Nonlinear Stochastic Galerkin and Collocation Methods: Application to a Ferromagnetic Cylinder Rotating at High Speed
Year: 2010
Communications in Computational Physics, Vol. 8 (2010), Iss. 5 : pp. 947–975
Abstract
The stochastic Galerkin and stochastic collocation method are two state-of-the-art methods for solving partial differential equations (PDE) containing random coefficients. While the latter method, which is based on sampling, can straightforwardly be applied to nonlinear stochastic PDEs, this is nontrivial for the stochastic Galerkin method and approximations are required. In this paper, both methods are used for constructing high-order solutions of a nonlinear stochastic PDE representing the magnetic vector potential in a ferromagnetic rotating cylinder. This model can be used for designing solid-rotor induction machines in various machining tools. A precise design requires to take ferromagnetic saturation effects into account and uncertainty on the nonlinear magnetic material properties. Implementation issues of the stochastic Galerkin method are addressed and a numerical comparison of the computational cost and accuracy of both methods is performed. The stochastic Galerkin method requires in general less stochastic unknowns than the stochastic collocation approach to reach a certain level of accuracy, however at a higher computational cost.
Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.4208/cicp.220509.200110a
Communications in Computational Physics, Vol. 8 (2010), Iss. 5 : pp. 947–975
Published online: 2010-01
AMS Subject Headings: Global Science Press
Copyright: COPYRIGHT: © Global Science Press
Pages: 29
-
Reconstruction of the doping profile in Vlasov–Poisson system
Lai, Ru-Yu | Li, Qin | Sun, WeiranInverse Problems, Vol. 40 (2024), Iss. 11 P.115004
https://doi.org/10.1088/1361-6420/ad7c78 [Citations: 0] -
Inverse radiative transfer with goal-oriented hp-adaptive mesh refinement: adaptive-mesh inversion
Du, Shukai | Stechmann, Samuel NInverse Problems, Vol. 39 (2023), Iss. 11 P.115002
https://doi.org/10.1088/1361-6420/acf785 [Citations: 2] -
Boundary-layer structures arising in linear transport theory
Gaggioli, E. L. | Estrada, Laura C. | Bruno, Oscar P.Physical Review E, Vol. 110 (2024), Iss. 2
https://doi.org/10.1103/PhysRevE.110.025306 [Citations: 0] -
On diffusive scaling in acousto-optic imaging
Chung, Francis J | Lai, Ru-Yu | Li, QinInverse Problems, Vol. 36 (2020), Iss. 8 P.085011
https://doi.org/10.1088/1361-6420/ab9f85 [Citations: 2] -
Stochastic models for the evaluation of magnetisation faults
Norio Takahashi, Prof. | Offermann, Peter | Hameyer, KayCOMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, Vol. 33 (2013), Iss. 1/2 P.245
https://doi.org/10.1108/COMPEL-10-2012-0210 [Citations: 4] -
Inverse transport problem in fluorescence ultrasound modulated optical tomography with angularly averaged measurements
Li, Wei | Yang, Yang | Zhong, YiminInverse Problems, Vol. 36 (2020), Iss. 2 P.025011
https://doi.org/10.1088/1361-6420/ab4609 [Citations: 5] -
Solving parameter estimation problems with discrete adjoint exponential integrators
Römer, Ulrich | Narayanamurthi, Mahesh | Sandu, AdrianOptimization Methods and Software, Vol. 33 (2018), Iss. 4-6 P.750
https://doi.org/10.1080/10556788.2018.1448087 [Citations: 3] -
Online learning in optical tomography: a stochastic approach
Chen, Ke | Li, Qin | Liu, Jian-GuoInverse Problems, Vol. 34 (2018), Iss. 7 P.075010
https://doi.org/10.1088/1361-6420/aac220 [Citations: 14] -
Stochastic Modeling and Regularity of the Nonlinear Elliptic curl--curl Equation
Römer, Ulrich | Schöps, Sebastian | Weiland, ThomasSIAM/ASA Journal on Uncertainty Quantification, Vol. 4 (2016), Iss. 1 P.952
https://doi.org/10.1137/15M1026535 [Citations: 8] -
Experimental spectro-angular mapping of light distribution in turbid media
Grabtchak, Serge
Journal of Biomedical Optics, Vol. 17 (2012), Iss. 6 P.067007
https://doi.org/10.1117/1.JBO.17.6.067007 [Citations: 12] -
Recovery of the absorption coefficient in radiative transport from a single measurement
Acosta, Sebastian
Inverse Problems & Imaging, Vol. 9 (2015), Iss. 2 P.289
https://doi.org/10.3934/ipi.2015.9.289 [Citations: 2] -
Numerical Approximation of the Magnetoquasistatic Model with Uncertainties
Uncertainty Quantification
Römer, Ulrich
2016
https://doi.org/10.1007/978-3-319-41294-8_5 [Citations: 0] -
Analysis of FE
Slawomir Wiak, Professor | Offermann, Peter | Hameyer, KayCOMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, Vol. 34 (2015), Iss. 2 P.596
https://doi.org/10.1108/COMPEL-07-2014-0174 [Citations: 0] -
Overview of diffuse optical tomography and its clinical applications
Hoshi, Yoko | Yamada, YukioJournal of Biomedical Optics, Vol. 21 (2016), Iss. 9 P.091312
https://doi.org/10.1117/1.JBO.21.9.091312 [Citations: 173] -
Primal-dual approach to optical tomography with discretized path integral with efficient formulations
Yuan, Bingzhi | Tamaki, Toru | Raytchev, Bisser | Kaneda, KazufumiJournal of Medical Imaging, Vol. 4 (2017), Iss. 3 P.033501
https://doi.org/10.1117/1.JMI.4.3.033501 [Citations: 0]