Review of design optimization methods for turbomachinery aerodynamics

Li, Zhihui; Zheng, Xinqian

doi:10.1016/j.paerosci.2017.05.003

Cited by 156 publications

(95 citation statements)

References 94 publications

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“…Then, CFD simulations were carried out for one hundred cases, and the results were used to start the metamodel coupled single-objective optimization. The metamodel provides a simplified algorithm to approximate the computationally expensive objective function in a computationally cheaper way [28]. In this study, a metamodel with non-parametric regression, which provides improved response quality and predictably high nonlinear behavior of the objective functions with respect to the design parameters, was selected to create the response surface [27] (Figure 8).…”

Section: Optimization Of Main Bladementioning

confidence: 99%

Aerodynamic Design Optimization of a Micro Radial Compressor of a Turbocharger

Atac

Yun

Noh³

2018

Energies

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Abstract:This study presents an aerodynamic design optimization of a micro radial compressor impeller on a turbocharger used in a 0.8 L two-cylinder gasoline engine. In the conventional design optimization of the impeller, the hub and shroud curve of the main blade is commonly parameterized with a beta distribution, and splitter blades are generally considered short versions of the full blade. However, geometrical parameterizations in our study mainly focus on the beta distribution of a full blade, and it is parameterized differently from the conventional way. Eight parameters are selected as design variables for the beta distribution. To maximize the isentropic efficiency, design points that are created by Design of Experiment (DOE) are evaluated through single-objective optimization coupled with a non-parametric regression surrogate model. Furthermore, the splitter leading edge location on the meridional plane is investigated to enhance the performance of the impeller after the optimization process. The results show that total efficiency enhancement of approximately 2.2% is achieved. Furthermore, the findings show that a full blade beta distribution and the splitter leading edge location are sufficient parameters to optimize the impeller, and, with the proposed optimization, splitter blades are no longer copies of the full blade for each application.

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Section: Optimization Of Main Bladementioning

confidence: 99%

Aerodynamic Design Optimization of a Micro Radial Compressor of a Turbocharger

Atac

Yun

Noh³

2018

Energies

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“…In addition, they usually require a large number of analyses of the problem with different input data, which involves in practice considerable computing effort, specially in CPU time. In this paper, the authors have developed analytically the first order derivatives of the objective function proposed in (16) and (17) and the first order derivatives of the constraints proposed in Section 3.4. The authors have also computed analytically the derivatives with respect to all the variables of the problem in order to facilitate the definition of other different optimization problems.…”

Section: Sensitivity Analysismentioning

confidence: 99%

“…For more information about design optimization methods in turbomachinery aerodynamics, see Ref. [17]. Concerning the optimization strategy and objective parameters, Li [18] proposed a two stages approach to optimize the required Net Positive Section Head (NPSHr) of an axial pump.…”

Section: Introductionmentioning

confidence: 99%

Efficiency of bio- and socio-inspired optimization algorithms for axial turbomachinery design

Chikh

Belaidi

Khelladi

et al. 2018

Applied Soft Computing

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Turbomachinery design is a complex problem which requires a lot of experience. The procedure may be speed up by the development of new numerical tools and optimization techniques. The latter rely on the parameterization of the geometry, a model to assess the performance of a given geometry and the definition of an objective functions and constraints to compare solutions. In order to improve the reference machine performance, two formulations including the off-design have been developed. The first one is the maximization of the total nominal efficiency. The second one consists to maximize the operation area under the efficiency curve. In this paper five optimization methods have been assessed for axial pump design: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Cuckoo Search (CS), Teaching Learning Based Optimization (TLBO) and Sequential Linear Programming (SLP). Four non-intrusive methods and the latter intrusive. Given an identical design point and set of constraints, each method proposed an optimized geometry. Their computing time, the optimized geometry and its performances (flow rate, head (H), efficiency (Á), net pressure suction head (NPSH) and power) are compared. Although all methods would converge to similar results and geometry, it is not the case when increasing the range and number of constraints. The discrepancy in geometries and the variety of results are presented and discussed. The computational fluid dynamics (CFD) is used to validate the reference and optimized machines performances in two main formulations. The most adapted approach is compared with some existing approaches in literature.

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“…The superposition of residual stress and assembly stress makes the distribution of stress fields at different positions and depths of the rotor components more complicated. The assembly quality of rotors at all levels has a great impact on the performance of aero-engines [ 1 , 2 , 3 ]. The unevenly distributed stress field will have a significant impact on the fatigue strength and structural deformation of the rotor, which will lead to the coaxiality error of the assembled rotor exceeding the standard.…”

Section: Introductionmentioning

confidence: 99%

Study on Propagation Depth of Ultrasonic Longitudinal Critically Refracted (LCR) Wave

Liu

Chen

et al. 2020

Sensors

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The accurate measurement of stress at different depths in the end face of a high-pressure compressor rotor is particularly important, as it is directly related to the assembly quality and overall performance of aero-engines. The ultrasonic longitudinal critically refracted (LCR) wave is sensitive to stress and can measure stress at different depths, which has a prominent advantage in stress non-destructive measurements. In order to accurately characterize the propagation depth of LCR waves and improve the spatial resolution of stress measurement, a finite element model suitable for the study of LCR wave propagation depths was established based on a wave equation and Snell law, and the generation and propagation process of LCR waves are analyzed. By analyzing the blocking effect of grooves with different depths on the wave, the propagation depth of the LCR wave at seven specific frequencies was determined in turn. On this basis, the LCR wave propagation depth model is established, and the effects of wedge materials, piezoelectric element diameters, and excitation voltages on the propagation depth of LCR waves are discussed. This study is of great significance to improve the spatial resolution of stress measurements at different depths in the end face of the aero-engine rotor.

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Review of design optimization methods for turbomachinery aerodynamics

Cited by 156 publications

References 94 publications

Aerodynamic Design Optimization of a Micro Radial Compressor of a Turbocharger

Aerodynamic Design Optimization of a Micro Radial Compressor of a Turbocharger

Efficiency of bio- and socio-inspired optimization algorithms for axial turbomachinery design

Study on Propagation Depth of Ultrasonic Longitudinal Critically Refracted (LCR) Wave

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