Study On The Movement Characteristics Of Particulate Pollutants In Oil

The movement characteristics and trends of particulate pollutants in the oil has an important significance to the safe operation of oil equipments. And the movement of oil and particulate pollutants is a typically dilute liquid-solid two phase turbulent flow.Therefore, this paper takes the particulate pollutants from the transformer oil in the horizontal square tube as the research object, utilizes the stochastic trajectory model to construct the dynamic equations of oil and particulate pollutants, analysis the movement characteristics of particulate pollutants. Then we adopts the Laser Doppler Velocimetry(LDV) technology to experimental study oil sample for containing single particle pollutants(Cu particle), and the Particle Image Velocimetry(PIV) technology experimental study oil sample for containing a variety of particulate pollutants oil(Cu particle, Fe particle, SiO2 particle), obtains the movement characteristics of particulate pollutants in oil, lays a solid foundation for the effective control of pollution status and development trend of oil.Firstly, this paper established the dynamic equations of oil and particulate pollutants based on Euler-Lagrange method, Realizable k-? turbulence model and stochastic trajectory model. When the particulate pollutants was subjected to stress analysis, the main consideration to gravity, drag force and Saffman lift force. The Fouier series is used to deal with the resultant force. Through the simulation obtained the movement characteristics of single type of particulate pollutants in oil. Simulation results show that the particulate pollutants concentration distribution is mainly affected by oil main beam, eddy current effect and the particle sedimentation effect; turbulent motion state of particulate pollutants affects turbulent conditions of the flow field,when the pollution degree is more high, the instantaneous velocity of the flow field is increases; When the initial speed of the oil liquid become larger, the axial and radial instantaneous velocity of the flow field is increases.Secondly, through the application of the LDV technology to experiment study on the velocity distribution of the single type of the particulate pollutants in the horizontal square tube. For the deficiency of original analysis methods of the particle instantaneous velocity in LDV, and put forward a new advanced analysis method of particle instantaneous velocity. By using this advanced analysis method to obtained the distribution characteristics of instantaneous velocity and the average velocity of the particulate pollutants in different pollution degree.And then according to the experimental results of LDV, the experimental study to the velocity distribution of the various types of the particulate pollutants in oil liquid velocity distribution in the horizontal square tube using the PIV technology.The MATLAB software is used to process the image of the particulate pollutant collected by PIV, access to the different degree of the distribution characteristics of the instantaneous velocity and average velocity along the axial distance and radial distance in different pollution degree. And we can gains the turbulent kinetic energy and the turbulent dissipation rate along the distance change of the turbulent situation in a horizontal square pipe at beginning end, middle segment of the pipeline, and the pipe end. The results show that the distribution of the instantaneous velocity and the average velocity of the particulate pollutants are mainly influenced by the mainstream flow of oil, the vortex entrainment and the particle sedimentation.Finally, the movement characteristics of particulate pollutants of the experimental results was compared with the simulation results, the overall trend of axial velocity of the particle is consistent, validated the proposed model can adequately express the effect of the eddy current generated by the oil on the particulate pollutants on the oil.The results could more effective access to contaminant particles in oil migration velocity, trajectory and concentration distribution. It can lay the foundation for the real-time control of oil pollution status.