Pol D. Spanos – författare

This monograph considers engineering systems with random parame­ ters. Its context, format, and timing are correlated with the intention of accelerating the evolution of the challenging field of Stochastic Finite Elements. The random system parameters are modeled as second order stochastic processes defined by their mean and covari­ ance functions. Relying on the spectral properties of the covariance function, the Karhunen-Loeve expansion is used'' to represent these processes in terms of a countable set of un correlated random vari­ ables. Thus, the problem is cast in a finite dimensional setting. Then, various spectral approximations for the stochastic response of the system are obtained based on different criteria. Implementing the concept of Generalized Inverse as defined by the Neumann Ex­ pansion, leads to an explicit expression for the response process as a multivariate polynomial functional of a set of un correlated random variables. Alternatively, the solution process is treated as an element in the Hilbert space of random functions, in which a spectral repre­ sentation in terms of the Polynomial Chaoses is identified. In this context, the solution process is approximated by its projection onto a finite subspace spanned by these polynomials.

This monograph considers engineering systems with random parame­ ters. Its context, format, and timing are correlated with the intention of accelerating the evolution of the challenging field of Stochastic Finite Elements. The random system parameters are modeled as second order stochastic processes defined by their mean and covari­ ance functions. Relying on the spectral properties of the covariance function, the Karhunen-Loeve expansion is used' to represent these processes in terms of a countable set of un correlated random vari­ ables. Thus, the problem is cast in a finite dimensional setting. Then, various spectral approximations for the stochastic response of the system are obtained based on different criteria. Implementing the concept of Generalized Inverse as defined by the Neumann Ex­ pansion, leads to an explicit expression for the response process as a multivariate polynomial functional of a set of un correlated random variables. Alternatively, the solution process is treated as an element in the Hilbert space of random functions, in which a spectral repre­ sentation in terms of the Polynomial Chaoses is identified. In this context, the solution process is approximated by its projection onto a finite subspace spanned by these polynomials.

This book organizes and explains, in a systematic and pedagogically effective manner, recent advances in path integral solution techniques with applications in stochastic engineering dynamics. It fills a gap in the literature by introducing to the engineering mechanics community, for the first time in the form of a book, the Wiener path integral as a potent uncertainty quantification tool. Since the path integral flourished within the realm of quantum mechanics and theoretical physics applications, most books on the topic have focused on the complex-valued Feynman integral with only few exceptions, which present path integrals from a stochastic processes perspective. Remarkably, there are only few papers, and no books, dedicated to path integral as a solution technique in stochastic engineering dynamics. Summarizing recently developed techniques, this volume is ideal for engineering analysts interested in further establishing path integrals as an alternative potent conceptual and computational vehicle in stochastic engineering dynamics.

This book organizes and explains, in a systematic and pedagogically effective manner, recent advances in path integral solution techniques with applications in stochastic engineering dynamics. It fills a gap in the literature by introducing to the engineering mechanics community, for the first time in the form of a book, the Wiener path integral as a potent uncertainty quantification tool. Since the path integral flourished within the realm of quantum mechanics and theoretical physics applications, most books on the topic have focused on the complex-valued Feynman integral with only few exceptions, which present path integrals from a stochastic processes perspective. Remarkably, there are only few papers, and no books, dedicated to path integral as a solution technique in stochastic engineering dynamics. Summarizing recently developed techniques, this volume is ideal for engineering analysts interested in further establishing path integrals as an alternative potent conceptual and computational vehicle in stochastic engineering dynamics.

This symposium is the seventh of a series of IUTAM sponsored symposia which focus on probabilistic methods in mechanics. It is the sequel to the series of meetings in Coventry, UK (1972), Southhampton, UK (1976), Frankfurt/Oder, Germany (1982), Stockholm, Sweden (1984), Innsbruck/Igls, Austria (1987), and Turin, Italy (1991). The symposium focused on advances in the area of probabilistic mechanics with direct application to structural reliability issues. The contributed papers address collectively the four components of a structural reliability problem. They are: characterization of stochastic loads, description of material properties in terms of fatigue and fracture, response determination, and quantitative assessment of the reliability of the structural system. Four Keynote Lectures by V. Bolotin (Russia), o. Ditlevsen (Denmark), R. Heller (USA), and F. Ziegler (Austria) were delivered; the remaining contributed papers were organized in ten technical sessIons. A reception was hosted by Dr. Y. Wu the first day of the symposium; the second day of the symposium a banquet was hosted by Dr. P. Spanos, with Dr. N. Abramson serving as the banquet speaker. Closing remarks were provided by the IUTAM Secretary General, Dr. F. Ziegler.