• CN: 11-2187/TH
  • ISSN: 0577-6686

›› 2010, Vol. 46 ›› Issue (8): 83-87.

• Article • Previous Articles     Next Articles

Solution for Difficulties in Simulation Analysis of Turbine Runner Based on Similarity Theory

JI Shude; ZHANG Liguo;LIU Xuesong; FANG Hongyuan;YU Dongyuan   

  1. Aeronautical Manufacturing Process Digitization Key Lab of Fundamental Science for National Defense, Shenyang Institute of Aeronautical Engineering State Key Laboratory of Advanced Welding Production Technology, Harbin Institute of Technology
  • Published:2010-04-20

Abstract: In order to solve the difficulties with large number of elements and increments in the process of turbine runner simulation, the corresponding relation of welding residual stress between practical component and simulative component is established on the basis of similarity theory, the conception of virtual simulative component and the auxiliary value of welding residual stress deduced on the basis of welding conduction theory. The simulation analysis is done between the practical runner and the runner’s simulative component. Moreover, the proportionality coefficient of dimensions between the practical structure and simulative component is 1.5:1. The results show that the distribution of welding residual stress along the blade outlet of the runner’s simulative component is the same as that of the practical runner. The relative value of welding stress attained by the simulation method between the practical runner and the simulative component is compared with the relative value obtained from the similarity theory. Moreover, the error is less than 10%. Those results adequately prove that the runner’s simulative component established on the basis of similarity theory can substitute the practical runner to carry out simulation. Therefore, the difficulties in the process of runner simulation are solved.

Key words: Runner, Similarity theory, Simulative component, Welding residual stress, commercial vehicle, co-simulation, lateral control, PSO optimization, RBF neural network, TruckSim, automobile engineering

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