Evolution of particle metrics in a buoyant aerosol cloud from explosive releases

Abstract

The detonation of high explosive (HE) material generates a cloud containing a high concentration of detonation products in the form of aerosol particles and gases. Modeling and simulation of aerosol metrics in an explosive cloud is a complex problem as it involves various processes such as chemical reaction, nucleation, volume expansion, and coagulation. Several models have been developed to study the atmospheric dispersion of these detonation products, but very few or no model is available to study the evolution of aerosol metrics at the early stage. In this work, we present a numerical model to simulate the temporal evolution of aerosol metrics in an expanding cloud by coupling transient thermodynamic properties with important microphysical processes. To illustrate the application, the numerical model is applied to a typical HE, and the aerosol particle properties such as size distribution, number concentration, and average size are estimated from the numerical results. These results will provide the essential input conditions for atmospheric dispersion models to estimate the atmospheric concentration and deposition of aerosol particles.

Copyright © 2020 American Association for Aerosol Research     

Reducing Statistical Noise and Extending the Size Spectrum by Applying Weighted Simulation Particles in Monte Carlo Simulation of Coagulation

The direct simulation Monte Carlo (DSMC) method is widely utilized to simulate microscopic dynamic processes in dispersed systems that give rise to the population balance equation. In conventional DSMC approaches, simulation particles are equally weighted, even for broad size distributions where number concentrations in different size intervals are significantly different. The resulting statistical noise and limited size spectrum severely restrict the application of these DSMC methods. This study proposes a new Monte Carlo (MC) method, the differentially weighted time-driven method, which captures the coagulation dynamics in dispersed systems with low noise and is simultaneously able to track the size distribution over the full size range. Key elements of this method include constructing a new jump Markov process based on a new coagulation rule for two differentially weighted simulation particles, and restricting the number of simulation particles in each size interval within prescribed bounds. The method is validated by using an ideal coagulation kernel with a known analytical solution and a real coagulation kernel for which an accurate solution can be found numerically (self-preserving particle size distribution in the continuum regime).     

Analysis of four Monte Carlo methods for the solution of population balances in dispersed systems

Monte Carlo (MC) constitutes an important class of methods for the numerical solution of the general dynamic equation (GDE) in particulate systems. We compare four such methods in a series of seven test cases that cover typical particulate mechanisms. The four MC methods studied are: time-driven direct simulation Monte Carlo (DSMC), stepwise constant-volume Monte Carlo, constant number Monte Carlo, and multi-Monte Carlo (MMC) method. These MC's are introduced briefly and applied numerically to simulate pure coagulation, breakage, condensation/evaporation (surface growth/dissolution), nucleation, and settling (deposition). We find that when run with comparable number of particles, all methods compute the size distribution within comparable levels of error. Because each method uses different approaches for advancing time, a wider margin of error is observed in the time evolution of the number and mass concentration, with event-driven methods generally providing better accuracy than time-driven methods. The computational cost depends on algorithmic details but generally, event-driven methods perform faster than time-driven methods. Overall, very good accuracy can be achieved using reasonably small numbers of simulation particles, O(10³), requiring computational times of the order 10²−10³ s on a typical desktop computer.     

凝并和冷凝/蒸发对颗粒尺度分布的影响

利用多重Monte Carlo算法对13种典型工况进行数值模拟,考察不同类型的凝并核和冷凝/蒸发核对多分散性颗粒尺度分布时间演变的影响。发现常凝并核要比线性和二次方凝并核对小颗粒的影响大一些、对大颗粒的影响小一些,线性和二次方凝并核对颗粒尺度分布的时间演变影响则取决于具体情况;常冷凝核要比线性冷凝核对小颗粒的影响大一些、对大颗粒的影响小一些;连续区布朗凝并核类似于常凝并核;扩散冷凝核对颗粒尺度分布的影响界于常冷凝核和线性冷凝核之间。     

Simulation of Aerosol Dynamics: A Comparative Review of Mathematical Models

A comparative review of mathematical models of aerosol dynamics is presented. Three approaches are considered that are based on continuous, discrete (sectional), and parametrized (lognormal) representations of the aerosol size distribution. Simulations of coagulation and diffusion-limited condensation are performed with these modeling approaches for three case studies typical of clear, hazy, and urban atmospheric aerosol concentrations. The relative accuracies and computational costs of models based on these approaches are compared. The models based on a continuous size distribution provide an accurate solution for both coagulation and condensation. Sectional approaches simulate coagulation very well but require a fine size resolution to minimize numerical diffusion in the simulation of condensation. The parametrized model based on log-normal modal size distributions is computationally efficient but tends to overestimate the rate of coagulation and the peak aerosol concentration resulting from condensational growth. The results of this study provide useful information for the selection of an aerosol model, depending on the accuracy requirements and computational constraints associated with a specific application.     

处理多分散颗粒凝并和冷凝/蒸发问题的多重Monte Carlo算法

提出一个新的多重Monte Carlo (MMC) 算法来求解同时考虑凝并和冷凝/蒸发的通用动力学方程 (GDE),该算法基于时间驱动, 模拟过程中保持模拟颗粒数目不变和计算区域体积不变. 描述了时间步长确定方法, 同时处理凝并和冷凝/蒸发的方案. 针对常凝并核和常冷凝核, 常凝并核和线性冷凝核, 线性凝并核和线性冷凝核三种特殊工况, MMC算法模拟了颗粒尺度分布函数的时间演变, 与理论分析解进行了比较, 表明MMC算法能解决普通Monte Carlo算法的计算精度和计算代价不能协调的矛盾, 具有较小的计算代价和较高的计算精度, 能够适用于工程应用.     

Simulation of Aerosol Dynamics: A Comparative Review of Algorithms Used in Air Quality Models

A comparative review of algorithms currently used in air quality models to simulate aerosol dynamics is presented. This review addresses coagula tion, condensational growth, nucleation, and gas particle mass transfer. Two major approaches are used in air quality models to represent the particle size distribution: (1) the sectional approach in which the size distribution is discretized into sections and particle properties are assumed to be constant over particle size sections and (2) the modal approach in which the size distribution is approxi mated by several modes and particle properties are assumed to be uniform in each mode. The sectional approach is accurate for coagulation and can reproduce the major characteristics of the evolution of the particle size distribution for condensa tional growth with the moving-center and hybrid algorithms. For coagulation and condensational growth, the modal approach provides more accurate results when the standard deviations of the modes are allowed to vary than it does when they are fixed. Predictions of H₂SO₄ nucleation rates are highly sensitive to environ mental variables and simulation of relative rates of condensation on existing particles and nucleation is a preferable approach. Explicit treatment of mass transfer is recommended for cases where volatile species undergo different equilib rium reactions in different particle size ranges (e.g., in the presence of coarse salt particles). The results of this study provide useful information for use in selecting algorithms to simulate aerosol dynamics in air quality models and for improving the accuracy of existing algorithms.     

Development and Validation of a Simple Numerical Model for Estimating Workplace Aerosol Size Distribution Evolution Through Coagulation,Settling, and Diffusion

Recent research has indicated that the toxicity of inhaled ultrafine particles may be associated with the size of discrete particles deposited in the lungs. However, it has been speculated that in some occupational settings rapid coagulation will lead to relatively low exposures to discrete ultrafine particles. Investigation of likely occupational exposures to ultrafine particles following the generation of aerosols with complex size distributions is most appropriately addressed using validated numerical models. A numerical model has been developed to estimate the size-distribution time-evolution of compact and fractal-like aerosols within workplaces resulting from coagulation, diffusional deposition, and gravitational settling. Good agreement has been shown with an analytical solution to lognormal aerosol evolution, indicating good compatibility with previously published models. Validation using experimental data shows reasonable agreement when assuming spherical particles and coalescence on coagulation. Assuming the formation of fractal-like particles within a range of diameters led to good agreement between modeled and experimental data. The model appears well suited to estimating the relationship between the size distribution of emitted well-mixed ultrafine aerosols, and the aerosol that is ultimately inhaled where diffusion loses are small.     

Modeling of the monomer role and the coalescence limitation in primary particle growth

The general dynamic equation (GDE) has been numerically solved to simulate the growth of ultrafine particles (UFPs) in a tubular aerosol reactor, approximating the particle size distribution by a lognormal function. The GDE includes all the terms describing diffusion, thermophoresis, nucleation, condensation and coagulation. We have also considered the efficiency of liquid-like coagulation to primary particles. The data calculated from our model were compared with those from the previous model and also with some experimental results from a TiO₂ UFP generator. The condensation term, which we split from a single coagulation term in the previous model, well described the monomer contribution to the particle growth. Introduction of one adjustable parameter, the efficiency of coagulation, was successful in limiting the growth of primary particles and fit the experimental data.     

Population Balance-Monte Carlo Simulation for Gas-to-Particle Synthesis of Nanoparticles

The process simulation of nanoparticle synthesis via the gas-phase method is essential to understanding the detailed dynamic evolution of nanoparticles within a very short time period under high temperature. The task is, however, very challengeable up to now as the conversion of the gaseous precursor to the end-use nanoparticle is a complex physicochemical process involving nucleation of the particulate phase, agglomeration between particles and sintering under industrial production conditions. In this article, we extended the differentially weighted Monte Carlo method for population balance to simulate the dynamic evolution of titania (TiO₂) nanoparticles synthesized by gas-to-particle conversion in a single aerosol reactor, considering simultaneous nucleation, agglomeration, and sintering. The simulated size distribution of TiO₂ agglomerate and primary particles produced by the thermal decomposition of titanium tetraisoproxide agreed well with the experimental data. In the simulation, the fast population balance-Monte Carlo method was utilized to accelerate the process simulation on a desktop PC. Results were obtained up to 178 times faster than that of a normal Monte Carlo method. The inhomogeneous internal structure of primary particles was considered through solving population balance of polydisperse primary particles within agglomerate. It was found the polydisperse model could predict the primary particle size distribution better. Simulation results revealed a complex competition relation among nucleation, agglomeration and sintering.

Copyright 2013 American Association for Aerosol Research     

MECCO: A method to estimate concentrations of condensing organics—Description and evaluation of a Markov chain Monte Carlo application

The development of a new method to estimate concentrations of condensing organics (MECCO) is described. A Markov chain Monte Carlo method is applied, and by using measured particle size distribution and random vapor concentrations as input, the predicted changes in particle population by an aerosol dynamics model are utilized. The method provides the ambient vapor concentrations required for the observed particle growth in particle number size distribution data, assuming all growth can be attributed to net condensation of super-saturated vapors. In this paper, MECCO was coupled with the UHMA box-model to provide aerosol dynamics. With few changes, MECCO could be applied to study other input parameters, and coupled with other dynamics models as well. Evaluation of the method was carried out with simulated output from the UHMA model using the assumption of three organic vapors, and MECCO-UHMA was able to estimate their concentrations with great accuracy. However, the condensation of vapors is currently considered irreversible, since the used particle size distribution data do not provide information on the composition of particles. The distinguishing between the vapors is based on few vapor parameters, which limits the possibilities of identifying actual vapors. An example of atmospheric application is also presented. This revealed the importance of quality control of the input particle concentrations: instrumental noise and changes in the observed air mass pose challenges for the presented method. Data need to be smoothed in a reasonable way so that the point-like measurements can be utilized, but also so that the important information on particle growth is conserved. MECCO is a useful tool to approximate vapor concentrations and may be applied to estimate vapor properties as well. However, a computationally efficient and physically accurate aerosol dynamics model is essential for MECCO's performance.     

Simulation of the influence of coarse mode particles on the properties of fine mode particles

The effects of coarse mode particles on aerosol dynamics with simultaneous processes are investigated by applying the modal approach. The Brownian coagulation and condensation processes are considered for an aerosol system with three modal aerosol distributions to simulate how the distribution changes when the coarse mode number concentration increases. Simulation results show that during the Brownian coagulation process, the number concentration in the nuclei and accumulation mode decrease due to inter-modal coagulation of the nuclei, accumulation and coarse modes particles. This inter-modal coagulation process is enhanced when the number concentration of the coarse mode increases, such as in dust storm events. It means that the coarse mode can influence on the nuclei and accumulation mode significantly, especially, when the number concentration of the coarse mode becomes large. For the case of gravitational coagulation, the intra-modal coagulation of coarse mode particles makes the number concentration to decrease, while the inter-modal gravitational coagulation between fine modes and coarse mode is negligible.     

A coupled CFD-Monte Carlo method for simulating complex aerosol dynamics in turbulent flows

A coupled computational fluid dynamics (CFD)-Monte Carlo method is presented to simulate complex aerosol dynamics in turbulent flows. A Lagrangian particle method-based probability density function (PDF) transport equation is formulated to solve the population balance equation (PBE) of aerosol particles. The formulated CFD-Monte Carlo method allows investigating the interaction between turbulence and aerosol dynamics and incorporating individual aerosol dynamic kernels as well as obtaining full particle size distribution (PSD). Several typical cases of aerosol dynamic processes including turbulent coagulation, nucleation and growth are studied and compared to the sectional method with excellent agreement. Coagulation in both laminar and turbulent flows is simulated and compared to demonstrate the effect of turbulence on aerosol dynamics. The effect of jet Reynolds (Re_j) number on aerosol dynamics in turbulent flows is fully investigated for each of the studied cases. The results demonstrate that Re_j number has significant impact on a single aerosol dynamic process (e.g., coagulation) and the simultaneous competitive aerosol dynamic processes in turbulent flows. This newly modified CFD-Monte Carlo/PDF method renders an efficient method for simulating complex aerosol dynamics in turbulent flows and provides a better insight into the interactions between turbulence and the full PSD of aerosol particles.

Copyright © 2017 American Association for Aerosol Research     

A One-Dimensional Model for Coagulation,Sintering, and Surface Growth of Aerosol Agglomerates

The size of the primary particles in aerosol agglomerates is determined in part by the interplay of surface growth, coagulation, and sintering. These processes are modelled by a one-dimensional (1-D) discrete-sectional model, DISGLOM2, which predicts the evolution of agglomerate and primary particle size distributions. DISGLOM2 is an extended version of DISGLOM (Rogak 1997), in which particles smaller than the "melting diameter" were assumed to sinter instantly while bigger particles did not sinter at all. Gradual sintering, "condensational obliteration" (whereby primary particles are lost during heavy surface growth), and diffusional wall deposition have been incorporated into DISGLOM2. Results from DISGLOM2 were comparable with those from 2-D sectional models, but DISGLOM2 was much faster. In addition, DISGLOM2 includes the effects of "condensation" of small spherical particles on large agglomerates, which were not modelled previously. The effect of condensation was shown to be significant at low temperature. DISGLOM2 was used to predict the primary particle diameter of titania particles generated by precursor reaction. By adding gradual sintering, the growth rate of agglomerate particles by coagulation was slightly decreased and the primary particle size considerably increased compared with the results given by DISGLOM. Although DISGLOM2 is an efficient model of the relevant physical processes, the predictions are sensitive to the kinetics of precursor reactions and particle sintering, which can be difficult to characterize in real experimental systems.     

Sizing Small Sulfuric Acid Particles with an Ultrafine Particle Condensation Nucleus Counter

The sizing capability of an ultrafine particle condensation nucleus counter (which uses butanol as the condensing fluid) equipped with pulse height analysis was evaluated in terms of particle composition for sulfuric acid aerosol and sulfuric acid aerosol to which gas-phase ammonia had been added. The response of the counter depended on composition for a range of particle sizes when the water partial pressure was low. For water partial pressures < 5 Torr and for particles > 4 nm in diameter, the response (pulse heights) of the instrument to particles of a given size was substantially different for sulfuric acid particles and those that were neutralized with ammonia. For water partial pressures > 5 Torr, however, neutralizing the particles with ammonia had little effect on pulse height distributions. For particles smaller than 4 nm diameter the pulse heights were insensitive to exposure to ammonia.     

Techniques for Dispersion of Microorganisms into Air

ABSTRACT

Many commercially available devices initially developed for dispersion of biologically inert particles have been adopted for aerosolization of microoganisms in laboratory settings. However, these dispersion devices are not always adequate for microbial particles, as they do not simulate natural release into air. Wet dispersion methods are appropriate for viruses and most bacteria, whereas dry methods are more suitable for most fungal and actinomycete spores. Characteristics of the resulting aerosol are dependent on the dispersing shear forces and the sensitivity and agglomeration of the tested microorganisms. Consequently, each microbial group may need a specific dispersion technique. The following devices have been developed and tested in this study: the bubbling aerosol disperser, the agar-tube disperser, and the swirling-flow disperser. Testing included the evaluation of both physical and microbiological characteristics of aerosolized microorganisms. Each of the dispersers has shown several advantages over commercially available ones. When used for the dispersion of bacteria from the liquid suspension, the bubbling aerosol disperser was found to produce considerably fewer amounts of microbial fragments and much lower levels of microbial metabolic injury than the commercially available Collison nebulizer. Fungal spores dispersed from their colonies by the agar-tube disperser were found to have a more stable aerosol concentration and a lower fraction of agglomerates than achievable by conventional powder dispersion. The swirling-flow dispersion technique was used for aerosolization of actinomycetes because the agar-tube disperser could not provide a stable concentration of these spores due to their smaller size. The tests have shown that new methods minimize the changes of properties of the microorganisms during their aerosolization in the laboratory.     

Numerical Simulation of the Conditioning of Volatile Particles in Laminar Flow Tube Reactors

The conditioning of aerosol particles to a predefined composition and size can be considered as a standard problem in aerosol technology. Quite often aerosols generated by dispersing diluted solutions are conditioned in a subsequent flow reactor.To make the design of such reactors easier, a computer model was developed to simulate the behavior of particles with a volatile component during their passage through the reactor. The model is based on the assumption that part of the surface of the reactor is covered with a layer of the requested activity of the volatile component whose fraction has to be adjusted. The diffusion to or from this surface and the corresponding change of the particle size and composition is calculated for each streamline of the flow on the basis of a laminar flow profile. At the moment data for the system H 2 O/H 2 SO 4 are implemented in the model, but an extension to other systems can easily be done. Circular as well as annular flow cross sections can be taken into account.     

OPTICAL PROPERTIES OF AEROSOLS

ABSTRACT

The evolution of small aerosol particles accompanying the combustion of straw for energy production is investigated. A sampling equipment specially designed for field measurements is described and characterized. The aerosol is studied by low-pressure cascade impactor and scanning mobility particle sizer, the particle morphology by transmission electron microscopy, and the chemical composition by energy dispersive x-ray analysis. The combustion gas contains 3–500 mg/Nm³ of submicron particles with a mean diameter of approximately 0.3 μm. The particles consist of almost pure potassium chloride and sulphate. The formation mechanism is analyzed by a theoretical simulation of the chemical reactions and the aerosol change during cooling of the flue gas. It is concluded that some sulphation of KC1 occurs in the gas phase although the sulphate concentration is much lower than predicted by an equilibrium assumption. The theoretical simulation proves that the fine mode particles can be formed by homogeneous nucleation of either KCl or K2SO₄ as the first step and further growth occurs by coagulation and diffusive condensation of both KC1 and K₄SO₄ on existing particles.