Volume 51, pp. 169-218, 2019.

Topological derivative for the nonlinear magnetostatic problem

Samuel Amstutz and Peter Gangl

Abstract

The topological derivative represents the sensitivity of a domain-dependent functional with respect to a local perturbation of the domain and is a valuable tool in topology optimization. Motivated by an application from electrical engineering, we derive the topological derivative for an optimization problem which is constrained by the quasilinear equation of two-dimensional magnetostatics. Here, the main ingredient is to establish a sufficiently fast decay of the variation of the direct state at scale 1 as $|x|\to \mathrm{\infty }$. In order to apply the method in a bi-directional topology optimization algorithm, we derive both the sensitivity for introducing air inside ferromagnetic material and the sensitivity for introducing material inside an air region. We explicitly compute the arising polarization matrices and introduce a way to efficiently evaluate the obtained formulas. Finally, we employ the derived formulas in a level-set based topology optimization algorithm and apply it to the design optimization of an electric motor.

Full Text (PDF) [3.4 MB], BibTeX , DOI: 10.1553/etna_vol51s169

Key words

topological derivative, nonlinear magnetostatics, topology optimization, electrical machine

AMS subject classifications

35J62, 49Q10, 49Q12, 78M35, 78M50