Nonstationary Stochastic Response Determination of Nonlinear Systems: A Wiener Path Integral Formalism

AbstractA novel approximate analytical technique is developed for determining the nonstationary response probability density function (PDF) of randomly excited nonlinear multidegree-of-freedom (MDOF) systems. Specifically, the concept of the Wiener path integral (WPI) is used in conjunction with a variational formulation to derive an approximate closed-form solution for the system response PDF. Notably, determining the nonstationary response PDF is accomplished without the need to advance the solution in short time steps as it is required by existing alternative numerical path integral solution schemes, which rely on a discrete version of the Chapman-Kolmogorov (C-K) equation. In this manner, the analytical WPI-based technique developed by the authors is extended and generalized herein to account for hysteretic nonlinearities and MDOF systems. This enhancement of the technique affords circumventing approximations associated with the stochastic averaging treatment of the previously developed technique. Hop...

[1]  A. V. Skorohod,et al.  The theory of stochastic processes , 1974 .

[2]  P. Spanos,et al.  Harmonic wavelet-based statistical linearization of the Bouc-Wen hysteretic model , 2011 .

[3]  P. Spanos,et al.  Harmonic wavelets based statistical linearization for response evolutionary power spectrum determination , 2012 .

[4]  P. Spanos,et al.  Response and First-Passage Statistics of Nonlinear Oscillators via a Numerical Path Integral Approach , 2013 .

[5]  R. Bouc Forced Vibration of Mechanical Systems with Hysteresis , 1967 .

[6]  A functional Stieltjes measure and generalized diffusion processes , 1977 .

[7]  E. Tirapegui,et al.  Functional integrals and the Fokker-Planck equation , 1979 .

[8]  B. Øksendal Stochastic differential equations : an introduction with applications , 1987 .

[9]  Hermann Haken,et al.  Generalized Onsager-Machlup function and classes of path integral solutions of the Fokker-Planck equation and the master equation , 1976 .

[10]  Arvid Naess,et al.  Stationary and non-stationary random vibration of oscillators with bilinear hysteresis , 1996 .

[11]  H. Dekker Time-local gaussian processes, path integrals and nonequilibrium nonlinear diffusion , 1976 .

[12]  Y. Wen Method for Random Vibration of Hysteretic Systems , 1976 .

[13]  L. Arnold Stochastic Differential Equations: Theory and Applications , 1992 .

[14]  Y. K. Wen,et al.  Methods of Random Vibration for Inelastic Structures , 1989 .

[15]  Paolo Nistri,et al.  Mathematical Models for Hysteresis , 1993, SIAM Rev..

[16]  C. W. Gardiner,et al.  Handbook of stochastic methods - for physics, chemistry and the natural sciences, Second Edition , 1986, Springer series in synergetics.

[17]  Arvid Naess,et al.  Reliability of systems with randomly varying parameters by the path integration method , 2011 .

[18]  D. Falkoff Statistical theory of irrversible processes: Part I. Intergral over fluctuation path formulation , 1958 .

[19]  G. Cai,et al.  Reliability of Nonlinear Structural Frame Under Seismic Excitation , 1998 .

[20]  W. Horsthemke,et al.  Onsager-Machlup Function for one dimensional nonlinear diffusion processes , 1975 .

[21]  Pol D. Spanos,et al.  Survival Probability Determination of Nonlinear Oscillators Subject to Evolutionary Stochastic Excitation , 2014 .

[22]  A. Naess,et al.  Response statistics of nonlinear, compliant offshore structures by the path integral solution method , 1993 .

[23]  Robert Graham,et al.  Path integral formulation of general diffusion processes , 1977 .

[24]  R. Santoro,et al.  Path integral solution for non-linear system enforced by Poisson White Noise , 2008 .

[25]  Patrick Habets,et al.  Two-Point Boundary Value Problems: Lower and Upper Solutions , 2012 .

[26]  E. Cohen,et al.  Inertial Effects in Nonequilibrium Work Fluctuations by a Path Integral Approach , 2007, 0706.1199.

[27]  Jianbing Chen,et al.  Stochastic Dynamics of Structures , 2009 .

[28]  F. Ikhouane,et al.  Systems with Hysteresis: Analysis, Identification and Control Using the Bouc-Wen Model , 2007 .

[29]  H. D. Miller,et al.  The Theory Of Stochastic Processes , 1977, The Mathematical Gazette.

[30]  W. G. Wolfer,et al.  Numerical evaluation of path-integral solutions to Fokker-Planck equations. III. Time and functionally dependent coefficients. , 1987, Physical review. A, General physics.

[31]  Mohammed Ismail,et al.  The Hysteresis Bouc-Wen Model, a Survey , 2009 .

[32]  Yu-Kweng Michael Lin Probabilistic Theory of Structural Dynamics , 1976 .

[33]  Isaak D. Mayergoyz,et al.  The science of hysteresis , 2005 .

[34]  R. Eisenschitz Statistical theory of irreversible processes , 1958 .

[35]  Pol D. Spanos,et al.  An approximate approach for nonlinear system response determination under evolutionary stochastic excitation , 2009 .

[36]  M. Grigoriu Stochastic Calculus: Applications in Science and Engineering , 2002 .

[37]  A. Pirrotta,et al.  Probabilistic response of nonlinear systems under combined normal and Poisson white noise via path integral method , 2011 .

[38]  Pol D. Spanos,et al.  Nonlinear MDOF system stochastic response determination via a dimension reduction approach , 2013 .

[39]  F. Witte,et al.  Book Review: Path Integrals in Quantum Mechanics, Statistics, Polymer Physics and Financial Markets. Prof. Dr. Hagen Kleinert, 3rd extended edition, World Scientific Publishing, Singapore , 2003 .

[40]  R. Feynman,et al.  Space-Time Approach to Non-Relativistic Quantum Mechanics , 1948 .

[41]  Applications of diffusion models to reliability analysis of Daniels systems , 1990 .

[42]  Jianbing Chen,et al.  Stochastic seismic response analysis of structures exhibiting high nonlinearity , 2010 .

[43]  P. Spanos,et al.  An analytical Wiener path integral technique for non-stationary response determination of nonlinear oscillators , 2012 .

[44]  Lars Onsager,et al.  Fluctuations and Irreversible Processes , 1953 .

[45]  L. Tisza,et al.  Fluctuations and irreversible thermodynamics , 1957 .

[46]  Marc P. Mignolet,et al.  Random Plastic Analysis Using a Constitutive Model to Predict the Evolutionary Stress-Related Responses and Time Passages to Failure , 2008 .

[47]  M. Wehner Numerical Evaluation of Path Integral Solutions to Fokker-Planck Equations with Application to Void Formation. , 1983 .

[48]  Ravi P. Agarwal,et al.  Ordinary and Partial Differential Equations: With Special Functions, Fourier Series, and Boundary Value Problems , 2008 .

[49]  Y. Wen Equivalent Linearization for Hysteretic Systems Under Random Excitation , 1980 .

[50]  D. Dürr,et al.  Functionals of paths of a diffusion process and the Onsager-Machlup function , 1977 .

[51]  Michael F. Wehner,et al.  Numerical evaluation of path-integral solutions to Fokker-Planck equations. II. Restricted stochastic processes , 1983 .

[52]  T. T. Soong,et al.  Random Vibration of Mechanical and Structural Systems , 1992 .

[53]  Alex H. Barbat,et al.  Equivalent linearization of the Bouc-Wen hysteretic model , 2000 .

[54]  P. Spanos,et al.  Random vibration and statistical linearization , 1990 .

[55]  Lars Onsager,et al.  Fluctuations and Irreversible Process. II. Systems with Kinetic Energy , 1953 .

[56]  Lawrence F. Shampine,et al.  Solving ODEs with MATLAB , 2002 .

[57]  Yi-Kwei Wen,et al.  Stochastic response and damage analysis of inelastic structures , 1986 .

[58]  R. Feynman,et al.  Quantum Mechanics and Path Integrals , 1965 .

[59]  Derivation of quasideterministic Fokker-Planck dynamics , 1978 .

[60]  H. Risken The Fokker-Planck equation : methods of solution and applications , 1985 .

[61]  Detlef Dürr,et al.  The Onsager-Machlup function as Lagrangian for the most probable path of a diffusion process , 1978 .

[62]  Fayal Ikhouane,et al.  Systems with Hysteresis , 2007 .

[63]  H. Kleinert Path Integrals in Quantum Mechanics, Statistics, Polymer Physics, and Financial Markets , 2006 .

[64]  George M. Ewing Calculus of Variations with Applications , 2016 .

[65]  N. Wiener The Average of an Analytic Functional. , 1921, Proceedings of the National Academy of Sciences of the United States of America.