The “acoustic black hole” (ABH) phenomenon can be exploited for flexural vibration suppressions in beam and plate structures. Conventional ABH structures, however, are tied with the inherent structural weakness due to the low local stiffness required and possibly high stress concentration caused by the small residual cross-section thickness of the ABH taper, thus hampering their practical applications. In this study, the dynamic and static properties of a compound ABH beam are investigated through numerical simulations. It is shown that, whilst ensuring an effective ABH effect, the compound ABH structure allows a significant improvement in the static properties of the structure. For the former, the compound design is shown to outperform its counterpart in the conventional ABH configuration in terms of the damping enhancement and the vibration suppression. For the latter, the compound ABH structure is also shown to provide much better static properties in terms of structural stiffness and strength. Meanwhile, the structural damping can be further improved by using an extended platform at the tip of tailored profile, which improves the structural strength but reduces the structural stiffness at the same time. Therefore, when choosing the platform length, a balance needs to be struck among the desired ABH effect and the mechanical properties of the structure.
This paper deals with computations and statistical properties, as well as transfer function selections involved in frequency response estimation for normalized coprime factors (NCF). A simple expression and the probability density function (PDF) are derived for the maximum likelihood estimate (MLE). It is shown that the statistical characteristics of the MLE are independent of the auxiliary plant. Based on this observation, all the coprime factors of the auxiliary transfer function have been derived which lead to an almost unbiased estimate when the noise level is low. Moreover, an analytic expression has been established for the involved free transfer functions which minimize both the bias and the variance of the estimate. The theoretical conclusions have been verified through numerical simulations.
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