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Computational Electromagnetism and Acoustics

Computational Electromagnetism and Acoustics

Abstract

Computational electromagnetics and acoustics revolve around a few key challenges, among which are the non-local nature of the underlying phenomena and resonance effects. The bulk of the contributions to the workshop addressed mathematical and numerical approaches meant to grapple with these two difficulties. Frequency domain integral equation methods continue to receive much attention, with a particular focus on (i) frequency robust matrix compression algorithms through so-called directional schemes or “butterfly algorithms”, and (ii) domain decomposition approaches. Time domain integral equation methods still enjoy rapid development and much progress was made in their numerical analysis. Of course, efficient and accurate absorbing boundary conditions remain a persistent topic and were covered in a few contributions. Resonance induced phenomena in a broad sense affect the analytical and numerical model for meta-materials, periodic structures, and micro-structured media. There is a lot left to be explored in this field in terms of analysis and algorithm development and a few presentations were devoted to such issues.

Keywords

Konferenzschrift, 510

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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!
0
Average
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