Insights through Modal Minimal Models for Analysis of Linear and Nonlinear Dynamic Problems

Dynamic analysis of three-dimensional structures is common practice in industry to optimize products and in research to gain insights on the influence of parameters. The complexity differs based on the linearity or nonlinearity of the underlying problem, the type of excitation, e.g., forced or self-...

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Published inShock and vibration Vol. 2022; pp. 1 - 8
Main Authors Hohl, Andreas, Kulke, Vincent, Ostermeyer, Georg-Peter
Format Journal Article
LanguageEnglish
Published Cairo Hindawi 24.01.2022
John Wiley & Sons, Inc
Wiley
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ISSN1070-9622
1875-9203
DOI10.1155/2022/6888399

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Abstract Dynamic analysis of three-dimensional structures is common practice in industry to optimize products and in research to gain insights on the influence of parameters. The complexity differs based on the linearity or nonlinearity of the underlying problem, the type of excitation, e.g., forced or self-excitation, and the number of degrees of freedom that need to be examined. Reduced order models and optimized numerical methods are used to optimize the time and computational power needed to gain a certain insight. This article focusses on a specific class of problems where the modes of the structure do not or do not significantly change through the (damping) device or force that is added to the structure. Herein, lumped mass models are commonly used for analysis of the dynamic response of the system. In the article, it is highlighted that lumped mass models can give quantitative insight but modally reduced models allow a direct optimization of the problems with respect to the physical degree of freedom that, for example, is subject to self-excitation or dampened. The benefit of modal minimal models and its limitations are shown and discussed for different linear and nonlinear dynamic problems.
AbstractList Dynamic analysis of three-dimensional structures is common practice in industry to optimize products and in research to gain insights on the influence of parameters. The complexity differs based on the linearity or nonlinearity of the underlying problem, the type of excitation, e.g., forced or self-excitation, and the number of degrees of freedom that need to be examined. Reduced order models and optimized numerical methods are used to optimize the time and computational power needed to gain a certain insight. This article focusses on a specific class of problems where the modes of the structure do not or do not significantly change through the (damping) device or force that is added to the structure. Herein, lumped mass models are commonly used for analysis of the dynamic response of the system. In the article, it is highlighted that lumped mass models can give quantitative insight but modally reduced models allow a direct optimization of the problems with respect to the physical degree of freedom that, for example, is subject to self-excitation or dampened. The benefit of modal minimal models and its limitations are shown and discussed for different linear and nonlinear dynamic problems.
Audience Academic
Author Hohl, Andreas
Ostermeyer, Georg-Peter
Kulke, Vincent
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10.1016/j.ymssp.2011.05.011
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Copyright Copyright © 2022 Andreas Hohl et al.
COPYRIGHT 2022 John Wiley & Sons, Inc.
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SubjectTerms Damping
Degrees of freedom
Dynamic response
Dynamical systems
Energy dissipation
Excitation
Interfaces
Linearity
Nonlinear dynamics
Nonlinearity
Numerical methods
Optimization
Partial differential equations
Reduced order models
Three dimensional analysis
Velocity
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Title Insights through Modal Minimal Models for Analysis of Linear and Nonlinear Dynamic Problems
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