Robust and efficient automatic model order reduction (MOR) is important in the design process of vibroacoustic structures. For correct assessment of the reduction error, reliable error measures are required. Error estimators do not ensure an approximation error below a certain bound, but can be used in iterative algorithms to automatically determine a reasonable order and expansion point distribution for reduced order models. A good error estimator is important in order to design an efficient adaptive MOR process requiring as little a-priori knowledge of the system response as possible. In this contribution, different error estimators for reduced models are presented and assessed regarding their applicability in an adaptive algorithm to automatically generate reduced models of vibro-acoustic systems. For many applications, vibro-acoustic systems need to be evaluated in a specific frequency range, as certain system characteristics are only observed in this region. Therefore, the employed error estimation method is also assessed regarding its effectiveness estimating the error in a particular frequency region.
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Robust and efficient automatic model order reduction (MOR) is important in the design process of vibroacoustic structures. For correct assessment of the reduction error, reliable error measures are required. Error estimators do not ensure an approximation error below a certain bound, but can be used in iterative algorithms to automatically determine a reasonable order and expansion point distribution for reduced order models. A good error estimator is important in order to design an efficient ad...
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