Autonomous, flexible and controllable generation of finest droplets

本文的目的是寻找一种液滴产生系统驱动参数的估计方法，以产生比喷嘴直径小得多的液滴。因此，设计了一个自主控制的压电液滴产生系统来进行实验，并在精确再现液滴产生器几何形状的基础上进行局部解析的压力分布模拟，为研究流体腔内的动力机制服务。其动机是从各种流体中产生不同直径的液滴。这种技术可以应用于增材制造和研究等领域。该自适应控制系统由多个传感器组成（压电致动器反馈信号、用于探测卫星液滴的CCD相机、用于评估液滴稳定性和液滴直径的微型PDA），并自动驱动压电发生器的参数范围以获得单分散液滴。基于神经模糊方法建立了控制系统的模型，并对其重现性、稳定性和动态性进行了研究。在精确了解液滴产生器的材料和几何结构的基础上，通过高分辨率CFD模拟来检验潜在的流体动力学关系。将实验中发现的驱动信号作为流体动力系统的激励，对物理现象进行研究和分类，并推导出不同流体参数产生不同直径液滴的关系和规律。

The aim of this proposal is to find an estimation method for the driving parameters of a droplet generator system to generate much smaller droplets than the nozzle diameter. Therefore, an autonomously controlled piezoelectrical droplet generator system is designed to perform experiments, and locally resolved simulations of the pressure distribution based on a precise reproduction of the geometry of the droplet generator serve for the investigation of the dynamical mechanisms within the fluid chamber. The motivation is to generate droplets with different diameters from a variety of fluids. This technique can be applied, e.g., in Additive Manufacturing as well as in research.The adaptive control system consists in several sensors (feedbach signal of the piezo actuator, CCD camera to detect satellite droplets, miniature PDA to evaluate stability and droplet diameter) and drives autonomously the parameter range of the piezo generator to get monodisperse droplets. The model of the control system is based on neuro-fuzzy methods and its reproducibility, stability, and dynamic are investigated.The underlying fluid dynamical relations are examined by high resolution CFD simulations with exact knowledge of materials and geometry of the droplet generator. The driving signals found in the experiments are applied as excitations of the fluid dynamical system to investigate and classify the physical phenomenon and to derive relations and rules for the generation of different droplet diameters depending on the parameters of the fluid.