Results 21 to 30 of about 73,174 (233)
Journal of Modern Power Systems and Clean Energy, 2021 In power systems, there are many uncertainty factors such as power outputs of distributed generations and fluctuations of loads. It is very beneficial to power system analysis to acquire an explicit function describing the relationship between these ...
Hao Wu +5 more
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Journal of Computational Physics, 2020 Closure modeling based on the Mori-Zwanzig formalism has proven effective to improve the stability and accuracy of projection-based model order reduction. However, closure models are often expensive and infeasible for complex nonlinear systems.
Qian Wang, N. Ripamonti, J. Hesthaven
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Finite volume POD-Galerkin stabilised reduced order methods for the parametrised incompressible Navier–Stokes equations [PDF]
Computers & Fluids, 2017 In this work a stabilised and reduced Galerkin projection of the incompressible unsteady Navier–Stokes equations for moderate Reynolds number is presented.
G. Stabile, G. Rozza
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Axioms, 2022 This paper is concerned with numerical solutions to Volterra integro-differential equations with weakly singular kernels. Making use of the transformed fractional Jacobi polynomials, we develop a class of piecewise fractional Galerkin methods for solving
Haiyang Li, Junjie Ma
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A stabilizer-free weak Galerkin finite element method on polytopal meshes
Journal of Computational and Applied Mathematics, 2020 A stabilizing/penalty term is often used in finite element methods with discontinuous approximations to enforce connection of discontinuous functions across element boundaries.
X. Ye, Shangyou Zhang
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Galerkin eigenvector approximations [PDF]
Mathematics of Computation, 2000 39 ...
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Communications in Mathematical Research, 2020 Recent years have witnessed growing interests in solving partial differential equations by deep neural networks, especially in the high-dimensional case.
Jingrun Chen, Rui Du, Keke Wu
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Uncertainty Analysis of Neutron Diffusion Eigenvalue Problem Based on Reduced-order Model
Yuanzineng kexue jishu, 2023 In order to improve the efficiency of core physical uncertainty analysis based on sampling statistics, the proper orthogonal decomposition (POD) and Galerkin projection method were combined to study the application feasibility of reduced-order model ...
In order to improve the efficiency of core physical uncertainty analysis based on sampling statistics, the proper orthogonal decomposition (POD) and Galerkin projection method were combined to study the application feasibility of reduced-order model based on POD-Galerkin method in core physical uncertainty analysis. The two-dimensional two group TWIGL benchmark question was taken as the research object, the key variation characteristics of the core flux distribution were extracted under the finite perturbation of the group constants of each material region, and the full-order neutron diffusion problem was projected on the variation characteristics to establish a reduced-order neutron diffusion model. The reduced-order model was used to replace the full-order model to carry out the uncertainty analysis of the group constants of the material region. The results show that the bias of the mathematical expectation of keff calculated by reduced-order and full-order models is close to 1 pcm. In addition, compared with the calculation time required for uncertainty analysis of full-order model, the analysis time of reduced-order model (including the calculation time of the full-order model required for the construction of reduced-order model) is only 11.48%, which greatly improves the efficiency of uncertainty analysis. The biases of mathematical expectation of keff calculated by reduced-order and full-order models based on Latin hypercube sampling and simple random sampling are less than 8 pcm, and under the same sample size, the bias from the Latin hypercube sampling result is smaller. From the TWIGL benchmark test results, under the same sample size, Latin hypercube sampling method is more recommended for POD-Galerkin reduced-order model.
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Discontinuous Galerkin algorithms for fully kinetic plasmas [PDF]
Journal of Computational Physics, 2017 We present a new algorithm for the discretization of the non-relativistic Vlasov–Maxwell system of equations for the study of plasmas in the kinetic regime.
J. Juno +4 more
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Split form nodal discontinuous Galerkin schemes with summation-by-parts property for the compressible Euler equations [PDF]
Journal of Computational Physics, 2016 Fisher and Carpenter (2013) [12] found a remarkable equivalence of general diagonal norm high-order summation-by-parts operators to a subcell based high-order finite volume formulation. This equivalence enables the construction of provably entropy stable
G. Gassner, A. R. Winters, D. Kopriva
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