Path integral techniques and Gröbner basis approaches for stochastic response analysis and optimization of diverse nonlinear dynamic systems

This thesis focuses primarily on generalizations and enhancements of the Wiener path integral (WPI) technique for stochastic response analysis and optimization of diverse nonlinear dynamic systems of engineering interest. Concisely, the WPI technique, which has proven to be a potent mathematical tool in theoretical physics, has been recently extended to address problems in stochastic engineering dynamics. Herein, the WPI technique has been significantly enhanced in terms of computational efficiency and versatility; these results are presented in Chapters 2-5. Specifically, in Chapter 2 a brief introduction to the standard WPI solution approach is outlined. In Chapter 3, a novel methodology is presented, which utilizes theoretical results from calculus of variations to extend the WPI for determining marginalized response PDFs of n-degree-of-freedom (n-DOF) nonlinear systems. The associated computational cost relates to the dimension of the PDF and is essentially independent from the dimension n of the system. In several commonly encountered cases, the aforementioned methodology improves the computational efficiency of the WPI by orders of magnitude, and exhibits a significant advantage over the commonly utilized Monte-Carlo-simulation (MCS). Moreover, in Chapter 4, an extension of the WPI technique is presented for addressing the challenge of determining the stochastic response of nonlinear dynamical systems under the presence of singularities in the diffusion matrix. The key idea behind this approach is to partition the original system into an underdetermined system of SDEs corresponding to a nonsingular diffusion matrix and an underdetermined system of homogeneous differential equations; the latter is treated as a dynamic constraint that allows for employing constrained variational/optimization solution methods. In Chapter 5, this approach is applied for the stochastic response analysis and optimization of electromechanical vibratory energy harvesters. Next, in Chapter 6, a technique from computational algebraic geometry has been developed, which is based on the concept of Gröbner basis and is capable of determining the entire solution set of systems of polynomial equations. This technique has been utilized to address diverse challenging problems in engineering mechanics. First, after formulating the WPI as a minimization problem, it is shown in Chapter 7 that the corresponding objective function is convex, and thus, convergence of numerical schemes to the global optimum is guaranteed. Second, in Chapter 8, the computational algebraic geometry technique has been applied to the challenging problem of determining nonlinear normal modes (NNMs) corresponding to multi-degree-of-freedom dynamical systems as defined in [1], and has been shown to yield improvements in accuracy compared to the standard treatment in the literature.