Multi-objective Pareto optimization of axial compressors using genetic algorithms

Authors:
N. Amanifard;N. Nariman-Zadeh;A. Jamali;M. H. Farahani;R. Farzane-Kari
Affiliations:
Department of Mechanical Engineering, University of Guilan, Rasht, Iran;Department of Mechanical Engineering, University of Guilan, Rasht, Iran;Department of Mechanical Engineering, University of Guilan, Rasht, Iran;Department of Mechanical Engineering, University of Guilan, Rasht, Iran;Department of Mechanical Engineering, University of Guilan, Rasht, Iran
Venue:
ICCOMP'06 Proceedings of the 10th WSEAS international conference on Computers
Year:
2006

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Abstract

Multi-objective genetic algorithm (GAs) (non-dominated sorting genetic algorithm, NSGA-II) with a new diversity preserving mechanism is used for Pareto optimization of axial compressor. The conflicting design objectives of axial compressor are, total efficiency (ηtt), and pressure ratio (πs) and the input parameters are stage inlet angle (α1), inlet Mach number (M1), and the diffusion factor (D). Optimal Pareto front of the axial compressor is obtained which exhibit the trade-off between the corresponding conflicting objectives and, thus, provides different non-dominated optimal choices of axial compressors for designer.