scholarly journals Development and validation of a hybrid aerodynamic design method for curved diffusers using genetic algorithm and ball-spine inverse design method

2021 ◽  
Vol 60 (3) ◽  
pp. 3021-3036 ◽  
Author(s):  
Mahdi Nili-Ahmadabadi ◽  
Farzad Aghabozorgi ◽  
Dae-Seung Cho ◽  
Kyung Chun Kim
Author(s):  
H-Y Fan

A genetic algorithm incorporating a neural network technique is proposed to search for a turbo-machinery diffuser blade profile that produces a given velocity distribution on its surface. Such a new inverse design method works through minimizing the error between the surface velocity distribution of candidate blades and the target velocity distribution. For ease of employing the genetic algorithm, the blade profiles to be searched are parameterized by Bezier curves. To fix the surface velocity distribution of a candidate blade, a special type of back propagation (BP) neural network is implemented. The proposed approach is illustrated by a diffuser having two-dimensional blades with constant height and thickness. The simulations show that the new method is not only feasible but also reliable and efficient.


Author(s):  
Renfang Huang ◽  
Xianwu Luo ◽  
Zhihong Zhai ◽  
Jiajian Zhou

A mixed-flow waterjet pump with a vaneless diffuser is treated to improve its hydraulic efficiency as well as cavitation performance. In order to conduct the design optimization, the authors apply a multiobjective strategy combined with design of experiments (DOE), computational fluid dynamics (CFD), inverse design method, surface response method (RSM) and non-dominated sorting genetic algorithm-II (NSGA-II). The hydraulic efficiency and the total vapor volume are selected as the optimization targets, and nine parameters are used to describe the blade shape with the same meridional section. For numerical simulation, RANS method is applied with SST k-ω turbulence model and a mass transfer cavitation model based on the Rayleigh-Plesset equation. Optimal Latin hypercube design method is used in the design of experiments to uniformly sample in variation ranges and global optimization is then conducted by using non-dominated sorting genetic algorithm-II (NSGA-II) based on the input-target approximation functions built by the response surface model (RSM). The optimization results demonstrate that both hydraulic efficiency and cavitation performance are improved at the design point through this multiobjective strategy. Based on analysis of the internal flows, secondary flows would be important contributor to the hydraulic loss as well as the nonuniform flow at impeller exit, and can be suppressed by adjusting the blade load along the hub or shroud by using the inverse design method.


2020 ◽  
Vol 51 (1) ◽  
pp. 1-13
Author(s):  
Anatoliy Longinovich Bolsunovsky ◽  
Nikolay Petrovich Buzoverya ◽  
Nikita Aleksandrovich Pushchin

2021 ◽  
Vol 11 (11) ◽  
pp. 4845
Author(s):  
Mohammad Hossein Noorsalehi ◽  
Mahdi Nili-Ahmadabadi ◽  
Seyed Hossein Nasrazadani ◽  
Kyung Chun Kim

The upgraded elastic surface algorithm (UESA) is a physical inverse design method that was recently developed for a compressor cascade with double-circular-arc blades. In this method, the blade walls are modeled as elastic Timoshenko beams that smoothly deform because of the difference between the target and current pressure distributions. Nevertheless, the UESA is completely unstable for a compressor cascade with an intense normal shock, which causes a divergence due to the high pressure difference near the shock and the displacement of shock during the geometry corrections. In this study, the UESA was stabilized for the inverse design of a compressor cascade with normal shock, with no geometrical filtration. In the new version of this method, a distribution for the elastic modulus along the Timoshenko beam was chosen to increase its stiffness near the normal shock and to control the high deformations and oscillations in this region. Furthermore, to prevent surface oscillations, nodes need to be constrained to move perpendicularly to the chord line. With these modifications, the instability and oscillation were removed through the shape modification process. Two design cases were examined to evaluate the method for a transonic cascade with normal shock. The method was also capable of finding a physical pressure distribution that was nearest to the target one.


Author(s):  
M. H. Noorsalehi ◽  
M. Nili-Ahamadabadi ◽  
E. Shirani ◽  
M. Safari

In this study, a new inverse design method called Elastic Surface Algorithm (ESA) is developed and enhanced for axial-flow compressor blade design in subsonic and transonic flow regimes with separation. ESA is a physically based iterative inverse design method that uses a 2D flow analysis code to estimate the pressure distribution on the solid structure, i.e. airfoil, and a 2D solid beam finite element code to calculate the deflections due to the difference between the calculated and target pressure distributions. In order to enhance the ESA, the wall shear stress distribution, besides pressure distribution, is applied to deflect the shape of the airfoil. The enhanced method is validated through the inverse design of the rotor blade of the first stage of an axial-flow compressor in transonic viscous flow regime. In addition, some design examples are presented to prove the effectiveness and robustness of the method. The results of this study show that the enhanced Elastic Surface Algorithm is an effective inverse design method in flow regimes with separation and normal shock.


2021 ◽  
Vol 119 (15) ◽  
pp. 153503
Author(s):  
Chengfu Gu ◽  
Zengtao Yang ◽  
Hua Wang

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