2019
DOI: 10.1016/j.apm.2018.09.026
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Fast spectral solutions of the double-gyre problem in a turbulent flow regime

Abstract: Several semi-analytical models are considered for a double-gyre problem in a turbulent flow regime for which a reference fully numerical eddy-resolving solution is obtained. The semianalytical models correspond to solving the depth-averaged Navier-Stokes equations using the spectral Galerkin approach. The robustness of the linear and Smagorinsky eddy-viscosity models for turbulent diffusion approximation is investigated. To capture essential properties of the double-gyre configuration, such as the integral kin… Show more

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Cited by 3 publications
(1 citation statement)
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“…Any effort to approximate the differential evolution of states, i.e., differential kinematics of a Cosserat rod, in terms of a representation with finite number of states, e.g., Pseudo Rigid Body kinematics, is often called Model Order Reduction approach in classic continuum mechanics. Although commonly employed for FEM (Tunay, 2013), Computational Fluid Dynamics (Naghibi et al, 2019), and in control theory (Moore, 1981;Antoulas, 2005;Van Dooren et al, 2008), the application of lightweight slender rigid manipulators for space explorations, undergoing infinitesimal deformations, has motivated the usage of Model Order Reduction techniques in robotics research since 1980s (Book, 1990). More recently, Model Order Reduction (also referred to as Reduction or, interchangeably, as Reduced Order Modeling) techniques are utilized for Soft Robotics research to capture the complex dynamics of active highly deformable structures.…”
Section: Data-driven and Learning-based Modelsmentioning
confidence: 99%
“…Any effort to approximate the differential evolution of states, i.e., differential kinematics of a Cosserat rod, in terms of a representation with finite number of states, e.g., Pseudo Rigid Body kinematics, is often called Model Order Reduction approach in classic continuum mechanics. Although commonly employed for FEM (Tunay, 2013), Computational Fluid Dynamics (Naghibi et al, 2019), and in control theory (Moore, 1981;Antoulas, 2005;Van Dooren et al, 2008), the application of lightweight slender rigid manipulators for space explorations, undergoing infinitesimal deformations, has motivated the usage of Model Order Reduction techniques in robotics research since 1980s (Book, 1990). More recently, Model Order Reduction (also referred to as Reduction or, interchangeably, as Reduced Order Modeling) techniques are utilized for Soft Robotics research to capture the complex dynamics of active highly deformable structures.…”
Section: Data-driven and Learning-based Modelsmentioning
confidence: 99%