Open Access

ARTICLE

Jet Pump Structural Optimization through CFD Analysis and Experimental Validation

Zhengqiang Peng^1,*, Rendong Feng¹, Fang Han¹, Jing Guo¹, Shen Chi¹, Wenao Huang¹, Jie Luo²

1 China Oilfield Services Limited, Tianjin, 300459, China
2 State Key Laboratory of Oil & Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu, 610500, China

* Corresponding Author: Zhengqiang Peng. Email:

(This article belongs to the Special Issue: Model-Based Approaches in Fluid Mechanics: From Theory to industrial Applications)

Fluid Dynamics & Materials Processing 2025, 21(12), 2945-2961. https://doi.org/10.32604/fdmp.2025.073281

Received 15 September 2025; Accepted 26 November 2025; Issue published 31 December 2025

Abstract

Jet pumps often suffer from efficiency losses due to the intense mixing of power and suction fluids, which leads to significant kinetic energy dissipation. Enhancing the efficiency of such pumps requires careful optimization of their structural parameters. In this study, a computational fluid dynamics (CFD) model of a hydraulic jet sand-flushing pump is developed to investigate the effects of throat-to-nozzle distance, area ratio, and throat length on the pump’s sand-carrying performance. An orthogonal experimental design is employed to optimize the structural parameters, while the influence of sand characteristics on pumping performance is systematically evaluated. Complementary indoor experiments are used to validate the numerical results, yielding an optimized configuration with a throat-to-nozzle cross-sectional area ratio of 4, a throat length five times the throat diameter, and a throat-to-nozzle distance equal to the nozzle diameter. Under a power fluid flow rate of 1.7 m³/h with this area ratio, the sand-carrying efficiency reaches its peak, achieving a sand transport rate of 290 g/min (6.7 L/h). Comparison of CFD predictions with experimental data across different area ratios demonstrates excellent agreement, with an average relative error of 2.44% and an average absolute error of 3.56%, confirming the reliability of the simulation approach.

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Keywords

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