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Research On Multi-phase Erosion Characteristics And Characterization Predicted Method Of REAC Outlet Piping

Posted on:2019-10-21Degree:MasterType:Thesis
Country:ChinaCandidate:X F XuFull Text:PDF
GTID:2371330545996175Subject:Control Science and Engineering
Abstract/Summary:PDF Full Text Request
The hydrogenation reaction effluent air cooler?REAC?system is one of the key equipment in the petrochemical refining industry.With the widespread use of hydrogenation processes and degradation of crude oil,it has long been facing the erosion of multi-phase flow corrosive media.Tube bursts and tube explosions are frequent and bring great security risks and economic losses.Due to the complicated erosion mechanism and numerous influencing factors,there is no mature system for predicting the erosion-corrosion failure.Therefore,the accurate prediction of the high-risk area of??pipeline erosion by means of suitable characterization methods is imminent.In this paper,the failure case of outlet piping elbow in the air-cooler system of TJ Petrochemical acid water stripping plant is analyzed.Based on the composition and operating conditions of the multiphase flow,the erosion failure mechanism of the outlet pipe elbow is analyzed,and the water phase fraction,mass transfer coefficient and the maximum shear stress were used as the key parameters for erosion characterization prediction.Mixture multiphase model and SST k-?turbulence model were used to simulate the inlet and outlet piping,and the high-risk areas were predicted based on the distribution of flow parameters.The results show that the NH4HS in the multiphase flow medium is the main corrosion phase that causes the pipe erosion,and there is a large bias in the multiphase flow medium and the flow parameters,such as the flow velocity and the water phase fraction in the A-202C are relatively large;The risk of erosion in 8thh pipe is the highest.The section between the peak values of the water phase fraction,the mass transfer coefficient and the maximum shear stress curve?55°???85°?is the erosion high risk area,and the comparison failure report and elbow analyzing the thickness measurement data,it was found that the predicted results were basically consistent with the actual failure position.The characterization prediction method based on the fraction of water phase,mass transfer coefficient and maximum shear stress was applied to the outlet piping of the REAC system of WH Petrochemical's diesel hydrogenation unit.Erosion risk assessment results showed that there was a slight bias flow in the inlet piping.The high tube bundle number is symmetrical about the left and right sides.Analysis of the distribution of the flow parameters of the elbows reveals that the elbow pipe 3-2 faces the high erosion risk,and the elbow pipes2-1,2-3,and 3-1 areas of upper intermediate risk of erosion,and the elbows 1-1,1-2,1-6,2-2,and 2-4 are areas of medium erosion risk,and bends 1-4,1-5,and 1-7 are areas of lower intermedium risk erosion,bends 1-3 and 1-8 are low erosion risk areas;the most serious position of high-risk elbow erosion is mainly concentrated in the range of 60°???90°,followed by 40°???60°,and finally 10°???30°.Three kinds of stationing method used for different erosion risks are proposed,and thick-gauge distribution plans decided according to its assessment results.The innovative works of this thesis are:based on the study of the erosion mechanism of the elbow,aiming at the stress of the corrosion product film in the multi-phase flow environment,the maximum shear stress is solved by the triaxial stress analysis as the fluid dynamics erosion characterization parameters.The risk of elbow erosion is assessed by mentioned characterization and prediction method,the results of the assessment are applied to determine the petrochemical industry REAC outlet piping thickness measurement and stationing plan,the previous dense measurement of thick stationing method can be improved scientifically.
Keywords/Search Tags:REAC outlet piping, erosion characteristics, mass transfer coefficient, maximum shear stress, characterization prediction
PDF Full Text Request
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