Modeling subfilter soot-turbulence interactions in Large Eddy Simulation: An a priori study

A new LES model for subfilter soot-turbulence interactions is developed based on an a priori analysis using large-scale DNS data of temporally evolving non premixed n-heptane jet flames at a jet Reynolds number of 15,000. In this work, soot formation is modeled in LES by solving explicit transport equations for soot moments, and the unclosed filtered soot moment source terms are closed by a presumed PDF approach. Due to the strong intermittency of soot fields, a previous modeling approach assumes the presumed PDF to be bimodal accounting for sooting and non-sooting subfilter regions but neglects any sub-structure of the soot distribution. In this work, the modeling framework is improved by a new presumed PDF model that explicitly accounts for the sub-structure of the sooting mode, which is modeled by a log-normal distribution. The previous and new models are assessed by means of their prediction of the filtered source terms and the filtered intermittency, and the log-normal distribution is found to significantly reduce modeling errors, in particular, for the coagulation source term. Introducing a log-normal distribution for the PDF of the sooting mode involves a large amount of additional model parameters, such as the width of the distribution and correlation coefficients among different soot moments, so model assumptions to reduce the number of model parameters are discussed by means of the DNS data. The conclusions are found to be robust with respect to a variation in the global Damköhler number in the DNS datasets. The final model formulation only requires solving two additional transport equations in LES compared to previous models, while significantly improved model predictions are obtained for the coagulation source term which is import for predicting the number of soot particles.     

The verification of the Taylor-expansion moment method for the nanoparticle coagulation in the entire size regime due to Brownian motion

The closure of moment equations for nanoparticle coagulation due to Brownian motion in the entire size regime is performed using a newly proposed method of moments. The equations in the free molecular size regime and the continuum plus near-continuum regime are derived separately in which the fractal moments are approximated by three-order Taylor-expansion series. The moment equations for coagulation in the entire size regime are achieved by the harmonic mean solution and the Dahneke??s solution. The results produced by the quadrature method of moments (QMOM), the Pratsinis??s log-normal moment method (PMM), the sectional method (SM), and the newly derived Taylor-expansion moment method (TEMOM) are presented and compared in accuracy and efficiency. The TEMOM method with Dahneke??s solution produces the most accurate results with a high efficiency than other existing moment models in the entire size regime, and thus it is recommended to be used in the following studies on nanoparticle dynamics due to Brownian motion.     

自由分子区布朗凝并作用下的颗粒尺寸分布变化

对于燃烧过程中生成的亚微米颗粒,其一次颗粒的长大过程主要是通过碰撞凝并实现的。本文通过对颗粒的初始分布作出一个合理的正态对数分布的假设,运用矩方法(Moment Method)研究了自由分子区的颗粒在布朗碰撞作用下的颗粒尺寸分布的变化情况。所得到的长时间碰撞凝并结果符合布朗碰撞凝并过程的自保持特性。数值结果还表明,颗粒初始的宽粒径分布会显著提高粒子云的在凝并初期的凝并速率和生成粒子的平均直径,且最终生成的粒子尺寸都是宽分布的。这说明在预报微细颗粒的迁移和长大过程中有必要考虑粒子的宽分布特性。     

The collision efficiency of spherical dioctyl phthalate aerosol particles in the Brownian coagulation

The collision efficiency in the Brownian coagulation is investigated. A new mechanical model of collision between two identical spherical particles is proposed, and a set of corresponding collision equations is established. The equations are solved numerically, thereby obtaining the collision efficiency for the monodisperse dioctyl phthalate spherical aerosols with diameters ranging from 100 to 760 nm in the presence of van der Waals force and the elastic deformation force. The calculated collision efficiency, in agreement with the experimental data qualitatively, decreases with the increase of particle diameter except a small peak appearing in the particles with a diameter of 510 nm. The results show that the interparticle elastic deformation force cannot be neglected in the computation of particle Brownian coagulation. Finally, a set of new expressions relating collision efficiency to particle diameter is established.     

Multiplicative processes and power laws in human reaction times derived from hyperbolic functions

In sensory psychophysics reaction time is a measure of the stochastic latency elapsed from stimulus presentation until a sensory response occurs as soon as possible. A random multiplicative model of reaction time variability is investigated for generating the reaction time probability density functions. The model describes a generic class of hyperbolic functions by Piéron?s law. The results demonstrate that reaction time distributions are the combination of log-normal with power law density functions. A transition from log-normal to power law behavior is found and depends on the transfer of information in neurons. The conditions to obtain Zipf?s law are analyzed.     

Second-order conditional moment closure modeling of a turbulent CH4/H2/N2 jet diffusion flame

The second-order CMC model for a detailed chemical mechanism is used to model a turbulent CH₄/H₂/N₂ jet diffusion flame. Second-order corrections are made to the three rate limiting steps of methane–air combustion, while first-order closure is employed for all the other steps. Elementary reaction steps have a wide range of timescales with only a few of them slow enough to interact with turbulent mixing. Those steps with relatively large timescales require higher-order correction to represent the effect of fluctuating scalar dissipation rates. Results show improved prediction of conditional mean temperature and mass fractions of OH and NO. Major species are not much influenced by second-order corrections except near the nozzle exit. A parametric study is performed to evaluate the effects of the variance parameter in log-normal scalar dissipation PDF and the constants for the dissipation term in conditional variance and covariance equations.     

Finite-size scaling studies of one-dimensional reaction-diffusion systems. Part I. Analytical results

We consider two single-species reaction-diffusion models on one-dimensional lattices of lengthL: the coagulation-decoagulation model and the annihilation model. For the coagulation model the system of differential equations describing the time evolution of the empty interval probabilities is derived for periodic as well as for open boundary conditions. This system of differential equations grows quadratically withL in the latter case. The equations are solved analytically and exact expressions for the concentration are derived. We investigate the finite-size behavior of the concentration and calculate the corresponding scaling functions and the leading corrections for both types of boundary conditions. We show that the scaling functions are independent of the initial conditions but do depend on the boundary conditions. A similarity transformation between the two models is derived and used to connect the corresponding scaling functions.     

A Model for Coagulation with Mating

We consider in this work a model for aggregation, where the coalescing particles initially have a certain number of potential links (called arms) which are used to perform coagulations. There are two types of arms, male and female, and two particles may coagulate only if one has an available male arm, and the other has an available female arm. After a coagulation, the used arms are no longer available. We are interested in the concentrations of the different types of particles, which are governed by a modification of Smoluchowski’s coagulation equation—that is, an infinite system of nonlinear differential equations. Using generating functions and solving a nonlinear PDE, we show that, up to some critical time, there is a unique solution to this equation. The Lagrange Inversion Formula allows in some cases to obtain explicit solutions, and to relate our model to two recent models for limited aggregation. We also show that, whenever the critical time is infinite, the concentrations converge to a state where all arms have disappeared, and the distribution of the masses is related to the law of the size of some two-type Galton-Watson tree. Finally, we consider a microscopic model for coagulation: we construct a sequence of Marcus-Lushnikov processes, and show that it converges, before the critical time, to the solution of our modified Smoluchowski’s equation.     

The Becker–Döring Process: Pathwise Convergence and Phase Transition Phenomena

In this note, we study an infinite reaction network called the stochastic Becker–Döring process, a sub-class of the general coagulation–fragmentation models. We prove pathwise convergence of the process towards the deterministic Becker–Döring equations which improves classical tightness-based results. Also, we show by studying the asymptotic behavior of the stationary distribution, that the phase transition property of the deterministic model is also present in the finite stochastic model. Such results might be interpreted closed to the so-called gelling phenomena in coagulation models. We end with few numerical illustrations that support our results.

     

Maximum entropy formalism,fractals, scaling phenomena,and 1/f noise: A tale of tails

In this report on examples of distribution functions with long tails we (a) show that the derivation of distributions with inverse power tails from a maximum entropy formalism would be a consequence only of an unconventional auxilliary condition that involves the specification of the average value of a complicated logarithmic function, (b) review several models that yield log-normal distributions, (c) show that log normal distributions may mimic 1/f noise over a certain range, and (d) present an amplification model to show how log-normal personal income distributions are transformed into inverse power (Pareto) distributions in the high income range.     

Coarse-grained computation for particle coagulation and sintering processes by linking Quadrature Method of Moments with Monte-Carlo

The study of particle coagulation and sintering processes is important in a variety of research studies ranging from cell fusion and dust motion to aerosol formation applications. These processes are traditionally simulated using either Monte-Carlo methods or integro-differential equations for particle number density functions. In this paper, we present a computational technique for cases where we believe that accurate closed evolution equations for a finite number of moments of the density function exist in principle, but are not explicitly available. The so-called equation-free computational framework is then employed to numerically obtain the solution of these unavailable closed moment equations by exploiting (through intelligent design of computational experiments) the corresponding fine-scale (here, Monte-Carlo) simulation. We illustrate the use of this method by accelerating the computation of evolving moments of uni- and bivariate particle coagulation and sintering through short simulation bursts of a constant-number Monte-Carlo scheme.     

Implementation of an advanced fixed sectional aerosol dynamics model with soot aggregate formation in a laminar methane/air coflow diffusion flame

An advanced fixed sectional aerosol dynamics model describing the evolution of soot particles under simultaneous nucleation, coagulation, surface growth and oxidation processes is successfully implemented to model soot formation in a two-dimensional laminar axisymmetric coflow methane/air diffusion flame. This fixed sectional model takes into account soot aggregate formation and is able to provide soot aggregate and primary particle size distributions. Soot nucleation, surface growth and oxidation steps are based on the model of Fairweather et al. Soot equations are solved simultaneously to ensure convergence. The numerically calculated flame temperature, species concentrations and soot volume fraction are in good agreement with the experimental data in the literature. The structures of soot aggregates are determined by the nucleation, coagulation, surface growth and oxidation processes. The result of the soot aggregate size distribution function shows that the aggregate number density is dominated by small aggregates while the aggregate mass density is generally dominated by aggregates of intermediate size. Parallel computation with the domain decomposition method is employed to speed up the calculation. Three different domain decomposition schemes are discussed and compared. Using 12 processors, a speed-up of almost 10 is achieved which makes it feasible to model soot formation in laminar coflow diffusion flames with detailed chemistry and detailed aerosol dynamics.     

Laser-induced incandescence for soot-particle sizing at elevated pressure

This paper describes the applicability of laser-induced incandescence (LII) as a measurement technique for primary soot particle sizes at elevated pressure. A high-pressure burner was constructed that provides stable, laminar, sooting, premixed ethylene/air flames at 1–10 bar. An LII model was set up that includes different heat-conduction sub-models and used an accommodation coefficient of 0.25 for all pressures studied. Based on this model experimental time-resolved LII signals recorded at different positions in the flame were evaluated with respect to the mean particle diameter of a log-normal particle-size distribution. The resulting primary particle sizes were compared to results from TEM images of soot samples that were collected thermophoretically from the high-pressure flame. The LII results are in good agreement with the mean primary particle sizes of a log-normal particle-size distribution obtained from the TEM-data for all pressures, if the LII signals are evaluated with the heat-conduction model of Fuchs combined with an aggregate sub-model that describes the reduced heat conduction of aggregated primary soot particles. The model, called LIISim, is available online via a web interface. PACS 65.80.+n; 78.20.Nv; 42.62.-b; 47.70.Pq     

The Structure of Typical Clusters in Large Sparse Random Configurations

The initial purpose of this work is to provide a probabilistic explanation of recent results on a version of Smoluchowski’s coagulation equations in which the number of aggregations is limited. The latter models the deterministic evolution of concentrations of particles in a medium where particles coalesce pairwise as time passes and each particle can only perform a given number of aggregations. Under appropriate assumptions, the concentrations of particles converge as time tends to infinity to some measure which bears a striking resemblance with the distribution of the total population of a Galton-Watson process started from two ancestors. Roughly speaking, the configuration model is a stochastic construction which aims at producing a typical graph on a set of vertices with pre-described degrees. Specifically, one attaches to each vertex a certain number of stubs, and then join pairwise the stubs uniformly at random to create edges between vertices. In this work, we use the configuration model as the stochastic counterpart of Smoluchowski’s coagulation equations with limited aggregations. We establish a hydrodynamical type limit theorem for the empirical measure of the shapes of clusters in the configuration model when the number of vertices tends to ∞. The limit is given in terms of the distribution of a Galton-Watson process started with two ancestors.     

Capacity of wander and spread beams in log-normal distribution non-Kolmogorov turbulence optical links

We model the average channel capacity of optical wireless communication systems in weak turbulence horizontal channels, using the log-normal distribution models. The effects of beam wander and spread, pointing errors, turbulence inner scale, turbulence outer scale and the spectral index of non-Kolmogorov turbulence on system's performance are included. The model can evaluate the influence of the atmospheric turbulence conditions in the performance of a ground-to-train optical wireless communication system.     

Average capacity of ground-to-train log-normal wireless optical interconnects

A model of the average capacity of a ground-to-train optical wireless communication link in a horizontal channel is established by using the log-normal distribution model of the weak turbulence. The average capacity model include the effects of the turbulent wander and spread of bwams, pointing errors of links, turbulence inner scale and turbulence outer scale.     

Stochastic weighted particle methods for population balance equations

A class of coagulation weight transfer functions is constructed, each member of which leads to a stochastic particle algorithm for the numerical treatment of population balance equations. These algorithms are based on systems of weighted computational particles and the weight transfer functions are constructed such that the number of computational particles does not change during coagulation events. The algorithms also facilitate the simulation of physical processes that change single particles, such as growth, or other surface reactions.     

A causal multifractal stochastic equation and its statistical properties

Multiplicative cascades have been introduced in turbulence to generate random or deterministic fields having intermittent values and long-range power-law correlations. Generally this is done using discrete construction rules leading to discrete cascades. Here a causal log-normal stochastic process is introduced; its multifractal properties are demonstrated together with other properties such as the composition rule for scale dependence and stochastic differential equations for time and scale evolutions. This multifractal stochastic process is continuous in scale ratio and in time. It has a simple generating equation and can be used to generate sequentially time series of any length.Received: 15 April 2003, Published online: 23 July 2003PACS: 02.50.Ey Stochastic processes - 05.45.Df Fractals - 47.27.Eq Turbulence simulation and modeling     

基于高阶累计量的大气光通信自适应信号处理

针对强湍流信道下信号衰落的特点,分析了对数正态分布模型与K分布模型的适用范围.基于K分布模型建立大气光通信接收信号模型,并给出了自适应最优门限检测方法.采用四阶和六阶累计量对强湍流信道参量进行估计,采用二阶累计量对其它高斯噪音进行估计,得到K分布参量及高斯噪音统计量的预测值,实现自适应门限更新.基于Monte Calro算法进行仿真,给出了门限更新算法对通信系统误码率的影响,同时分析了信号采样率对估计参量偏差的影响.计算表明,在强湍流情况下,大气光通信系统的误码率性能得到极大的改善,优于基于MLSD检测的接收机.