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International Journal for Uncertainty Quantification

Published 6 issues per year

ISSN Print: 2152-5080

ISSN Online: 2152-5099

The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) IF: 1.7 To calculate the five year Impact Factor, citations are counted in 2017 to the previous five years and divided by the source items published in the previous five years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) 5-Year IF: 1.9 The Immediacy Index is the average number of times an article is cited in the year it is published. The journal Immediacy Index indicates how quickly articles in a journal are cited. Immediacy Index: 0.5 The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. Eigenfactor: 0.0007 The Journal Citation Indicator (JCI) is a single measurement of the field-normalized citation impact of journals in the Web of Science Core Collection across disciplines. The key words here are that the metric is normalized and cross-disciplinary. JCI: 0.5 SJR: 0.584 SNIP: 0.676 CiteScore™:: 3 H-Index: 25

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ENHANCED ADAPTIVE SURROGATE MODELS WITH APPLICATIONS IN UNCERTAINTY QUANTIFICATION FOR NANOPLASMONICS

Volume 10, Issue 2, 2020, pp. 165-193
DOI: 10.1615/Int.J.UncertaintyQuantification.2020031727
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ABSTRACT

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 scheme by enhancing sparse polynomial surrogates with conformal maps and adjoint error correction. The methodology is applied to Maxwell's source problem with random input data. This setting comprises many applications of current interest from computational nanoplasmonics, such as grating couplers or optical waveguides. Using a nontrivial benchmark model, we show the benefits and drawbacks of using enhanced surrogate models through various numerical studies. The proposed strategy allows us to conduct a thorough uncertainty analysis, taking into account a moderately large number of random parameters.

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CITED BY
  1. Georg Niklas, Römer Ulrich, Conformally mapped polynomial chaos expansions for Maxwell's source problem with random input data, International Journal of Numerical Modelling: Electronic Networks, Devices and Fields, 33, 6, 2020. Crossref

  2. Römer Ulrich, Bollhöfer Matthias, Sreekumar Harikrishnan, Blech Christopher, Christine Langer Sabine, An adaptive sparse grid rational Arnoldi method for uncertainty quantification of dynamical systems in the frequency domain, International Journal for Numerical Methods in Engineering, 122, 20, 2021. Crossref

  3. Georg Niklas, Lehmann Christian, Römer Ulrich, Schuhmann Rolf, Multifidelity Uncertainty Quantification for Optical Structures, in Scientific Computing in Electrical Engineering, 36, 2021. Crossref

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