Estimating flow fields with reduced order models [PDF]
Heliyon, 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
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Deep learning-based reduced order models in cardiac electrophysiology. [PDF]
PLoS 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
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Multifidelity computing for coupling full and reduced order models. [PDF]
PLoS 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
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Improving reduced-order models through nonlinear decoding of projection-dependent outputs [PDF]
Patterns, 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
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Optimal Sensor Placement in Reduced-Order Models Using Modal Constraint Conditions [PDF]
Sensors, 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
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Reduced order models for thermally coupled low Mach flows [PDF]
Advanced Modeling and Simulation in Engineering Sciences, 2018 In this paper we present a collection of techniques used to formulate a projection-based reduced order model (ROM) for zero Mach limit thermally coupled Navier–Stokes equations. The formulation derives from a standard proper orthogonal decomposition (POD)
Ricardo Reyes +3 more
doaj +6 more sources
High fidelity adaptive mirror simulations with reduced order models [PDF]
Journal of Mathematics in IndustryIn 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
Computational design of patterned interfaces using reduced order models. [PDF]
Sci Rep, 2014 Patterning is a familiar approach for imparting novel functionalities to free surfaces. We extend the patterning paradigm to interfaces between crystalline solids.
Vattré AJ +3 more
europepmc +4 more sources
Rational Function-Based Approach for Integrating Tableting Reduced-Order Models with Upstream Unit Operations: Lubricants and Glidants Case Study [PDF]
PharmaceuticalsBackground/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
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Augmented reduced order models for turbulence
Frontiers 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
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