2025
Zhao, Jiantao; Pei, Ji; Wang, Zhongsheng; Zhang, Benying; Wang, Wenjie; Gan, Xingcheng; Pavesi, Giorgio
In: Energy, vol. 328, 2025, ISSN: 18736785.
Abstract | Links | BibTeX | Tags: Approximate model, CFD simulation, Energy efficiency enhancement, Flow diagnosis, Inverse Design, Multistage Centrifugal Pump
@article{Zhao2025,
title = {Energy efficiency optimization of multistage centrifugal pumps based on blade loading control: Insights into flow instability suppression mechanism},
author = {Jiantao Zhao and Ji Pei and Zhongsheng Wang and Benying Zhang and Wenjie Wang and Xingcheng Gan and Giorgio Pavesi},
doi = {10.1016/j.energy.2025.136586},
issn = {18736785},
year = {2025},
date = {2025-01-01},
journal = {Energy},
volume = {328},
publisher = {Elsevier Ltd},
abstract = {Multistage centrifugal pumps (MSCPs) are critical for high-pressure fluid transport, and their hydraulic efficiency directly affects the energy consumption of energy systems. However, flow instabilities result in substantial energy loss. This study employed blade loading theory, which is closely related to the flow field state, to achieve a parametric blade design. A non-expert-driven optimization framework was constructed by integrating the Metamodel of Optimal Prognosis (MoP) with the technique for order of preference by similarity to the ideal solution based on the entropy weight method (EW-TOPSIS). The optimization objective was to improve the hydraulic efficiency of the pump in the preferred operating range, with a constant pressure-boosting performance as a constraint. The results demonstrated that the efficiency improvement exceeded 2 % across the targeted operating range. Moreover, the MoP exhibited a strong predictive capability, even in multi-parameter scenarios with limited sample data. Further vortex dynamics analysis revealed that loading redistribution reduced the incidence angle, suppressed flow separation on the blade suction surface, and, under high-flow conditions, regulated the dominant vortex transport mechanisms governed by vortex diffusion and dissipation. This research demonstrated that optimizing blade loading serves as an effective passive flow control strategy for MSCPs, enabling significant improvements in energy conservation.},
keywords = {Approximate model, CFD simulation, Energy efficiency enhancement, Flow diagnosis, Inverse Design, Multistage Centrifugal Pump},
pubstate = {published},
tppubtype = {article}
}
Multistage centrifugal pumps (MSCPs) are critical for high-pressure fluid transport, and their hydraulic efficiency directly affects the energy consumption of energy systems. However, flow instabilities result in substantial energy loss. This study employed blade loading theory, which is closely related to the flow field state, to achieve a parametric blade design. A non-expert-driven optimization framework was constructed by integrating the Metamodel of Optimal Prognosis (MoP) with the technique for order of preference by similarity to the ideal solution based on the entropy weight method (EW-TOPSIS). The optimization objective was to improve the hydraulic efficiency of the pump in the preferred operating range, with a constant pressure-boosting performance as a constraint. The results demonstrated that the efficiency improvement exceeded 2 % across the targeted operating range. Moreover, the MoP exhibited a strong predictive capability, even in multi-parameter scenarios with limited sample data. Further vortex dynamics analysis revealed that loading redistribution reduced the incidence angle, suppressed flow separation on the blade suction surface, and, under high-flow conditions, regulated the dominant vortex transport mechanisms governed by vortex diffusion and dissipation. This research demonstrated that optimizing blade loading serves as an effective passive flow control strategy for MSCPs, enabling significant improvements in energy conservation.
2022
Gan, Xingcheng; Pavesi, Giorgio; Pei, Ji; Yuan, Shouqi; Wang, Wenjie; Yin, Tingyun
Parametric investigation and energy efficiency optimization of the curved inlet pipe with induced vane of an inline pump Journal Article
In: Energy, vol. 240, 2022, ISSN: 03605442.
Abstract | Links | BibTeX | Tags: Correlation analysis, Energy efficiency enhancement, Flow loss visualization, Inline pump, Multi-objective optimization, Parametric investigation
@article{GanPavesi2022-02,
title = {Parametric investigation and energy efficiency optimization of the curved inlet pipe with induced vane of an inline pump},
author = {Xingcheng Gan and Giorgio Pavesi and Ji Pei and Shouqi Yuan and Wenjie Wang and Tingyun Yin},
url = {https://www.sciencedirect.com/science/article/pii/S0360544221030735},
doi = {10.1016/j.energy.2021.122824},
issn = {03605442},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
journal = {Energy},
volume = {240},
publisher = {Elsevier Ltd},
abstract = {The world energy consumption is currently growing at an alarming rate to support the increase of the world economy and population, which has brought a host of environmental issues. Improving energy efficiency is considered as the crucial solution for changing this situation. The widespread use of inline pumps in the water supply consumes a large amount of electricity, while the efficiency of such devices is lower than the average level. This research is aimed to study the relationship between the shape of the curved inlet pipe and the energy loss distributions by using flow loss visualization technology and correlation analysis. An induced vane was placed at the end of the inlet pipe to suppress the flow phenomena that cause efficiency losses. 700 designs of the inlet pipe with induced vane were generated and calculated to support the research using the automatic simulation approach. An optimization work was also presented to improve the comprehensive performance of the inline pump by using the multi-layer feed-forward neural network and multi-objective particle swarm optimization. An excellent performance improvement was found after the optimization, and a deep analysis of four different design schemes based on the loss visualization method was presented to figure out the main reasons for hydraulic losses in the curved inlet pipe.},
keywords = {Correlation analysis, Energy efficiency enhancement, Flow loss visualization, Inline pump, Multi-objective optimization, Parametric investigation},
pubstate = {published},
tppubtype = {article}
}
The world energy consumption is currently growing at an alarming rate to support the increase of the world economy and population, which has brought a host of environmental issues. Improving energy efficiency is considered as the crucial solution for changing this situation. The widespread use of inline pumps in the water supply consumes a large amount of electricity, while the efficiency of such devices is lower than the average level. This research is aimed to study the relationship between the shape of the curved inlet pipe and the energy loss distributions by using flow loss visualization technology and correlation analysis. An induced vane was placed at the end of the inlet pipe to suppress the flow phenomena that cause efficiency losses. 700 designs of the inlet pipe with induced vane were generated and calculated to support the research using the automatic simulation approach. An optimization work was also presented to improve the comprehensive performance of the inline pump by using the multi-layer feed-forward neural network and multi-objective particle swarm optimization. An excellent performance improvement was found after the optimization, and a deep analysis of four different design schemes based on the loss visualization method was presented to figure out the main reasons for hydraulic losses in the curved inlet pipe.
Gan, Xingcheng; Pei, Ji; Pavesi, Giorgio; Yuan, Shouqi; Wang, Wenjie
Application of intelligent methods in energy efficiency enhancement of pump system: A review Journal Article
In: Energy Reports, vol. 8, pp. 11592-11606, 2022, ISSN: 23524847.
Abstract | Links | BibTeX | Tags: Energy efficiency enhancement, Energy-efficient control, Inline pump, Intelligent method, Optimization, Pump system
@article{GanPavesi2022-01,
title = {Application of intelligent methods in energy efficiency enhancement of pump system: A review},
author = {Xingcheng Gan and Ji Pei and Giorgio Pavesi and Shouqi Yuan and Wenjie Wang},
doi = {10.1016/j.egyr.2022.09.016},
issn = {23524847},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
journal = {Energy Reports},
volume = {8},
pages = {11592-11606},
publisher = {Elsevier Ltd},
abstract = {Energy consumption around the world is growing at an alarming rate. That brings enormous pressure on energy production and environmental issues. Nowadays, energy efficiency enhancement strategies are considered the crucial approaches to release this problem. The pumps accounts for nearly 21% of the world electricity consumption of industrial motor-driven systems. Hence, much research focused on improving the energy efficiency of the pumps and their systems. According to the works of literature, the level of design of pumps for most applications is already extremely high while the system performance could be further improved by regulations, and the average energy savings potential achievable through pump system adjustments is about 30%. This paper focuses on the advanced characteristic modeling methods, and energy efficiency enhancement regulation approaches for the parallel pumping system. A comprehensive summary of traditional scheduling methods and advanced regulation methods based on computational intelligence has been made to provide insight for future research.},
keywords = {Energy efficiency enhancement, Energy-efficient control, Inline pump, Intelligent method, Optimization, Pump system},
pubstate = {published},
tppubtype = {article}
}
Energy consumption around the world is growing at an alarming rate. That brings enormous pressure on energy production and environmental issues. Nowadays, energy efficiency enhancement strategies are considered the crucial approaches to release this problem. The pumps accounts for nearly 21% of the world electricity consumption of industrial motor-driven systems. Hence, much research focused on improving the energy efficiency of the pumps and their systems. According to the works of literature, the level of design of pumps for most applications is already extremely high while the system performance could be further improved by regulations, and the average energy savings potential achievable through pump system adjustments is about 30%. This paper focuses on the advanced characteristic modeling methods, and energy efficiency enhancement regulation approaches for the parallel pumping system. A comprehensive summary of traditional scheduling methods and advanced regulation methods based on computational intelligence has been made to provide insight for future research.
