Results 31 to 40 of about 27,402 (200)
Galerkin projected residual method applied to diffusion–reaction problems [PDF]
Computer Methods in Applied Mechanics and Engineering, 2008 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Dutra do Carmo, Eduardo Gomes +3 more
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Advanced Modeling and Simulation in Engineering Sciences, 2023 We present a Reduced Order Model (ROM) which exploits recent developments in Physics Informed Neural Networks (PINNs) for solving inverse problems for the Navier–Stokes equations (NSE).
Saddam Hijazi +2 more
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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.
doaj
To be or not to be intrusive? The solution of parametric and stochastic equations - the "plain vanilla" Galerkin case [PDF]
, 2013 In parametric equations - stochastic equations are a special case - one may want to approximate the solution such that it is easy to evaluate its dependence of the parameters.
Giraldi, Loïc +5 more
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Journal of Inequalities and Applications, 2010 We analyze discontinuous Galerkin methods with penalty terms, namely, symmetric interior penalty Galerkin methods, to solve nonlinear Sobolev equations.
Hyun Young Lee +2 more
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Известия высших учебных заведений. Поволжский регион: Физико-математические науки, 2023 Background. The purpose of this study is to prove the convergence of the projection method in the problem of diffraction of electromagnetic waves by scatterers of a complex shape. Material and methods.
Aleksey A. Tsupak
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Greedy low-rank algorithm for spatial connectome regression [PDF]
, 2019 Recovering brain connectivity from tract tracing data is an important computational problem in the neurosciences. Mesoscopic connectome reconstruction was previously formulated as a structured matrix regression problem (Harris et al., 2016), but existing
Benner, Peter +3 more
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On the Peculiarities of Solving the Coefficient Inverse Problem of Heat Conduction for a Two-Part Layer [PDF]
Известия Саратовского университета. Новая серия: Математика. Механика. Информатика, 2019 The coefficient inverse problem of thermal conductivity about the determination of the thermophysical characteristics of the functional-gradient part of a two-component layer is posed.
Vatulyan, Alexandr Ovanesovitsch +1 more
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Frontiers in Physics, 2022 High order entropy stable schemes provide improved robustness for computational simulations of fluid flows. However, additional stabilization and positivity preserving limiting can still be required for variable-density flows with under-resolved features.
Jesse Chan +5 more
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BUQEYE guide to projection-based emulators in nuclear physics
Frontiers in Physics, 2023 The BUQEYE collaboration (Bayesian Uncertainty Quantification: Errors in Your effective field theory) presents a pedagogical introduction to projection-based, reduced-order emulators for applications in low-energy nuclear physics.
C. Drischler +5 more
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