Optimization of Centrifugal Pump Impeller for Pumping Viscous Fluids Using Direct Design Optimization Technique

Bubryur Kim, Mohammed Hamid Siddique, Abdus Samad, Gang Hu, Dong Eun Lee

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Pumping viscous fluids using centrifugal pumps in the subsea industry is very common. The pump performance degrades drastically when the viscosity of fluids increases, which ultimately gives rise to the installation and oil production cost. Their design optimization can lead to a significant improvement in their performance. Therefore, this study presented the effect of impeller geometry on pumping fluid viscosity through impeller design optimization. Here, pump operation is simulated numerically by solving the Reynolds-averaged Navier-Stokes (RANS) equations at different flowrates. Experimental testing is also performed using the same oils, for numerical validation. Artificial neural-network-assisted multiobjective optimization was performed with two independent design parameters; wrap angle and splitter blade length of impeller, with head and input power as objective functions. Wrap angle and splitter blade length, both significantly affect pump performance while pumping viscous oils; as the oil viscosity increases, increasing splitter length and decreasing wrap angle improve the head significantly.

Original languageEnglish
Article number774
JournalMachines
Volume10
Issue number9
DOIs
StatePublished - Sep 2022

Keywords

  • artificial neural network
  • computational fluid dynamics
  • hydraulic efficiency
  • multiobjective optimization
  • vorticity

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