Multi-objective optimization of dual-arc blades in a squirrel-cage fan using modified non-dominated sorting genetic algorithm

Yang, Xiaopei; Jiang, Boyan; Wang, Jun; Huang, Yougen; Yang, Weigang; Yuan, Kemin; Shi, Xuna

doi:10.1177/0957650919898983

Cited by 13 publications

(7 citation statements)

References 15 publications

(15 reference statements)

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“…The impeller is the only rotating part of the fan, and its shape greatly influences the internal flow field and performance of the squirrel-cage fan. Yang et al [24] used more complex double-arc blades to replace the commonly used single-arc blades. It was found that compared with single-arc blades with the same inlet and outlet angles, double-arc blades have higher fan pressure and harm efficiency.…”

Section: Geometric Modelmentioning

confidence: 99%

Squirrel-Cage Fan System Optimization and Flow Field Prediction Using Parallel Filling Criterion and Surrogate Model

Xiao

Shi²,

Wu³

et al. 2021

Processes

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In this study, the blade shape of the squirrel-cage fan system inside the range hood was optimized using the surrogate model to improve the maximum volume flow rate. The influence of computational fluid dynamics (CFD) noise was concerned. The regression Kriging model (RKM) was used as a surrogate model to reflect the relationship between the design parameters of the blade and the volume flow rate. The parallel filling criterion after re-interpolation was used to improve the optimization efficiency further and ensure global optimization. Through experimental verification, we found that the relative error between the volume flow rate of the optimal sample of RKM and the experiment was only 0.4%. Compared with the prototype, the maximum volume flow rate of the optimal sample of RKM was increased by 2.9%, and the efficiency under the corresponding working conditions was increased by 2%. RKM was used to predict the velocity field of the volute and impeller exit section to explore the feasibility of the RKM in the flow field prediction. Research shows that the RKM cannot accurately predict the velocity of each grid on the cross-section. Still, it can accurately predict the changing trend of the velocity.

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Section: Geometric Modelmentioning

confidence: 99%

Squirrel-Cage Fan System Optimization and Flow Field Prediction Using Parallel Filling Criterion and Surrogate Model

Xiao

Shi²,

Wu³

et al. 2021

Processes

Self Cite

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“…Hence for the purpose of energy conservation, researchers from both academic and industry communities have devoted numerous efforts to elevate the aerodynamic performance of squirrel cage fans by redesigning or optimizing the impeller blade. [1][2][3] With deeper understanding of the loss mechanisms in the squirrel cage fan, increasing attention is paid to investigation of the stationary components, i.e., the inlet nozzle and the outlet volute. The flow in the stationary components has a large pressure gradient or a non-uniform pattern, and then causes considerable energy los.…”

Section: Introductionmentioning

confidence: 99%

Integrated aerodynamic optimization for stationary components of squirrel cage fan Considering impeller-Volute interaction

Wang

Shi

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part A:

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As the flow state in the volute plays an important role in the energy loss of the squirrel cage fan, the optimization design of the fan volute has drawn great attention. To further improve the overall performance of the fan, the aerodynamic match between the volute and the inlet nozzle as well as the local flow pattern within the fan components should be considered in the optimization. In the present work, a high-dimensional optimization method based on the genetic algorithm, support vector regression surrogate model, Latin hypercube sampling method and the mixed adaptive sampling algorithm is developed. Then, the integrated optimization for inlet nozzle and volute of the fan is carried out, in which both the aerodynamic performance and the impeller-volute interaction are considered. The optimization results show that the total efficiency of the fan increases by 2.24% and the static pressure recover coefficient increases by 2.18%. The reversed flow at the impeller outlet is restrained, and the flow uniformity at the impeller inlet is improved. This work is helpful for the design of squirrel cage fans with high aerodynamic performance.

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“…Ciocan et al 15 and Marjavaara et al 14 used RSM in conjunction with NSGA-II to optimize the shape of a simplified hydraulic turbine, which improved the hydraulic performance. Therefore, the surrogate model (RSM) and multi-objective evolutionary algorithm (NSGA-II), which have proven their search effectiveness and reliability to obtain the Pareto frontier, 17,18 are applied for the siphon shape optimization analysis. Air compressibility has not been considered during the siphoning formation process in previous research.…”

Section: Introductionmentioning

confidence: 99%

“…Figure18. The distribution of the hydraulic loss coefficient in the different parts of the original and optimized designs.…”

mentioning

confidence: 99%

Multi-objective shape optimization of siphon outlet in pumping station considering two-phase flow

Chen

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part A:

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The siphon outlet is widely used in pumping stations due to its reliable and convenient cut-off performance. Long siphoning time or high hydraulic loss caused by the inappropriate design of the siphon outlet can significantly affect the safety of stations. The air compressibility volume-of-fluid (VOF) method is conducted to simulate the two-phase flow in the siphoning formation process at the design points selected by the optimal Latin hypercube design (OLHD), the results of which show good agreement with the experimental data. In this work, the siphoning time and hydraulic loss coefficient are selected as the objective functions, and a multi-objective shape optimization strategy is proposed for the siphon outlet in conjunction with the response surface method (RSM). This optimization strategy can not only reconcile conflicting objective functions but also obtain the effect and interaction of design variables. Sensitivity analysis on the constructed response surface models indicates that among three design variables, the aspect ratio has the greatest effect on the objective functions, the descending angle has the second greatest effect, and the ascending angle has almost no effect. Compared with the original design, the hydraulic loss coefficient and siphoning time of the optimized design are reduced by 2.95% and 26.76%, respectively. A higher vorticity magnitude and more uniform outflow are created in the optimized design, which results in the improvement of hydraulic performance.

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Multi-objective optimization of dual-arc blades in a squirrel-cage fan using modified non-dominated sorting genetic algorithm

Cited by 13 publications

References 15 publications

Squirrel-Cage Fan System Optimization and Flow Field Prediction Using Parallel Filling Criterion and Surrogate Model

Squirrel-Cage Fan System Optimization and Flow Field Prediction Using Parallel Filling Criterion and Surrogate Model

Integrated aerodynamic optimization for stationary components of squirrel cage fan Considering impeller-Volute interaction

Multi-objective shape optimization of siphon outlet in pumping station considering two-phase flow

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