Design and optimization of turbine blade preform forging using RSM and NSGA II
- 441 Downloads
Forging is one of the production methods of turbine blades. But, because of the complexities of the blades, they cannot be produced in one stage and using preforms is necessary. In this paper, an extruded elliptical cross section was considered as blade preform, then response surface method and multi-objective genetic algorithm was used to optimize this preform. Maximum filling ratio of the final die and minimum flash volume, forging force and strain variance of final blade were considered as objectives of optimization. Design Expert software was used for design of experiment and optimization. Also Deform-3D software was applied to simulate the forging process. The optimized preform was compared with the preform resulted from conventional preform designing method. Results show that optimization method gives better results than conventional method. Also physical modeling was used for verification of simulation results. Results show simulation results have a good corresponding with experimental results.
KeywordsForging of turbine blades Preform optimization Response surface method Multi-objective optimization
- Bakhtiari, H., Karimi, M., & Rezazadeh, S. (2014). Modeling, analysis and multi-objective optimization of twist extrusion process using predictive models and meta-heuristic approaches, based on finite element results. Journal of Intelligent Manufacturing. doi: 10.1007/s10845-014-0879-6.
- Deb, K. (2001). Multi-objective optimization using evolutionary algorithms (Vol. 16). New Jersey: Wiley.Google Scholar
- DEFORMTM, S. (2007). 3D Version 6.1 (sp1) User’s Manual Oct 10th 2007, Corporation SFT.Google Scholar
- Montgomery, D. C. (2008). Design and analysis of experiments. New Jersey: Wiley.Google Scholar
- Ou, H., & Balendra, R. (1998). Modelling techniques for nett-forging of turbine blades. in IMECHE Conference Transactions. Mechanical Engineering Publications.Google Scholar
- Pareto, V. (1897). Cours d’Economic Politique (Vol. II). Lausanne: F. Rouge.Google Scholar
- Shao, Y., Lu, B., Ou, H., & Chen, J. (2014). A new approach of preform design for forging of 3D blade based on evolutionary structural optimization. Structural and Multidisciplinary Optimization. doi: 10.1007/s00158-014-1110-2.
- Yanhui, Y., et al. (2009). Multi-objective preform optimization using RSM. Rare Metal Materials and Engineering, 38(6), 1019–1024.Google Scholar