[BOOK][B] Optimal control of partial differential equations
This is a book on Optimal Control Problems (OCPs): how to formulate them, how to set up a
suitable mathematical framework for their analysis, how to approximate them numerically …
suitable mathematical framework for their analysis, how to approximate them numerically …
Isogeometric analysis-based physics-informed graph neural network for studying traffic jam in neurons
The motor-driven intracellular transport plays a crucial role in supporting a neuron cell's
survival and function, with motor proteins and microtubule (MT) structures collaborating to …
survival and function, with motor proteins and microtubule (MT) structures collaborating to …
Regularization-robust preconditioners for time-dependent PDE-constrained optimization problems
In this article, we motivate, derive, and test effective preconditioners to be used with the
Minres algorithm for solving a number of saddle point systems which arise in PDE …
Minres algorithm for solving a number of saddle point systems which arise in PDE …
Driving bifurcating parametrized nonlinear PDEs by optimal control strategies: application to Navier–Stokes equations with model order reduction
This work deals with optimal control problems as a strategy to drive bifurcating solution of
nonlinear parametrized partial differential equations towards a desired branch. Indeed, for …
nonlinear parametrized partial differential equations towards a desired branch. Indeed, for …
Reduced order methods for parametric optimal flow control in coronary bypass grafts, toward patient‐specific data assimilation
Coronary artery bypass grafts (CABG) surgery is an invasive procedure performed to
circumvent partial or complete blood flow blockage in coronary artery disease. In this work …
circumvent partial or complete blood flow blockage in coronary artery disease. In this work …
A low-rank in time approach to PDE-constrained optimization
The solution of time-dependent PDE-constrained optimization problems is a challenging
task in numerical analysis and applied mathematics. All-at-once discretizations and …
task in numerical analysis and applied mathematics. All-at-once discretizations and …
Low-rank solvers for unsteady Stokes–Brinkman optimal control problem with random data
We consider the numerical simulation of an optimal control problem constrained by the
unsteady Stokes–Brinkman equation involving random data. More precisely, we treat the …
unsteady Stokes–Brinkman equation involving random data. More precisely, we treat the …
A streamline upwind Petrov-Galerkin reduced order method for advection-dominated partial differential equations under optimal control
In this paper we will consider distributed Linear-Quadratic Optimal Control Problems dealing
with Advection-Diffusion PDEs for high values of the Péclet number. In this situation …
with Advection-Diffusion PDEs for high values of the Péclet number. In this situation …
POD–Galerkin model order reduction for parametrized time dependent linear quadratic optimal control problems in saddle point formulation
In this work we deal with parametrized time dependent optimal control problems governed
by partial differential equations. We aim at extending the standard saddle point framework of …
by partial differential equations. We aim at extending the standard saddle point framework of …
POD-Galerkin model order reduction for parametrized nonlinear time-dependent optimal flow control: an application to shallow water equations
In the present paper we propose reduced order methods as a reliable strategy to efficiently
solve parametrized optimal control problems governed by shallow waters equations in a …
solve parametrized optimal control problems governed by shallow waters equations in a …