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Fatigue-Induced Failure of Polysilicon MEMS: Nonlinear Reduced-Order Modeling and Geometry Optimization of On-Chip Testing Device

• Authors : Daniel Calegaro; Massimiliano Merli; Giacomo Ferrari

Subjects: polysilicon MEMS; on-chip testing; reliability

• Source: Micromachines, Vol 15, Iss 12, p 1480 (2024)

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A Novel Reduced-Order Modeling Approach of a Grid-Tied Hybrid Photovoltaic–Wind Turbine–Battery Energy Storage System for Dynamic Stability Analysis

• Authors : Mohammad Adnan K. Magableh; Amr Ahmed A. Radwan; Yasser Abdel-Rady I. Mohamed

Subjects: Grid-tied hybrid PV-wind-battery generation; reduced-order modeling; singular perturbation analysis

• Source: IEEE Open Journal of Power Electronics, Vol 5, Pp 1459-1483 (2024)

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Reduced-Order Modeling for Second-Order Computational Homogenization With Applications to Geometrically Parameterized Elastomeric Metamaterials

• Authors : Guo, T.; Kouznetsova, V.G.; Geers, M.G.D.

Subjects: empirical cubature method; geometrical transformation; hyperreduction

• Source: Guo , T , Kouznetsova , V G , Geers , M G D , Veroy , K & Rokoš , O 2025 , ' Reduced-Order Modeling for Second-Order Computational

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Bridging Large Eddy Simulation and Reduced-Order Modeling of Convection-Dominated Flows through Spatial Filtering: Review and Perspectives

• Authors : Annalisa Quaini; Omer San; Alessandro Veneziani

Subjects: large eddy simulation; reduced-order modeling; spatial filtering

• Source: Fluids, Vol 9, Iss 8, p 178 (2024)

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Reduced-order modeling using the frequency-domain method for parabolic partial differential equations

• Authors : Jeong-Kweon Seo; Byeong-Chun Shin

Subjects: reduced-order modeling; proper orthogonal decomposition; finite element method

• Source: AIMS Mathematics, Vol 8, Iss 7, Pp 15255-15268 (2023)

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Reduced-Order Modeling of Steady and Unsteady Flows with Deep Neural Networks

• Authors : Bryan Barraza; Andreas Gross

Subjects: reduced-order modeling; machine learning; deep neural networks

• Source: Aerospace, Vol 11, Iss 7, p 506 (2024)

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Reduced-order modeling for stochastic large-scale and time-dependent flow problems using deep spatial and temporal convolutional autoencoders

• Authors : Azzedine Abdedou; Azzeddine Soulaimani

Subjects: Uncertainty propagation; Reduced-order modeling; Deep learning

• Source: Advanced Modeling and Simulation in Engineering Sciences, Vol 10, Iss 1, Pp 1-27 (2023)

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Fast and accurate reduced-order modeling of a MOOSE-based additive manufacturing model with operator learning.

• Authors : Yaseen, Mahmoud¹ (AUTHOR); Yushu, Dewen² (AUTHOR); German, Peter³ (AUTHOR)

• Source: International Journal of Advanced Manufacturing Technology. Nov2023, Vol. 129 Issue 7/8, p3123-3139. 17p.

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Analytical, computational, and reduced-order modeling of vortical and turbulent flows

• Authors : Chu, Tianyi

Subjects: Mechanical engineering; computational methods; Modal analysis

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A hybrid numerical methodology coupling Reduced Order Modeling and Graph Neural Networks for non-parametric geometries: applications to structural dynamics problems

• Authors : Matray, Victor; Amlani, Faisal; Feyel, Frédéric ...

Subjects: Reduced-Order Modeling; Non-Parametric Geometries; Graph Neural Networks

• Source: ISSN: 0045-7825 ; Computer Methods in Applied Mechanics and Engineering ; https://hal.science/hal-04585018 ; Computer Methods in Applied Mechanics and Engineering, 2024, 430, pp.117243.

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