Performance prediction and optimization strategy for LNG multistage centrifugal pump based on PSO-LSSVR surrogate model

Abstract

The Multistage LNG cryogenic submersible pump is one of the crucial power equipment in LNG transport process. However, the high hydraulic losses and low efficiency of this pump make it necessary to optimize the structure of its impeller in order to reduce energy losses. In this study, an optimization strategy based on particle swarm optimization (PSO) and least squares support vector regression (LSSVR) machine is proposed to optimize the structure of impeller. The optimization of the impeller structure with the PSO-LSSVR method increased the head and efficiency of the LNG cryogenic submersible pump by 0.57% and 2.72%, respectively. Comparing the calculation results of PSO-LSSVR method with the CFD results, we found that the relative error between them don’t exceed 3%, which verified the calculation accuracy of the method. Then, an enstrophy dissipation theory is introduced to quantitatively analyze the pump energy loss. Comparing the impellers before and after optimization revealed that the maximum reduction in impeller energy loss was 18%.. The distribution and mechanism of vortex generation inside the impeller were analyzed with the Q-criterion and the relative vortex transport equation. The relative vortex transport equation revealed that the horseshoe vortex structure at the leading edge of the optimized impeller blade was suppressed, and the relative vortex stretching term and the Coriolis force term, which dominate the evolution of the vortex structure, were reduced. This study will provide related reference for the optimal design of Multistage LNG cryogenic submersible pumps.