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Electrical Engineering
Article . 2023 . Peer-reviewed
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Article . 2022
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Article . 2025
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Adjoint variable method for transient nonlinear electroquasistatic problems

Authors: M. Greta Ruppert; Yvonne Späck-Leigsnering; Julian Buschbaum; Herbert De Gersem;

Adjoint variable method for transient nonlinear electroquasistatic problems

Abstract

AbstractMany optimization problems in electrical engineering consider a large number of design parameters. A sensitivity analysis identifies the design parameters with the strongest influence on the problem of interest. This paper introduces the adjoint variable method as an efficient approach to study sensitivities of nonlinear electroquasistatic problems in time domain. In contrast to the more common direct sensitivity method, the adjoint variable method has a computational cost nearly independent of the number of parameters. The method is applied to study the sensitivity of the field grading material parameters on the performance of a 320 kV cable joint specimen, which is modeled as a finite element nonlinear transient electroquasistatic problem. Special attention is paid to the treatment of quantities of interest, which are evaluated at specific points in time or space. It is shown that the method is a valuable tool to study this strongly nonlinear and highly transient technical example.

Country
Germany
Keywords

Computational Engineering, Finance, and Science (cs.CE), FOS: Computer and information sciences, J.2, G.1.8; J.2, G.1.8, Computer Science - Computational Engineering, Finance, and Science

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Top 10%
Top 10%
Average
Green
hybrid