On Uncertainty Quantification for Models Involving Hysteresis Operators

2019 ◽  
pp. 271-275
Author(s):  
Olaf Klein
Keyword(s):  
Uncertainty Quantification ◽  
Hysteresis Operators

scholarly journals On forward and inverse uncertainty quantification for models involving hysteresis operators

2020 ◽  
Vol 15 ◽  
pp. 53
Author(s):  
Olaf Klein ◽  
Daniele Davino ◽  
Ciro Visone
Keyword(s):  
Weight Function ◽  
Uncertainty Quantification ◽  
Real World ◽  
Yield Limit ◽  
Play Operator ◽  
Stochastic Yield ◽  
Hysteresis Operators

Parameters within hysteresis operators modeling real world objects have to be identified from measurements and are therefore subject to corresponding errors. To investigate the influence of these errors, the methods of Uncertainty Quantification (UQ) are applied. Results of forward UQ for a play operator with a stochastic yield limit are presented. Moreover, inverse UQ is performed to identify the parameters in the weight function in a Prandtl-Ishlinskiĭ operator and the uncertainties of these parameters.

INVERSE UNCERTAINTY QUANTIFICATION OF A CELL MODEL USING A GAUSSIAN PROCESS METAMODEL

2020 ◽  
Vol 10 (4) ◽  
pp. 333-349
Author(s):  
Kevin de Vries ◽  
Anna Nikishova ◽  
Benjamin Czaja ◽  
Gábor Závodszky ◽  
Alfons G. Hoekstra
Keyword(s):  
Gaussian Process ◽  
Uncertainty Quantification ◽  
Cell Model ◽  
A Cell
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