Performance improvement of a transonic centrifugal compressor impeller with splitter blade by three-dimensional optimization

Ekradi, Khalil; Madadi, Ali

doi:10.1016/j.energy.2020.117582

Cited by 55 publications

(13 citation statements)

References 15 publications

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“…The error may be due to the following three reasons: From Figure 9, it can be seen that the numerical calculation of the isentropic efficiency and the test data are close, with the overall value of the total pressure ratio being higher than the reference value (a relative error of 15%). The numerical results are consistent with those of Krain [42] and other researchers [28,[43][44][45]. The error may be due to the following three reasons:…”

Section: Numerical Methods and Validationsupporting

confidence: 90%

“…Figure 9 From Figure 9, it can be seen that the numerical calculation of the isentropic efficiency and the test data are close, with the overall value of the total pressure ratio being higher than the reference value (a relative error of 15%). The numerical results are consistent with those of Krain [42] and other researchers [28,[43][44][45]. The error may be due to the following three reasons: From Figure 9, it can be seen that the numerical calculation of the isentropic efficiency and the test data are close, with the overall value of the total pressure ratio being higher than the reference value (a relative error of 15%).…”

Section: Numerical Methods and Validationsupporting

confidence: 86%

“…Improvements in the total pressure ratio (by 5.3%) and isentropic efficiency (by 1.9%) were captured. Khalil Ekradi and Ali Madadi [28] present a procedure for three-dimensional optimization of a transonic radial compressor impeller with splitter blades by integrating a 3D blade parameterization method, a genetic algorithm (GA), an artificial neural network, and a CFD solver. The isentropic efficiency is increased by 0.97% at the design point, and the total pressure ratio and mass flow rate are increased by 0.74% and 0.65%, respectively.…”

Section: Introductionmentioning

confidence: 99%

“…Compared with traditional parameterization methods [22][23][24][25][26][27][28][29][30][31], which, for a single blade, can require hundreds of variables and full 3D optimization surfaces that are difficult to construct, the number of variables in the MDOF surface parameterization method is effectively reduced to 20, which successfully achieves dimensionality reduction in the parameterization method and easy construction of the surface. At the same time, the method can achieve better flexibility of reshaping, it takes into account the changes in pressure surface and suction surface, maintains the smoothness of the blade profile, increases the design optimization space, and provides a parametric basis for the flexible design of radial compressor impeller blades.…”

mentioning

confidence: 99%

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A Novel Surface Parameterization Method for Optimizing Radial Impeller Design in Fuel Cell System

Liu

Fang

et al. 2021

Energies

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The aerodynamic performance improvement of radial impellers is of positive significance to improve the overall performance of hydrogen fuel cell systems (FCS). Our team proposes a multi-degree-of-freedom (MDOF) surface parameterization method for the global automatic optimization of radial impeller aerodynamics. The MDOF surface parameterization is characterized by fewer variables, construction ease, smoothness, good flexibility, and blade strength maintenance. In this paper, a radial impeller for a 100-kW fuel cell stack is optimized, showing the isentropic efficiency increase of 0.7%, the flow rate increase of 3.77%, and the total pressure ratio increase of 0.37%. The results revealed that the performance of the optimized radial impeller significantly improved, verifying the validity and reliability of the proposed novel design optimization method and providing technical support and methodological research of radial impeller aerodynamic optimization for hydrogen FCS.

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Section: Numerical Methods and Validationsupporting

confidence: 90%

Section: Numerical Methods and Validationsupporting

confidence: 86%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

A Novel Surface Parameterization Method for Optimizing Radial Impeller Design in Fuel Cell System

Liu

Fang

et al. 2021

Energies

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“…It was shown that the two optimized impellers located at PF showed significant improvement in efficiency and operating range, respectively, compared to the original impeller. Ekradi et al [8] used the ANN-GA optimization system to study the effect of impeller blade angle on the performance of the centrifugal compressor.…”

Section: Introductionmentioning

confidence: 99%

A Low-Sample-Count, High-Precision Pareto Front Adaptive Sampling Algorithm Based on Multi-Criteria and Voronoi

Liang

Sang

et al. 2021

Preprint

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In this paper, a Pareto front (PF)-based sampling algorithm, PF-Voronoi sampling method, is proposed to solve the problem of computationally intensive multi-objectives of medium size. The Voronoi diagram is introduced to classify the region containing PF prediction points into Pareto front cells (PFCs). Valid PFCs are screened according to the maximum crowding criterion (MCC), maximum LOO error criterion (MLEC), and maximum mean MSE criterion (MMMSEC). Sampling points are selected among the valid PFCs based on the Euclidean distance. The PF-Voronoi sampling method is applied to the coupled Kringing and NASG-II models and its validity is verified on the ZDT mathematical cases. The results show that the MCC criterion helps to improve the distribution diversity of PF. The MLEC criterion and the MMMSEC criterion reduce the number of training samples by 38.9% and 21.7%, respectively. The computational cost of the algorithm is reduced by more than 44.2%, compared to EHVIMOPSO and SAO-MOEA algorithms. The algorithm can be applied to multidisciplinary, multi-objective, and computationally intensive complex systems.

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Multidisciplinary optimization of the SRV2-O radial compressor using an adjoint-based approach

Châtel

Verstraete

2023

Struct Multidisc Optim

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Performance improvement of a transonic centrifugal compressor impeller with splitter blade by three-dimensional optimization

Cited by 55 publications

References 15 publications

A Novel Surface Parameterization Method for Optimizing Radial Impeller Design in Fuel Cell System

A Novel Surface Parameterization Method for Optimizing Radial Impeller Design in Fuel Cell System

A Low-Sample-Count, High-Precision Pareto Front Adaptive Sampling Algorithm Based on Multi-Criteria and Voronoi

Multidisciplinary optimization of the SRV2-O radial compressor using an adjoint-based approach

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