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Research Papers: Flows in Complex Systems

Profile Design and Multifidelity Optimization of Solid Rocket Motor Nozzle

[+] Author and Article Information
Kuahai Yu

Department of Engineering Mechanics,
Henan University of Science and Technology,
Luoyang 471023, China;
Luoyang Opt-Electro Development Center,
Luoyang 471009, China
e-mail: yukuahai@hotmail.com

Xi Yang

Department of Engineering Mechanics,
Henan University of Science and Technology,
Luoyang 471023, China
e-mail: yanglxz@qq.com

Zhan Mo

Luoyang Opt-Electro Development Center,
Luoyang 471009, China
e-mail: nihao010-313@163.com

1Corresponding author.

2Current address: Department of Engineering Mechanics, Henan University of Science and Technology, Luoyang, 471023, China.

Contributed by the Fluids Engineering Division of ASME for publication in the JOURNAL OF FLUIDS ENGINEERING. Manuscript received February 5, 2013; final manuscript received December 9, 2013; published online February 10, 2014. Assoc. Editor: Elias Balaras.

J. Fluids Eng 136(3), 031104 (Feb 10, 2014) (6 pages) Paper No: FE-13-1090; doi: 10.1115/1.4026248 History: Received February 05, 2013; Revised December 09, 2013

This paper presents a new profile modeling method and multifidelity optimization procedure for the solid rocket motor contoured nozzle design. Two quartic splines are proposed to construct the nozzle divergent section profile, and the coefficients of the splines' functions are calculated by a fortran program. Two-dimensional axisymmetric and three-dimensional compressible Navier–Stokes equations with Re-Normalisation Group (RNG) k-ε turbulent models solve the flow field as low- and high-fidelity models, respectively. An optimal Latin hypercube sampling method produces the sampling points, and Kriging functions establish the surrogate model combining with the low- and high-fidelity models. Finally, the adaptive simulated annealing algorithm is selected to complete the profile optimization, with the objectives of maximizing the thrust and the total pressure recovery coefficient. The optimization improves the thrust by 4.27%, and enhances the recovery coefficient by 4.63%. The result shows the proposed profile modeling method is feasible and effective to enhance the nozzle performance. The multifidelity optimization strategy is valid for improving the computational efficiency.

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Figures

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Fig. 1

Parametric design of contoured nozzle

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Fig. 2

Profile curves with different variables and negative gradient near throat

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Fig. 3

Grid of 3D nozzle model

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Fig. 4

Grid independence study for axial Mach number

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Fig. 5

Space response surface of design variables and objective variable

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Fig. 6

Solid rocket motor nozzle multifidelity optimization procedure

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Fig. 7

Comparison of outlet Mach number

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Fig. 8

Comparison of nozzle divergent section profile

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