Transient probabilistic solutions of stochastic oscillator with even nonlinearities by exponential polynomial closure method

2021 ◽  
pp. 107754632098777
Author(s):  
Kun Wang ◽  
Zhihui Zhu ◽  
Lei Xu

The current work is devoted to analyze the transient probability density function solutions of stochastic oscillator with even nonlinearities under external excitation of Gaussian white noise by applying the extended exponential polynomial closure method. Specifically, the Fokker–Planck–Kolmogorov equation which governs the probability density function solutions of the nonlinear system is presented first. The residual error of the Fokker–Planck–Kolmogorov equation is then derived by assuming the probability density function solution as the type of exponential polynomial with time-dependent variables. Finally, by making the projection of the residual error vanish, a set of nonlinear ordinary differential equations is established and solved numerically. Numerical analysis show that the extended exponential polynomial closure method with polynomial order being six is both effective and efficient for solving the transient analysis of the stochastic oscillator with even nonlinearities by comparing the numerical results obtained by the proposed method with those obtained by Monte Carlo simulation method. Numerical results also show that the transient probability density function solutions of the system responses are not symmetric about their nonzero means due to the existence of even nonlinearities.

2012 ◽  
Vol 134 (5) ◽  
Author(s):  
Guo-Kang Er ◽  
Siu-Siu Guo ◽  
Vai Pan Iu

The probabilistic solutions of the nonlinear stochastic oscillators with even nonlinearity in displacement are investigated with the exponential-polynomial closure method. Numerical results show that the results obtained from the exponential-polynomial closure method agree well with the simulated solution in the presented case, even if the mean of displacement is nonzero and the probability density function of the displacement is nonsymmetric about its mean.


2011 ◽  
Vol 688 ◽  
pp. 219-257 ◽  
Author(s):  
Manav Tyagi ◽  
Patrick Jenny

AbstractA probabilistic approach to model macroscopic behaviour of non-wetting-phase ganglia or blobs in multi-phase flow through porous media is proposed. The key idea is to consider a set of stochastic Markov processes that can mimic the microscopic multi-phase dynamics. These processes are characterized by equilibrium probability density functions (PDFs) and correlation times, which can be obtained from micro-scale simulation studies or experiments. A Lagrangian viewpoint is adopted, where stochastic particles represent infinitesimal fluid elements and evolve in the physical and probability space. Ganglion mobilization and trapping are modelled by a two-state jump process with transition probabilities given as functions of ganglion size. Coalescence and breakup of ganglia influence the ganglion size distribution, which is modelled by a Langevin type equation. The joint probability density function (JPDF) of the chosen stochastic variables is governed by a high-dimensional Chapman–Kolmogorov equation. This equation can be used to derive moment (e.g. saturation, mean mobility etc.) transport equations, which in general do not form a closed system. However, in some special cases, which arise in the limit of one time scale being smaller or larger than the others, a closed set of moment transport equations can be obtained. For slowly varying and quasi-uniform flows, the saturation transport equation appears in closed form with the mean mobility fully determined, if the equilibrium PDFs are known. Furthermore, it is shown how statistical parameters such as mobilization and trapping rates and equilibrium PDFs can be obtained from the birth–death type approach, in which ganglia breakup and coalescence are explicitly considered. A two-equation transport model (one equation for the total saturation and one for the trapped saturation) is obtained in the limit of very fast coalescence and breakup processes. This model is employed to mimic hysteresis in relative permeability–saturation curves; a well known phenomenon observed in the successive processes of imbibition and drainage. For the general case, the JPDF-equation is solved using the stochastic particle method, which was proposed in our previous paper (Tyagi et al. J. Comput. Phys. 227, 2008, 6696–6714). Several one- and two-dimensional numerical simulation results are presented to show the influence of correlation times on the averaged macroscopic flow behaviour.


2012 ◽  
Vol 09 (01) ◽  
pp. 1240018 ◽  
Author(s):  
H. T. ZHU ◽  
G. K. ER ◽  
V. P. IU ◽  
K. P. KOU

The probability density function (PDF) solution of the response is formulated for nonlinear systems under discrete Poisson impulse excitation. The PDF solution is governed by the Kolmogorov–Feller (KF) equation, which is approximately solved by the exponential–polynomial closure (EPC) method. A Duffing oscillator is further investigated in the case of either Gaussian or non-Gaussian distributed amplitude of Poisson impulse to show the effectiveness of the EPC method in these cases. The numerical analysis shows that the EPC method with the polynomial order being 6 presents a good result compared with the simulated result, even in the tails of the PDF of the oscillator response.


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