电流体动力喷墨打印中液滴生成的建模与实验验证,用于打印质量预测

Liangkui Jiang, P. Premaratne, Yanhua Huang, Zhan Zhang, H. Qin
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引用次数: 1

摘要

电流体动力(EHD)喷墨打印是一种微纳米级增材制造技术。液滴的产生机理对电流体动力喷墨打印的过程控制、打印质量和打印性能有着重要的影响。由于EHD打印中使用的打印系统设计变化较大,工艺优化技术有限,导致确定工作条件的实验程序复杂,并且需要较长时间才能完成实验。在EHD打印中,多物理场条件下的液滴生成机制的流体动力学研究也是一个挑战。计算流体动力学(CFD)的发展和高性能计算的最新进展可以用来缓解上述挑战。本文基于Taylor-Melchar漏介质模型,建立了EHD打印液滴生成机理的数值模拟模型。该模型成功地模拟了单个打印周期,包括泰勒锥形成、锥射流产生、射流断裂和射流收缩。进一步的模拟研究表明,在不同的工作条件下(如脉冲交流电压的电压和占空比),可以准确预测液滴体积和喷射直径。实验验证了仿真模型及其预测结果。这种建模的进步可以用来优化印刷过程,并指导在给定新油墨的情况下快速选择印刷条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling and Experimental Validation of Droplet Generation in Electrohydrodynamic Inkjet Printing for Prediction of Printing Quality
Electrohydrodynamic (EHD) Inkjet printing is one type of micro/nano scale additive manufacturing technique. The droplet generation mechanism plays an important role in electrohydrodynamic (EHD) inkjet printing due to its significant effects on process control, printing quality, and printing performance. The large variation of printing system design used in EHD printing and the limited process optimization techniques resulted in a complex experimental procedure to determine a working condition, and it takes a long time to finish such experiments. It is also challenging to understand the droplet generation mechanism’s fluid dynamics under a multiphysical field in EHD printing. The development of computational fluid dynamics (CFD) and the recent advancements in high performance computing can be utilized to alleviate the aforementioned challenges. In this study, a numerical simulation model was developed to model the droplet generation mechanism in EHD printing based on Taylor-Melchar leaky-dielectric model. This model successfully simulated a single printing cycle, including Taylor cone formation, cone-jet generation, jet break, and jet retraction. A further simulation study demonstrated accurate predictions of the droplet volume and the jetting diameter under different working conditions (e.g., voltages and duty ratio of pulsed AC voltage). Experiments validated the simulation model and its prediction results. Such advancement in modeling can be used to optimize the printing process as well as guide the quick selection of printing conditions given a new ink.
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CiteScore
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