Results 31 to 40 of about 4,522,001 (282)
An Artificial Compression Reduced Order Model [PDF]
SIAM Journal on Numerical Analysis, 2020 We propose a novel artificial compression, reduced order model (AC-ROM) for the numerical simulation of viscous incompressible fluid flows. The new AC-ROM provides approximations not only for velocity, but also for pressure, which is needed to calculate forces on bodies in the flow and to connect the simulation parameters with pressure data. The new AC-
Victor DeCaria +4 more
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Reduced Order Modeling with Skew-Radial Basis Functions for Time Series Prediction
Engineering 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
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Passivity-preserving parameterized model order reduction using singular values and matrix interpolation [PDF]
, 2013 We present a parameterized model order reduction method based on singular values and matrix interpolation. First, a fast technique using grammians is utilized to estimate the reduced order, and then common projection matrices are used to build ...
Dhaene, Tom +3 more
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A Reduced Order Model for Monitoring Aeroengines Condition in Real Time
Aerospace, 2023 A very fast reduced order model is developed to monitor aeroengines condition (defining their degradation from a baseline state) in real time, by using synthetic data collected in specific sensors.
Jose Rodrigo +3 more
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Aerospace, 2021 Several classical and non-classical reduced-order nucleation rate models are presented and compared to experimental values for the homogeneous nucleation rate of CO2 in supersonic nozzles.
Philip A. Lax, Sergey B. Leonov
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Efficient high-dimensional variational data assimilation with machine-learned reduced-order models [PDF]
Geoscientific Model Development, 2022 Data assimilation (DA) in geophysical sciences remains the cornerstone of robust forecasts from numerical models. Indeed, DA plays a crucial role in the quality of numerical weather prediction and is a crucial building block that has allowed dramatic ...
R. Maulik +8 more
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Reduced-Order Modeling of Gust Responses [PDF]
Journal of Aircraft, 2017 This paper describes two approaches to the construction of reduced-order models from computational fluid dynamics to predict the gust response of airfoils and wings.
Wales, Christopher +2 more
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Probabilistic Rotor Life Assessment Using Reduced Order Models
Shock and Vibration, 2009 Probabilistic failure assessments for integrally bladed disks are system reliability problems where a failure in at least one blade constitutes a rotor system failure.
Brian K. Beachkofski
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A method to generate computationally efficient reduced order models [PDF]
, 2009 A new method is presented to generate reduced order models (ROMs) in Fluid Dynamics problems. The method is based on the expansion of the flow variables on a Proper Orthogonal Decomposition (POD) basis, calculated from a limited number of snapshots ...
A. Velazquez +21 more
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Generative adversarial reduced order modelling
Scientific ReportsAbstractIn 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 +5 more sources