Stochastic dynamic analysis of the nonlinear system is an open research question which has drawn many scholars'attention for its importance and challenge.Fokker–Planck–Kolmogorov(FPK)equation is of great signifi...Stochastic dynamic analysis of the nonlinear system is an open research question which has drawn many scholars'attention for its importance and challenge.Fokker–Planck–Kolmogorov(FPK)equation is of great significance because of its theoretical strictness and computational accuracy.However,practical difficulties with the FPK method appear when the analysis of multi-degree-offreedom(MDOF)with more general nonlinearity is required.In the present paper,by invoking the idea of equivalence of probability flux,the general high-dimensional FPK equation related to MDOF system is reduced to one-dimensional FPK equation.Then a cell renormalized method(CRM)which is based on the numerical reconstruction of the derived moments of FPK equation is introduced by coarsening the continuous state space into a discretized region of cells.Then the cell renormalized FPK(CR-FPK)equation is solved by difference method.Three numerical examples are illustrated and the effectiveness of proposed method is assessed and verified.展开更多
In this paper, the method proposed recently by the author for the solution of probability density function (PDF) of nonlinear stochastic systems is presented in detail and extended for more general problems of stochas...In this paper, the method proposed recently by the author for the solution of probability density function (PDF) of nonlinear stochastic systems is presented in detail and extended for more general problems of stochastic differential equations (SDE), therefore the Fokker Planck Kolmogorov (FPK) equation is expressed in general form with no limitation on the degree of nonlinearity of the SDE, the type of δ correlated excitations, the existence of multiplicative excitations, and the dimension of SDE or FPK equation. Examples are given and numerical results are provided for comparing with known exact solution to show the effectiveness of the method.展开更多
The Fokker–Planck–Kolmogorov（FPK） equation plays an essential role in nonlinear stochastic dynamics. However, neither analytical nor numerical solution is available as yet to FPK equations for high-dimensional sys...The Fokker–Planck–Kolmogorov（FPK） equation plays an essential role in nonlinear stochastic dynamics. However, neither analytical nor numerical solution is available as yet to FPK equations for high-dimensional systems. In the present paper, the dimension reduction of FPK equation for systems excited by additive white noise is studied. In the proposed method, probability density evolution method（PDEM）, in which a decoupled generalized density evolution equation is solved, is employed to reproduce the equivalent flux of probability for the marginalized FPK equation. A further step of constructing an equivalent coefficient finally completes the dimension-reduction of FPK equation. Examples are illustrated to verify the proposed method.展开更多
文摘Stochastic dynamic analysis of the nonlinear system is an open research question which has drawn many scholars'attention for its importance and challenge.Fokker–Planck–Kolmogorov(FPK)equation is of great significance because of its theoretical strictness and computational accuracy.However,practical difficulties with the FPK method appear when the analysis of multi-degree-offreedom(MDOF)with more general nonlinearity is required.In the present paper,by invoking the idea of equivalence of probability flux,the general high-dimensional FPK equation related to MDOF system is reduced to one-dimensional FPK equation.Then a cell renormalized method(CRM)which is based on the numerical reconstruction of the derived moments of FPK equation is introduced by coarsening the continuous state space into a discretized region of cells.Then the cell renormalized FPK(CR-FPK)equation is solved by difference method.Three numerical examples are illustrated and the effectiveness of proposed method is assessed and verified.
文摘In this paper, the method proposed recently by the author for the solution of probability density function (PDF) of nonlinear stochastic systems is presented in detail and extended for more general problems of stochastic differential equations (SDE), therefore the Fokker Planck Kolmogorov (FPK) equation is expressed in general form with no limitation on the degree of nonlinearity of the SDE, the type of δ correlated excitations, the existence of multiplicative excitations, and the dimension of SDE or FPK equation. Examples are given and numerical results are provided for comparing with known exact solution to show the effectiveness of the method.
基金supported by the National Natural Science Foundation of China(11172210)the Shuguang Program of Shanghai City(11SG21)
文摘The Fokker–Planck–Kolmogorov（FPK） equation plays an essential role in nonlinear stochastic dynamics. However, neither analytical nor numerical solution is available as yet to FPK equations for high-dimensional systems. In the present paper, the dimension reduction of FPK equation for systems excited by additive white noise is studied. In the proposed method, probability density evolution method（PDEM）, in which a decoupled generalized density evolution equation is solved, is employed to reproduce the equivalent flux of probability for the marginalized FPK equation. A further step of constructing an equivalent coefficient finally completes the dimension-reduction of FPK equation. Examples are illustrated to verify the proposed method.
