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Published in:
2020 | OriginalPaper | Chapter
Machine Learning in Adaptive FETI-DP – A Comparison of Smart and Random Training Data
Authors : Alexander Heinlein, Axel Klawonn, Martin Lanser, Janine Weber
Published in: Domain Decomposition Methods in Science and Engineering XXV
Publisher: Springer International Publishing
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The convergence rate of classical domain decomposition methods for diffusion or elasticity problems usually deteriorates when large coefficient jumps occur along or across the interface between subdomains. In fact, the constant in the classical condition number bounds [11, 12] will depend on the coefficient jump.