A stochastic framework to model bending of textile antennas [PDF]
, 2014 The polynomial chaos expansion is combined with a dedicated cylindrical cavity model to quantify the statistical variations in textile antenna performance under random bending ...
Boeykens, Freek +4 more
core +1 more source
Asymptotic expansion for some local volatility models arising in finance [PDF]
, 2018 In this paper we study the small noise asymptotic expansions for certain classes of local volatility models arising in finance. We provide explicit expressions for the involved coefficients as well as accurate estimates on the remainders.
ALbeverio, Sergio +3 more
core +2 more sources
From wind to loads: wind turbine site-specific load estimation with surrogate models trained on high-fidelity load databases [PDF]
Wind Energy Science, 2018 We define and demonstrate a procedure for quick assessment of site-specific lifetime fatigue loads using simplified load mapping functions (surrogate models), trained by means of a database with high-fidelity load simulations.
N. Dimitrov +3 more
doaj +1 more source
STOCHASTIC POLYNOMIAL CHAOS EXPANSIONS TO EMULATE STOCHASTIC SIMULATORS
International Journal for Uncertainty Quantification, 2023 In the context of uncertainty quantification, computational models are required to be repeatedly evaluated. This task is intractable for costly numerical models. Such a problem turns out to be even more severe for stochastic simulators, the output of which is a random variable for a given set of input parameters.
Zhu, Xujia +1 more
openaire +3 more sources
Numerical approximation of poroelasticity with random coefficients using Polynomial Chaos and Hybrid High-Order methods [PDF]
, 2019 In this work, we consider the Biot problem with uncertain poroelastic coefficients. The uncertainty is modelled using a finite set of parameters with prescribed probability distribution.
Botti, Michele +3 more
core +3 more sources
An Efficient Polynomial Chaos Method for Stiffness Analysis of Air Spring Considering Uncertainties
Complexity, 2021 Traditional methods for stiffness analysis of the air spring are based on deterministic assumption that the parameters are fixed. However, uncertainties have widely existed, and the mechanic property of the air spring is very sensitive to these ...
Feng Kong, Penghao Si, Shengwen Yin
doaj +1 more source
Impact on signal integrity of interconnect variabilities [PDF]
, 2014 In this paper, literature results on the statistical simulation of lossy and dispersive interconnect networks with uncertain physical properties are extended to general nonlinear circuits.
Canavero, Flavio +3 more
core +1 more source
Polynomial chaos expansions for damped oscillators
, 2015 Uncertainty quantification is the state-of-the-art framework dealing with uncertainties arising in all kind of real-life problems. One of the framework’s functions is to propagate uncertainties from the stochastic input factors to the output quantities of interest, hence the name uncertainty propagation.
Mai, Chu V., Sudret, Bruno
openaire +4 more sources
Bayesian inference of earthquake rupture models using polynomial chaos expansion [PDF]
Geoscientific Model Development, 2018 In this paper, we employed polynomial chaos (PC) expansions to understand earthquake rupture model responses to random fault plane properties. A sensitivity analysis based on our PC surrogate model suggests that the hypocenter location plays a ...
H. Cruz-Jiménez +5 more
doaj +1 more source
Stochastic macromodeling of nonlinear systems via polynomial chaos expansion and transfer function trajectories [PDF]
, 2014 A novel approach is presented to perform stochastic variability analysis of nonlinear systems. The versatility of the method makes it suitable for the analysis of complex nonlinear electronic systems. The proposed technique is a variation-aware extension
De Jonghe, Dimitri +5 more
core +2 more sources