journal article·2025-09-09

An Improved Interpolation Method for Simulating Electrohydrodynamic Atomization in the Cone-Jet Regime

Kofi Owusu-Sekyere, Yongzhong Chen, Jiameng Tian, Haojie Xu, Bin Li, Junfeng Wang, Qingming Dong, Zhentao Wang

Langmuir· Volume 41· Issue 35
Publisher page

Abstract

Electrospray technology in the cone-jet regime has been numerically studied with the development of computational fluid dynamics (CFD). A novel interpolation method, the hybrid averaging mean (HAM), is presented in the present work, aimed at enhancing the accuracy of numerical simulations in electrohydrodynamic (EHD) atomization. Traditional methods such as the weighted arithmetic mean (WAM) and Weighted Harmonic Mean (WHM) have been widely used; however, the limitations are exhibited in terms of stability and computational efficiency. The HAM method combines the strengths of WHM's stability and WAM's simplicity, providing a balanced method to improve the accuracy of capturing interfacial dynamics and charge characteristics in EHD atomization. Through comprehensive numerical and experimental benchmarks, the effectiveness of HAM is evaluated against WAM and WHM, focusing on charge distribution, meniscus evolution, and droplet formation across varying regimes. The findings reveal that HAM significantly improves the modeling of electric field distributions and interfacial forces. The predictive accuracy of the methods is quantified with HAM achieving 4.5% error in beam current calculations, while WHM at 10.4% and WAM at 17.5% error. For droplet diameter predictions, HAM shows 1.2% error, while WHM has 11.8% error, and WAM has 11.2% error. The results underscore the importance of selecting appropriate interpolation methods to enhance the simulation accuracy and reliability in complex electrohydrodynamic systems.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Electrohydrodynamics and Fluid Dynamics · Mass Spectrometry Techniques and Applications · Fluid Dynamics and Heat Transfer

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Energy and Power Engineering

Jiangsu University

Chongqing University

Key Laboratory of Advanced Reactor Engineering and Safety, Ministry of Education

Tsinghua University

Funding

National Natural Science Foundation of China · Key Laboratory of Advanced Reactor Engineering and Safety of Ministry of Education

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