Atomistic hybrid DSMC/NEMD method for nonequilibrium multiscale simulations

A multiscale hybrid method for coupling the direct simulation Monte Carlo (DSMC) method to the nonequilibrium molecular dynamics (NEMD) method is introduced. The method addresses Knudsen layer type gas flows within a few mean free paths of an interface or about an object with dimensions of the order of a few mean free paths. It employs the NEMD method to resolve nanoscale phenomena closest to the interface along with coupled DSMC simulation of the remainder of the Knudsen layer. The hybrid DSMC/NEMD method is a particle based algorithm without a buffer zone. It incorporates a new, modified generalized soft sphere (MGSS) molecular collision model to improve the poor computational efficiency of the traditional generalized soft sphere GSS model and to achieve DSMC compatibility with Lennard-Jones NEMD molecular interactions. An equilibrium gas, a Fourier thermal flow, and an oscillatory Couette flow, are simulated to validate the method. The method shows good agreement with Maxwell–Boltzmann theory for the equilibrium system, Chapman–Enskog theory for Fourier flow, and pure DSMC simulations for oscillatory Couette flow. Speedup in CPU time of the hybrid solver is benchmarked against a pure NEMD solver baseline for different system sizes and solver domain partitions. Finally, the hybrid method is applied to investigate interaction of argon gas with solid surface molecules in a parametric study of the influence of wetting effects and solid molecular mass on energy transfer and thermal accommodation coefficients. It is determined that wetting effect strength and solid molecular mass have a significant impact on the energy transfer between gas and solid phases and thermal accommodation coefficient.     

Monte Carlo solution of the Boltzmann equation via a discrete velocity model

A new discrete velocity scheme for solving the Boltzmann equation is described. Directly solving the Boltzmann equation is computationally expensive because, in addition to working in physical space, the nonlinear collision integral must also be evaluated in a velocity space. Collisions between each point in velocity space with all other points in velocity space must be considered in order to compute the collision integral most accurately, but this is expensive. The computational costs in the present method are reduced by randomly sampling a set of collision partners for each point in velocity space analogous to the Direct Simulation Monte Carlo (DSMC) method. The present method has been applied to a traveling 1D shock wave. The jump conditions across the shock wave match the Rankine–Hugoniot jump conditions. The internal shock wave structure was compared to DSMC solutions, and good agreement was found for Mach numbers ranging from 1.2 to 10. Since a coarse velocity discretization is required for efficient calculation, the effects of different velocity grid resolutions are examined. Additionally, the new scheme’s performance is compared to DSMC and it was found that upstream of the shock wave the new scheme performed nearly an order of magnitude faster than DSMC for the same upstream noise. The noise levels are comparable for the same computational effort downstream of the shock wave.     

含振动能激发Boltzmann模型方程气体动理论统一算法验证与分析

为模拟研究高温高马赫数下多原子气体内能激发对跨流域非平衡流动的影响,将转动能、振动能分别作为气体分子速度分布函数的自变量,把转动能和振动能处理为连续分布的能量模式,将Boltzmann方程的碰撞项分解成弹性碰撞项和非弹性碰撞项,同时将非弹性碰撞按一定松弛速率分解为平动-转动能松弛过程和平动-转动-振动能松弛过程,构造了一类考虑振动能激发的Boltzmann模型方程,并证明了其守恒性和H定理.基于内部能量变量对分布函数无穷积分,引入三个约化速度分布函数,得到一组考虑振动能激发的约化速度分布函数控制方程组,使用离散速度坐标法,基于LU-SGS隐式格式和有限体积法求解离散速度分布函数,建立含振动能激发的气体动理论统一算法.通过开展高稀薄流到连续流圆柱绕流问题统一算法与直接模拟蒙特卡罗法模拟结果对比分析,特别是过渡流区平动、转动、振动非平衡效应对绕流流场与物面力热特性的影响机制,证实了所建立的含振动能激发的Boltzmann模型方程及气体动理论统一算法的准确可靠性.     

Optimum fuzzy combination of robust decoupled sliding mode and adaptive feedback linearization controllers for uncertain under-actuated nonlinear systems

In this paper, an optimum fuzzy combination of decoupled sliding mode control (DSMC) and adaptive feedback linearization (FBL) is presented for under-actuated nonlinear systems with uncertainties. At first, DSMC and FBL are separately designed and the feedback linearization parameters are adapted by using the gradient descent approach; then, a fuzzy weighted summation of the two controllers is introduced. The multi-objective non-dominated sorting genetic algorithm II (NSGAII) is employed to properly choose the control gains. The objective functions for the optimization process are defined as the integrals of time multiplied by absolute errors, which have been minimized, simultaneously. In addition, the ball and beam system, as a well-known and popular benchmark, is investigated to test and challenge the proposed strategy. Simulation results illustrate that this approach would provide better performance in terms of settling time and control input compared with other methods reported in the literature.     

A hybrid method for hydrodynamic-kinetic flow – Part II – Coupling of hydrodynamic and kinetic models

In this work we present a non stationary domain decomposition algorithm for multiscale hydrodynamic-kinetic problems, in which the Knudsen number may span from equilibrium to highly rarefied regimes. Our approach is characterized by using the full Boltzmann equation for the kinetic regime, the Compressible Euler equations for equilibrium, with a buffer zone in which the BGK-ES equation is used to represent the transition between fully kinetic to equilibrium flows.In this fashion, the Boltzmann solver is used only when the collision integral is non-stiff, and the mean free path is of the same order as the mesh size needed to capture variations in macroscopic quantities. Thus, in principle, the same mesh size and time steps can be used in the whole computation. Moreover, the time step is limited only by convective terms.Since the Boltzmann solver is applied only in wholly kinetic regimes, we use the reduced noise DSMC scheme we have proposed in Part I of the present work. This ensures a smooth exchange of information across the different domains, with a natural way to construct interface numerical fluxes. Several tests comparing our hybrid scheme with full Boltzmann DSMC computations show the good agreement between the two solutions, on a wide range of Knudsen numbers.     

Searching for a near neighbor particle in DSMC cells using pseudo-subcells

LeBeau et al. (2003) [4] introduced the ‘virtual-subcell’ (VSC) method of finding a collision partner for a given DSMC particle in a cell; all potential collision partners in the cell are examined to find the nearest neighbor, which becomes the collision partner. Here I propose a modification of the VSC method, the ‘pseudo-subcell’ (PSC) method, whereby the search for a collision partner stops whenever a ‘near-enough’ particle is found, i.e. whenever another particle is found within the ‘pseudo-subcell’ of radius δ centered on the first particle. The radius of the pseudo-subcell is given by δ = Fd_n, where d_n is the expected distance to the nearest neighbor and F is a constant which can be adjusted to give a desired trade-off between CPU time and accuracy as measured by a small mean collision separation (MCS). For 3D orthogonal cells, of various aspect ratios, d_n/L ≈ 0.746/N^0.383 where N is the number of particles in the cell and L is the cube root of the cell volume. There is a good chance that a particle will be found in the pseudo-subcell and there is a good chance that such a particle is in fact the nearest neighbor. If no particle is found within the pseudo-subcell the closest particle becomes the collision partner.     

On the approach to kinetic theory due to Gross

A classical kinetic theory introduced by Gross is explored in further detail. The theory consists of a sequence of approximations to the Liouville distribution function, with each approximation leading to a truncation of the BBGKY hierarchy at successively higher order. We formulate the truncation scheme at general order in terms of a set of time-dependent equilibrium correlation functions. It has the correct symmetries and, as is implied by the work of Gross with the first two approximations, is such that the interparticle potential appears only implicitly via static equilibrium correlation functions. We arrange the theory as a sequence of linear kinetic equations for the phase-space density correlation function, and solve for the collision kernels which result in each order. The collision kernel of the second approximation, which involves only binary dynamics, is shown to be a mean-field generalization of the known low-density kernel. The third approximation gives a similar generalization of the triple-collision kernel. The nth approximation also reproduces the frequency moments of S(kω) through order ω²ⁿ. More generally, the approximations are shown to give a continued-fraction expansion of the collision kernel, with the levels governed by the dynamics of successively larger numbers of particles. This is a renormalized kinetic theory in the sense that the potential is eliminated and clusters of particles are never isolated.     

Convergence of a Distributional Monte Carlo Method for the Boltzmann Equation

Direct Simulation Monte Carlo (DSMC) methods for the Boltzmann equation employ a point measure approximation to the distribution function, as simulated particles may possess only a single velocity. This representation limits the method to converge only weakly to the solution of the Boltzmann equation. Utilizing kernel density estimation we have developed a stochastic Boltzmann solver which possesses strong convergence for bounded and $L^\infty$ solutions of the Boltzmann equation. This is facilitated by distributing the velocity of each simulated particle instead of using the point measure approximation inherent to DSMC. We propose that the development of a distributional method which incorporates distributed velocities in collision selection and modeling should improve convergence and potentially result in a substantial reduction of the variance in comparison to DSMC methods. Toward this end, we also report initial findings of modeling collisions distributionally using the Bhatnagar-Gross-Krook collision operator.     

Simulation of unsteady flows by the DSMC macroscopic chemistry method

In the Direct Simulation Monte-Carlo (DSMC) method, a combination of statistical and deterministic procedures applied to a finite number of ‘simulator’ particles are used to model rarefied gas-kinetic processes. In the macroscopic chemistry method (MCM) for DSMC, chemical reactions are decoupled from the specific particle pairs selected for collisions. Information from all of the particles within a cell, not just those selected for collisions, is used to determine a reaction rate coefficient for that cell. Unlike collision-based methods, MCM can be used with any viscosity or non-reacting collision models and any non-reacting energy exchange models. It can be used to implement any reaction rate formulations, whether these be from experimental or theoretical studies. MCM has been previously validated for steady flow DSMC simulations. Here we show how MCM can be used to model chemical kinetics in DSMC simulations of unsteady flow. Results are compared with a collision-based chemistry procedure for two binary reactions in a 1-D unsteady shock-expansion tube simulation. Close agreement is demonstrated between the two methods for instantaneous, ensemble-averaged profiles of temperature, density and species mole fractions, as well as for the accumulated number of net reactions per cell.     

Multiple temperature model for the information preservation method and its application to nonequilibrium gas flows

The information preservation (IP) method has been successfully applied to various nonequilibrium gas flows. Comparing with the direct simulation Monte Carlo (DSMC) method, the IP method dramatically reduces the statistical scatter by preserving collective information of simulation molecules. In this paper, a multiple temperature model is proposed to extend the IP method to strongly translational nonequilibrium gas flows. The governing equations for the IP quantities have been derived from the Boltzmann equation based on an assumption that each simulation molecule represents a Gaussian distribution function with a second-order temperature tensor. According to the governing equations, the implementation of IP method is divided into three steps: molecular movement, molecular collision, and update step. With a reasonable multiple temperature collision model and the flux splitting method in the update step, the transport of IP quantities can be accurately modeled. We apply the IP method with the multiple temperature model to shear-driven Couette flow, external force-driven Poiseuille flow and thermal creep flow, respectively. In the former two cases, the separation of different temperature components is clearly observed in the transition regime, and the velocity, temperature and pressure distributions are also well captured. The thermal creep flow, resulting from the presence of temperature gradients along boundary walls, is properly simulated. All of the IP results compare well with the corresponding DSMC results, whereas the IP method uses much smaller sampling sizes than the DSMC method. This paper shows that the IP method with the multiple temperature model is an accurate and efficient tool to simulate strongly translational nonequilibrium gas flows.     

Particle-in-cell plus direct simulation Monte Carlo (PIC-DSMC)approach for self-consistent plasma-gas simulations

The particle-in-cell (PIC) and direct simulation Monte Carlo (DSMC) approaches have been combined into a PIC-DSMC model for self-consistent simulations of low-temperature collisional plasmas and the background gas. This novel approach is based on the weighting collision simulation scheme allowing for disparate number densities and time scales of different species. The applicability of the developed algorithm is illustrated by simulations of one-dimensional direct current and two-dimensional magnetron sputtering discharges in argon. An appreciable effect of the energetic discharge species on the density, temperature, and flow field of the background gas shows the importance of the coupled plasma-gas simulation for such technologies as sputtering, dry etching, plasma enhanced vapor deposition, etc     

Convergence behavior of a new DSMC algorithm

The convergence rate of a new direct simulation Monte Carlo (DSMC) method, termed “sophisticated DSMC”, is investigated for one-dimensional Fourier flow. An argon-like hard-sphere gas at 273.15 K and 266.644 Pa is confined between two parallel, fully accommodating walls 1 mm apart that have unequal temperatures. The simulations are performed using a one-dimensional implementation of the sophisticated DSMC algorithm. In harmony with previous work, the primary convergence metric studied is the ratio of the DSMC-calculated thermal conductivity to its corresponding infinite-approximation Chapman–Enskog theoretical value. As discretization errors are reduced, the sophisticated DSMC algorithm is shown to approach the theoretical values to high precision. The convergence behavior of sophisticated DSMC is compared to that of original DSMC. The convergence of the new algorithm in a three-dimensional implementation is also characterized. Implementations using transient adaptive sub-cells and virtual sub-cells are compared. The new algorithm is shown to significantly reduce the computational resources required for a DSMC simulation to achieve a particular level of accuracy, thus improving the efficiency of the method by a factor of 2.     

Direct Monte Carlo simulation of high-temperature chemical reactions in air

A novel approach to modeling high-temperature nonequilibrium dissociation in air at a level of molecular collisions is proposed. Information on the energy dependence of the specific reaction cross sections, which is necessary for such modeling, is determined numerically from available macroscopic information on the dependence of the reaction rate constant on translational and vibrational temperatures. The results of Direct Simulation Monte Carlo (DSMC) computations show that the proposed model yields a correct reaction rate in vibrational-translational nonequilibrium. The use of the new model in DSMC computations of high-altitude aerothermodynamics results in obtaining a noticeably different flow structure and a higher heat flux, as compared to that predicted by standard DSMC models (such as the total collision energy model).     

Inverse scattering method and vector higher order non-linear Schrödinger equation

A generalized inverse scattering method has been developed for arbitrary n-dimensional Lax equations. Subsequently, the method has been used to obtain N-soliton solutions of a vector higher order non-linear Schrödinger equation, proposed by us. It has been shown that under a suitable reduction, the vector higher order non-linear Schrödinger equation reduces to the higher order non-linear Schrödinger equation. An infinite number of conserved quantities have been obtained by solving a set of coupled Riccati equations. Gauge equivalence is shown between the vector higher order non-linear Schrödinger equation and the generalized Landau–Lifshitz equation and the Lax pair for the latter equation has also been constructed in terms of the spin field, establishing direct integrability of the spin system.     

Beyond direct simulation Monte Carlo (DSMC) modelling of collision environments

ABSTRACT

Direct simulation Monte Carlo (DSMC) models have been successfully adopted and adapted to describe gas flows in a wide range of environments since the method was first introduced by Bird in the 1960s. We propose a new approach to modelling collisions between gas-phase particles in this work – operating in a similar way to the DSMC model, but with one key difference. Particles move in a mean field, generated by all previously propagated particles, which removes the requirement that all particles be propagated simultaneously. This yields a significant reduction in computation effort and lends itself to applications for which DSMC becomes intractable, such as when a species of interest is only a minor component of a large gas mixture.     

DSMC方法的压力边界条件实现

提出了一种实现DSMC压力边界条件的新方法,新方法不仅可以避免传统"通量法"造成的计算发散问题,又较之"入口平均法"有更快的收敛速度.使用这种方法,对不同压差驱动下等壁温微通道内的气体流动进行了模拟,并与传统的基于连续介质假设的滑移理论所得结果进行了比较.     

The transition operator for depolarizing collisions

The transition operator accounting for changes of the Zeeman sublevels of a¹ P-state or closely spaced² P-states has been derived using the classical-path approximation. In a first order approach to the problem thep-state atom is assumed to enter the range of a foreign atom non-adiabatically fast until reaching the point of the closest distance. There it is assumed to stop for the entire collision time. During this time the molecular σ and π states suffer phase-shifts due to the interaction with the molecular electric field. Subsequently thep-state atom leaves the range of the foreign atom again non-adiabatically fast. TheT-operator hence derived gives rise to the so-calledm _j-selection rule. In a better approach thep-state atom is assumed to stop twice when passing the range of the foreign atom. From this approximation additional terms to theT-operator arise which characteristically account for ‘molecular coupling’ phenomena during the collision. Consequently, these terms violate the afore-mentionedm _j-selection rule.     

Brownian Approximation and Monte Carlo Simulation of the Non-Cutoff Kac Equation

The non-cutoff Boltzmann equation can be simulated using the DSMC method, by a truncation of the collision term. However, even for computing stationary solutions this may be very time consuming, in particular in situations far from equilibrium. By adding an appropriate diffusion, to the DSMC-method, the rate of convergence when the truncation is removed, may be greatly improved. We illustrate the technique on a toy model, the Kac equation, as well as on the full Boltzmann equation in a special case.