Titlebook: Design Methods for Reducing Failure Probabilities with Examples from Electrical Engineering; Mona Fuhrl?nder Book 2023 The Editor(s) (if a

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Numerical Applications and Results,Chap.?2 we introduced two benchmark problems, a rectangular waveguide and a PMSM. In Sect.?6.1 we will specify these general applications to concrete model problems, which will be used for the numerical testing afterwards.

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Antonio Ricardo de Mattos Tenóriod optimization methods proposed in Chap.?.. Thirdly, we introduce three approximation methods commonly used in the field of uncertainty quantification, namely MC analysis, SC and GPR. The yield estimation methods proposed in Chap.?. build on these concepts.

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2190-5053 in manufacturing processes.Combines machine learning with m.This book deals with efficient estimation and optimization methods to improve the design of electrotechnical devices under uncertainty. Uncertainties caused by manufacturing imperfections, natural material variations, or unpredictable envi

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Book 2023 caused by manufacturing imperfections, natural material variations, or unpredictable environmental influences, may lead, in turn, to?deviations in operation. This book describes two novel methods for yield (or failure probability) estimation. Both are hybrid methods that combine the accuracy of Mon

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Yield Estimation,n GPR. The aim of these methods is to maintain the high estimation accuracy achieved with classic MC, while the computational effort is reduced by evaluating most of the sample points on surrogate models. The content and structure of this chapter follow our work in?[1, 2].

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Panagiotis Papadimitriou,Ines Houidi,Wajdi Louati,Djamal Zeghlache,Christoph Werle,Roland Bless,Laurtein glycosylation. We also describe potential applications of the spatial tissue glycomic profiles, including histochemical analysis for evaluating distribution of lectin ligands and a fluorescence LMD–LMA method for cell type-selective glycomic profiling using a cell type-specific probe, composed

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