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.Comment: 23 pages, 28 figure
