Numerical Simulation And Prediction Of Flow Characteristics Of Droplet Impacting On The Wall

Droplet impacting on the wall is a very common natural phenomenon,which widely exists in nature,production and life.In the process of droplet impacting on the wall,the characteristics of the wall and the initial state of the droplet have a great influence on the spreading process.According to the different parameters of wall wettability,droplet diameter,surface tension and mass,the droplet will produce different deformation under the impact force,and the shape after reaching stability will also be different.In order to simulate the dynamic process of droplet impacting on the wall,the Kernel Gradient Correction(KGC)technique,artificial viscosity coefficient,Extended Smoothed Particle Hydrodynamics(XSPH),density reinitialization and boundary treatment are adopted in this paper.Firstly,the natural flow process of fluid in square cavity are simulated and analyzed.Then,the Continuum Surface Force(CSF)model is introduced to simulate the natural change process of the square droplet without gravity field,and compared with other research results,which shows that the method used in this paper is effective and accurate.At the same time,the selection of initial particle diameter,kernel function and artificial viscosity coefficient is analyzed.Then,the dynamic flow process of droplet impacting on a constant temperature wall is simulated and compared with the experimental results.The effects of wall wettability,temperature difference between the wall and droplet and key parameters of the droplet on the droplet flow characteristics are analyzed.The results show that the deformation process of the droplet impacting on the wall is in good agreement with the experimental results,and the deformation of the droplet in the contraction stage of the impacting process is greatly affected by the wettability of the wall.Without considering phase transition,the temperature difference between the wall and the droplet is small,the physical time is very short,the influence of the temperature difference between the wall and the droplet on the droplet flow characteristics could be negligible.However,by analyzing the change of the droplet energy,it can be seen that there is energy exchange between the wall and the droplet;the surface tension,density or impact velocity of the droplet will affect the spreading velocity,the maximum spreading rate and the time required to reach the maximum spreading rate.As an interdisciplinary subject with rapid development in recent years,machine learning has a wide range of applications because it can independently obtain data from samples,analyze rules and then predict,and meet the needs of all walks of life.When different machine learning methods predict the same sample set,different prediction models with different accuracy may be obtained.Choosing the appropriate algorithm can greatly save the time cost of simulation and obtain accurate data.Therefore,we use a variety of machine learning algorithms to predict the change of droplet diameter and energy,and compare the prediction results with the simulation results.Through the comprehensive analysis,we selected a suitable machine learning method for the problem of the droplet impacting on the wall,which can greatly reduce the time required for the simulation process.