Reduced Order Methods for Parametrized Non-linear and Time Dependent Optimal Flow Control Problems, Towards Applications in Biomedical and Environmental Sciences

DOI10.1007/978-3-030-55874-1_83zbMath1478.49017arXiv1912.07886OpenAlexW3165126898MaRDI QIDQ5152883

Zakia Zainib, Maria Strazzullo, Francesco Ballarin, Gianluigi Rozza

Publication date: 27 September 2021

Published in: Lecture Notes in Computational Science and Engineering (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1912.07886

zbMATH Keywords

optimal flow control problemsPOD-Galerkin reduction

Mathematics Subject Classification ID

Optimality conditions for problems involving partial differential equations (49K20) Navier-Stokes equations (35Q30) Biochemistry, molecular biology (92C40) Existence theories for optimal control problems involving partial differential equations (49J20) Variational principles of physics (49S05)

Related Items (5)

POD-Galerkin model order reduction for parametrized nonlinear time-dependent optimal flow control: an application to shallow water equations ⋮ POD-Galerkin model order reduction for parametrized time dependent linear quadratic optimal control problems in saddle point formulation ⋮ POD-based reduced order methods for optimal control problems governed by parametric partial differential equation with varying boundary control ⋮ An extended physics informed neural network for preliminary analysis of parametric optimal control problems ⋮ Driving bifurcating parametrized nonlinear PDEs by optimal control strategies: application to Navier–Stokes equations with model order reduction

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