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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Computational fluid dynamics modeling of a wafer etch temperature control system
Digital Chemical Engineering, 2023 Next-generation etching processes for semiconductor manufacturing exploit the potential of a variety of operating conditions, including cryogenic conditions at which high etch rates of silicon and very low etch rates of the photoresist are achieved. Thus,
Henrique Oyama +5 more
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A Comparison of Data‐Driven Approaches to Build Low‐Dimensional Ocean Models
Journal of Advances in Modeling Earth Systems, 2021 We present a comprehensive inter‐comparison of linear regression (LR), stochastic, and deep‐learning approaches for reduced‐order statistical emulation of ocean circulation.
Niraj Agarwal +4 more
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Neural Network-Based Model Reduction of Hydrodynamics Forces on an Airfoil
Fluids, 2021 In this paper, an artificial neural network (ANN)-based reduced order model (ROM) is developed for the hydrodynamics forces on an airfoil immersed in the flow field at different angles of attack.
Hamayun Farooq +3 more
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Pressure Stabilization Strategies for a LES Filtering Reduced Order Model
Fluids, 2021 We present a stabilized POD–Galerkin reduced order method (ROM) for a Leray model. For the implementation of the model, we combine a two-step algorithm called Evolve-Filter (EF) with a computationally efficient finite volume method.
Michele Girfoglio +2 more
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Verification of Reduced Order Modeling based Uncertainty/Sensitivity Estimator (ROMUSE)
Nuclear Engineering and Technology, 2019 This paper presents a number of verification case studies for a recently developed sensitivity/uncertainty code package. The code package, ROMUSE (Reduced Order Modeling based Uncertainty/Sensitivity Estimator) is an effort to provide an analysis tool to
Bassam Khuwaileh +3 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 of non-linear monopile dynamics via an AE-LSTM scheme
Frontiers in Energy Research, 2023 Non-linear analysis is of increasing importance in wind energy engineering as a result of their exposure in extreme conditions and the ever-increasing size and slenderness of wind turbines.
Thomas Simpson +4 more
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Predictive and stochastic reduced-order modeling of wind turbine wake dynamics [PDF]
Wind Energy Science, 2022 This article presents a reduced-order model of the highly turbulent wind turbine wake dynamics. The model is derived using a large eddy simulation (LES) database, which cover a range of different wind speeds. The model consists of several sub-models: (1)
S. J. Andersen, J. P. Murcia Leon
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Convolutional Autoencoders for Reduced-Order Modeling
CoRR, 2021 In the construction of reduced-order models for dynamical systems, linear projection methods, such as proper orthogonal decompositions, are commonly employed. However, for many dynamical systems, the lower dimensional representation of the state space can most accurately be described by a \textit{nonlinear} manifold.
Sreeram Venkat +2 more
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