Abo Bibliothek: Guest
Digitales Portal Digitale Bibliothek eBooks Zeitschriften Referenzen und Berichte Forschungssammlungen
International Journal for Uncertainty Quantification
Impact-faktor: 3.259 5-jähriger Impact-Faktor: 2.547 SJR: 0.417 SNIP: 0.8 CiteScore™: 1.52

ISSN Druckformat: 2152-5080
ISSN Online: 2152-5099

Offener Zugang

International Journal for Uncertainty Quantification

DOI: 10.1615/Int.J.UncertaintyQuantification.2013005436
pages 95-110

ENABLING THE ANALYSIS OF FINITE ELEMENT SIMULATION BUNDLES

Rodrigo Iza Teran
Fraunhofer Institute for Scientific Computing, 53757 Sankt Augustin, Germany

ABSTRAKT

We propose a methodology capable of allowing a fast evaluation of thousands of finite element design variants simultaneously. This approach uses a high dimensional analysis concept, namely diffusion maps, that has been in use successfully for years in many areas of science. Using feature vectors from a bundle of finite element simulations containing information on the design variables on different mesh sizes and applying this analysis concept is the purpose of this paper. Applying this approach enables the identification of a set of parameters (reduction coordinates) along which (i) geometrical variants can be identified and (ii) for random time-dependent problems, slow variables can be identified that show the variables with the most significant impact on a design. We demonstrate the application of this approach in several industrial examples in the areas of metal forming and vibration analysis as well as vehicle crash simulation, which is a noisy stochastic process. Finally, we show per example that this approach can identify and expound on the occurrence of a bifurcation point, a very important issue in vehicle design.


Articles with similar content:

HIERARCHICAL SPARSE BAYESIAN LEARNING FOR STRUCUTRAL HEALTH MONITORING WITH INCOMPLETE MODAL DATA
International Journal for Uncertainty Quantification, Vol.5, 2015, issue 2
Yong Huang, James L. Beck
VARIABLE-SEPARATION BASED ITERATIVE ENSEMBLE SMOOTHER FOR BAYESIAN INVERSE PROBLEMS IN ANOMALOUS DIFFUSION REACTION MODELS
International Journal for Uncertainty Quantification, Vol.9, 2019, issue 3
Yuming Ba, Na Ou, Lijian Jiang
OPTIMIZATION-BASED SAMPLING IN ENSEMBLE KALMAN FILTERING
International Journal for Uncertainty Quantification, Vol.4, 2014, issue 4
Alexander Bibov, Heikki Haario, Antti Solonen, Johnathan M. Bardsley
THE USE OF THE MONTE CARLO METHOD FOR TOOL SELECTION IN THE SHEET METAL INDUSTRY
Flexible Automation and Intelligent Manufacturing, 1997:
Proceedings of the Seventh International FAIM Conference, Vol.0, 1997, issue
E. Appleton, E. Summad
ANALYSIS OF VARIANCE-BASED MIXED MULTISCALE FINITE ELEMENT METHOD AND APPLICATIONS IN STOCHASTIC TWO-PHASE FLOWS
International Journal for Uncertainty Quantification, Vol.4, 2014, issue 6
Guang Lin, Yalchin Efendiev, Lijian Jiang, Jia Wei