On a numerical subgrid upscaling algorithm for Stokes–Brinkman equations

This paper discusses a numerical subgrid resolution approach for solving the Stokes–Brinkman system of equations, which is describing coupled flow in plain and in highly porous media. Various scientific and industrial problems are described by this system, and often the geometry and/or the permeability vary on several scales. A particular target is the process of oil filtration. In many complicated filters, the filter medium or the filter element geometry are too fine to be resolved by a feasible computational grid. The subgrid approach presented in this paper is aimed at describing how these fine details are accounted for by solving auxiliary problems in appropriately chosen grid cells on a relatively coarse computational grid. This is done via a systematic and careful procedure of modifying and updating the coefficients of the Stokes–Brinkman system in chosen cells. This numerical subgrid approach is motivated from one side from homogenization theory, from which we borrow the formulations for the so-called cell problem, and from the other side from the numerical upscaling approaches, such as Multiscale Finite Volume, Multiscale Finite Element, etc. Results on the algorithm’s efficiency, both in terms of computational time and memory usage, are presented. Comparison of the full fine grid solution (when possible) of the Stokes–Brinkman system with the subgrid solution of the upscaled Stokes–Brinkman system (including effective permeabilities for the quasi-porous cells), are presented in order to evaluate the accuracy and the efficiency. Advantages and limitations of the considered subgrid approach are discussed.     

Anticipatory distributed packet filter configurations for carrier-grade IP networks

Packet filters have traditionally been used to shield IP networks from known attack flows, usually within firewall systems connecting trusted and non-trusted network segments. As IP networks grow and tend to connect to more and more neighbor networks with unknown trust status, carrier-grade operators in particular are beginning to experience raising costs due to increasingly complex filter configurations that have to be applied to their networks, in order to maintain a desired security level. In this paper, we discuss the general properties of distributed packet filter configurations in large networks. Additionally, an algorithm for a simplified compilation of anticipatory static packet filter configurations in heterogeneous IP networks as well as simulation results that demonstrate possible filter cost reduction is presented.     

Solution of problems of oil reservoirs flooded with water using polymer-dispersed systems on a multiprocessor computer system

The paper provides the results of the numerical simulation of the impact of polymer-dispersed systems on oil reservoirs in order to increase the flow resistance of flooded areas and to involve nonmoving or slow-moving oil reserves in active development. The mathematical model of this process was built based on the known laws of the conservation of mass and momentum. The capillary model of the porous medium was used to construct closure relations that allowed us to describe the formation of polymer-dispersed components and their influence on a porous medium. The complexity of solving the problem of the impact of polymer-dispersed systems on the process of oil displacement by water from a porous medium is related to the three-dimensionality and nonstationarity processes of filtration, as well as the need to calculate the fields of polymer concentration, pressure and saturation fields, and the structural changes in porosity and permeability at each time step and at each point in space. All these factors require significant computer time and resources. The paper presents the algorithm of parallel calculations using a multiprocessor computer system with the MPI library. Calculations on a real field demonstrated the efficiency of the algorithm.     

Filter shape dependence and effective scale separation in large-eddy simulations based on relaxation filtering

The influence of the filter shape on the effective scale separation and the numerical accuracy of large-eddy simulations based on relaxation filtering (LES-RF) is investigated. The simulation of the turbulent flow development of a high-Reynolds number low-subsonic compressible mixing layer is performed using the LES-RF procedure, for discrete filters of order 2–10. A reference solution is first obtained using high-order numerical algorithms and shows a good agreement with experimental data found in the literature. Discrete filters of order 2, 4, 6, 8 and 10 are then considered to study the influence of the filter shape on numerical results. The 2nd-order scheme turns out to be too dissipative and prevents the emergence of unsteady motions within the mixing layer. For higher order schemes, from 4th- to 10th-order, the flow solutions are turbulent but exhibit mean flows and turbulent intensities depending on the filter. The investigation of the one-dimensional kinetic energy spectra then shows that the 4th-order filter may still be too dissipative whereas large scales remain unaffected using the 6th-, 8th- and 10th-order filters. A further study of the kinetic energy spectra nonetheless demonstrates that the effective spatial bandwidth of the LES increases with the order of the filtering scheme. Simulations using the 6th-, 8th- and 10th-order filters, with mesh sizes chosen to provide the same effective LES cut-off wavenumber, are performed and yield similar results. It is hence found that the value of the effective LES cut-off wavenumber, rather than to the filter shape itself, is mainly responsible for the discrepancies between the flow statistics obtained using different filters. One may conclude that filter shape independence is consequently achieved in the present LES of a mixing layer.     

Multiphase and multiphysics particle in cell simulation of soot deposition inside a diesel particulate filter single channel

In the diesel particulate filters technology a key aspect is represented by the properties of the particulate matter that is collected inside their structure. The work presented is focused on the development of an innovative mathematical tool based on the particle-in-cell method (PIC) for the simulation of the soot distribution inside a single channel of a diesel particulate filter. The basic fluid dynamic equations are solved for the gas phase inside the channel using a novel technique based on the solution of the same set of equations everywhere in the system including the porous medium. This approach is presented as alternative to the more conventional methods of matching conditions across the boundary of the porous region where a Darcy-like flow is developed. The motion of the soot solid particles is instead described through a particle-by-particle approach based on Newton's equations of motion. The coupling between the dynamics of the gas and that of the soot particles, i.e. between these two sub-models, is performed through the implementation of the particle-in-cell technique. This model allows the detailed simulation of the deposition and compaction of the soot inside the filter channels and its characterization in terms of density, permeability and thickness. The model then represents a unique tool for the optimization of the design of diesel particulate filters. The details of the technique implementation and some paradigmatic examples will be shown.     

一种基于多相带通结构的信道化滤波器算法

针对信道化滤波器要求运算速度快、消耗资源多、难以实时处理的突出问题,从多相滤波器,信道化滤波器的结构、原理和运算效率分析出发,推导了一种基于多相带通结构的信道化滤波器算法模型。这种算法将现有多相结构信道化滤波器模型中的低通设计改为带通设计,实现了复数乘法运算全部集中在带通滤波环节当中,并采用协调分级DFT算法的实现方案,大幅度节省了硬件资源,提高了运算效率,实现了信道化滤波器在通用FP—GA和DSP芯片中的实时处理,硬件仿真结果验证了算法模型的正确性和有效性。     

一种改进的α-β目标跟踪滤波算法

数据处理系统是相控阵雷达实现搜索和对多目标精确跟踪的关键部分，目标跟踪滤波算法的优劣将直接决定系统的性能。介绍了一种改进的α-β滤波算法，然后将它和最小二乘滤波算法、卡尔曼滤波算法进行比较，对三种算法跟踪空中目标的直线飞行、改变航向的直线飞行两种情况的距离、方位、速度和航向等参数的均方差加以分析，证明了改进的α-β滤波算法在直线飞行模型下有着很好的综合效果，且计算量小，更有利于系统建模与仿真。     

Fuzzy adaptive filters, with application to nonlinear channelequalization

Two fuzzy adaptive filters are developed: one uses a recursive-least-squares (RLS) adaptation algorithm, and the other uses a least-mean-square (LMS) adaptation algorithm. The RLS fuzzy adaptive filter is constructed through the following four steps: (1) define fuzzy sets in the filter input space Rn whose membership functions cover U; (2) construct a set of fuzzy IF-THEN rules which either come from human experts or are determined during the adaptation procedure by matching input-output data pairs; (3) construct a filter based on the set of rules; and (4) update the free parameters of the filter using the RLS algorithm. The design procedure for the LMS fuzzy adaptive filter is similar. The most important advantage of the fuzzy adaptive filters is that linguistic information (in the form of fuzzy IF-THEN rules) and numerical information (in the form of input-output pairs) can be combined in the filters in a uniform fashion. The filters are applied to nonlinear communication channel equalization problems     

Parallel adaptive reservoir simulation

In oil-industry it is common use to simulate the exploitation of an oil-reservoir by means of some numerical method. Such a numerical method may use the concept of dynamical local grid refinement, in order to mark fronts of water and oil, which move through the reservoir. In this paper, we discuss a domain decomposition method, which may be used to parallelize reservoir simulation. The parallel algorithm and timing experiments on a hypercube-type parallel computer are considered.     

Marginalized particle filter for spacecraft attitude estimation from vector measurements

An algorithm based on the marginalized particle filters (MPF) is given in details in this paper to solve the spacecraft attitude estimation problem: attitude and gyro bias estimation using the biased gyro and vector observations. In this algorithm, by marginalizing out the state appearing linearly in the spacecraft model, the Kalman filter is associated with each particle in order to reduce the size of the state space and computational burden. The distribution of attitude vector is approximated by a set of particles and estimated using particle filter, while the estimation of gyro bias is obtained for each one of the attitude particles by applying the Kalman filter. The efficiency of this modified MPF estimator is verified through numerical simulation of a fully actuated rigid body. For comparison, unscented Kalman filter (UKF) is also used to gauge the performance of MPF. The results presented in this paper clearly demonstrate that the MPF is superior to UKF in coping with the nonlinear model.     

Marginalized particle filter for spacecraft attitude estimation from vector measurements

An algorithm based on the marginalized particle filters （MPF） is given in details in this paper to solve the spacecraft attitude estimation problem： attitude and gyro bias estimation using the biased gyro and vector observations. In this algorithm, by marginalizing out the state appearing linearly in the spacecraft model, the Kalman filter is associated with each particle in order to reduce the size of the state space and computational burden. The distribution of attitude vector is approximated by a set of particles and estimated using particle filter, while the estimation of gyro bias is obtained for each one of the attitude particles by applying the Kalman filter. The efficiency of this modified MPF estimator is verified through numerical simulation of a fully actuated rigid body. For comparison, unscented Kalman filter （UKF） is also used to gauge the performance of MPE The results presented in this paper clearly derfionstrate that the MPF is superior to UKF in coping with the nonlinear model.     

Globally conservative high-order filters for large-eddy simulation and computational aero-acoustics

In computational aero-acoustics, large-eddy simulations (LES) or direct numerical simulations (DNS) are often employed for flow computations in the source region. As part of the numerical implementation or required modeling, explicit spatial filters are frequently employed. For instance, in LES spatial filters are employed in the formulation of various subgrid-scale (SGS) models such as the dynamic model or the variational multi-scale (VMS) Smagorinsky model; both in LES or DNS, spatial high-pass filters are often used to remove undesired grid-to-grid oscillations. Though these type of spatial filters adhere to local accuracy requirements, in practice, they often destroy global conservation properties in the presence of non-periodic boundaries conditions. This leads to the incorrect prediction of the flow properties near hard boundaries, such as walls. In the current work, we present globally conservative high-order accurate filters, which combine traditional filters at the internal points with one-sided conservative filters near the wall boundary. We test these filters to remove grid-to-grid oscillations both in a channel-flow case and in 2D cavity flow. We find that the use of a non-conservative filter leads to erroneous predictions of the skin friction in channel flows up to 30%. In the cavity-flow simulations, the use of non-conservative filters to remove grid-to-grid oscillations leads to important shifts in the Strouhal number of the dominant mode, and a change of the flow pattern inside the cavity. In all cases, the use of conservative high-order filter formulations to remove grid-to-grid oscillations lead to very satisfactory results. Finally, in our channel-flow test case, we also illustrate the importance of using conservative filters for the formulation of the VMS Smagorinsky model.     

Direct‐coupled waveguide filters for the lower gigahertz frequency range

An analysis method based on the coupled‐integral‐equations technique (CIET) and the mode‐matching technique (MMT) is presented for the design of a variety of direct‐coupled waveguide filters suitable for applications in the lower gigahertz frequency range. The method is verified by comparison with data obtained through other numerical techniques and measurements. With reference to standard waveguide filters, the issues of filter miniaturization and stopband extension toward higher frequency bands are investigated. For given frequency specifications in the 2‐GHz frequency range, examples of rectangular coaxial waveguide filters, ridge waveguide filters, ridge waveguide filters including coupling irises and T‐septum waveguide filters are presented. It is demonstrated that the rectangular/square coaxial waveguide filter achieves the highest degree of miniaturization, but that ridge and, especially, T‐septum waveguide filter technology is advantageous with respect to stopband performance toward higher frequencies. In particular, a T‐septum filter centered at 2.155 GHz is shown to block the entire frequency range up to 7.5 GHz. © 2002 Wiley Periodicals, Inc. Int J RF and Microwave CAE 12: 217–225, 2002.     

Fuzzy Particle Filtering for Uncertain Systems

In this paper, we propose a novel fuzzy particle filtering method for online estimation of nonlinear dynamic systems with fuzzy uncertainties. This approach uses a sequential fuzzy simulation to approximate the possibilities of the state intervals in the state-space, and estimates the state by fuzzy expected value operator. To solve the degeneracy problem of the fuzzy particle filter, one corresponding resampling technique is introduced. In addition, we compare the fuzzy particle filter with ordinary particle filter in both aspects of the theoretical basis and algorithm design, and demonstrate that the proposed filter outperforms standard particle filters especially when the number of the particles is small. The numerical simulations of two continuous-state nonlinear systems and a jump Markov system are employed to show the effectiveness and robustness of the proposed fuzzy particle filter.     

Gaussian filters for nonlinear filtering problems

We develop and analyze real-time and accurate filters for nonlinear filtering problems based on the Gaussian distributions. We present the systematic formulation of Gaussian filters and develop efficient and accurate numerical integration of the optimal filter. We also discuss the mixed Gaussian filters in which the conditional probability density is approximated by the sum of Gaussian distributions. A new update rule of weights for Gaussian sum filters is proposed. Our numerical tests demonstrate that new filters significantly improve the extended Kalman filter with no additional cost, and the new Gaussian sum filter has a nearly optimal performance     

基于UKF和优化组合策略的改进粒子滤波算法

针对标准粒子滤波算法存在的粒子退化与贫化问题,提出了一种新的改进粒子滤波算法。该算法采用无迹卡尔曼滤波、优化组合策略和标准粒子滤波相结合的方法,运用UKF产生重要性密度函数,解决标准PF算法中以先验概率密度函数作为建议分布所引发的退化问题;运用优化组合重采样策略保证所有粒子的信息以一定概率得到继承,维持粒子集中粒子的多样性。理论分析与仿真结果均表明,改进算法能有效地解决标准粒子滤波存在的粒子退化问题并避免粒子贫化现象的出现,具有更高的状态估计精度。     

A study on pressure-driven gas transport in porous media: from nanoscale to microscale

Gas flow in porous media can be seen in various engineering devices such as catalytic converters and fuel cells. It is important to understand transport phenomena in porous media for improvement of the performance of such devices. Porous media with pores as small as the mean free path of gas molecules are used in such devices as proton exchange membrane fuel cells. It is difficult to measure molecular transport through such small pores in the experimental approach. In addition, even when using theoretical or numerical approaches, gas flow through nanoscale pores must be treated by the Boltzmann equation rather than the Navier–Stokes equations because it cannot be considered as a continuum. Thus, conventional analyses based on the continuum hypothesis are inadequate and the transport phenomena in porous media with nanoscale pores are not yet clearly understood. In this study, we represented porous media by randomly arranged solid spherical particles and simulated pressure-driven gas flow through the porous media by using the direct simulation Monte Carlo (DSMC) method based on the Boltzmann equation. DSMC simulations were performed for different porosities and different sizes of solid particles of porous media. It was confirmed that Darcy’s law holds even in the case of porous media with micro-/nanoscale pores. Using the obtained results, we constructed expressions to estimate the pressure-driven gas transport in porous media with micro-/nanoscale pores and porosity ranging from 0.3 to 0.5. The flow velocities estimated by using the constructed expressions agreed well with those obtained in the DSMC simulations.     

AN OPTIMAL DESIGN OF IIR DIGITAL FILTER USING PARTICLE SWARM OPTIMIZATION

In this article, a novel approach for infinite-impulse response (IIR) digital filters using particle swarm optimization (PSO) is presented. IIR filter is essentially a digital filter with recursive responses. Because the error surface of digital IIR filters is generally nonlinear and multimodal, so global optimization techniques are required in order to avoid local minima. This study is based on a heuristic way to design IIR filters. PSO is a powerful global optimization algorithm introduced in combinatorial optimization problems. This study finds the optimum coefficients of the IIR digital filter through PSO. It is found that the calculated values are more optimal than the FDA tool and GA available for the design of the filter in MATLAB. Design of low-pass and high-pass IIR digital filters is proposed in order to provide an estimate of the transition band. The simulation results of the employed examples show an improvement on the transition band. The stability of designed filters is described by the position of Pole-Zeros.     

一种针对规则集不一致性的测试数据包选取算法

在防火墙规则集正确性测试中,现有的测试数据包选取算法大多随机选取数据包和从规则顶点选取数据包。然而,这种做法忽略了存在规则不一致性的区域,从而导致不能检测出所有因规则不一致性而产生的配置错误。针对这一情况,提出了一种针对规则集不一致性的测试数据包选取算法。该算法以两条规则为基本单位,计算其不一致性区域。算法不但从规则顶点选取数据包,而且从规则集不一致性区域选取数据包。测试表明,与常见测试数据包选取算法相比,该算法只需增加少量测试数据包,就能检测出所有因规则不一致性而带来的配置错误。     

New explicit two-dimensional higher order filters

In the present work, a new class of explicit two-dimensional filter is proposed that is significantly different from the conventional one-dimensional Padè type filters. Comparison of performance between one- and two-dimensional filters are made in studying propagation problems and actual viscous flow problems. In this preliminary work, the focus is kept solely on developing central filters with its real transfer function. Many applications related to Navier–Stokes equation have been shown to demonstrate that these two-dimensional filters help in numerical stabilization; control aliasing and control over spurious upstream propagating disturbances. Furthermore, its potential for large eddy simulation (LES) is suggested by band-limiting the solution via filters in post-processing mode.