四川轻化工大学学报（自然科学版）2025，Vol.38Issue(2)：37-46,10.DOI:10.11863/j.suse.2025.02.05
基于VOF法和改进DNN模型的三维液滴曲率算法
Three-dimensional Droplet Curvature Algorithm Based on VOF Method and Improved DNN Model
摘要
Abstract
The VOF(Volume Of Fluid)method can represent smooth interfaces through discrete volume fraction fields on an Eulerian grid,which is widely used in the numerical simulation of immiscible fluids.An algorithm for calculating droplet curvature in multiphase flow simulations has been developed.Firstly,a new data generation method is proposed,involving random sampling on droplet interfaces to enhance the information content of volume fractions within the grid and adjust the value range to cover both positive and negative curvatures.Secondly,the traditional deep neural network(DNN)model is improved to maintain symmetry when calculating curvature.Based on the VOF method and the improved DNN model,curvature is calculated using the volume fractions of the target cell and its neighboring cells.Finally,the optimal model is selected and applied in the Basilisk software to improve the accuracy and stability of curvature calculations.Test results show that the curvature calculation is accurate and stable.When calculating the curvature of small-radius droplets,the error is reduced by 25%to 50%,and the model can be used for droplet merging simulations,proving its application value.关键词
VOF法/液滴曲率/深度神经网络/数值模拟/液滴仿真Key words
VOF method/droplet curvature/deep neural network/numerical simulation/droplet simulation分类
通用工业技术引用本文复制引用
曾西平,刘牧远..基于VOF法和改进DNN模型的三维液滴曲率算法[J].四川轻化工大学学报（自然科学版）,2025,38(2):37-46,10.基金项目
国家自然科学基金青年科学基金项目(11902275) （11902275）
