Assessment of a Neural-Network-Based Optimization Tool: A Low Specific-Speed Impeller Application
This work provides a detailed description of the fluid dynamic design of a low specific-speed industrial pump centrifugal impeller. The main goal is to guarantee a certain value of the specific-speed number at the design flow rate, while satisfying geometrical constraints and industrial feasibility....
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2011-01-01
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| Series: | International Journal of Rotating Machinery |
| Online Access: | http://dx.doi.org/10.1155/2011/817547 |
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| Summary: | This work provides a detailed description of the fluid dynamic design of a low specific-speed industrial pump centrifugal impeller. The main goal is to guarantee a certain value of the specific-speed number at
the design flow rate, while satisfying geometrical constraints and industrial feasibility. The design procedure relies on a modern optimization technique such as an Artificial-Neural-Network-based approach (ANN). The impeller geometry is parameterized in order to allow geometrical variations over a large design space. The computational framework suitable
for pump optimization is based on a fully viscous three-dimensional numerical solver, used for the impeller analysis. The performance prediction of the pump has been obtained by coupling the CFD analysis with a 1D correlation tool, which accounts for the losses due to the other components not included in the CFD domain. Due to both manufacturing and geometrical constraints, two different optimized impellers with 3 and 5 blades have been developed, with the
performance required in terms of efficiency and suction capability. The predicted performance of both configurations were compared with the measured head and efficiency characteristics. |
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| ISSN: | 1023-621X 1542-3034 |