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Multiscale model reduction for neutron diffusion equation
Журнал «Математические заметки СВФУ», 2021Modelling of dynamic processes in nuclear reactors is carried out, mainly, on the basis of the multigroup diffusion approximation for the neutron flux. The neutron diffusion approximation is widely used for reactor analysis and applied in most engineering calculation codes.
Vasilev, Aleksandr O. +2 more
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Theoretical and Mathematical Physics, 2022
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Ammosov, D. A. +3 more
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ammosov, D. A. +3 more
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Numerical Homogenization and Model Order Reduction for Multiscale Inverse Problems
Multiscale Modeling & Simulation, 2019Summary: A new numerical method based on numerical homogenization and model order reduction is introduced for the solution of multiscale inverse problems. We consider a class of elliptic problems with highly oscillatory tensors that varies on a microscopic scale.
Abdulle, Assyr, Di Blasio, Andrea
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Fractal Model for Drag Reduction on Multiscale Nonwetting Rough Surfaces
Langmuir, 2020Rough surfaces in contact with a flow of fluid exhibit alternating no-slip and free shear boundary conditions at the solid-liquid and air-liquid interfaces, respectively, thereby potentially offering drag reduction benefits. The balance between the dynamic pressure in the flow and the restoring capillary pressure in the interasperity spaces determines ...
S. Hatte, R. Pitchumani
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A Stochastic Multiscale Model for Microstructure Model Reduction
2011Abstract : The mechanical properties of a deformed workpiece are sensitive to the initial microstructure. Often, the initial microstructure is random in nature and location specific. To model the variability of properties of the workpiece induced by variability in the initial microstructure, one needs to develop a reduced order stochastic input model ...
Nichols Zabaras, Bin Wen
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Diagnostic Goal-Driven Reduction of Multiscale Process Models
2006Fault detection and diagnosis in large-scale process systems is of great practical importance and present various challenging research problems at the same time. One of them is the computational complexity of the algorithms that causes an exponential growth of the computational resources (time and memory) with increasing system sizes.
Németh, E., Lakner, R., Hangos, K. M.
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Multiscale Model Reduction with Generalized Multiscale Finite Element Methods in Geomathematics
2014In this chapter, we discuss multiscale model reduction using Generalized Multiscale Finite Element Methods (GMsFEM) in a number of geomathematical applications. GMsFEM has been recently introduced (Efendiev et al. 2012) and applied to various problems.
Efendiev, Yalchin R., Presho, Michael
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Dimensional Reduction of a Multiscale Continuum Model of Microtubule Gliding Assays
SIAM Journal on Applied Mathematics, 2014Microtubule gliding assays, in which molecular motors anchored to a plate drive the gliding motion of filaments in a quasi--two-dimensional fluid layer, have been shown to organize into a variety of large-scale patterns. We derive a fully three-dimensional multiscale coarse-grained model of a gliding assay including the evolution of densities of rigid ...
Christel Hohenegger +2 more
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Model Reduction of Multiscale Chemical Langevin Equations: A Numerical Case Study
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2009Two very important characteristics of biological reaction networks need to be considered carefully when modeling these systems. First, models must account for the inherent probabilistic nature of systems far from the thermodynamic limit. Often, biological systems cannot be modeled with traditional continuous-deterministic models.
Vassilios Sotiropoulos +3 more
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A multi-stage deep learning based algorithm for multiscale model reduction
Journal of Computational and Applied Mathematics, 2021Eric Chung +2 more
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