Topology Optimization Based Material Design for 3D Domains Using MATLAB
Applied Sciences, 2022 In this work, a simple, easy to use MATLAB code is presented for the optimal design of materials for 3D domains. For the optimal design of materials, the theoretical framework of topology optimization and that of homogenization were utilized to develop a
George Kazakis, Nikos D. Lagaros
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Reduced Order Models for the Quasi-Geostrophic Equations: A Brief Survey
Fluids, 2020 Reduced order models (ROMs) are computational models whose dimension is significantly lower than those obtained through classical numerical discretizations (e.g., finite element, finite difference, finite volume, or spectral methods).
Changhong Mou +4 more
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Reduced Order Probabilistic Emulation for Physics‐Based Thermosphere Models
Space Weather, 2023 The geospace environment is volatile and highly driven. Space weather has effects on Earth's magnetosphere that cause a dynamic and enigmatic response in the thermosphere, particularly on the evolution of neutral mass density.
Richard J. Licata, Piyush M. Mehta
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odibua/Fit-Hiearchy-of-Reduced-Comb-Drive-Models: Fit Hierarchical Reduced Comb-Drive Models
, 2018 <p>Beta release of parameter fitting for reduced order models</p ...
Ohi Dibua
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Causal and stable reduced-order model for linear high-frequency systems [PDF]
, 2008 With the ever-growing complexity of high-frequency systems in the electronic industry, formation of reduced-order models of these systems is paramount.
Deschrijver, D +6 more
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Deep Learning-Based Accuracy Upgrade of Reduced Order Models in Topology Optimization
Applied Sciences, 2021 Topology optimization problems pose substantial requirements in computing resources, which become prohibitive in cases of large-scale design domains discretized with fine finite element meshes.
Nikos Ath. Kallioras +2 more
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Modern methods of mathematical modeling of blood flow using reduced order methods [PDF]
Компьютерные 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
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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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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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Reduced order models for Lagrangian hydrodynamics
Computer Methods in Applied Mechanics and Engineering, 2022 42 pages, 7 figure, 8 ...
Dylan Matthew Copeland +3 more
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