activity
20182023
most citedUncertainty Quantification for Maxwell's Eigenproblem based on Isogeometric Analysis and Mode Tracking

17 citations · 62 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CE2023★ 5 cited

Rational kernel-based interpolation for complex-valued frequency response functions

Julien Bect, Niklas Georg, Ulrich Römer +1

This work is concerned with the kernel-based approximation of a complex-valued function from data, where the frequency response function of a partial differential equation in the f…

cs.CE2022★ 8 cited

An -adaptive multi-element stochastic collocation method for surrogate modeling with information re-use

Armin Galetzka, Dimitrios Loukrezis, Niklas Georg +2

This paper introduces an -adaptive multi-element stochastic collocation method, which additionally allows to re-use existing model evaluations during either - or -refinem…

cs.CE2022★ 7 cited

Mode Recognition by Shape Morphing for Maxwell's Eigenvalue Problem

Anna Ziegler, Niklas Georg, Wolfgang Ackermann +1

In electrical engineering, for example during the design of superconducting radio-frequency cavities, eigenmodes must be identified based on their field patterns. This allows to un…

cs.CE2020

Conformally Mapped Polynomial Chaos Expansions for Maxwell's Source Problem with Random Input Data

Niklas Georg, Ulrich Römer

Generalized Polynomial Chaos (gPC) expansions are well established for forward uncertainty propagation in many application areas. Although the associated computational effort may b…

cs.CE2019★ 10 cited

Yield Optimization based on Adaptive Newton-Monte Carlo and Polynomial Surrogates

Mona Fuhrländer, Niklas Georg, Ulrich Römer +1

In this paper we present an algorithm for yield estimation and optimization exploiting Hessian based optimization methods, an adaptive Monte Carlo (MC) strategy, polynomial surroga…

cs.CE2019★ 8 cited

Uncertainty Modeling and Analysis of the European X-ray Free Electron Laser Cavities Manufacturing Process

Jacopo Corno, Niklas Georg, Shahnam Gorgi Zadeh +9

This paper reports on comprehensive efforts on uncertainty quantification and global sensitivity analysis for accelerator cavity design. As a case study object the TESLA shaped sup…

cs.CE2018★ 7 cited

Enhanced adaptive surrogate models with applications in uncertainty quantification for nanoplasmonics

Niklas Georg, Dimitrios Loukrezis, Ulrich Römer +1

We propose an efficient surrogate modeling technique for uncertainty quantification. The method is based on a well-known dimension-adaptive collocation scheme. We improve the schem…

cs.CE2018★ 17 cited

Uncertainty Quantification for Maxwell's Eigenproblem based on Isogeometric Analysis and Mode Tracking

Niklas Georg, Wolfgang Ackermann, Jacopo Corno +1

The electromagnetic field distribution as well as the resonating frequency of various modes in superconducting cavities used in particle accelerators for example are sensitive to s…