Topology optimization of structures subjected to stochastic dynamic excitation
type: CreativeWork
description: The field of topology optimization has progressed substantially in recent years, with applications varying in terms of the type of structures, boundary conditions, loadings, and materials. Nevertheless, topology optimization of stochastically excited structural systems has received relatively little attention. Due to the vast number of degrees of freedom typically required for topology optimization, conventional approaches for solving the random vibration problem are time prohibitive; moreover, the application of non-gradient-based optimization algorithms is not feasible due to the extensive number of design variables. Consequently, new techniques are required to obtain the response due to stochastic excitation and perform the sensitivity analysis of these quantities efficiently for large systems. In this research, a direct approach to this problem is proposed, modeling the excitation as a filtered white noise. The excitation model is combined with the structural model to form an augmented representation, and the covariance of the structural response is obtained by solving a Lyapunov equation. The objective function is defined in terms of the response covariance. For the stationary problem, a fast large-scale solver of the Lyapunov equation is implemented for sparse matrices; and an efficient adjoint method is proposed to obtain the sensitivities of the objective function. Model reduction techniques are also considered to improve the efficiency of the approach for buildings. The proposed formulation and numerical solutions are extended to consider other representative problems such as non-stationary excitations or minimizing the maximum response. Furthermore, the proposed method is extended to perform simultaneous optimization of topology and supplemental damping distribution of buildings subjected to stochastic dynamic excitation. The proposed topology optimization framework and its components are illustrated through several numerical examples: application to ideal…
abstract: The field of topology optimization has progressed substantially in recent years, with applications varying in terms of the type of structures, boundary conditions, loadings, and materials. Nevertheless, topology optimization of stochastically excited structural systems has received relatively little attention. Due to the vast number of degrees of freedom typically required for topology optimization, conventional approaches for solving the random vibration problem are time prohibitive; moreover, the application of non-gradient-based optimization algorithms is not feasible due to the extensive number of design variables. Consequently, new techniques are required to obtain the response due to stochastic excitation and perform the sensitivity analysis of these quantities efficiently for large systems. In this research, a direct approach to this problem is proposed, modeling the excitation as a filtered white noise. The excitation model is combined with the structural model to form an augmented representation, and the covariance of the structural response is obtained by solving a Lyapunov equation. The objective function is defined in terms of the response covariance. For the stationary problem, a fast large-scale solver of the Lyapunov equation is implemented for sparse matrices; and an efficient adjoint method is proposed to obtain the sensitivities of the objective function. Model reduction techniques are also considered to improve the efficiency of the approach for buildings. The proposed formulation and numerical solutions are extended to consider other representative problems such as non-stationary excitations or minimizing the maximum response. Furthermore, the proposed method is extended to perform simultaneous optimization of topology and supplemental damping distribution of buildings subjected to stochastic dynamic excitation. The proposed topology optimization framework and its components are illustrated through several numerical examples: application to ideal…
author: Gomez Sanchez, Fernando Daniel
language: en
keywords: Topology optimization, stochastic dynamics, Lyapunov equation, seismic design, wind design, damping devices, finite element
date published: 2021-09-17T02:34:44Z
date modified: 2026-07-22T22:24:52Z
provider: University of Illinois - Urbana-Champaign
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Illinois at Urbana-Champaign

PropertyValue
property ID: Handle
value: http://hdl.handle.net/2142/110728