Mathematical modeling and simulations of stress mitigation by coating polycrystalline particles in lithium-ion batteries

A chemo-mechanical model is developed to investigate the effects on the stress development of the coating of polycrystalline Ni-rich LiNixMnyCo_(z)O_(2)(x≥0.8)(NMC)particles with poly(3,4-ethylenedioxythiophene)(PEDOT).The simulation results show that the coating of primary NMC particles significantly reduces the stress generation by efficiently accommodating the volume change associated with the lithium diffusion,and the coating layer plays roles both as a cushion against the volume change and a channel for the lithium transport,promoting the lithium distribution across the secondary particles more homogeneously.Besides,the lower stiffness,higher ionic conductivity,and larger thickness of the coating layer improve the stress mitigation.This paper provides a mathematical framework for calculating the chemo-mechanical responses of anisotropic electrode materials and fundamental insights into how the coating of NMC active particles mitigates stress levels.

On the energy conservation electrostatic particle-in-cell/Monte Carlo simulation: Benchmark and application to the radio frequency discharges

We benchmark and analyze the error of energy conservation （EC） scheme in particle-in-cell/Monte Carlo （PIC/MC） algorithms by simulating the radio frequency discharge. The plasma heating behaviors and electron distributing functions obtained by one-dimensional （1D） simulation are analyzed. Both explicit and implicit algorithms are checked. The results showed that the EC scheme can eliminated the self-heating with wide grid spacing in both cases with a small reduction of the accuracies. In typical parameters, the EC implicit scheme has higher precision than EC explicit scheme. Some ＂numerical cooling＂ behaviors are observed and analyzed. Some other errors are also analyzed. The analysis showed that the EC implicit scheme can be used to qualitative estimation of some discharge problems with much less computational resource cost without much loss of accuracies.

Sample size adaptive strategy for time-dependent Monte Carlo particle transport simulation

When multiphysics coupling calculations contain time-dependent Monte Carlo particle transport simulations, these simulations often account for the largest part of the calculation time, which is insufferable in certain important cases. This study proposes an adaptive strategy for automatically adjusting the sample size to fulfil more reasonable simulations. This is realized based on an extension of the Shannon entropy concept and is essentially different from the popular methods in timeindependent Monte Carlo particle transport simulations, such as controlling the sample size according to the relative error of a target tally or by experience. The results of the two models show that this strategy can yield almost similar results while significantly reducing the calculation time. Considering the efficiency, the sample size should not be increased blindly if the efficiency cannot be enhanced further. The strategy proposed herein satisfies this requirement.

Implicit electrostatic particle-in-cell/Monte Carlo simulation for the magnetized plasma:Algorithms and application in gas-inductive breakdown

An implicit electrostatic particle-in-cell/Monte Carlo （PIC/MC） algorithm is developed for the magnetized discharging device simulation. The inductive driving force can be considered. The direct implicit PIC algorithm （DIPIC） and energy conservation scheme are applied together and the grid heating can be eliminated in most cases. A tensor-susceptibility Poisson equation is constructed. Its discrete form is made up by a hybrid scheme in one-dimensional （1D） and two- dimensional （2D） cylindrical systems. A semi-coarsening multigrid method is used to solve the discrete system. The algorithm is applied to simulate the cylindrical magnetized target fusion （MTF） pre-ionization process and get qualitatively correct results. The potential application of the algorithm is discussed briefly.

Electromagnetic Particle-in-Cell Simulations of Electron Holes Formed During the Electron Two-Stream Instability

Previous electrostatic particle-in-cell （PIC） simulations have pointed out that elec- tron phase-space holes （electron holes） can be formed during the nonlinear evolution of the electron two-stream instability. The parallel cuts of the parallel and perpendicular electric field have bipolar and unipolar structures in these electron holes, respectively. In this study, two-dimensional （2D） electromagnetic PIC simulations are performed in the x - y plane to investigate the evolution of the electron two-stream instability, with the emphasis on the magnetic structures associated with these electron holes in different plasma conditions. In the simulations, the background magnetic field （Bo = Boer） is along the x direction. In weakly magnetized plasma （Ωe 〈ωpe, where Ωe and ωpe are the electron gyrofrequency and electron plasma frequency, respectively）, several 2D electron holes are formed. In these 2D electron holes, the parallel cut of the fluctuating magnetic field δBx and δBz has unipolar structures, while the fluctuating magnetic field δBy has bipolar structures. In strongly magnetized plasma （Ωe 〉 ωpe）, several quasi-lD electron holes are formed. The electrostatic whistler waves with streaked structures of Ey are excited. The fluctuating mag- netic field δBx and δBz also have streaked structures. The fluctuating magnetic field δBx and δBy are produced by the current in the z direction due to the electric field drift of the trapped elec- trons, while the fluctuating magnetic field δBz can be explained by the Lorentz transformation of a moving quasielectrostatic structure. The influences of the initial temperature anisotropy on the magnetic structures of the electron holes are also analyzed. The electromagnetic whistler waves are found to be excited in weakly magnetized plasma. However, they do not have any significant effects on the electrostatic structures of the electron holes.

Particle-in-cell simulation for effect of anode temperature on discharge characteristics of a Hall effect thruster

Propellant gas flow has an important impact on the ionization and acceleration process of Hall effect thrusters （HETs）. In this paper, a particle-in-cell numerical method is used to study the effect of the anode temperature, i.e., the flow speed of the propellant gas, on the discharge characteristics of a HET. The simulation results show that, no matter the magnitude of the discharge voltage, the calculated variation trends of performance parameters with the anode temperature are in good agreement with the experimental ones presented in the literature. Further mechanism analysis indicates that the magnitude of the electron temperature is responsible for the two opposing variation laws found under different discharge voltages. When the discharge voltage is low, the electron temperature is low, and so is the intensity of the propellant ionization; the variation of the thruster performance with the anode temperature is thereby determined by the variation of the neutral density that affects the propellant utilization efficiency. When the discharge voltage is high, the electron temperature is large enough to guarantee a high degree of the propellant utilization no matter the magnitude of the anode temperature. The change of the thruster performance with the anode temperature is thus dominated by the change of the electron temperature and consequently the electron-neutral collisions as well as the electron cross-field mobility that affect the current utilization efficiency.

Validation of the current and pressure coupling schemes with nonlinear simulations of TAE and analysis on the linear stability of tearing mode in the presence of energetic particles

Both current and pressure coupling schemes have been adopted in the hybrid kinetic–magnetohydrodynamic code CLT-K recently.Numerical equivalences between these two coupling schemes are strictly verified under different approximations.First,when considering only the perturbed distribution function of energetic particles(EPs),the equivalence can be proved analytically.Second,when both the variations of the magnetic field and the EP distribution function are included,the current and pressure coupling schemes numerically produce the same result in the nonlinear simulations.On this basis,the influences of co-/counter-passing and trapped EPs on the linear stabilities of the m/n=2/1 tearing mode(TM)have been investigated(where m and n represent the poloidal and toroidal mode numbers,respectively).The results of scanningβh of EPs show that the co-passing and trapped EPs are found to stabilize the TM,while the counter-passing EPs tend to destabilize the TM.The behind(de)stabilization mechanisms of the TM by EPs are carefully analyzed.Furthermore,after exceeding critical EP betas,the same branch of the high-frequency mode is excited by co-/counterpassing and trapped EPs,which is identified as the m/n=2/1 energetic particle mode.

An efficient non-iterative smoothed particle hydrodynamics fluid simulation method with variable smoothing length

In classical smoothed particle hydrodynamics(SPH)fluid simulation approaches,the smoothing length of Lagrangian particles is typically constant.One major disadvantage is the lack of adaptiveness,which may compromise accuracy in fluid regions such as splashes and surfaces.Attempts to address this problem used variable smoothing lengths.Yet the existing methods are computationally complex and non-efficient,because the smoothing length is typically calculated using iterative optimization.Here,we propose an efficient non-iterative SPH fluid simulation method with variable smoothing length(VSLSPH).VSLSPH correlates the smoothing length to the density change,and adaptively adjusts the smoothing length of particles with high accuracy and low computational cost,enabling large time steps.Our experimental results demonstrate the advantages of the VSLSPH approach in terms of its simulation accuracy and efficiency.

Effects of electron trapping on nonlinear electron-acoustic waves excited by an electron beam via particle-in-cell simulations

By performing one-dimensional particle-in-cell simulations, the nonlinear effects of electronacoustic(EA) waves are investigated in a multispecies plasma, whose constituents are hot electrons, cold electrons, and beam electrons with immobile neutralized positive ions. Numerical analyses have identified that EA waves with a sufficiently large amplitude tend to trap cold electrons. Because EA waves are dispersive, where the wave modes with different wavenumbers have different phase velocities, the trapping may lead to the mixing of cold electrons. The cold electrons finally get thermalized or heated. The investigation also shows that the excited EA waves give rise to a broad range of wave frequencies, which may be helpful for understanding the broadband-electrostatic-noise spectrum in the Earth’s auroral region.

Analysis of microwave propagation in a time-varying plasma slab with particle-in-cell simulations

Continuous microwave propagation through a time-varying plasma and frequency up-conversion has been demonstrated by particle-in-cell (PIC) simulation. In principle, it is possible to transform a 2.45 GHz source radiation to an arbitrary larger frequency radiation. The energy conversion is also obtained by the theoretical analysis and has been testified by PIC simulation. The source wave was propagating in a parallel plate waveguide locally filled with the ionized gas. In this paper we would discuss the effects of the rise time, the plasma length, the switching time and the collision frequency on the energy conversion, and the methods to improve the upshift wave energy are proposed. We also put forward the new concept of the critical values of the rise time and the source wave amplitude to provide a theoretical basis for the selection of parameters in the experiments.

Particle-in-cell/Monte Carlo simulation of filamentary barrier discharges

The plasma behavior of filamentary barrier discharges in helium is simulated using a twodimensional（2D） particle-in-cell/Monte Carlo model. Four different phases have been suggested in terms of the development of the discharge： the Townsend phase; the space-charge dominated phase; the formation of the cathode layer, and the extinguishing phase. The spatialtemporal evolution of the particle densities, velocities of the charged particles, electric fields, and surface charges has been demonstrated. Our simulation provides insights into the underlying mechanism of the discharge and explains many dynamical behaviors of dielectric barrier discharge（DBD） filaments.

Three-dimensional particle-in-cell method of simulating high power terahertz gyrotrons with planar structure

Based on analyzing the large-signal theory of the planar gyrotron, it is suggested that a simplified structure of the device is used for simulating this kind of device, with the working characteristics of the device kept unchanged, i.e., the same as those of the device with the original structure. Thus, the computational burden can be significantly reduced. Using the proposed method, we simulate a planar gyrotron with its simplified parameters by using the UNIPIC-3D code. Numerical results show that the working frequency, output power, and electron efficiency are respectively about 0.813 THz, 14 kW, and 21%.

Study of deep transportation and plugging performance of deformable gel particles in porous media

Deformable gel particles(DGPs) possess the capability of deep profile control and flooding. However, the deep migration behavior and plugging mechanism along their path remain unclear. Breakage, an inevitable phenomenon during particle migration, significantly impacts the deep plugging effect. Due to the complexity of the process, few studies have been conducted on this subject. In this paper, we conducted DGP flow experiments using a physical model of a multi-point sandpack under various injection rates and particle sizes. Particle size and concentration tests were performed at each measurement point to investigate the transportation behavior of particles in the deep part of the reservoir. The residual resistance coefficient and concentration changes along the porous media were combined to analyze the plugging performance of DGPs. Furthermore, the particle breakage along their path was revealed by analyzing the changes in particle size along the way. A mathematical model of breakage and concentration changes along the path was established. The results showed that the passage after breakage is a significant migration behavior of particles in porous media. The particles were reduced to less than half of their initial size at the front of the porous media. Breakage is an essential reason for the continuous decreases in particle concentration, size, and residual resistance coefficient. However, the particles can remain in porous media after breakage and play a significant role in deep plugging. Higher injection rates or larger particle sizes resulted in faster breakage along the injection direction, higher degrees of breakage, and faster decreases in residual resistance coefficient along the path. These conditions also led to a weaker deep plugging ability. Smaller particles were more evenly retained along the path, but more particles flowed out of the porous media, resulting in a poor deep plugging effect. The particle size is a function of particle size before injection, transport distance, and different injection parameters(injection rate or the diameter ratio of DGP to throat). Likewise, the particle concentration is a function of initial concentration, transport distance, and different injection parameters. These models can be utilized to optimize particle injection parameters, thereby achieving the goal of fine-tuning oil displacement.

Effect of Ellipsoidal Particle Shape on Tribological Properties of Lubricants Containing Nanoparticles

Adding nanoparticles can significantly improve the tribological properties of lubricants.However,there is a lack of understanding regarding the influence of nanoparticle shape on lubrication performance.In this work,the influence of diamond nanoparticles(DNPs)on the tribological properties of lubricants is investigated through friction experiments.Additionally,the friction characteristics of lubricants regarding ellipsoidal particle shape are investigated using molecular dynamics(MD)simulations.The results show that DNPs can drastically lower the lubricant's friction coefficientμfrom 0.21 to 0.117.The shearing process reveals that as the aspect ratio(α)of the nanoparticles approaches 1.0,the friction performance improves,and wear on the wall diminishes.At the same time,the shape of the nanoparticles tends to be spherical.When 0.85≤α≤1.0,rolling is ellipsoidal particles'main form of motion,and the friction force changes according to a periodic sinusoidal law.In the range of 0.80≤α<0.85,ellipsoidal particles primarily exhibit sliding as the dominant movement mode.Asαdecreases within this range,the friction force progressively increases.The friction coefficientμcalculated through MD simulation is 0.128,which is consistent with the experimental data.

Influence of syngas components and ash particles on the radiative heat transfer in a radiant syngas cooler

Radiant syngas cooler(RSC)is widely used as a waste heat recovery equipment in industrial gasification.In this work,an RSC with radiation screens is established and the impact of gaseous radiative property models,gas components,and ash particles on heat transfer is investigated by the numerical simulation method.Considering the syngas components and the pressure environment of the RSC,a modified weighted-sum-of-gray-gases model was developed.The modified model shows high accuracy in validation.In computational fluid dynamics simulation,the calculated steam production is only 0.63%in error with the industrial data.Compared with Smith's model,the temperature decay along the axial direction calculated by the modified model is faster.Syngas components are of great significance to heat recovery capacity,especially when the absorbing gas fraction is less than 10%.After considering the influence of particles,the outlet temperature and the proportion of radiative heat transfer are less affected,but the difference in steam output reaches 2.7 t·h^(-1).The particle deposition on the wall greatly reduces the heat recovery performance of an RSC.

Particle size spatial distribution in landslide dams

The particle composition and spatial distribution of landslide-induced dam bodies are critical geotechnical parameters for studying the hazards of dam-break floods.However,current research often neglects the influence of the initial particle composition and spatial distribution of the landslide on the particle composition and spatial distribution of the landslide dam.This study investigated the impact of initial particle size distribution,volume,and sliding length on the energy and velocity changes of characteristic particles during the sliding process and the spatial distribution of particle sizes in the landslide dam body.Numerical simulations and physical models were employed to examine the effects of sequential gradient arrangements(where particle sizes decrease from top to bottom)and four other different initial particle arrangements on the energy and velocity changes of particles and the spatial distribution of particle sizes in the dam body.The study reveals the characteristics of translational and rotational energy of different particles and the laws of mechanical energy conversion,obtaining the spatial distribution patterns of particle sizes in landslide-induced dams.The results show that under the sequential gradient arrangement,the energy dissipation of the landslide movement is lower,with larger particles mainly distributed at the distal end and smaller particles at the proximal end of the landslide dam.In contrast,under the reverse gradient arrangement,the energy dissipation of the landslide movement is higher,and the distribution pattern of the dam particles is opposite to that of the sequential gradient arrangement.For the other arrangement modes,the spatial distribution of dam particles falls between the aforementioned two.There is a positive correlation between particle size and translational kinetic energy within the particle flow during the landslide process,and rotational motion increases energy dissipation.Under constant slope conditions,sliding length does not affect the movement pattern of the particle flow or the spatial distribution of particles in the dam body.The findings of this study provide a scientific basis for the accurate simulation and prediction of dam-break flood processes.

Modeling analysis of cobalt-based Fischer-Tropsch catalyst particles

The influences of particle size,shape,and catalyst distribution on the reactivity and hydrocarbon product selectivity of a cobalt-based catalyst for Fischer-Tropsch synthesis were investigated in the present work.A self-consistent kinetic model for Fischer-Tropsch reaction proposed here was found to correlate experimental data well and hence was used to describe the consumption rates of reactants and formation rates of hydrocarbon products.The perturbed-chain statistical associating fluid theory equation of state was used to describe vapor-liquid equilibrium behavior associated with Fischer-Tropsch reaction.Local interaction between intraparticle diffusion and Fischer-Tropsch reaction was investigated in detail.Results showed that in order to avoid the adverse influence of intraparticle diffusional limitations on catalyst reactivity and product selectivity,the use of small particles is necessary.Large eggshell spherical particles are shown to keep the original catalyst reactivity and enhance the selectivity of heavy hydrocarbon products.The suitable layer thickness for a spherical particle with a diameter of 2 mm is nearly 0.15 mm.With the same outer diameter of 2 mm,the catalyst reactivity and heavy product selectivity of hollow cylindrical particles with a layer thickness of 0.25 mm are found to be larger than eggshell spherical particles.From the viewpoint of catalytic performance,hollow cylindrical particles are a better choice for industrial applications.

Location and Capacity Determination Method of Electric Vehicle Charging Station Based on Simulated Annealing Immune Particle Swarm Optimization

As the number of electric vehicles(EVs)continues to grow and the demand for charging infrastructure is also increasing,how to improve the charging infrastructure has become a bottleneck restricting the development of EVs.In other words,reasonably planning the location and capacity of charging stations is important for development of the EV industry and the safe and stable operation of the power system.Considering the construction and maintenance of the charging station,the distribution network loss of the charging station,and the economic loss on the user side of the EV,this paper takes the node and capacity of charging station planning as control variables and the minimum cost of system comprehensive planning as objective function,and thus proposes a location and capacity planning model for the EV charging station.Based on the problems of low efficiency and insufficient global optimization ability of the current algorithm,the simulated annealing immune particle swarm optimization algorithm(SA-IPSO)is adopted in this paper.The simulated annealing algorithm is used in the global update of the particle swarm optimization(PSO),and the immune mechanism is introduced to participate in the iterative update of the particles,so as to improve the speed and efficiency of PSO.Voronoi diagram is used to divide service area of the charging station,and a joint solution process of Voronoi diagram and SA-IPSO is proposed.By example analysis,the results show that the optimal solution corresponding to the optimisation method proposed in this paper has a low overall cost,while the average charging waiting time is only 1.8 min and the charging pile utilisation rate is 75.5%.The simulation comparison verifies that the improved algorithm improves the operational efficiency by 18.1%and basically does not fall into local convergence.

Refinement of Adaptive Dynamical Simulation of Quantum Mechanical Double Slit Interference Phenomenon

We applied adaptive dynamics to double slit interference phenomenon using particle model and obtained partial successful results in our previous report. The patterns qualitatively corresponded well with experiments. Several properties such as concave single slit pattern and large influence of slight displacement of the emission position were different from the experimental results. In this study we tried other slit conditions and obtained consistent patterns with experiments. We do not claim that the adaptive dynamics is the principle of quantum mechanics, but the present results support the probability of adaptive dynamics as the candidate of the basis of quantum mechanics. We discuss the advantages of the adaptive dynamical view for foundations of quantum mechanics.

Cascade refrigeration system synthesis based on hybrid simulated annealing and particle swarm optimization algorithm

Cascade refrigeration system(CRS)can meet a wider range of refrigeration temperature requirements and is more energy efficient than single-refrigerant refrigeration system,making it more widely used in low-temperature industry processes.The synthesis of a CRS with simultaneous consideration of heat integration between refrigerant and process streams is challenging but promising for significant cost saving and reduction of carbon emission.This study presented a stochastic optimization method for the synthesis of CRS.An MINLP model was formulated based on the superstructure developed for the CRS,and an optimization framework was proposed,where simulated annealing algorithm was used to evolve the numbers of pressure/temperature levels for all sub-refrigeration systems,and particle swarm optimization algorithm was employed to optimize the continuous variables.The effectiveness of the proposed methodology was verified by a case study of CRS optimization in an ethylene plant with 21.89%the total annual cost saving.