Developing theory of probability density function for stochastic modeling of turbulent gas-particle flows

Turbulent gas-particle flows are studied by a kinetic description using a prob- ability density function （PDF）. Unlike other investigators deriving the particle Reynolds stress equations using the PDF equations, the particle PDF transport equations are di- rectly solved either using a finite-difference method for two-dimensional （2D） problems or using a Monte-Carlo （MC） method for three-dimensional （3D） problems. The proposed differential stress model together with the PDF （DSM-PDF） is used to simulate turbulent swirling gas-particle flows. The simulation results are compared with the experimental results and the second-order moment （SOM） two-phase modeling results. All of these simulation results are in agreement with the experimental results, implying that the PDF approach validates the SOM two-phase turbulence modeling. The PDF model with the SOM-MC method is used to simulate evaporating gas-droplet flows, and the simulation results are in good agreement with the experimental results.

Reconstruction of Probability Density Function for Gamma Distribution

The probability distributions of small sample data are difficult to determine,while a large proportion of samples occur in the early failure period,so it is particularly important to make full use of these data in the statistical analysis.Based on gamma distribution,four methods of probability density function(PDF)reconstruction with early failure data are proposed,and then the mean time between failures(MTBF)evaluation expressions are concluded from the reconstructed PDFs.Both theory analysis and an example show that method 2 is the best evaluation method in dealing with early-failure-small-sample data.The reconstruction methods of PDF also have certain guiding significance for other distribution types.

Identification of Neuro-Fuzzy Hammerstein Model Based on Probability Density Function

A new identification method of neuro-uzzy Hammerstein model based on probability density function(PDF) is presented,which is different from the idea that mean squared error(MSE) is employed as the index function in traditional identification methods.Firstly,a neuro-fuzzy based Hammerstein model is constructed to describe the nonlinearity of Hammerstein process without any prior process knowledge.Secondly,a kind of special test signal is used to separate the link parts of the Hammerstein model.More specifically,the conception of PDF is introduced to solve the identification problem of the neuro-fuzzy Hammerstein model.The antecedent parameters are estimated by a clustering algorithm,while the consequent parameters of the model are identified by designing a virtual PDF control system in which the PDF of the modeling error is estimated and controlled to converge to the target.The proposed method not only guarantees the accuracy of the model but also dominates the spatial distribution of PDF of the model error to improve the generalization ability of the model.Simulated results show the effectiveness of the proposed method.

A New Maximum Entropy Probability Function for the Surface Elevation of Nonlinear Sea Waves

Based on the maximum entropy principle a new probability density function （PDF） f（x） for the surface elevation of nonlinear sea waves, X, is derived through performing a coordinate transform of X and solving a variation problem subject to three constraint conditions of f（ x ）. Compared with the maximum entropy PDFs presented previously, the new PDF has the following merits： （1） it has four parameters to be determined and hence can give more refined fit to observed data and has wider suitability for nonlinear waves in different conditions; （2） these parameters are expressed in terms of distribution moments of X in a relatively simple form and hence are easy to be determined from observed data; （3） the PDF is free of the restriction of weak nonlinearity and possible to be used for sea waves in complicated conditions, such as those in shallow waters with complicated topography; and （4） the PDF is simple in form and hence convenient for theoretical and practical uses. l.aboratory wind-wave experiments have been conducted to test the competence of the new PDF for the surface elevation of nonlinear waves. The experimental results manifest that the new PDF gives somewhat better fit to the laboratory wind-wave data than the well-known Gram-Charlier PDF and beta PDF.

Shape control on probability density function in stochastic systems

A novel strategy of probability density function （PDF） shape control is proposed in stochastic systems. The control er is designed whose parameters are optimal y obtained through the improved particle swarm optimization algorithm. The parameters of the control er are viewed as the space position of a particle in particle swarm optimization algorithm and updated continual y until the control er makes the PDF of the state variable as close as possible to the expected PDF. The proposed PDF shape control technique is compared with the equivalent linearization technique through simulation experiments. The results show the superiority and the effectiveness of the proposed method. The control er is excellent in making the state PDF fol ow the expected PDF and has the very smal error between the state PDF and the expected PDF, solving the control problem of the PDF shape in stochastic systems effectively.

Probability Density Function Method for Observing Reconstructed Attractor Structure

Probability density function (PDF) method is proposed for analysing the structure of the reconstructed attractor in computing the correlation dimensions of RR intervals of ten normal old men. PDF contains important information about the spatial distribution of the phase points in the reconstructed attractor. To the best of our knowledge, it is the first time that the PDF method is put forward for the analysis of the reconstructed attractor structure. Numerical simulations demonstrate that the cardiac systems of healthy old men are about 6-6.5 dimensional complex dynamical systems. It is found that PDF is not symmetrically distributed when time delay is small, while PDF satisfies Gaussian distribution when time delay is big enough. A cluster effect mechanism is presented to explain this phenomenon. By studying the shape of PDFs, that the roles played by time delay are more important than embedding dimension in the reconstruction is clearly indicated. Results have demonstrated that the PDF method represents a promising numerical approach for the observation of the reconstructed attractor structure and may provide more information and new diagnostic potential of the analyzed cardiac system.

Probability density analysis of SINR in massive MIMO systems with matched filter beamformer

This paper derives an approximate formula for probability density function(PDF) of received signal-to-interference-and-noise ratio(SINR) at user terminal when matched filter(MF) is adopted at a base station(BS).This distribution of SINR can be used to make an analysis of average sum-rate,outage probability,and symbol error rate of massive MIMO downlink with MF at BS.From simulation,it is found that the derived approximate analytical expression for PDF of SINR is consistent with the simulated exact PDF from the definition of SINR in medium-scale and large-scale MIMO systems.

Stochastic Distribution Control of Singular Systems: Output PDF Shaping

This paper presents a new algorithm designed to control the shape of the output probability density function (PDF) of singular systems subjected to non-Gaussian input. The aim is to select a control input uk such that the output PDF is made as close as possible to a given PDF.Based on the B-spline neural network approximation of the output PDF, the control algorithm is formulated by extending the developed PDF control strategies of non-singular systems to singular systems. It has been shown that under certain conditions the stability of the closed-loop system can be guaranteed. Simulation examples are given to show the effectiveness of the proposed control algorithm.

Nonlinear dynamics and performance analysis of modified snap-through vibration energy harvester with time-varying potential function

Vibration energy harvesting has emerged as a promising method to harvest energy for small-scale applications.Enhancing the performance of a vibration energy harvester(VEH)incorporating nonlinear techniques,for example,the snap-through VEH with geometric non-linearity,has gained attention in recent years.A conventional snap-through VEH is a bi-stable system with a time-invariant potential function,which was investigated extensively in the past.In this work,a modified snap-through VEH with a time-varying potential function subject to harmonic and random base excitations is investigated.Modified snap-through VEHs,such as the one considered in this study,are used in wave energy harvesters.However,the studies on their dynamics and energy harvesting under harmonic and random excitations are limited.The dynamics of the modified snap-through VEH is represented by a system of differential algebraic equations(DAEs),and the numerical schemes are proposed for its solutions.Under a harmonic excitation,the system exhibits periodic and chaotic motions,and the energy harvesting is superior compared with the conventional counterpart.The dynamics under a random excitation is investigated by the moment differential method and the numerical scheme based on the modified Euler-Maruyama method.The Fokker-Planck equation representing the dynamics is derived,and the marginal and joint probability density functions(PDFs)are obtained by the Monte Carlo simulation.The study shows that the modified snap-through oscillator based VEH performs better under both harmonic and random excitations.The dynamics of the system under stochastic resonance(SR)is investigated,and performance enhancement is observed.The results from this study will help in the development of adaptive VEH techniques in the future.

考虑化学反应的标量耗散率及其在PDF小尺度混合模型中的应用

在 Sanders和 Borghi工作的基础上 ,推导出考虑化学反应的标量耗散率和标量时间尺度 ,在标量的联合概率密度函数方程的小尺度混合模型中采用考虑化学反应的标量的时间尺度 ,结合求解流场的 k- ε模型对甲烷轴对称射流扩散火焰进行了计算 ,最后分析了标量时间尺度对小尺度混合模型 (IEM模型 )和计算结果的影响。

气液两相段塞流的PSD和PDF特征分析

在气液两相段塞流理论基础上,通过大量实验,利用LabVIEW平台进行数据采集和处理,并引进数字信号理论和统计学分析方法,得出了段塞流在不同时期、不同形态的概率密度函数(PDF)特征和功率谱密度函数(PSD)特征.段塞流的压力概率密度函数呈现单峰、双峰、多峰分布,尤以双峰分布最为普遍;段塞流的压差概率密度函数分布符合正态分布,呈现单峰分布;段塞流的功率谱在整个频率范围内随着频率增大而缓慢下降,频率范围内出现两个幅度比较明显的特征峰.利用PSD和PDF特征分析可以进行气液两相流的流型识别,为研究流型和管道系统设计提供帮助.

基于建模误差PDF形状的间歇过程数据驱动模型

间歇过程的优化控制依赖于过程精确的数学模型,数据驱动的建模方法是目前间歇过程模型研究中的热点问题。突破传统数据驱动建模方法中采用均方差(mean squared error,MSE)作为准则函数的思想,提出一种新颖的间歇过程数据驱动建模方法,引入了概率密度函数(probability density function,PDF)控制的概念,构造间歇过程模型误差控制系统,将模型的可调参数作为控制系统的输入,模型误差PDF的形状作为控制系统的输出,从而把开环模型参数辨识问题转化为模型误差PDF形状的闭环控制问题。通过可调参数控制模型误差PDF的空间分布状态,不仅能够保障模型精度,还可控制模型误差的空间分布状态,从而消除模型中的有色噪声。仿真实验表明,基于模型误差PDF形状的间歇过程数据驱动模型具有较好的建模精度、鲁棒性和泛化能力,为间歇过程的数据驱动建模提供了一条新途径。

随机分布系统基于广义H_∞控制的PDF跟踪控制

针对非高斯随机系统,提出了基于线性B样条逼近的广义系统建模方法;讨论了这类广义系统基于H∞状态反馈控制器的设计,解决了非高斯随机系统输出概率密度函数(PDF)跟踪控制和干扰抑制问题;基于线性矩阵不等式,得到了该问题H∞状态反馈控制器存在的充分必要条件。最后,运用仿真验证了所提出方法的有效性。

基于LES-PDF方法的双旋流模型燃烧室数值模拟

文章使用基于LES-PDF方法的AECSC两相程序,对模型燃烧室GTMC进行了数值模拟,以此验证AECSC程序对燃烧室模拟的可行性和可信度,并对旋流燃烧室的流动和燃烧特性进行分析.首先,分别用商用软件Fluent 18.1和AECSC程序的LES方法对GTMC的冷态工况进行了模拟.与实验结果相比,程序计算的轴向、径向、切向速度峰值的相对误差在大多数统计点上在20%以内,3个方向速度峰值位置的相对误差基本都在10%以内.同时发现,AECSC程序的计算结果在一定程度上比Fluent的计算结果更接近实验值.文章进一步使用AECSC程序对GTMC的热态工况进行了模拟.在计算结果中,整体的时间平均温度在数值和分布上和实验结果很接近,并很好地再现了实验的“V形”火焰和内外低温回流区,但是高温区出现的位置相比实验结果有些靠前.总体来说,热态结果和实验结果比较吻合,尤其在液雾的模拟方面,计算结果和实验结果相比有着很好的一致性.这说明将LES和PDF相结合的方法在模拟湍流燃烧方面有较强的优势,可以成为未来的研究和发展方向.

A probability density function of liftoff velocities in mixed-size wind sand flux

With the discrete element method(DEM) ,employing the diameter distribution of natural sands sampled from the Tengger Desert,a mixed-size sand bed was produced and the particle-bed collision was simulated in the mixed-size wind sand movement. In the simulation,the shear wind velocity,particle diameter,incident velocity and incident angle of the impact sand particle were given the same values as the experimental results. After the particle-bed collision,we collected all the initial velocities of rising sand particles,including the liftoff angular velocities,liftoff linear velocities and their horizontal and vertical components. By the statistical analysis on the velocity sample for each velocity component,its probability density functions were obtained,and they are the functions of the shear wind velocity. The liftoff velocities and their horizontal and vertical components are distributed as an exponential density function,while the angular velocities are distributed as a normal density function.

Study of detection performance of passive bistatic radars based on FM broadcast

The passive bistatic radar based on the FM broadcast has inherent superiority with respect to its survivability. In this article, the ambiguity function （AF） and the cross ambiguity function （CAF） of the FM radio signal are analyzed and illustrated. The Kolmogorov Smirnov （K-S） test verifies that the amplitude probability density function of the CAF side lobes is exponential; the distribution of the target is also deduced. Finally, the detection performance of the passive radar is studied, and the result shows that this new type bistatic radar has favorable detection capability.

Path integral solution of vibratory energy harvesting systems

A transition Fokker-Planck-Kolmogorov(FPK) equation describes the procedure of the probability density evolution whereby the dynamic response and reliability evaluation of mechanical systems could be carried out. The transition FPK equation of vibratory energy harvesting systems is a four-dimensional nonlinear partial differential equation. Therefore, it is often very challenging to obtain an exact probability density. This paper aims to investigate the stochastic response of vibration energy harvesters(VEHs)under the Gaussian white noise excitation. The numerical path integration method is applied to different types of nonlinear VEHs. The probability density function(PDF)from the transition FPK equation of energy harvesting systems is calculated using the path integration method. The path integration process is introduced by using the GaussLegendre integration scheme, and the short-time transition PDF is formulated with the short-time Gaussian approximation. The stationary probability densities of the transition FPK equation for vibratory energy harvesters are determined. The procedure is applied to three different types of nonlinear VEHs under Gaussian white excitations. The approximately numerical outcomes are qualitatively and quantitatively supported by the Monte Carlo simulation(MCS).

A hybrid LES (Large Eddy Simulation)/assumed sub-grid PDF (Probability Density Function) model for supersonic turbulent combustion

A hybrid LES (Large Eddy Simulation)/assumed sub-grid PDF (Probability Density Function) closure model has been devel-oped for supersonic turbulent combustion. Scalar transport equations for all species in a given chemical kinetic mechanism were solved, which are necessary in the supersonic combustion where the non-equilibrium chemistry is essentially involved. The clipped Gaussian PDF of temperature and multivariate ? PDF of composition were used to close the sub-grid chemical sources that appear in the conservation equations. The sub-grid variances of temperature and composition were constructed based on scale similarity approach. A semi-implicit approach based on the PDF model was proposed to tackle the resulting numerical stiffness associated with finite rate chemistry. The model was applied to simulate a supersonic, coaxial H2-air burner, where both the mean and rms (root mean square) results were compared with the experimental data. In general, good agree-ments were achieved, which indicated that the present sub-grid PDF method could work well in simulating supersonic turbu-lent combustion. Moreover, the calculation showed that the sub-grid fluctuations of temperature and major species in the combustion region were of the order of 10%-20% of their rms, while the sub-grid fluctuation of hydroxyl might be as high as 40%-50% of its rms.

Technique of Probability Density Function Shape Control for Nonlinear Stochastic Systems

The shape control of probability density function(PDF) of the system state is an important topic in stochastic systems. In this paper, we propose a control technique for PDF shape of the state variable in nonlinear stochastic systems. Firstly, we derive and prove the form of the controller by investigating the Fokker-PlanckKolmogorov(FPK) equation arising from the stochastic system. Secondly, an approach for getting approximate solution of the FPK equation is provided. A special function including some parameters is taken as the approximate stationary solution of the FPK equation. We use nonlinear least square method to solve the parameters in the function, and capture the approximate solution of the FPK equation. Substituting the approximate solution into the form of the controller, we can acquire the PDF shape controller. Lastly, some example simulations are conducted to verify the algorithm.

A Novel PDF Shape Control Approach for Nonlinear Stochastic Systems

In this work,a novel shape control approach of the probability density function(PDF)for nonlinear stochastic systems is presented.First,we provide the formula for the PDF shape controller without devising the control law of the controller.Then,based on the exact analytical solution of the Fokker-PlanckKolmogorov(FPK)equation,the product function of the polynomial and the exponential polynomial is regarded as the stationary PDF of the state response.To validate the performance of the proposed control approach,we compared it with the exponential polynomial method and the multi-Gaussian closure method by implementing comparative simulation experiments.The results show that the novel PDF shape control approach is effective and feasible.Using an equal number of parameters,our method can achieve a similar or better control effect as the exponential polynomial method.By comparison with the multiGaussian closure method,our method has clear advantages in PDF shape control performance.For all cases,the integral of squared error and the errors of first four moments of our proposed method were very small,indicating superior performance and promising good overall control effects of our method.The approach presented in this study provides an alternative for PDF shape control in nonlinear stochastic systems.