Optimization of a reconstructed middle ear using an evolution strategy

Abstract

Optimization of complex multibody systems requires a great computational effort. Therefore, sophisticated optimization methods must be applied. This chapter presents a paper that describes an approach for the optimization of multibody systems in a systematic way and is applied to the optimization of a human middle ear. For the optimization, the software package called NEWOPT/AIMS is used, which includes several algorithms for the analysis and optimization of multibody systems. The goal of the optimization is to improve sound transfer for the reconstruction of a damaged middle ear by variation of insertion conditions of a passive middle-ear implant. The disadvantage of evolution strategies, which requires a high number of criteria evaluations, is reduced by calculating the criteria parallelly on different workstations. For this parallelization, a master–slave approach can be implemented and used for several large-scale optimizations. For the optimization of a reconstructed middle ear with respect to sound transfer to an inner ear, a criteria formulation in the frequency domain can be used for an efficient assessment of system behaviors. An improved hearing can be achieved by adaptation of insertion conditions of the implant.