자료유형  

 학위논문

Control Number  

0016933335

International Standard Book Number  

9798379908683

Dewey Decimal Classification Number  

624

Main Entry-Personal Name  

Seawright, Jordan.

Publication, Distribution, etc. (Imprint  

[S.l.] : University of Washington., 2023

Publication, Distribution, etc. (Imprint  

Ann Arbor : ProQuest Dissertations & Theses, 2023

Physical Description  

1 online resource(123 p.)

General Note  

Source: Dissertations Abstracts International, Volume: 85-01, Section: B.

General Note  

Advisor: Wiebe, Richard;Perez, Ricardo.

Dissertation Note  

Thesis (Ph.D.)--University of Washington, 2023.

Restrictions on Access Note  

This item must not be sold to any third party vendors.

Summary, Etc.  

요약A reduction in the number of Degrees Of Freedom (DOFs) of a nonlinear structural model can significantly decrease the computational time of dynamic analyses, especially in problems where long analyses are required. A Reduced-Order Model (ROM) of a structural system can be generated using some combination of dimensionality reduction techniques, such as substitution of a modal basis or static condensation of membrane DOFs. Perhaps the most common and widespread framework for developing low-order models of continuous systems is the Ritz method in conjunction with a smooth modal basis. The Ritz method requires access to the closed form governing differential equations and is difficult to implement for problems with complex boundary conditions. In recent decades, an alternative framework that instead constructs a low-order model from an existing Finite Element Model (FEM) has been developed. Such models are typically known as NonLinear Reduced-Order Models (NLROMs). Such NLROMs can be used to handle complex boundary conditions so long as the FEM can do the same, and they allow the analyst to start from an existing finite element package as opposed to directly working with the governing differential equations. The form of the NLROM restoring force function is assumed by the analyst prior to identifying the model, and the parameters of the function are identified to achieve a high-quality fit to the FEM load-displacement data.This research aims in part to use Ritz method approximations to analytically predict the model parameters of identified NLROMs. Specifically, the shallow von Karman beam equation is used as a basis for the study of geometrically nonlinear beams. An approximate form of the statically Condensed Von Karman (CVK) beam equation is attained using the Ritz method, and the equivalence between the CVK coefficients and the NLROM coefficients is shown. In another study, the matrix and vector parameters of the CVK beam equation are treated as parameters to be identified from an FEM rather than being derived analytically using the properties of the structure. A simplified identification procedure is proposed which requires only two static solutions of an FEM, regardless of the number of modes included in the reduced-order basis. An arc-length continuation algorithm is used to predict the static load-displacement response of the models studied and to assess the accuracy of the ROMs. In the case of initially straight, post-buckled beams, the proposed identification procedure is shown to generate a model that generally outperforms a corresponding NLROM identified using conventional parameter identification techniques.Identifying NLROMs from beams with large initial curvature has frequently been accompanied by numerical stability issues. This work implements a displacement-based implicit condensation approach to the reduced-order model identification of curved beams that allows for the precise specification of transverse displacements in mid- and post-snap-through configurations. The configurations used to generate training data are extracted from points of interest on the static equilibrium path, which is determined using an arc-length method. The error in the reduced-order model approximation is characterized and plotted versus the arc-length step, and the improvements in targeted areas of the response are demonstrated. It is determined that specifying additional training data around mid- and post-snap-through configurations significantly improves the accuracy of the large-deformation response and model stability. It is shown that the simplified restoring force template provides comparable results to the full restoring force in a form with significantly fewer parameters.As a third application, a substructuring approach is used to reduce the order of a plane stress FEM of a deep planar beam. The model is divided into two substructures-one modeled with a full-order FEM and one modeled with an NLROM. The coupling between the NLROM substructure and the FEM substructure is accomplished using interface modes which represent the characteristic response of the structure at the interface. Directly coupling the NLROM and FEM substructures results in elevated errors in the stresses at the interface. A transition zone is added between the NLROM and FEM substructures, whereby certain DOFs that were expanded as a function of the NLROM DOFs are instead modeled as full-order finite element DOFs. Using a transition zone of approximately one beam depth proved to be effective in reducing the stress errors to acceptable levels. A multi-layer beam was successfully modeled using an identified interface mode that reflected the thickness-varying material properties of the beam.

Subject Added Entry-Topical Term  

Civil engineering.

Subject Added Entry-Topical Term  

Engineering.

Subject Added Entry-Topical Term  

Materials science.

Index Term-Uncontrolled  

Degrees Of Freedom

Index Term-Uncontrolled  

Structural model

Index Term-Uncontrolled  

Material properties

Index Term-Uncontrolled  

Condensed Von Karman

Index Term-Uncontrolled  

Reduction techniques

Added Entry-Corporate Name  

University of Washington Civil and Environmental Engineering

Host Item Entry  

Dissertations Abstracts International. 85-01B.

Host Item Entry  

Dissertation Abstract International

Electronic Location and Access  

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Control Number  

joongbu:639755