Multi-objective optimization design of a sewage pump based on non-dominated sorting genetic algorithm III DOI
Yun Ren,

Xiaofan Mo,

B. S. Yang

et al.

Physics of Fluids, Journal Year: 2024, Volume and Issue: 36(9)

Published: Sept. 1, 2024

Accumulation of sanitary refuse, such as flexible cloth-like structures or the so-called rags, inflows through sewage pumps are prone to tangling, ultimately leading clogging and wear. To prevent this, ability handle wet wipes, similar materials is a key feature that must be considered designed. Therefore, this paper proposed multi-objective optimization strategy based on fluid–structure interaction simulation, Support Vector Regression (SVR), non-dominated sorting genetic algorithm III (NSGA-III). First, values objectives were obtained by Coupled Computational Fluid Dynamics-Discrete Element Method (CFD-DEM) approach. Then, SVR was utilized establish an approximate model between design variables objectives. The NSGA-III applied search Pareto front. Finally, improved impeller selected adopting technique for order preference similarity ideal solution (TOPSIS) with entropy weight. results show method suitable pumps. Comparing numerical calculations original pump optimized pump, head efficiency increased 9.7% 7.13%, respectively. improves passage rate rag effectively behavior. wear amount significantly reduced 32.54%.

Language: Английский

Multi-objective optimization design of a sewage pump based on non-dominated sorting genetic algorithm III DOI
Yun Ren,

Xiaofan Mo,

B. S. Yang

et al.

Physics of Fluids, Journal Year: 2024, Volume and Issue: 36(9)

Published: Sept. 1, 2024

Accumulation of sanitary refuse, such as flexible cloth-like structures or the so-called rags, inflows through sewage pumps are prone to tangling, ultimately leading clogging and wear. To prevent this, ability handle wet wipes, similar materials is a key feature that must be considered designed. Therefore, this paper proposed multi-objective optimization strategy based on fluid–structure interaction simulation, Support Vector Regression (SVR), non-dominated sorting genetic algorithm III (NSGA-III). First, values objectives were obtained by Coupled Computational Fluid Dynamics-Discrete Element Method (CFD-DEM) approach. Then, SVR was utilized establish an approximate model between design variables objectives. The NSGA-III applied search Pareto front. Finally, improved impeller selected adopting technique for order preference similarity ideal solution (TOPSIS) with entropy weight. results show method suitable pumps. Comparing numerical calculations original pump optimized pump, head efficiency increased 9.7% 7.13%, respectively. improves passage rate rag effectively behavior. wear amount significantly reduced 32.54%.

Language: Английский

Citations

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