Results 41 to 50 of about 27,402 (200)
Nonlinear model order reduction via Dynamic Mode Decomposition [PDF]
, 2016 We propose a new technique for obtaining reduced order models for nonlinear dynamical systems. Specifically, we advocate the use of the recently developed Dynamic Mode Decomposition (DMD), an equation-free method, to approximate the nonlinear term.
Alla, Alessandro, Kutz, J. Nathan
core +2 more sources
Accelerating CFD via local POD plus Galerkin projections
, 2022 Se desarrollan varias técnicas basadas en descomposición ortogonal propia (DOP) local y proyección de tipo Galerkin para acelerar la integración numérica de problemas de evolución, de tipo parabólico, no lineales. Las ideas y métodos que se presentan conllevan un nuevo enfoque para la modelización de tipo DOP, que combina intervalos temporales cortos ...
openaire +3 more sources
Breaking the Kolmogorov Barrier in Model Reduction of Fluid Flows
Fluids, 2020 Turbulence modeling has been always a challenge, given the degree of underlying spatial and temporal complexity. In this paper, we propose the use of a partitioned reduced order modeling (ROM) approach for efficient and effective approximation of ...
Shady E. Ahmed, Omer San
doaj +1 more source
Solving Continuous Models with Dependent Uncertainty: A Computational Approach
Abstract and Applied Analysis, 2013 This paper presents a computational study on a quasi-Galerkin projection-based method to deal with a class of systems of random ordinary differential equations (r.o.d.e.’s) which is assumed to depend on a finite number of random variables (r.v.’s).
J.-C. Cortés +4 more
doaj +1 more source
Error Estimates for Local Discontinuous Galerkin Methods for Linear Fourth-order Equations
Journal of Harbin University of Science and Technology, 2021 This paper studies the stability and error estimates of the local discontinuous Galerkin method for fourth-order linear partial differential equations based on upwind-biased fluxes. Consider using the semi-discrete form of numerical format in the spatial
BI Hui, CHEN Sha-sha
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Conservative model reduction for finite-volume models
, 2018 This work proposes a method for model reduction of finite-volume models that guarantees the resulting reduced-order model is conservative, thereby preserving the structure intrinsic to finite-volume discretizations.
Carlberg, Kevin +2 more
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Local convergence of the FEM for the integral fractional Laplacian
, 2020 We provide for first order discretizations of the integral fractional Laplacian sharp local error estimates on proper subdomains in both the local $H^1$-norm and the localized energy norm.
Faustmann, Markus +2 more
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Journal of Inequalities and Applications, 2022 In this paper, we study the error estimates of local discontinuous Galerkin methods based on the generalized numerical fluxes for the one-dimensional linear fifth order partial differential equations.
Hui Bi, Yixin Chen
doaj +1 more source
POD-Galerkin reduced-order modeling of the El Niño-Southern Oscillation (ENSO)
Applied Ocean ResearchReduced-order modeling (ROM) aims to mitigate computational complexity by reducing the size of a high-dimensional state space. In this study, we demonstrate the efficiency, accuracy, and stability of proper orthogonal decomposition (POD)-Galerkin ROM ...
Yusuf Aydogdu +1 more
doaj +1 more source
Model order reduction for a flow past a wall-mounted cylinder
Archives of Mechanics, 2016 Reduced order models allow quickly predict fluid behaviour and to better understand flow phenomena. They are the key enablers of closed-loop flow control.
W. Stankiewicz +4 more
doaj +1 more source