合肥工业大学校徽

合肥工业大学学报自科版

合肥工业大学学报(自然科学版)

JOURNAL OF HEFEI UNIVERSITY OF TECHNOLOGY (NATURAL SCIENCE)

主管：中华人民共和国教育部

主办：合肥工业大学

ISSN 1003-5060, CN 34-1083/N

基于 VLES 的横向射流喷雾数值模拟研究

Numerical simulation study of transverse jet spray based on VLES

期刊信息

合肥工业大学（自然科学版），2025年9月，第48卷第9期：1168-1175

DOI: 10.3969/j.issn.1003-5060.2025.09.003

作者信息

周涛涛，钱玉荣，唐志全，王辰，张郁

（合肥工业大学汽车与交通工程学院，安徽合肥230009）

摘要和关键词

摘要: 文章使用超大涡模拟（very large eddy simulation，VLES）方法耦合离散相模型对液体射流在横向气流中雾化过程进行模拟，并对比多套网格尺度下不同湍流模型的预测结果。结果表明，VLES方法能够较为准确地预测横向射流的基本形态及参数。相对其他湍流模型在不同网格尺度下模拟结果波动明显，VLES方法对网格尺寸敏感度较低，并在模拟流场流动细节方面能够捕捉到更多液柱破碎的表面结构，较雷诺平均（Reynolds-averaged Navier-Stokes，RANS）模拟方法有显著优势，且计算量比大涡模拟（large eddy simulation，LES）方法大大降低，在工程实际运用中是一种颇具潜力的数值研究方法。

关键词: 横向射流；数值模拟；超大涡模拟（VLES）；雾化；湍流模型

Authors

ZHOU Taotao, QIAN Yurong, TANG Zhiquan, WANG Chen, ZHANG Yu

(School of Automobile and Traffic Engineering, Hefei University of Technology, Hefei 230009, China)

Abstract and Keywords

Abstract: In this paper, the very large eddy simulation (VLES) method coupled with the discrete phase model (DPM) is used to simulate the atomization process of the liquid jet in the transverse gas flow. The prediction results of different turbulence models at multiple grid scales are compared. The results show that the VLES method can predict the basic morphology and parameters of the transverse jet accurately. Compared to other turbulence models that show significant fluctuation in the simulation results across different grid scales, the VLES model is less sensitive to grid size and captures more intricate surface structures of liquid column fragmentation in flow field simulation. It has a significant advantage over the Reynolds-averaged Navier-Stokes (RANS) simulation method and greatly reduces computational cost compared to large eddy simulation (LES) method. It is a promising numerical research method in engineering practice.

Keywords: transverse jet; numerical simulation; very large eddy simulation (VLES); atomization; turbulence model

基金信息

国家自然科学基金青年科学基金资助项目(52106138); 安徽省自然科学基金资助项目(2008085ME166); 中国博士后科学基金资助项目(2021M690181)和合肥工业大学学术新人提升B计划资助项目(JZ2021HGTB0085)

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