Preprint · March 020 citations reads 277 5

Konstantinos Vlachas

Dept. of Civil, Environmental and Geomatic Engr.
ETH Zurich Zurich, Switzerland
[e-mail]

Konstantinos Tatsis

Dept. of Civil, Environmental and Geomatic Engr.
ETH Zurich Zurich, Switzerland
[e-mail]

Konstantinos Agathos

Dept. of Civil, Environmental and Geomatic Engr.
ETH Zurich Zurich, Switzerland
[e-mail]

Adam R. Brink

Solid Mechanics Sandia National Laboratories Albuquerque, New Mexico,
[e-mail]

arXiv:2003.07716v1 [math.NA] 16 Mar 2020

Eleni Chatzi

Dept. of Civil, Environmental and Geomatic Engr.
ETH Zurich Zurich, Switzerland
[e-mail]
March 18, 2020


ABSTRACT
The efficient condition assessment of engineered systems requires the coupling of high fidelity models with data extracted from the state of the system ‘as-is’. In enabling this task, this paper implements a parametric Model Order Reduction (pMOR) scheme for nonlinear structural dynamics, and the particular case of material nonlinearity. A physics-based parametric representation is developed, incorporating dependencies on system properties and/or excitation characteristics. The pMOR formulation relies on use of a Proper Orthogonal Decomposition applied to a series of snapshots of the nonlinear dynamic response. A new approach to manifold interpolation is proposed, with interpolation taking place on the reduced coefficient matrix mapping local bases to a global one. We demonstrate the performance of this approach firstly on the simple example of a shear-frame structure, and secondly on the more complex 3D numerical case study of an earthquake-excited wind turbine tower. Parametric dependence pertains to structural properties, as well as the temporal and spectral characteristics of the applied excitation. The developed parametric Reduced Order Model (pROM) can be exploited for a number of tasks including monitoring and diagnostics, control of vibrating structures, and residual life estimation of critical components.

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Keywords As-Built As-Deployed Structures Parametric Model Order Reduction (pMOR) Nonlinear Reduction Reduced Bases Interpolation

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