We consider linear dynamical systems including random parameters for uncertainty quantification. A sensitivity analysis of the stochastic model is applied to the input-output behaviour of the systems. Thus the parameters that contribute most to the variance are detected. Both intrusive and non-intrusive methods based on the polynomial chaos yield the required sensitivity coefficients. We use this approach to analyse a test example from electrical engineering
AbstractSensitivity analysis and uncertainty quantification are computationally expensive procedures...
International audienceThis study aims at pointing out the somehow complex behavior of the structural...
Knowledge of the impact of uncertain inputs is valuable, especially in power systems with large amou...
We consider linear dynamical systems including random parameters for uncertainty quantification. A s...
We consider linear dynamical systems defined by di¿erential algebraic equations. The associated inpu...
AbstractUncertainty in the model input parameters are to be taken into account in order to assess th...
It is interesting to analyze the parameter sensitivity of mathematical models that describe physical...
International audienceIn this paper, we discuss the sensitivity analysis of model response when the ...
In this paper, we offer a short overview of a number of methods that have been reported in the compu...
© 2015 IEEE. Electrical machines that are produced in mass production suffer from stochastic deviati...
Thesis (Ph.D.)--University of Washington, 2020Uncertainties exist in both physics-based and data-dri...
The quantification of the uncertainty effect of random system parameters, such as the loading condit...
AbstractSensitivity analysis and uncertainty quantification are computationally expensive procedures...
International audienceThis study aims at pointing out the somehow complex behavior of the structural...
Knowledge of the impact of uncertain inputs is valuable, especially in power systems with large amou...
We consider linear dynamical systems including random parameters for uncertainty quantification. A s...
We consider linear dynamical systems defined by di¿erential algebraic equations. The associated inpu...
AbstractUncertainty in the model input parameters are to be taken into account in order to assess th...
It is interesting to analyze the parameter sensitivity of mathematical models that describe physical...
International audienceIn this paper, we discuss the sensitivity analysis of model response when the ...
In this paper, we offer a short overview of a number of methods that have been reported in the compu...
© 2015 IEEE. Electrical machines that are produced in mass production suffer from stochastic deviati...
Thesis (Ph.D.)--University of Washington, 2020Uncertainties exist in both physics-based and data-dri...
The quantification of the uncertainty effect of random system parameters, such as the loading condit...
AbstractSensitivity analysis and uncertainty quantification are computationally expensive procedures...
International audienceThis study aims at pointing out the somehow complex behavior of the structural...
Knowledge of the impact of uncertain inputs is valuable, especially in power systems with large amou...