Microfluidics proved to be a key technology in various applications, allowing to reproduce large-scale laboratory settings at a more sustainable small-scale. The current effort is focused on enhancing the mixing process of different passive species at the micro-scale, where a laminar flow regime damps turbulence effects. Chaotic advection is often used to improve mixing effects also at very low Reynolds numbers. In particular, we focus on passive micromixers, where chaotic advection is mainly achieved by properly selecting the geometry of microchannels. In such a context, reduced order modeling can play a role, especially in the design of new geometries. In this chapter, we verify the reliability and the computational benefits lead by a Hierarchical Model (HiMod) reduction when modeling the transport of a passive scalar in an S-shaped microchannel. Such a geometric configuration provides an ideal setting where to apply a HiMod approximation, which exploits the presence of a leading dynamics to commute the original three-dimensional model into a system of one-dimensional coupled problems. It can be proved that HiMod reduction guarantees a very good accuracy when compared with a high-fidelity model, despite a drastic reduction in terms of number of unknowns.
翻译:微流体被证明是各种应用中的一项关键技术,能够以更可持续的小规模方式复制大型实验室环境。目前的努力重点是在微规模上加强不同被动物种的混合过程,在微规模上,一种拉米纳流机制会阻隔动荡效应。潮湿抗冲往往用来改善混合效应,同样在非常低的雷诺斯数字中也是如此。特别是,我们注重被动微混合器,这种微型混合器主要是通过正确选择微通道的几何测量法来取得混乱的抗冲。在这种情况下,降低定序模型可以发挥作用,特别是在设计新的地貌方面。在本章中,我们核查一个等级模型(Himmod)的可靠性和计算效益,在模拟S型微通道中,一个被动的电路标的运输模式(Himmod Saltar)的运输模式(Himod Smallar ) 通常被用来改善混合效应。这样的几何结构提供了一个理想的环境,即利用领先的动态将原始的三维模型转换成一个一维并存问题的系统。可以证明,在高位模型(Himmod destrain)的减少时,尽管该模型的精确度将保证了非常精确性,但该模型的精确性是未知的减少次数。