The reliability assessment of complex adaptive systems requires the identification of dominant input parameters and the
quantitative evaluation of the associated effects on the system performance. This can be achieved using experimental and
numerical sensitivity analysis methods. In this paper a simulation based approach is presented, assessing the system
performance of an active vibration isolation device with respect to parameter variations, such as temperature, load
amplitude, material properties and geometry dimensions of the structural elements. The modeling of the active system is
described utilizing the Finite Element Method and a Krylov Subspace based model order reduction scheme. The
implemented Morris screening technique and variance based sensitivity analysis are discussed. For the example of an
active vibration system the sensitivity analysis strategy is outlined and it is shown that a quantitative assessment of the
system performance considering large scale parameter variations is provided.
The reliability assessment of complex active systems requires simulation methods, which reproduce complex system
performance and also account for failure and fatigue scenarios. More and more, test methods traditionally carried out
experimentally are replaced by computational or 'virtual' methods. Reliability of these complex adaptive systems is hard
to estimate for several reasons. A priori undetermined interaction between various influencing parameters, unknown
fatigue properties of the multifunctional materials employed in sensors and actuators and very complex system
performance requirements make it difficult to predict under which circumstances the system may fail. Sensitivity
Analysis (SA) of the comprehensive adaptive system model has proven to be a valuable tool for the identification and
assessment of scenarios that are relevant for system reliability. For the example of an active oil pan, which is equipped
with piezoelectric sensors and actuators to suppress structural vibrations, the method is outlined.
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