Path Integrals in Stochastic Engineering Dynamics

Inbunden, Engelska, 2024

Av Ioannis A. Kougioumtzoglou, Apostolos F. Psaros, Pol D. Spanos

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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.

Produktinformation

Utgivningsdatum2024-06-06
Mått155 x 235 x 18 mm
Vikt580 g
FormatInbunden
SpråkEngelska
Antal sidor228
FörlagSpringer International Publishing AG
ISBN9783031578625

Tillhör följande kategorier

Introduction.- Wiener path integral formalism.- Linearsystems under Gaussian white noise excitation: exact closed form solutions.- Nonlinearsystems under Gaussian white noise excitation.- Nonlinear systems undernon-white, non-Gaussian and non-stationary excitation.- Nonlinear systems with singulardiffusion matrices: a broad perspective including hysteresis modeling.- High-dimensionalnonlinear systems: circumventing the curse of dimensionality via areduced-order formulation.- Efficient numerical implementation strategies viasparse representations and compressive sampling.- An enhanced quadratic Wienerpath integral approximation with applications to nonlinear system reliabilityassessment.- Epilogue.