Results 201 to 210 of about 1,546 (231)

Adjoint Error Estimation for Stochastic Collocation Methods

2014
This paper deals with partial differential equations with random input data. An efficient way of solving such problems is adaptive stochastic collocation on sparse grids. For higher efficiency and a better understanding of the method, we derive adjoint error estimates for nonlinear stochastic solution functionals.
Bettina Schieche, Jens Lang
openaire   +1 more source

An h-adaptive stochastic collocation method for stochastic EMC/EMI analysis

2010 IEEE Antennas and Propagation Society International Symposium, 2010
The analysis of electromagnetic compatibility and interference (EMC/EMI) phenomena is often fraught by randomness in a system's excitation (e.g., the amplitude, phase, and location of internal noise sources) or configuration (e.g., the routing of cables, the placement of electronic systems, component specifications, etc.).
Abdulkadir C Yucel, Hakan Bağci, Eric Michielssen   +2 more
openaire   +1 more source

Applications of Stochastic Collocation Method in Electromagnetic Compatibility

2017
The paper reviews the use of deterministic-stochastic models in some electromagnetic compatibility (EMC) applications where the uncertainty in input data set exists. In other words, of interest are cases where some properties of a system are partly or entirely unknown.
Poljak, Dragan, Šesnić, Silvestar, Šušnjara, Anna, Lallechere, Sebastien, Drissi, Khalil El Khamlichi.   +4 more
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Stochastic analysis of unsaturated flow with probabilistic collocation method

Water Resources Research, 2009
In this study, we present an efficient approach, called the probabilistic collocation method (PCM), for uncertainty analysis of flow in unsaturated zones, in which the constitutive relationship between the pressure head and the unsaturated conductivity is assumed to follow the van Genuchten‐Mualem model.
Weixuan Li, Zhiming Lu, Dongxiao Zhang
openaire   +1 more source

The stochastic collocation method for radiation transport in random media

Journal of Quantitative Spectroscopy and Radiative Transfer, 2011
Abstract Stochastic spectral expansions are used to represent random input parameters and the random unknown solution to describe radiation transport in random media. The total macroscopic cross section is taken to be a spatially continuous log-normal random process with known covariance function and expressed as a memoryless transformation of a ...
Erin D. Fichtl, Anil K. Prinja
openaire   +1 more source

Stochastic collocation methods for aeroelastic system with uncertainty

2009
Computation methods based on the Wiener chaos expansion have been developed to study the behaviors of the aeroelastic system with randomparameters. It is proven that the discrete wavelet transformation is one ofthe most accurate and efficient numerical schemes for this uncertainty quantizationproblem.
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Comparison between Wiener chaos methods and stochastic collocation methods

2017
In the last two chapters, we incorporated the recursive strategy into both Wiener chaos expansion (WCE) methods and stochastic collocation methods (SCM). In this chapter, we will compare both methods for linear stochastic advection-reaction-diffusion equations with commutative and noncommutative noises. To make a fair comparison, we develop a recursive
Zhongqiang Zhang, George Em Karniadakis
openaire   +1 more source

Applications of Stochastic Collocation Method in the Area of Bioelectromagnetism

2018
The paper brings the overview of the previous work by authors in area of stochastic bioelectromagnetism. Stochastic collocation method (SCM) is used to propagate the uncertainty from the input parameters to the output of the model. The efficiency of coupling between validated deterministic codes used in numerical dosimetry and SCM framework is ...
Šušnjara Nejašmić, Anna, Poljak, Dragan   +1 more
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Stochastic collocation methods for differential equations with white noise

2017
Stochastic collocation methods can lead to a fully decoupled system of PDEs, which can be readily implemented on parallel computers. However, stochastic collocation methods do not work when longer time integration is required. Though these methods are also cursed by the dimensionality, we apply the recursive strategy for longer time integration ...
Zhongqiang Zhang, George Em Karniadakis
openaire   +1 more source

Stochastic Collocation Method for Uncertainty Propagation

AIAA Guidance, Navigation, and Control Conference, 2012
Bin Jia, Sheng Cai, Yang Cheng, Ming Xin
openaire   +1 more source