Journal ArticleDOI
A review of indirect/non-intrusive reduced order modeling of nonlinear geometric structures
TLDR
In this article, a review of reduced order modeling techniques for geometrically nonlinear structures, more specifically those techniques that are applicable to structural models constructed using commercial finite element software, is presented.About:
This article is published in Journal of Sound and Vibration.The article was published on 2013-05-13. It has received 286 citations till now. The article focuses on the topics: Finite element method & Nonlinear system.read more
Citations
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Digital Twin: Values, Challenges and Enablers From a Modeling Perspective
TL;DR: This work reviews the recent status of methodologies and techniques related to the construction of digital twins mostly from a modeling perspective to provide a detailed coverage of the current challenges and enabling technologies along with recommendations and reflections for various stakeholders.
Application of nonlinear systems theory to transonic unsteady aerodynamic responses
TL;DR: In this article, a methodology for using the Volterra-Wiener theory of nonlinear systems in aeroservoelastic (ASE) analyses and design is presented, based on unit impulse responses, and applied to a simple bilinear single-input-single-output (SISO) system.
Journal ArticleDOI
A deep learning enabler for nonintrusive reduced order modeling of fluid flows
TL;DR: In this paper, a modular deep neural network (DNN) framework for data-driven reduced order modeling of dynamical systems relevant to fluid flows is proposed. But it is not suitable for modeling complex fluid flows.
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An artificial neural network framework for reduced order modeling of transient flows
TL;DR: In this article, a supervised machine learning framework for the non-intrusive model order reduction of unsteady fluid flows is proposed to provide accurate predictions of non-stationary state variables when the control parameter values vary.
Journal ArticleDOI
A deep learning enabler for non-intrusive reduced order modeling of fluid flows
TL;DR: A modular deep neural network (DNN) framework for data-driven reduced order modeling of dynamical systems relevant to fluid flows is introduced and can be used as a robust predictive tool for non-intrusive model order reduction of complex fluid flows.
References
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Book
Nonlinear Continuum Mechanics for Finite Element Analysis
Javier Bonet,Richard D. Wood +1 more
TL;DR: Bonet and Wood as discussed by the authors provide a complete, clear, and unified treatment of nonlinear continuum analysis and finite element techniques under one roof, providing an essential resource for postgraduates studying non-linear continuum mechanics and ideal for those in industry requiring an appreciation of the way in which their computer simulation programs work.
Book
Classical and Computational Solid Mechanics
TL;DR: In this paper, a tensor analysis of strain conservation laws elastic and plastic behaviour of materials linearized theory of elasticity solutions of problems by potentials two-dimensional problems in variational calculus, energy theorems, Saint-Venant's principle Hamilton's principle, wave propagation, applications of generalized co-ordinates elasticity and thermodynamics irreversible thermodynamics and viscoelasticity thermoelasticness visco-elasticy large deformation incremental approach to solving some nonlinear problems.
Journal ArticleDOI
On the physical interpretation of proper orthogonal modes in vibrations
Brian F. Feeny,R. V. Kappagantu +1 more
TL;DR: In this article, the authors relate the proper orthogonal modes, as applied in discrete vibration systems, to normal modes of vibration in systems with a known mass matrix in the case of undamped free vibration.
Journal ArticleDOI
On Structural Fatigue Under Random Loading
TL;DR: In this paper, the authors studied the stress spectrum and the "equivalent fatigue stress" of an elastic structure subjected to random loading, and derived a similarity expression for the probable value of the equivalent fatigue stress of a panel subjected to buffeting.
Journal ArticleDOI
Determination of nonlinear stiffness with application to random vibration of geometrically nonlinear structures
TL;DR: In this paper, a method for determining the nonlinear modal stiffness coefficients for an arbitrary finite element model is presented, which is suitable for use with commercial finite element codes having a geometrically nonlinear static capability.