A Finite-Volume based POD-Galerkin reduced order model is developed for fluid dynamics problems where the (time-dependent) boundary conditions are controlled using two different boundary control strategies: the lifting function method, whose aim is to obtain homogeneous basis functions for the reduced basis space and the penalty method where the boundary conditions are enforced in the reduced order model using a penalty factor. The penalty method is improved by using an iterative solver for the determination of the penalty factor rather than tuning the factor with a sensitivity analysis or numerical experimentation. The boundary control methods are compared and tested for two cases: the classical lid driven cavity benchmark problem and a Y-junction flow case with two inlet channels and one outlet channel. The results show that the boundaries of the reduced order model can be controlled with the boundary control methods and the same order of accuracy is achieved for the velocity and pressure fields. Finally, the reduced order models are 270-308 times faster than the full order models for the lid driven cavity test case and 13-24 times for the Y-junction test case.
翻译:在使用两种不同的边界控制战略控制(依赖时间的)边界条件的情况下,为流体动态问题开发了一个基于Finite-Volume的POD-Galerkin减少订单模型:提升功能方法,目的是为缩小基空间获得同质基础功能,而惩罚方法,即使用惩罚因素在缩小基空间模型中执行边界条件;惩罚方法通过使用一个迭代求解器来确定惩罚系数,而不是通过敏感度分析或数字实验对系数进行调整而得到改善;边界控制方法为两种情况进行了比较和测试:典型的利德驱动孔径基准问题和Y枢纽流,有两个内端通道和一个外端通道。结果显示,可以用边界控制方法控制缩小定序模型的边界,对速度和压力场也实现了同样的精确度。最后,降低的订单模型比利德驱动孔试验案件的全部定序模型快270-308倍,对Y号测试案件是13-24倍。