientations on the mechanical behaviors of the seal are also investigated. To our knowledge, this is the first systematic study on the cladding/core type of seal structures, and our results provide a valuable reference for the evaluation and optimization of aircraft seal in henceforth research.

Local ultra-densification of single-walled carbon nanotube films: Experiment and mesoscopic modeling

Fabrication of nanostructured metasurfaces poses a significant technological and fundamental challenge. Despite developing novel material systems that support reversible elongation and distortion, their nanoscale patterning and control of optical properties remain an open problem. Herein we report the atomic force microscope lithography application for nanoscale patterning of single-walled carbon nanotube films and the associated optical reflection coefficient tuning. Large scale mesoscopic distinct element method atomic force nanoindentation simulations of single-walled carbon nanotube samples comprising entangled dendritic nanotube bundles with branches extending down to individual tubes explain the mesoscale mechanism of local irreversible densification and further predict its impact on mechanical properties. All observed and calculated phenomena support each other and present a platform for developing patterned optical devices using nanofibrous matter.

Electroconvective instability near an ion-selective surface: A mesoscopic lattice Boltzmann study.

Direct numerical simulations of electroconvection instability near an ion-selective surface are conducted using a mesoscopic lattice Boltzmann method (LBM). An electrohydrodynamic model of ion transport and fluid flow is presented. We numerically solve the Poisson-Nernst-Planck equations for the electric field and the Navier-Stokes equations for the flow field. The results cover Ohmic, limiting, and overlimiting current regimes, and they are in good agreement with the asymptotic analytical solution for the relationship between current and voltage. The influences of different ion transport mechanisms on the voltage-current relationship are discussed. The results reveal that the electroconvection mechanism is as important as other ion transport mechanisms in electrohydrodynamic flow. By comparing the contribution of different regions in the numerical domain, we find that the flow in the extended space charge layer is dominated by electroconvection. We also study the influences of multiple driving parameters, and the electrohydrodynamic coupling constant plays a dominant role in triggering convective instability. The flow pattern and ion concentration distribution are described in detail. Moreover, the route of flow from steady state to periodic oscillation and then to chaos is discussed.

Multiparticle collision dynamics for ferrofluids.

Detailed studies of the intriguing field-dependent dynamics and transport properties of confined flowing ferrofluids require efficient mesoscopic simulation methods that account for fluctuating ferrohydrodynamics. Here, we propose such a new mesoscopic model for the dynamics and flow of ferrofluids, where we couple the multi-particle collision dynamics method as a solver for the fluctuating hydrodynamics equations to the stochastic magnetization dynamics of suspended magnetic nanoparticles. This hybrid model is validated by reproducing the magnetoviscous effect in Poiseuille flow, obtaining the rotational viscosity in quantitative agreement with theoretical predictions. We also illustrate the new method for the benchmark problem of flow around a square cylinder. Interestingly, we observe that the length of the recirculation region is increased, whereas the drag coefficient is decreased in ferrofluids when an external magnetic field is applied compared with the field-free case at the same effective Reynolds number. The presence of thermal fluctuations and the flexibility of this particle-based mesoscopic method provide a promising tool to investigate a broad range of flow phenomena of magnetic fluids, and the method could also serve as an efficient way to simulate solvent effects when colloidal particles are immersed in ferrofluids.

The calibration for many-body dissipative particle dynamics by using back-propagation neural networks

ABSTRACT The many-body dissipative particle dynamics (MDPD) is a promising mesoscopic method for solving various interfacial issues. However, an accurate mapping between simulation parameters and corresponding fluid properties is still ambiguous in MDPD due to its additional many-body interaction. In the present paper, we adopt the back-propagation Neural Network (BPNN) model with high-fidelity database as a rigorous calibration approach for MDPD. The relations between three main, simulation parameters (i.e. attractive and repulsive coefficient A,B and cut-off radius of repulsive force ) and four real-fluid static and dynamic properties (i.e. density, viscosity, self-diffusion coefficient and surface tension) are achieved accurately with the frame of BPNN. The influences of hyperparameters and training sets on mean squared errors (MSE) are also provided. Moreover, in order to improve the training efficiency of the model, we put forward three data selection methods: random data selection, extreme value data selection and the orthogonal experiment data selection. We compare three sampling methods for training data, and the orthogonal experiment design data selection is proved to be the most effective way to reduce MSE. The BPNN model is the potential to be a powerful tool for determining the simulation parameters within given fluid properties accurately and efficiently in the MDPD system.

A three-dimensional analysis of heat transfer based on mesoscopic method in nanoscale Si-MOSFET and Gr-FET

Thermal diffusion in the metal oxide semiconductor field effect transistor has received increased attention across a number of disciplines in recent years. This paper studies a three-dimensional (3D) heat conduction process in a MOSFET device based on Silicon (Si) and Graphene (Gr) materials. In order to perform analyses, a mesoscopic method was applied, based on lattice Boltzmann method (LBM) with D3Q15 model accounting the specularity parameter effects. The present study found that the maximal temperature is spotted at the interface whose value is 308.7 ​K and 324.5 ​K for the Gr-FET and Si-MOSFET, respectively, at t ​= ​30 ps and p ​= ​0.5. Also, the obtained results indicate that the specularity parameter has an important role in the phonon heat transport and thus in reducing the temperature in the nanotransistors. The preference of graphene device and the unique properties of graphene material make this material a good candidate for future nanoelectronics systems generation.

A two- and three-dimensional mesoscopic method for an updated non-homogeneous model of Newtonian and non-Newtonian nanofluids

A mesoscopic method based on a lattice Boltzmann method (LBM) for simulation of Newtonian and non-Newtonian nanofluids has been introduced. This investigation is a continuation of our recent study [G. H. R. Kefayati and A. Bassom, “A lattice Boltzmann method for single and two phase models of nanofluids: Newtonian and non-Newtonian nanofluids,” Phys. Fluids 33, 102008 (2021)], which proposed a two-dimensional LBM for a non-homogeneous model of nanofluids with Brownian diffusion and thermophoresis. Here, this model is improved by considering thermodynamic consistency, deposition rate, nanoparticle thermal dispersion, and hydrodynamic interactions around the nanoparticles, which are evaluated and reported in some thermodynamic and experimental observations. The proposed method is also developed for three-dimensional cases, applying all the above-mentioned elements. The revised macroscopic governing equations of mass (one for the carrier fluid and the other for the nanoparticles), momentum, and energy by considering the newly mentioned elements are presented, and then the proposed LBM, which has the ability to recover equations, is introduced while the derivations and proofs are provided. Different elements of the present code are validated with previous studies and demonstrated good agreement. To apply and evaluate the model in a case study, natural convection of Newtonian, shear-thinning, and viscoplastic nanofluids in a side-heated two-dimensional square enclosure and in a cubic cavity are investigated. The results for various volume fractions of nanofluids and Grashof numbers are shown in the formats of isotherms, streamlines, nanoparticle distributions, and local and average Nusselt numbers on the hot wall. In addition, the yielded/unyielded regions for viscoplastic nanofluids are defined and depicted.

Lattice Boltzmann simulation of binary three-dimensional droplet coalescence in a confined shear flow

Small-scale microscopic phenomena determine the behavior of large-scale droplets, which brings great challenges to accurately simulate the droplet coalescence process. In this paper, the mesoscopic lattice Boltzmann method based on the phase field theory is used to simulate the collision and coalescence of binary three-dimensional droplets in a confined shear flow. The numerical prediction of droplet coalescence behavior was first compared with the experimental result, and good agreement was reported. Then, we investigated the influences of a comprehensive range of capillary numbers (0.01≤Ca≤0.5) and Reynolds numbers (0.01≤Re≤10) on the shearing dynamics of binary droplets and also provided a quantitative description of droplet behavior in terms of the droplet deformation parameter and relative trajectory. A shearing regime diagram is further constructed based on the coupling effect of Ca and Re, which reveals three distinct types of droplet behaviors, including coalescence, breakup after the coalescence, and non-coalescence. Concretely, three different patterns of droplets can be completely captured with the variation of Ca at low Re; only two types of coalescence and non-coalescence can be observed for a medium Re, and two droplets just slide over each other without the occurrence of the coalescence when Re is sufficiently large. Also, we identified two critical capillary numbers in the lower Re region and one critical capillary number in the middle Re region, respectively, characterizing flow type transitions from the coalescence to breakup, from the breakup to the non-coalescence, and from the coalescence to the non-coalescence. It is found that all the capillary numbers decrease with Re.

Towards efficient and sustaining condensation via hierarchical meshed surfaces: A 3D LBM study

Condensation is of fundamental importance for a wide range of energy, environmental, and engineering applications. Extensive efforts have been made to boost droplet growth and condensation efficiency via delicately designing micro/nanostructured surfaces. However, simultaneously achieving rapid droplet growth and removal is still challenging. This study investigates the condensation on hierarchical mesh-covered surfaces employing the mesoscopic kinetic-based lattice Boltzmann method (LBM). The mechanism of dynamic growth and transport of droplets inside and outside the micro-pores is unraveled by resolving the heat transfer process and tracking the solid-liquid-vapor interactions. The proposed meshed surface realizes a robust self-refresh capability to clear the pinned droplets timely. The deterioration of hydrophobicity is avoided, contributing to a sustaining and prolonged dropwise condensation. The optimal case cuts down the droplet residence time and departure radius of 18% and 17% through rational design of mesh structures, respectively. Besides, the number of large droplets throughout the condensation process can also be reduced to different levels. The results can provide viable references to design various desirable meshed surfaces, facilitating efficient condensation in diverse engineering scenarios and applications.