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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Reduced-Order Modeling of Gust Responses [PDF]
Journal of Aircraft, 2017 This paper describes two approaches to the construction of reduced-order models from computational fluid dynamics to predict the gust response of airfoils and wings.
Wales, Christopher +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
doaj +1 more source
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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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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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 for Linearized Representations of Microphysical Process Rates
, 2022 <p>Datasets for "Reduced Order Modeling for Linearized Representations of Microphysical Process Rates"</p ...
Lamb, Kara +3 more
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Reduced order method for finite difference modeling of cardiac propagation
Current Directions in Biomedical Engineering, 2020 Efficient numerical simulation of cardiac electrophysiology is crucial for studying the electrical properties of the heart tissue. The cardiac bidomain model is the most widely accepted representation of the electrical behaviour of the heart muscle.
Khan Riasat +2 more
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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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