Results 31 to 40 of about 15,278,073 (285)

Modern methods of mathematical modeling of blood flow using reduced order methods [PDF]

open access: yesКомпьютерные исследования и моделирование, 2018
The study of the physiological and pathophysiological processes in the cardiovascular system is one of the important contemporary issues, which is addressed in many works.
Sergey Sergeevich Simakov
doaj   +1 more source

Pressure Stabilization Strategies for a LES Filtering Reduced Order Model

open access: yesFluids, 2021
We present a stabilized POD–Galerkin reduced order method (ROM) for a Leray model. For the implementation of the model, we combine a two-step algorithm called Evolve-Filter (EF) with a computationally efficient finite volume method.
Michele Girfoglio   +2 more
doaj   +1 more source

Reduced order method for finite difference modeling of cardiac propagation

open access: yesCurrent Directions in Biomedical Engineering, 2020
Efficient numerical simulation of cardiac electrophysiology is crucial for studying the electrical properties of the heart tissue. The cardiac bidomain model is the most widely accepted representation of the electrical behaviour of the heart muscle.
Khan Riasat   +2 more
doaj   +1 more source

Reduced order modeling of non-linear monopile dynamics via an AE-LSTM scheme

open access: yesFrontiers in Energy Research, 2023
Non-linear analysis is of increasing importance in wind energy engineering as a result of their exposure in extreme conditions and the ever-increasing size and slenderness of wind turbines.
Thomas Simpson   +4 more
doaj   +1 more source

Convolutional Autoencoders for Reduced-Order Modeling

open access: yesCoRR, 2021
In the construction of reduced-order models for dynamical systems, linear projection methods, such as proper orthogonal decompositions, are commonly employed. However, for many dynamical systems, the lower dimensional representation of the state space can most accurately be described by a \textit{nonlinear} manifold.
Sreeram Venkat   +2 more
openaire   +2 more sources

Reduced Order Modeling for Linearized Representations of Microphysical Process Rates

open access: yes, 2022
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Lamb, Kara   +3 more
core   +1 more source

Wall‐based reduced‐order modelling [PDF]

open access: yesInternational Journal for Numerical Methods in Fluids, 2015
SummaryIn this work, we propose a novel approach to model order reduction for incompressible fluid flows, which focuses on the spatio‐temporal description of the stresses on the surface of a body, that is, of the wall shear stress and of the wall pressure.
Lasagna, Davide, Tutty, Owen
openaire   +3 more sources

Reduced-Order Model Approaches for Predicting Airfoil Performance

open access: yesActuators
This study delves into the construction of reduced-order models (ROMs) of a flow field over a NACA 0012 airfoil at a moderate Reynolds number and an angle of attack of 8∘. Numerical simulations were computed through the finite-volume solver OpenFOAM. The
Antonio Colanera   +3 more
doaj   +1 more source

Reduced Order Modeling with Skew-Radial Basis Functions for Time Series Prediction

open access: yesEngineering Proceedings, 2023
We present a sparsity-promoting RBF algorithm for time-series prediction. We use a time-delayed embedding framework and model the function from the embedding space to predict the next point in the time series.
Manuchehr Aminian, Michael Kirby
doaj   +1 more source

Generative adversarial reduced order modelling

open access: yesScientific Reports
AbstractIn this work, we present GAROM, a new approach for reduced order modeling (ROM) based on generative adversarial networks (GANs). GANs attempt to learn to generate data with the same statistics of the underlying distribution of a dataset, using two neural networks, namely discriminator and generator.
Coscia, Dario   +2 more
openaire   +6 more sources

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