BibTeX
@ARTICLE{
Jurgelucks2018Oot,
crossref = "Christianson2018Sio",
author = "Benjamin Jurgelucks and Leander Claes and Andrea Walther and Bernd Henning",
title = "Optimization of triplering electrodes on piezoceramic transducers using algorithmic
differentiation",
journal = "Optimization Methods \& Software",
volume = "33",
number = "46",
pages = "868888",
year = "2018",
publisher = "Taylor \& Francis",
doi = "10.1080/10556788.2018.1435652",
url = "https://doi.org/10.1080/10556788.2018.1435652",
eprint = "https://doi.org/10.1080/10556788.2018.1435652",
abstract = "Data of material properties given by manufacturers of piezoelectric ceramics is
often flawed due to, for example, slightly different manufacturing conditions for each production
batch. Hence, the need for more reliable data arises. Recently published material parameter
estimation methods are based on the solution of an inverse problem fitting impedance measurements of
the piezoelectric ceramic to simulations by varying the material parameters in the simulation.
However, the sensitivity of impedance with respect to some material parameters is close to zero and
thus alternative measurement quantities which require expensive and errorprone measurement devices
would be required. In order to assist in experiment design, the simulation software must be able to
compute accurate sensitivity information. We applied the algorithmic differentiation (AD) package
ADOLC to the C++based sophisticated simulation software CFS++ and thus are now able to compute the
sensitivity of impedance with respect to material parameters without the use of finite differences.
As these sensitivities depend on the geometry of the piezoelectric ceramic and the electrodes, we
then use these sensitivities as a cost function for maximization. We compare the results of
optimization with results of optimization previously obtained using a finite difference scheme. We
document implementation issues and limits for integrating ADOLC into CFS++. Nevertheless, we show
the now much improved results of optimization using AD instead of finite differences and its
potential for further optimization.",
booktitle = "Special issue of Optimization Methods \& Software: Advances in
Algorithmic Differentiation",
editor = "Bruce Christianson and Shaun A. Forth and Andreas Griewank"
}
