Title :
Scalable Parallel Algorithms for Boundary Control of Thermally Convective Flows
Author :
Yang, Haijian ; Cai, Xiao-Chuan
Author_Institution :
Coll. of Math. & Econ., Hunan Univ., Changsha, China
Abstract :
Optimal control of fluid flows is an important and computationally challenging problem. In this paper, we investigate the application of a class of parallel and fully coupled two-grid Lagrange-Newton-Krylov-Schwarz (LNKSz) algorithms for the boundary control of thermally convective flows. The investigation focuses on the use of a two-grid inexact Newton solver for the necessary optimality condition obtained from the optimization problem and the use of a Krylov subspace solver together with an efficient two-level overlapping Schwarz preconditioner for the Jacobian system. Our parallel numerical results show that the proposed method is scalable with respect to the number of processors, the grid size, and robust with respect to some physical parameters such as the Reynolds number and the Grashof number. We also show some large scale calculations involving several million unknowns obtained on a supercomputer with more than two thousand processors.
Keywords :
flow; flow control; optimal control; optimisation; Grashof number; Jacobian system; Krylov subspace solver; Reynolds number; boundary control; fluid flow; grid size; optimal control; optimality condition; optimization problem; scalable parallel algorithm; supercomputer; thermally convective flow; two grid Lagrange-Newton-Krylov-Schwarz algorithm; two grid inexact Newton solver; two-level overlapping Schwarz preconditioner; Cavity resonators; Equations; Jacobian matrices; Newton method; Optimization; Program processors; Temperature control; Schwarz preconditioner; flow control; incompressible Navier-Stokes equations; inexact Newton; nonlinear constrained optimization; parallel computing; temperature control;
Conference_Titel :
Parallel and Distributed Processing Symposium Workshops & PhD Forum (IPDPSW), 2012 IEEE 26th International
Conference_Location :
Shanghai
Print_ISBN :
978-1-4673-0974-5
DOI :
10.1109/IPDPSW.2012.176