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Sensitivity Analysis of Weight Coefficients Used in Multiobjective Optimization in Genetic Algorithm Method for Axial Flow Compressor Design

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Proceedings of the National Aerospace Propulsion Conference

Part of the book series: Lecture Notes in Mechanical Engineering ((LNME))

Abstract

The sensitivity of the fitness function comprising of weight coefficients assigned to performance variables in a genetic algorithm for meanline design of a transonic compressor is studied. The sum of the weight coefficients is unity. Six performance variables considered are the pressure ratio, efficiency, De-Haller numbers (for rotor and stator), and diffusion factors (for rotor and stator). Based on prior trials, the optimum weight coefficients for pressure ratio and efficiency were considered 0.3 each in the fitness function. Hence the sum of the weight coefficients for the two De-Haller Numbers and two Diffusion Factors considered is 0.4. The values of assigned weights have a significant impact on optimization outcome. Optimized design trials of weight coefficients with higher weightage to DFR resulted in higher efficiency with lower pressure ratio. Optimized design trials with higher weightages to DEHR and DEHS yielded into higher pressure ratio but lower efficiency. The data generated provides a guideline to choose combinations of weight coefficients for fitness functions for several performance requirements of a similar class of compressors for various applications.

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Abbreviations

AR:

Blade Aspect Ratio

3-D:

Three-Dimensional

CFD:

Computational Fluid Dynamics

DEHR:

Rotor De-Haller Number

DEHS:

Stator De-Haller Number

DFR:

Rotor Diffusion Factor

DFS:

Stator Diffusion Factor

F:

Fitness function

GA:

Genetic Algorithm

H:

Total enthalpy (J)

K:

Flow blockage factor

N:

Rotational speed rpm

P:

Total Pressure (Pa)

PR:

Total Pressure Ratio

T:

Total temperature (K)

U:

Blade velocity (m/s)

V:

Absolute air velocity (m/s)

W’:

Mass flow rate (kg/s)

w:

Weight coefficient

α:

Swirl

Δ:

Property change (inlet to outlet)

η:

Efficiency

γ:

Ratio of specific heats

σ:

Solidity

φ:

Flow coefficient

ψ:

Loading coefficient

1:

Rotor inlet

2:

Rotor exit

3:

Stator inlet

4:

Stator exit

θ:

Circumferential direction

z:

Axial direction

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Authors and Affiliations

  1. Gas Turbine Research Establishment, Bangalore, Karnataka, India

    NB Balsaraf & S. Kishore Kumar

Authors
  1. NB Balsaraf
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  2. S. Kishore Kumar
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Corresponding author

Correspondence to NB Balsaraf .

Editor information

Editors and Affiliations

  1. Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, India

    Chetan S. Mistry

  2. Gas Turbine Research Establishment, Bangalore, Karnataka, India

    S. Kishore Kumar

  3. Indian Institute of Science Bangalore, Bangalore, Karnataka, India

    B. N. Raghunandan

  4. Gas Turbine Research Establishment, Bangalore, Karnataka, India

    Gullapalli Sivaramakrishna

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Balsaraf, N., Kishore Kumar, S. (2021). Sensitivity Analysis of Weight Coefficients Used in Multiobjective Optimization in Genetic Algorithm Method for Axial Flow Compressor Design. In: Mistry, C., Kumar, S., Raghunandan, B., Sivaramakrishna, G. (eds) Proceedings of the National Aerospace Propulsion Conference . Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-15-5039-3_2

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  • DOI: https://doi.org/10.1007/978-981-15-5039-3_2

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-5038-6

  • Online ISBN: 978-981-15-5039-3

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