The aim of this work is to present a model reduction technique in the framework of optimal control problems for partial differential equations. We combine two approaches used for reducing the computational cost of the mathematical numerical models: domain-decomposition (DD) methods and reduced-order modelling (ROM). In particular, we consider an optimisation-based domain-decomposition algorithm for the parameter-dependent stationary incompressible Navier-Stokes equations. Firstly, the problem is described on the subdomains coupled at the interface and solved through an optimal control problem, which leads to the complete separation of the subdomain problems in the DD method. On top of that, a reduced model for the obtained optimal-control problem is built; the procedure is based on the Proper Orthogonal Decomposition technique and a further Galerkin projection. The presented methodology is tested on two fluid dynamics benchmarks: the stationary backward-facing step and lid-driven cavity flow. The numerical tests show a significant reduction of the computational costs in terms of both the problem dimensions and the number of optimisation iterations in the domain-decomposition algorithm.
翻译:这项工作的目的是在部分差异方程式最佳控制问题的框架内提出一种模型减少技术;我们结合了用于降低数学数字模型计算成本的两个方法:域分解(DD)方法和减序模型(ROM);特别是,我们考虑为参数依赖的固定压抑性纳维埃-斯托克斯方程式采用基于优化的域分解算法;首先,在界面上对子域作了说明,并通过最佳控制问题解决,从而导致DD方法子域问题完全分离。此外,还建立了获得的最佳控制问题减少的模型;该程序以适当的Orthogonal分解技术和进一步的Galerkin预测为基础;所提出的方法在两个流体动态基准上进行了测试:固定后偏差步骤和液驱动孔流。数字测试显示,在问题尺寸和域分解方程式中,计算成本显著下降。