Analysis and Approximations of Dirichlet Boundary Control Of Stokes Flows in the Energy Space
Abstract
We study Dirichlet boundary control of Stokes flows in 2D polygonal domains. We consider cost functionals with two different boundary control regularization terms: the \bfitL 2(\Gamma)-norm and an energy space seminorm. We prove well-posedness, provide first order optimality conditions, derive regularity results, and develop finite element discretizations for both problems, and we also prove finite element error estimates for the latter problem. The motivation to study the energy space problem follows from our analysis: we prove that the choice of the control space \bfitL 2(\Gamma) can lead to an optimal control with discontinuities at the corners, even when the domain is convex. This phenomenon is also observed in numerical experiments. This behavior does not occur in Dirichlet boundary control problems for the Poisson equation on convex polygonal domains, and it may not be desirable in real applications. For the energy space problem, we show that the solution of the control problem is more regular than the solution of the problem with the \bfitL 2(\Gamma)-regularization. The improved regularity enables us to prove a priori error estimates for the control in the energy norm. We present several numerical experiments for both control problems on convex and nonconvex domains.
Recommended Citation
W. Gong et al., "Analysis and Approximations of Dirichlet Boundary Control Of Stokes Flows in the Energy Space," SIAM Journal on Numerical Analysis, vol. 60, no. 1, pp. 450 - 474, Society for Industrial and Applied Mathematics, Jan 2022.
The definitive version is available at https://doi.org/10.1137/21M1406799
Department(s)
Mathematics and Statistics
Keywords and Phrases
Dirichlet Boundary Control; Energy Space; Error Estimates; Finite Element Method; Regularity; Stokes Flows
International Standard Serial Number (ISSN)
0036-1429
Document Type
Article - Journal
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2022 Society for Industrial and Applied Mathematics, All rights reserved.
Publication Date
01 Jan 2022
Comments
This work was supported by the National Science Foundation, Grant MTM2017-83185-P.