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Showing 1 to 3 of 3 for “"Reduced Order Method"”.
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Application of Steepest-Entropy-Ascent Quantum Thermodynamics to Solid-State Phenomena
… of a condensed matter is constructed using a reduced-order method, where quantum models are replaced by typical solid-state models. The details of the approach are given and the method is applied to make kinetic predictions in various solid-state phenomena: the thermal expansion of silver, the …
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Data-Driven Deep Learning Methods for Physically-Based Simulations
… Networks, training Deep Learning models as reduced models for Uncertainty Quantification. In particular, we look for trained Neural Networks able to predict the outflowing fluxes of a Discrete Fracture Network model. These Neural Networks are also exploited to define a new backbone …
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Proper orthogonal decomposition with interpolation-based real-time modelling of the heart
… However, within the context of the Galerkin method, those simulations require high computational demand, ranging from 16 - 200 CPUs, and long calculation time, lasting from 1 h - 50 h. To solve this problem, this research proposes to make use of a Reduced Order Method (ROM) called the Proper …