DeepAI AI Chat
Log In Sign Up

Pressure-robustness in the context of optimal control

by   Christian Merdon, et al.

This paper studies the benefits of pressure-robust discretizations in the scope of optimal control of incompressible flows. Gradient forces that may appear in the data can have a negative impact on the accuracy of state and control and can only be correctly balanced if their L^2-orthogonality onto discretely divergence-free test functions is restored. Perfectly orthogonal divergence-free discretizations or divergence-free reconstructions of these test functions do the trick and lead to much better analytic a priori estimates that are also validated in numerical examples.


page 9

page 10

page 13

page 14


A New Global Divergence Free and Pressure-Robust HDG Method for Tangential Boundary Control of Stokes Equations

In [ESAIM: M2AN, 54(2020), 2229-2264], we proposed an HDG method to appr...

Pressure-robust error estimate of optimal order for the Stokes equations on domains with edges

The velocity solution of the incompressible Stokes equations is not affe...

Pressure robust mixed methods for nearly incompressible elasticity

Within the last years pressure robust methods for the discretization of ...

Data-Driven Distributionally Robust Optimal Control with State-Dependent Noise

This paper introduces innovative data-driven techniques for estimating t...

Evolvability Is Inevitable: Increasing Evolvability Without the Pressure to Adapt

Why evolvability appears to have increased over evolutionary time is an ...