TUHH Open Research
Help
New user? Click here to register.Have you forgotten your password?
Communities & Collections
Publications
Research Data
People
Institutions
Projects
  1. Home
  2. Publications
  3. Publication References
  4. Challenges of order reduction techniques for problems involving polymorphic uncertainty

Challenges of order reduction techniques for problems involving polymorphic uncertainty

Publikationstyp
Journal Article
Date Issued
2019-05
Sprache
English
Author(s)
Pivovarov, Dmytro
Willner, Kai
Steinmann, Paul
Brumme, Stephan
Müller, Michael
Srisupattarawanit, Tarin
Ostermeyer, Georg Peter
Henning, Carla
Ricken, Tim
Kastian, Steffen
Reese, Stefanie
Moser, Dieter
Grasedyck, Lars
Biehler, Jonas
Pfaller, Martin
Wall, Wolfgang
Kohlsche, Thomas
Estorff, Otto von
Gruhlke, Robert
Eigel, Martin
Ehre, Max
Papaioannou, Iason
Straub, Daniel
Leyendecker, Sigrid
Institut
Modellierung und Berechnung M-16
TORE-URI
http://hdl.handle.net/11420/2963
Journal
GAMM-Mitteilungen
Volume
42
Issue
2
Start Page
e201900011
Citation
GAMM Mitteilungen 2 (42): e201900011- (2019-05)
Publisher DOI
10.1002/gamm.201900011
Scopus ID
2-s2.0-85064502054
Modeling of mechanical systems with uncertainties is extremely challenging and requires a careful analysis of a huge amount of data. Both, probabilistic modeling and nonprobabilistic modeling require either an extremely large ensemble of samples or the introduction of additional dimensions to the problem, thus, resulting also in an enormous computational cost growth. No matter whether the Monte-Carlo sampling or Smolyak's sparse grids are used, which may theoretically overcome the curse of dimensionality, the system evaluation must be performed at least hundreds of times. This becomes possible only by using reduced order modeling and surrogate modeling. Moreover, special approximation techniques are needed to analyze the input data and to produce a parametric model of the system's uncertainties. In this paper, we describe the main challenges of approximation of uncertain data, order reduction, and surrogate modeling specifically for problems involving polymorphic uncertainty. Thereby some examples are presented to illustrate the challenges and solution methods.
Funding(s)
SPP 1886 - Polymorphe Unschärfemodellierungen für den numerischen Entwurf von Strukturen: "Modellierung von vibro-akustischen Systemen mit polymorphen Unschärfen am Beispiel der Schallabstrahlung von Reifen"
More Funding Information
This research was supported by the Deutsche Forschungs-Gemeinschaft (DFG); WI 1181/9-1; STE 544/59-1; OS 166/16-1; RI 1202/6-1; RE 1057/40-1; GR 3179/5-1; WA 1521/23-1; KO 4900/5-1; ES 70/8-1; EI 1050/1-1; STR 1140/6-1; LE 1841/4-1The support of this work by the Deutsche Forschungs-Gemeinschaft (DFG) through the Priority Programme SPP 1886 Polymorphic uncertainty modelling for the numerical design of structures under grants WI 1181/9-1, STE 544/59-1, OS 166/16-1, RI 1202/6-1, RE 1057/40-1, GR 3179/5-1, WA 1521/23-1, KO 4900/5-1, ES 70/8-1, EI 1050/1-1, STR 1140/6-1, and LE 1841/4-1 is gratefully acknowledged.
TUHH
Weiterführende Links
  • Contact
  • Send Feedback
  • Cookie settings
  • Privacy policy
  • Impress
DSpace Software

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science
Design by effective webwork GmbH

  • Deutsche NationalbibliothekDeutsche Nationalbibliothek
  • ORCiD Member OrganizationORCiD Member Organization
  • DataCiteDataCite
  • Re3DataRe3Data
  • OpenDOAROpenDOAR
  • OpenAireOpenAire
  • BASE Bielefeld Academic Search EngineBASE Bielefeld Academic Search Engine
Feedback