Design and optimization of turbine blade preform forging using RSM and NSGA II

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.

[1]  Cecil Armstrong,et al.  3D die shape optimisation for net-shape forging of aerofoil blades , 2009 .

[2]  D. Sarkar,et al.  Pareto-optimal solutions for multi-objective optimization of fed-batch bioreactors using nondominated sorting genetic algorithm. , 2005 .

[3]  George-Christopher Vosniakos,et al.  Logic programming for process planning in the domain of sheet metal forming with progressive dies , 2005, J. Intell. Manuf..

[4]  Sina Rezazadeh,et al.  Modeling, analysis and multi-objective optimization of twist extrusion process using predictive models and meta-heuristic approaches, based on finite element results , 2014, Journal of Intelligent Manufacturing.

[5]  Farid R. Biglari,et al.  Optimization of the forging of aerofoil blade using the finite element method and fuzzy-Pareto based genetic algorithm , 2012 .

[6]  Paolo Francesco Bariani,et al.  Hot Workability Studies of Nimonic 80A Applied to the Net-Shape Forging of Aerofoil Blades , 1999 .

[7]  Facai Ren,et al.  Evolutionary forging preform design optimization using strain-based criterion , 2014 .

[8]  Ramana V. Grandhi,et al.  Sensitivity analysis based preform die shape design for net-shape forging , 1997 .

[9]  Baoyu Wang,et al.  Optimization of an aluminum alloy anti-collision side beam hot stamping process using a multi-objective genetic algorithm , 2013 .

[10]  Xin Yao,et al.  Thermodynamic Pareto optimization of turbojet engines using multi-objective genetic algorithms , 2005 .

[11]  Trevor A. Dean,et al.  Aspects of forging of titanium alloys and the production of blade forms , 2001 .

[12]  Liu Dong,et al.  Optimization of Preform Shapes by RSM and FEM to Improve Deformation Homogeneity in Aerospace Forgings , 2010 .

[13]  Dong-Yol Yang,et al.  A new method of preform design in hot forging by using electric field theory , 2002 .

[14]  Bin Lu,et al.  A new approach of preform design for forging of 3D blade based on evolutionary structural optimization , 2015 .

[15]  Peter Williams,et al.  Mechanical Engineering Publications , 1989 .

[16]  Guoqun Zhao,et al.  Preform die shape design for uniformity of deformation in forging based on preform sensitivity analysis , 2002 .

[17]  He Yang,et al.  Deformation characteristic of the precision forging of a blade with a damper platform using 3D FEM analysis , 2004 .

[18]  Sandro Wartzack,et al.  Neural network based modeling and optimization of deep drawing – extrusion combined process , 2014, J. Intell. Manuf..

[19]  Taiying Liu,et al.  A new approach of preform design based on 3D electrostatic field simulation and geometric transformation , 2011 .

[20]  Margaret J. Robertson,et al.  Design and Analysis of Experiments , 2006, Handbook of statistics.

[21]  Yi-Wei Lin,et al.  Application of fuzzy-based Taguchi method to the optimization of extrusion of magnesium alloy bicycle carriers , 2012, J. Intell. Manuf..

[22]  Yang He,et al.  Physical modeling of blade forging , 2000 .

[23]  Hengan Ou,et al.  Preform Design for Forging of Aerofoil Sections using FE Simulation , 1998 .

[24]  Stefania Bruschi,et al.  Integrating physical and numerical simulation techniques to design the hot forging process of stainless steel turbine blades , 2004 .

[25]  V. Pareto,et al.  Vilfredo Pareto. Cours d’Économie Politique , 1897 .

[26]  Somnath Ghosh,et al.  A new approach to optimal design of multi-stage metal forming processes with micro genetic algorithms , 1997 .

[27]  A. Manzoni,et al.  Intelligent computation techniques for process planning of cold forging , 1998, J. Intell. Manuf..

[28]  Cheng Lv,et al.  3D FEM simulation of the multi-stage forging process of a gas turbine compressor blade , 2008 .

[29]  Naksoo Kim,et al.  Preform design in H-shaped cross sectional axisymmetric forging by the finite element method , 1990 .

[30]  Bin Lu,et al.  Shape optimisation of preform design for precision close-die forging , 2011 .

[31]  Kalyanmoy Deb,et al.  Multi-objective optimization using evolutionary algorithms , 2001, Wiley-Interscience series in systems and optimization.

[32]  高涛,et al.  Backward tracing simulation of precision forging process for blade based on 3D FEM , 2006 .

[33]  Fuyuan Yang,et al.  Using Artificial Neural Networks to Investigate the Influence of Temperature on Hot Extrusion of AZ61 Magnesium Alloy , 2006, J. Intell. Manuf..