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The purpose of this paper is to develop new types of direct expansion method of moments (DEMM) by using the n/3th moments for simulating nanoparticle Brownian coagulation in the free molecule regime. The feasibilities of new proposed DEMMs with n/3th moments are investigated to describe the evolution of aerosol size distribution, and some of the models will be applied to further simulation of physical processes.

The accuracy and efficiency of some kinds of methods of moments are mainly compared including the quadrature method of moments (QMOM), Taylor-expansion method of moments (TEMOM), the log-normal preserving method of moments proposed by Lee (LMM) and the derived DEMM in this paper. QMOM with 12 quadrature approximation points is taken as a reference to evaluate other methods.

The newly derived models, namely DEMM(4/3,4) and DEMM(2,6), as well as the previous DEMM(2,4), are considered to be qualified models due to their high accuracy and efficiency. They are confirmed to be valid and alternative models to describe the evolution of aerosol size distribution for particle dynamical process involving the n/3th moments.

The n/3th moments, which have clear physical interpretations when n stands for first several integers, are first introduced in the DEMM method for simulating nanoparticle Brownian coagulation in the free molecule regime.

The original v2-based sectional method assumes that the selected property quantity of particles is uniformly distributed in each section, which makes particle size distribution (PSD) fluctuate dramatically in the entire size range. The number concentration in each section as well as the zeroth moment of PSD also cannot be correctly predicted in case there are not enough sections used in calculation. In order to provide a more appropriate representation of PSD, different approximate models are used to close the conservation equations. The paper aims to discuss these issues.

The uniform distribution of the selected property quantity of particles in each section is not necessarily satisfied. Instead, the distribution is approximated using an expression with an approximation factor. Different models are investigated on recovering the initial size distribution and predicting the time evolution of size distribution as well as the first three moments so that the advantages and disadvantages of each model can be compared.

The approximate model with an approximation factor of 0.8 is capable of predicting the time evolution of the zeroth moment accurately no matter how many sections are used in simulations. The original v2-based model is recommended to calculate the first and second moments as long as the section number is larger than 50, otherwise, the model with an approximation factor of 0.15 would be a preferred choice.

Different approximate models can be used to improve the accuracy of the results supposing we know which moment is of great importance in calculation.

The purpose of this paper is to study nanoparticles diffusion and coagulation processes in a twin-jet.

Large eddy simulation (LES) and Taylor-series expansion moment method (TEMOM) are employed to deal with a nanoparticle-laden twin-jet flow.

The numerical results show that the interaction of the two jets and turbulence eddy structures rolling-up, paring and shedding in flow sharply affects particles number concentration. Particle diameter grows quickly at the interfaces of jets. Coagulation shows more obvious effect at initial stage than that in the subsequent period. Then diffusion makes the particle diameter distribution much more uniform.

In recent years a great number of attentions have been focussed on the issue of particulate dynamics processes including diffusion, coagulation and deposition, etc. However, up to now few works have been focus on the nanoparticles coagulation and dispersion in turbulent flows. The investigation on the diffusion and coagulation process of nanoparticles using TEMOM in a twin-jet flow has not been found.

The purpose of this study is to present a newly proposed and developed sorting algorithm-based merging weighted fraction Monte Carlo (SAMWFMC) method for solving the population balance equation for the weighted fraction coagulation process in aerosol dynamics with high computational accuracy and efficiency.

In the new SAMWFMC method, the jump Markov process is constructed as the weighted fraction Monte Carlo (WFMC) method (Jiang and Chan, 2021) with a fraction function. Both adjustable and constant fraction functions are used to validate the computational accuracy and efficiency. A new merging scheme is also proposed to ensure a constant-number and constant-volume scheme.

The new SAMWFMC method is fully validated by comparing with existing analytical solutions for six benchmark test cases. The numerical results obtained from the SAMWFMC method with both adjustable and constant fraction functions show excellent agreement with the analytical solutions and low stochastic errors. Compared with the WFMC method (Jiang and Chan, 2021), the SAMWFMC method can significantly reduce the stochastic error in the total particle number concentration without increasing the stochastic errors in high-order moments of the particle size distribution at only slightly higher computational cost.

The WFMC method (Jiang and Chan, 2021) has a stringent restriction on the fraction functions, making few fraction functions applicable to the WFMC method except for several specifically selected adjustable fraction functions, while the stochastic error in the total particle number concentration is considerably large. The newly developed SAMWFMC method shows significant improvement and advantage in dealing with weighted fraction coagulation process in aerosol dynamics and provides an excellent potential to deal with various fraction functions with higher computational accuracy and efficiency.

A study on convective aspects was carried out on a Couette flow in an irregular channel by applying a constant uniform magnetic field parallel to the channel flow.

The dynamic study of such a flow resulted in highly nonlinear coupled partial differential equations. To solve these partial differential equations analytically, regular perturbation method was invoked for velocity, temperature and concentration with a combined parameter of Soret and Forchheimer. The numerical computational results have been extracted for various nondimensional parameters with regard to fluid and particle flow as well as for temperature and solute concentration.

The current article presents a novel approach to assess the effects of drag force as well as the diffusion-based interactions between the velocity, temperature and concentrations with the aid of Soret and Dufour on two-dimensional MHD mixed with a dusty viscoelastic fluid.

The results found are in good agreement with the earlier studies in the absence of nonlinear effect of Forchheimer model.

The purpose of this study is to investigate the aerosol dynamics of the particle coagulation process using a newly developed weighted fraction Monte Carlo (WFMC) method.

The weighted numerical particles are adopted in a similar manner to the multi-Monte Carlo (MMC) method, with the addition of a new fraction function (α). Probabilistic removal is also introduced to maintain a constant number scheme.

Three typical cases with constant kernel, free-molecular coagulation kernel and different initial distributions for particle coagulation are simulated and validated. The results show an excellent agreement between the Monte Carlo (MC) method and the corresponding analytical solutions or sectional method results. Further numerical results show that the critical stochastic error in the newly proposed WFMC method is significantly reduced when compared with the traditional MMC method for higher-order moments with only a slight increase in computational cost. The particle size distribution is also found to extend for the larger size regime with the WFMC method, which is traditionally insufficient in the classical direct simulation MC and MMC methods. The effects of different fraction functions on the weight function are also investigated.

Stochastic error is inevitable in MC simulations of aerosol dynamics. To minimize this critical stochastic error, many algorithms, such as MMC method, have been proposed. However, the weight of the numerical particles is not adjustable. This newly developed algorithm with an adjustable weight of the numerical particles can provide improved stochastic error reduction.

The purpose of this paper is to create a computationally efficient reduced model (RM) for the moments of droplet size distribution (DSD) in condensing flow.

The kinetic equation (KE) exactly describes the time dependence of the DSD and can be regarded as the most rigorous representation of a system with condensation. Because of the typical wide range in droplet size, the KE requires excessive computational time and is not attractive for most practical applications. To reduce the overall computational efforts, a novel set of moment equations, derived from the KE has been proposed.

To demonstrate the simplicity and accuracy of the model, the authors employ a typical nucleation pulse experiment for which benchmark KE-solutions have also been computed. Comparison of predicted moments from both the RM and the KE approach reveals that the RM is capable of capturing the evolving feature of moments with reasonable accuracy.

The authors have created a novel reduced method for numerical computations of the lower-order moments of the DSD in condensing flow. Unlike the typical method of moments, the RM eliminates the need for assumptions on the shape of the distribution function and could estimate the moments at very low computational cost.

The purpose of this paper is to study the complex aerosol dynamic processes by using this newly developed stochastically weighted operator splitting Monte Carlo (SWOSMC) method.

Stochastically weighted particle method and operator splitting method are coupled to formulate the SWOSMC method for the numerical simulation of particle-fluid systems undergoing the complex simultaneous processes.

This SWOSMC method is first validated by comparing its numerical simulation results of constant rate coagulation and linear rate condensation with the corresponding analytical solutions. Coagulation and nucleation cases are further studied whose results are compared with the sectional method in excellent agreement. This SWOSMC method has also demonstrated its high numerical simulation capability when used to deal with simultaneous aerosol dynamic processes including coagulation, nucleation and condensation.

There always exists conflict and tradeoffs between computational cost and accuracy for Monte Carlo-based methods for the numerical simulation of aerosol dynamics. The operator splitting method has been widely used in solving complex partial differential equations, while the stochastic-weighted particle method has been commonly used in numerical simulation of aerosol dynamics. However, the integration of these two methods has not been well investigated.

The purpose of this paper is to study the evolution and growth of aerosol particles in a turbulent planar jet by using the newly developed large eddy simulation (LES)-differentially weighted operator splitting Monte Carlo (DWOSMC) method.

The DWOSMC method is coupled with LES for the numerical simulation of aerosol dynamics in turbulent flows.

Firstly, the newly developed and coupled LES-DWOSMC method is verified by the results obtained from a direct numerical simulation-sectional method (DNS-SM) for coagulation occurring in a turbulent planar jet from available literature. Then, the effects of jet temperature and Reynolds number on the evolution of time-averaged mean particle diameter, normalized particle number concentration and particle size distributions (PSDs) are studied numerically on both coagulation and condensation processes. The jet temperature and Reynolds number are shown to be two important parameters that can be used to control the evolution and pattern of PSD in an aerosol reactor.

The coupling between the Monte Carlo method and turbulent flow still encounters many technical difficulties. In addition, the relationship between turbulence, particle properties and collision kernels of aerosol dynamics is not yet well understood due to the theoretical limitations and experimental difficulties. In the present study, the developed and coupled LES-DWOSMC method is capable of solving the aerosol dynamics in turbulent flows.

The purpose of this paper is to use comprehensive model to investigate the effects of particle physical properties on in-flight nano-particles behavior for the radio frequency suspension plasma spray.

In this paper, both the effects thermal properties of solvent and solid particle on the evolution of particle size, velocity and temperature are discussed. Besides, the numerical analysis is also conducted to investigate the influences of particle physical properties on the characteristic distributions of particles for poly-disperse cases.

Results show the thermal properties of solvent have critical effects on the discharged point of the solid particles, but little influence on the final particle velocity and size, as well as their distributions. The final state of particle temperature is mainly determined by the solid particle thermal properties, especially depending on the boiling point.

Most of the former studies took the experimental approaches and mainly focussed on the operating conditions effects. While beyond the operating conditions, the variety of particle physical and thermal properties also has strong effect on particle heating performance.