Finite Element model data for Academic Rotor bladed-disc system

A computational finite element based technique is proposed for developing
a stochastic reduced order model for rotating bladed disc with spatial
random inhomogeneities. The spatial inhomogeneities imply the system to be
randomly mistuned. The formulation assumes the availability of a high
fidelity finite element (FE) model for the tuned system. The corresponding
FE matrices are antisymmetric on account of the Coriolis forces due to
rotation. The spatial inhomogeneities, available from limited point
measurements on the blades, are modelled as non-Gaussian random fields
with arbitrary distributions. A low order stochastic computational model
is developed by projecting the FE model onto a reduced dimensional state
space defined in terms of specified observable nodal points and expressing
the stochasticity through an arbitrary polynomial chaos (aPC) basis. This
model enables probabilistic quantification of the variabilities in the
system response and estimating failure probabilities. The methodology
enables drastic reduction in the state space and stochastic dimensions,
addresses the practical difficulties with having limited measurable data
points, antisymmetric FE matrices, aPC representation in complex irregular
geometries and carrying out probabilistic analyses on industrial systems,
at significantly reduced computational costs. The methodology is
illustrated through an academic rotor and an industrial rotor blade.