Results 11 to 20 of about 102,961 (219)
Verification of a simplified mathematical model of centrifugal compressor stages [PDF]
E3S Web of Conferences, 2019 To calculate the efficiency of a centrifugal compressor, it is sufficient to know the design parameters and similarity criteria: flow rate coefficient, loading factor, relative hub ratio, Mach number.
Rekstin A. +3 more
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Development of mathematical model of Universal modeling method for centrifugal compressors calculation [PDF]
E3S Web of Conferences, 2019 The heart of the Universal modeling engineering method is the physical model that is based on flow visualization and measurements inside rotating impellers. The experience of its application allowed finding ways of mathematical model development.
Galerkin Yuri +3 more
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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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Convergence Analysis of the Lowest Order Weakly Penalized Adaptive Discontinuous Galerkin Methods [PDF]
, 2012 In this article, we prove convergence of the weakly penalized adaptive discontinuous Galerkin methods. Unlike other works, we derive the contraction property for various discontinuous Galerkin methods only assuming the stabilizing parameters are large ...
Gudi, Thirupathi, Guzmán, Johnny
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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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Galerkin eigenvector approximations [PDF]
Mathematics of Computation, 2000 How close are Galerkin eigenvectors to the best approximation available out of the trial subspace? Under a variety of conditions the Galerkin method gives an approximate eigenvector that approaches asymptotically the projection of the exact eigenvector onto the trial subspace—and this occurs more rapidly than the underlying rate of
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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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Extensions of the deep Galerkin method
Applied Mathematics and Computation, 2022 We extend the Deep Galerkin Method (DGM) introduced in Sirignano and Spiliopoulos (2018)} to solve a number of partial differential equations (PDEs) that arise in the context of optimal stochastic control and mean field games. First, we consider PDEs where the function is constrained to be positive and integrate to unity, as is the case with Fokker ...
Ali Al-Aradi +4 more
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EXPLORING TRANSIENT, NEUTRONIC, REDUCED-ORDER MODELS USING DMD/POD-GALERKIN AND DATA-DRIVEN DMD [PDF]
EPJ Web of Conferences, 2021 There is growing interest in the development of transient, multiphysics models for nuclear reactors and analysis of uncertainties in those models. Reduced-order models (ROMs) provide a computationally cheaper alternative to compute uncertainties. However,
Elzohery Rabab, Roberts Jeremy
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Numerical Quantum Field Theory on the Continuum and a New Look at Perturbation Theory [PDF]
, 2001 The Source Galerkin method finds approximate solutions to the functional differential equations of field theories in the presence of external sources. While developing this process, it was recognized that approximations of the spectral representations of
D. Petrov +12 more
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