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Estimating flow fields with reduced order models [PDF]

open access: yesHeliyon, 2023
The estimation of fluid flows inside a centrifugal pump in realtime is a challenging task that cannot be achieved with long-established methods like CFD due to their computational demands.
Kamil David Sommer   +4 more
doaj   +5 more sources

Deep learning-based reduced order models in cardiac electrophysiology. [PDF]

open access: yesPLoS ONE, 2020
Predicting the electrical behavior of the heart, from the cellular scale to the tissue level, relies on the numerical approximation of coupled nonlinear dynamical systems.
Stefania Fresca   +3 more
doaj   +3 more sources

Multifidelity computing for coupling full and reduced order models. [PDF]

open access: yesPLoS ONE, 2021
Hybrid physics-machine learning models are increasingly being used in simulations of transport processes. Many complex multiphysics systems relevant to scientific and engineering applications include multiple spatiotemporal scales and comprise a ...
Shady E Ahmed   +4 more
doaj   +2 more sources

Improving reduced-order models through nonlinear decoding of projection-dependent outputs [PDF]

open access: yesPatterns, 2023
Summary: A fundamental hindrance to building data-driven reduced-order models (ROMs) is the poor topological quality of a low-dimensional data projection.
Kamila Zdybał   +2 more
doaj   +2 more sources

Optimal Sensor Placement in Reduced-Order Models Using Modal Constraint Conditions [PDF]

open access: yesSensors, 2022
Sensor measurements of civil structures provide basic information on their performance. However, it is impossible to install sensors at every location owing to the limited number of sensors available.
Eun-Taik Lee, Hee-Chang Eun
doaj   +2 more sources

High fidelity adaptive mirror simulations with reduced order models [PDF]

open access: yesJournal of Mathematics in Industry
In the design process of large adaptive mirrors numerical simulations represent the first step to evaluate the system design compliance in terms of performance, stability and robustness.
Bernadett Stadler   +5 more
doaj   +2 more sources

Rational Function-Based Approach for Integrating Tableting Reduced-Order Models with Upstream Unit Operations: Lubricants and Glidants Case Study [PDF]

open access: yesPharmaceuticals
Background/Objectives: Glidants and lubricants are commonly used pharmaceutical excipients that enhance powder flowability and reduce inter-particle friction, respectively, but they also negatively impact critical quality attributes such as tablet ...
Sunidhi Bachawala   +2 more
doaj   +2 more sources

Augmented reduced order models for turbulence

open access: yesFrontiers in Physics, 2022
The authors introduce an augmented-basis method (ABM) to stabilize reduced-order models (ROMs) of turbulent incompressible flows. The method begins with standard basis functions derived from proper orthogonal decomposition (POD) of snapshot sets taken ...
Kento Kaneko   +3 more
doaj   +1 more source

Uncertainty quantification for industrial numerical simulation using dictionaries of reduced order models

open access: yesMechanics & Industry, 2022
We consider the dictionary-based ROM-net (Reduced Order Model) framework [Daniel et al., Adv. Model. Simul. Eng. Sci. 7 (2020) https://doi.org/10.1186/s40323-020-00153-6] and summarize the underlying methodologies and their recent improvements.
Daniel Thomas   +4 more
doaj   +1 more source

A Class of Reduced-Order Regenerator Models

open access: yesEnergies, 2021
We present a novel class of reduced-order regenerator models that is based on Endoreversible Thermodynamics. The models rest upon the idea of an internally reversible (perfect) regenerator, even though they are not limited to the reversible description ...
Raphael Paul, Karl Heinz Hoffmann
doaj   +1 more source

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