Calibration of aero-structural reduced order models using full-field experimental measurements

Perez, Ricardo A.; Bartram, Gregory W.; Beberniss, Timothy J.; Wiebe, Richard; Spottswood, S. Michael

doi:10.1016/j.ymssp.2016.04.013

Cited by 19 publications

(4 citation statements)

References 20 publications

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“…The most recent contributions in this sense include [17] and [18][19][20]. In (ii), for datadriven ROMs we usually refer to ROMs constructed using previous FOM simulation data (or experimental data, [21]), as opposed to model-driven methods that rely on some intrinsic properties of the model itself for ROM construction, such as modal approaches [22][23][24][25]. As for intrusiveness, we usually denote a ROM as non-intrusive [26] if it can be used with routines and solvers of commercial FE software and, conversely, as intrusive a method requiring dedicated routines.…”

Section: Introductionmentioning

confidence: 99%

A higher-order parametric nonlinear reduced-order model for imperfect structures using Neumann expansion

et al. 2021

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We present an enhanced version of the parametric nonlinear reduced-order model for shape imperfections in structural dynamics we studied in a previous work. In this model, the total displacement is split between the one due to the presence of a shape defect and the one due to the motion of the structure. This allows to expand the two fields independently using different bases. The defected geometry is described by some user-defined displacement fields which can be embedded in the strain formulation. This way, a polynomial function of both the defect field and actual displacement field provides the nonlinear internal elastic forces. The latter can be thus expressed using tensors, and owning the reduction in size of the model given by a Galerkin projection, high simulation speedups can be achieved. We show that the adopted deformation framework, exploiting Neumann expansion in the definition of the strains, leads to better accuracy as compared to the previous work. Two numerical examples of a clamped beam and a MEMS gyroscope finally demonstrate the benefits of the method in terms of speed and increased accuracy.

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Section: Introductionmentioning

confidence: 99%

A higher-order parametric nonlinear reduced-order model for imperfect structures using Neumann expansion

et al. 2021

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show abstract

“…The most recent contributions in this sense include [18] and [19,20]. In (ii), for data-driven ROMs we usually refer to ROMs constructed using previous FOM simulation data (or experimental data, [21]), as opposed to model-driven methods that rely on some intrinsic properties of the model itself for ROM construction, such as modal approaches [22,23,24,25]. As for intrusiveness, we usually denote a ROM as non-intrusive [26] if it can be used with routines and solvers of commercial FE software and, conversely, as intrusive a method requiring dedicated routines.…”

Section: Introductionmentioning

confidence: 99%

An enhanced parametric nonlinear reduced order model for imperfect structures using Neumann expansion

Marconi,

Tiso,

Quadrelli

et al. 2021

Preprint

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We present an enhanced version of the parametric nonlinear reduced order model for shape imperfections in structural dynamics we studied in a previous work [1]. The model is computed intrusively and with no training using information about the nominal geometry of the structure and some user-defined displacement fields representing shape defects, i.e. small deviations from the nominal geometry parametrized by their respective amplitudes. The linear superposition of these artificial displacements describe the defected geometry and can be embedded in the strain formulation in such a way that, in the end, nonlinear internal elastic forces can be expressed as a polynomial function of both these defect fields and the actual displacement field. This way, a tensorial representation of the internal forces can be obtained and, owning the reduction in size of the model given by a Galerkin projection, high simulation speed-ups can be achieved. We show that by adopting a rigorous deformation framework we are able to achieve better accuracy as compared to the previous work. In particular, exploiting Neumann expansion in the definition of the Green-Lagrange strain tensor, we show that our previous model is a lower order approximation with respect to the one we present now. Two numerical examples of a clamped beam and a MEMS gyroscope finally demonstrate the benefits of the method in terms of speed and increased accuracy.

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“…Similarly, a so called equivalent linearization (EL) analysis was introduced in [22] for nonlinear response analysis of laminated plates subject to acoustic excitation. R. Perrez et al [23] further calibrated the NLROM using full-field experimental data. These studies show that the NLROM has great potentials for nonlinear response analysis of plates subject to acoustic excitation, therefore, can be used as efficient design and analysis tools for structure design.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear reduced order modeling for nonlinear response simulation of panels via Large Eddy Simulation

et al. 2021

Journal of Sound and Vibration

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Calibration of aero-structural reduced order models using full-field experimental measurements

Cited by 19 publications

References 20 publications

A higher-order parametric nonlinear reduced-order model for imperfect structures using Neumann expansion

A higher-order parametric nonlinear reduced-order model for imperfect structures using Neumann expansion

An enhanced parametric nonlinear reduced order model for imperfect structures using Neumann expansion

Nonlinear reduced order modeling for nonlinear response simulation of panels via Large Eddy Simulation

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