Reduced-order modeling of soft robots. [PDF]
PLoS ONE, 2018 We present a general strategy for the modeling and simulation-based control of soft robots. Although the presented methodology is completely general, we restrict ourselves to the analysis of a model robot made of hyperelastic materials and actuated by ...
Jean Chenevier +4 more
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Reduced order modeling and model order reduction for continuum manipulators: an overview [PDF]
Frontiers in Robotics and AI, 2023 Soft robot’s natural dynamics calls for the development of tailored modeling techniques for control. However, the high-dimensional configuration space of the geometrically exact modeling approaches for soft robots, i.e., Cosserat rod and Finite Element ...
S.M.H. Sadati +4 more
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Reduced order modeling with shallow recurrent decoder networks [PDF]
Nature CommunicationsReduced order modeling is of paramount importance for efficiently inferring high-dimensional spatio-temporal fields in parametric contexts. However, conventional dimensionality reduction techniques are typically limited to known and constant parameters ...
Matteo Tomasetto +4 more
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Lagrangian Reduced Order Modeling Using Finite Time Lyapunov Exponents
Fluids, 2020 There are two main strategies for improving the projection-based reduced order model (ROM) accuracy—(i) improving the ROM, that is, adding new terms to the standard ROM; and (ii) improving the ROM basis, that is, constructing ROM bases that yield more ...
Xuping Xie +4 more
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Reduced order modeling and analysis of the human complement system. [PDF]
PLoS ONE, 2017 Complement is an important pathway in innate immunity, inflammation, and many disease processes. However, despite its importance, there are few validated mathematical models of complement activation.
Adithya Sagar +4 more
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AEROM: NASA’s Unsteady Aerodynamic and Aeroelastic Reduced-Order Modeling Software [PDF]
Aerospace, 2018 The origins, development, implementation, and application of AEROM, NASA’s patented reduced-order modeling (ROM) software, are presented. Using the NASA FUN3D computational fluid dynamic (CFD) code, full and ROM aeroelastic solutions are computed at ...
Walter A. Silva
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Geometry Reduced Order Modeling (GROM) with application to modeling of glymphatic function
Brain Research BulletinComputational modeling of the brain has become a key part of understanding how the brain clears metabolic waste, but patient-specific modeling on a significant scale is still out of reach with current methods. We introduce a novel approach for leveraging
Andreas Solheim +3 more
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Progressive transfer learning for advancing machine learning-based reduced-order modeling [PDF]
Scientific ReportsTo maximize knowledge transfer and improve the data requirement for data-driven machine learning (ML) modeling, a progressive transfer learning for reduced-order modeling (p-ROM) framework is proposed.
Teeratorn Kadeethum +4 more
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REDUCED-ORDER MODELLING OF PARAMETERIZED TRANSIENT FLOWS IN CLOSED-LOOP SYSTEMS [PDF]
EPJ Web of Conferences, 2021 In this paper, two Galerkin projection based reduced basis approaches are investigated for the reduced-order modeling of parameterized incompressible Navier-Stokes equations for laminar transient flows. The first approach solves only the reduced momentum
German Péter +3 more
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Reduced Order Modeling Using Advection-Aware Autoencoders
Mathematical and Computational Applications, 2022 Physical systems governed by advection-dominated partial differential equations (PDEs) are found in applications ranging from engineering design to weather forecasting.
Sourav Dutta +3 more
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