The Forming Process And Computer Simulation Of Large-diameter T-tube

T-tube is a special pipe-connector which is a large quantity of application and a wide range of application in modernize industry. It appears local eddy which is significant impact on pipe performance when T-tube carries liquid or gas.We apply traditional manufacturing methods to manufacture T-tube which has many major defects.Now the research and manufacture of some means which manily use high-quality seamless steel pipe for forming T-tube is at the initial stage at home. The article mainly introduced high-pressure process and flanging process to manufacture large-diameter seamless T-tube.Firstly,the article applied DYNAFORM software to carry on numerical simulation of the internal high-pressure forming(IHF).It analyzed the loading path of process parameters which include internal pressure, axial feed and back pressure to consist of the IHF quality of T-tube.Results of linear loading paths show:(1)Enough axial feed is necessary to obtain a certain amount of branch-tube, but too much axial feed will increase the thickness severely.(2) Too large internal pressure or too small back pressure will reduce the thickness severely or even cause burst,on the contrary, too small internal pressure or too large back pressure will result in a small amount of branch-tube. Because the back pressure will play a negative role on the growing of branch-tube. Further, the influence of friction coefficient and corner radius were also studied. The smaller friction coefficient or larger corner radius could produce a forming quality of the better T-tube. Then it forecasted and optimized the match of the IHF parameters for different diameter T-tube, by means of Neural Network and Genetic Algorithms.It could obtain forming quality of the better T-tube. The results show that combined use of Neural Network and Genetic Algorithms is a effective way to solve the process parameters forecast and optimization problem in IHF.The enterprise applies multipass flanging process to manufacture large-diameter T-tube now. The article mainly studied once flanging process. Firstly,the article analyzed influencing factor of flanging process,and confirmed that the shape of pre-manufactured hole is the key of forming quality.Then it applied pre-manufactured hole pipe which was designed by pressing deformation law to once forming equal T-tube,and used DEFORM software to put up numerical simulation of flanging process. Then it applied Artifical Neural Network and Genetic Algorithms to optimize flanging process parameters of large-diameter T-tube,which include pre-manufactured hole of tube and movement velocity of punch,and obtained T-tube of better forming quality. Finally,through researching flanging process of small-diameter T-tube we can come to the conclusion: Tube of pre-manufactured hole which is based on pressing deformation law can once form T-tube of specific altitudes,but we must optimize flanging process parameters which include pre-manufactured hole of tube and movement velocity of punch. Reducing pipe is another special pipe-connector. Shrink mouth is one of pressing basic process.We insufficiently investigate this forming process at present.We mainly design shrink mouth process through method of trial and error which has long debugging period, causes waste of resources,and increases cost of production. The article mainly researched shrink mouth process of large-diameter thick-walled seamless tube.Firstly,it analyzed influencing factor of shrink mouth process.Then it used DEFORM software to simulate shrink mouth process,and obtained forming quality of the better reducing pipe.Through the analysis of shrink mouth process parameters and reducing pipe stress, we can come to the conclusion:(1)Firstly,we must advance cutting accuracy of shrink mouth process.(2)We must confirm necking coefficient before simulation.If necking coefficient is too small,we must carry on multipass shrink mouth process.(3) Deformation mainly occurs to necking zone and sizing area when tube goes through shrink mouth. Wall thickness in necking zone becomes thick.