Sensitivity analysis of frequency response functions of composite sandwich plates containing viscoelastic layers

Lima, Antônio Marcos Gonçalves de; Faria, Albert Willian; Rade, Domingos A.

doi:10.1016/j.compstruct.2009.08.017

Cited by 46 publications

(31 citation statements)

References 10 publications

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“…This procedure enables to account for modifications and/or uncertainties in the values of the design variables in a straightforward way during iterative optimization and/or model updating. Also, it facilitates the evaluation of the sensitivities of the responses with respect to the design parameters (de Lima et al, 2010a).…”

Section: Parameterization Of the Fe Modelmentioning

confidence: 99%

Optimization of viscoelastic systems combining robust condensation and metamodeling

Lima¹,

Rade²,

Bouhaddi³

2010

J. Braz. Soc. Mech. Sci. & Eng.

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Passive control is recognized as being advantageous in terms of stability, effectiveness in broader bandwidths and ease of implementation (Nashif et al., 1985). In particular, the use of viscoelastic materials has been regarded as a convenient strategy in many types of industrial applications, where they can be applied either as discrete devices or surface treatments at a relatively low cost (Samali and Kwok, 1995;Rao, 2001;de Lima et al., 2009; Espíndola et al., 2005). However, viscoelastic materials present some inherent drawbacks such as the influence of operational and environmental factors (frequency, temperature, pre-loads, moisture, etc.). Also, viscoelastic damping systems (specially, surface treatments) are prone to induce considerable mass additions. This last feature leads to the necessity of performing optimization aiming at achieving the desired performance and, at the same time, complying with design and construction constraints.In the last decades, much effort has been devoted to the development of finite element (FE) models capable of accounting for the typical dependence of the viscoelastic behavior with respect to frequency and temperature (Bagley and Torvik, 1983;MacTavish and Hughes, 1993;Lesieutre and Lee, 1996;Galucio et al., 2004). As a result, it is currently possible to model complex real-world engineering structures such as automobiles, airplanes, communication satellites, buildings and space structures (Balmès and Germès, 2002). A natural extension of this modeling capability is the optimization of the viscoelastic devices aiming the reduction of cost and/or the maximization of performance (Hao et al., 2004;Lee et al., 2004). In the quest for optimization, engineers are frequently faced with conflicting objectives. Such situations are conveniently dealt with by the so-called multiobjective or multicriteria optimization approach (Eschenauer et al., 1990). However, multiobjective optimization generally requires a large number of evaluations of the cost functions involved. For large finite element models of viscoelastic systems, typically composed of many thousands of degrees-of-freedom (DOFs), if such evaluations are made based on exact response computations performed on the full FE matrices, computation times can become prohibitive.The work reported herein intends to propose a general strategy for the reduction of the computational burden involved in the optimization of viscoelastic structures by combining Multiobjective Evolutionary Algorithms (MOEAs), robust condensation and Artificial Neural Networks (ANNs). The motivation for the use of (2002) and Masson et al. (2003), which is based on the use of an enriched modal basis for approximate model reduction. A so-named robust basis is constructed to take into account the structural modifications introduced by the inclusion of the viscoelastic treatments into the original system in such a way that updating of the reduction basis by exact re-analysis is avoided, leading to a drastic reduction of the time required to evaluate the cost fun...

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Section: Parameterization Of the Fe Modelmentioning

confidence: 99%

Optimization of viscoelastic systems combining robust condensation and metamodeling

Lima¹,

Rade²,

Bouhaddi³

2010

J. Braz. Soc. Mech. Sci. & Eng.

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“…However, HSDT presents an increased analytical framework and a higher number of degrees of freedom as compared with the FSDT, which represents higher computational cost. Also, FSDT generates precise mechanical characteristics, as deflections, natural frequencies and buckling loads (Lima et al, 2010).…”

Section: Robust Optimal Control Applied To a Composite Laminated Beammentioning

confidence: 99%

Robust Optimal Control Applied to a Composite Laminated Beam

Koroishi

Fabián

Lara-Molina

et al. 2015

J.Aerosp. Technol. Manag.

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This paper proposes an active vibration control technique, which is based on linear matrix inequalities, that is applied to a piezoelectric actuator bonded to a composite structure, forming a so-called smart composite structure. Serendipity-type finite element, based on first-order shear deformation theory with rectangular shape, eight nodes, five mechanical degrees of freedom (DOF) per node and eight electrical DOF per piezoelectric layer, is established for the composite structural model. Additionally, a mixed theory that uses a single equivalent layer for the discretization of the mechanical displacement field and a layerwise representation of the electrical field is adopted. Temperature effects are neglected. Simulation results illustrate the effectiveness of the proposed vibration control methodology for composite structures.

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“…Lima et al (2010) used the receptance or Frequency Response Function (FRF) matrix to analyze the deterministic system, whose components are complex functions of the excitation frequency that establish linear relations between the amplitudes of the harmonic responses and the amplitudes of the excitation forces and moments, as expressed by Eq. (2):…”

Section: Modeling Of Flexible Rotorsmentioning

confidence: 99%

Uncertainty analysis of flexible rotors considering fuzzy parameters and fuzzy-random parameters

Lara-Molina

Koroishi

Steffen

2015

Lat. Am. j. solids struct.

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The components of flexible rotors are subjected to uncertainties. The main sources of uncertainties include the variation of mechanical properties. This contribution aims at analyzing the dynamics of flexible rotors under uncertain parameters modeled as fuzzy and fuzzy random variables. The uncertainty analysis encompasses the modeling of uncertain parameters and the numerical simulation of the corresponding flexible rotor model by using an approach based on fuzzy dynamic analysis. The numerical simulation is accomplished by mapping the fuzzy parameters of the deterministic flexible rotor model. Thereby, the flexible rotor is modeled by using both the Fuzzy Finite Element Method and the Fuzzy Stochastic Finite Element Method. Numerical simulations illustrate the methodology conveyed in terms of orbits and frequency response functions subject to uncertain parameters.

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Sensitivity analysis of frequency response functions of composite sandwich plates containing viscoelastic layers

Cited by 46 publications

References 10 publications

Optimization of viscoelastic systems combining robust condensation and metamodeling

Optimization of viscoelastic systems combining robust condensation and metamodeling

Robust Optimal Control Applied to a Composite Laminated Beam

Uncertainty analysis of flexible rotors considering fuzzy parameters and fuzzy-random parameters

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