Multi-Objective Shape Optimization on the Inlet Pipe of a Vertical Inline Pump

Pei, Ji; Gan, Xingcheng; Wang, Wenjie; Yuan, Shouqi; Tang, Yunqing

doi:10.1115/1.4043056

Cited by 27 publications

(20 citation statements)

References 20 publications

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“…In 2018, a multi-objective optimization on the inlet pipe of a vertical inline pump was carried out based on a multi-objective genetic algorithm and artificial neural network by Pei Ji [27]. The performance at different operating conditions improved after optimization, and it also reported that the design of the inlet pipe has a slight influence on the performance of the inline pump under the overload condition.…”

Section: Literature Reviewmentioning

confidence: 99%

“…As Ji Pei [27] reported that the design of the inlet pipe has little effect on the performance at the over-load condition of the vertical inline pump, therefore, the efficiencies at part-load and nominal conditions were selected to be the objective functions of the optimization process. The mathematical descriptions of the objective functions are given as follows:…”

Section: Objective Functionsmentioning

confidence: 99%

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Direct Shape Optimization and Parametric Analysis of a Vertical Inline Pump via Multi-Objective Particle Swarm Optimization

et al. 2020

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The vertical inline pump is a single-suction single-stage centrifugal pump with a curved inlet pipe before the impeller, which usually causes a significant increase of hydraulic losses in the inline pump. Considering the matching relationship between the inlet pipe and impeller, a multi-objective direct optimization based on the MOPSO of the inlet pipe and impeller was carried out to broaden the efficient operating area of the vertical inline pump. Bezier curves were adopted to control the profiles of the inlet pipe and impeller and 39 coordinates of the control points and the blade number were selected as the optimization variables. The efficiencies of the inline pump at the part-load and nominal conditions were chosen as the objective functions, which were obtained by the automatic simulation program. A dramatic improvement in pump performance was found after optimization. In the set of Pareto solutions, the maximum increases of efficiency at part-load and nominal conditions were 8.06% and 7.33% respectively. It also reported that the inlet pipe with longer horizontal length and lower bend curvature could reduce the hydraulic losses of the inlet pipe and increase the pump performance.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Objective Functionsmentioning

confidence: 99%

Direct Shape Optimization and Parametric Analysis of a Vertical Inline Pump via Multi-Objective Particle Swarm Optimization

et al. 2020

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“…To speed up the calculation time and still maintain accuracy in iterations, it is necessary to carry out a grid-independence analysis for the numerical simulation. Based on similar works [27][28][29][30], five independent high quality structural hexahedral meshes were built and a grid sensitivity analysis was executed. Simulations were performed at steady state at the design flow rate of Q d = 0.139 m 3 /s to determine the mesh influence on pump head and efficiency.…”

Section: Computational Grid and Mesh Sensitivitymentioning

confidence: 99%

A Practical Method for Speeding up the Cavitation Prediction in an Industrial Double-Suction Centrifugal Pump

et al. 2019

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Researches have over the past few years have been applying optimization algorithms to quickly find optimum parameter combinations during cavitation optimization design. This method, although better than the traditional trial-and-error design method, consumes lots of computational resources, since it involves several numerical simulations to determine the critical cavitation point for each test case. As such, the Traditional method for NPSHr prediction was compared to a novel and alternative approach in an axially-split double-suction centrifugal pump. The independent and dependent variables are interchanged at the inlet and outlet boundary conditions, and an algorithm adapted to estimate the static pressure at the pump outlet. Experiments were conducted on an original size pump, and the two numerical procedures agreed very well with the hydraulic and cavitation results. For every flow condition, the time used by the computational resource to calculate the NPSHr for each method was recorded and compared. The total number of hours used by the new and alternative approach to estimate the NPSHr was reduced by 54.55% at 0.6 Qd, 45.45% at 0.8 Qd, 50% at 1.0 Qd, and 44.44% at 1.2 Qd respectively. This new method was demonstrated to be very efficient and robust for real engineering applications and can, therefore, be applied to reduce the computation time during the application of intelligent cavitation optimization methods in pump design.

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“…To further improve the cavitation performance in centrifugal pumps, there has been a shift from the usual trial-and-error methods of optimization to the application of genetic algorithms (GA) and surrogate models to find optimum global geometrical parameter combinations that can achieve optimum results. 22,23 The process involves calculation of several test cases to determine the net positive suction head required (NPSHr) for each case, which consumes a lot of computational time particularly when the sample size is large. 24–26 This is because in cavitation simulation, the exact inlet pressure at which the head would correspond to a 3% drop in the pump head is not known.…”

Section: Introductionmentioning

confidence: 99%

Unsteady flow characteristics and cavitation prediction in the double-suction centrifugal pump using a novel approach

Pei

Osman

Yuan

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part A:

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The recent advances in centrifugal pump design do not only require a better suction performance but also there have been attempts to reduce design time at a lower cost. The traditional trial-and-error optimization design method, however, depends on the designer's experience, which requires longer cycles. This is because the computational process of calculating the net positive suction head required (NPSHr) involves several calculation steps and this consumes a lot of computational time. An investigation was therefore carried out to test a novel NPSHr prediction method in a double-suction centrifugal pump using unsteady numerical simulations. In the new approach, a new boundary pair was introduced and an algorithm was used to estimate a good value for a static pressure value that correlates to a 3% drop in pump head to determine the critical cavitation point. Experiments were conducted to validate the hydraulic performance and the cavitation model. The NPSHr and the characteristic “sudden” head-drop were very well predicted by the novel approach in only three simulation steps. The internal flow analysis showed that for 0.6 Q d, the flow around the volute tongue was uneven at NPSH = 10.06 m, inducing flow separation and recirculation at the tongue region. Attached cavities were also observed around the suction ring in the spiral suction domain. The pressure fluctuations were analyzed also and the dominant frequency at the pump outlet and tongue region was the blade passing frequency. Consequently, the novel approach proved very robust and efficient in NPSHr prediction and would be a good alternative to shorten simulation time during cavitation optimization design process in centrifugal pumps.

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Multi-Objective Shape Optimization on the Inlet Pipe of a Vertical Inline Pump

Cited by 27 publications

References 20 publications

Direct Shape Optimization and Parametric Analysis of a Vertical Inline Pump via Multi-Objective Particle Swarm Optimization

Direct Shape Optimization and Parametric Analysis of a Vertical Inline Pump via Multi-Objective Particle Swarm Optimization

A Practical Method for Speeding up the Cavitation Prediction in an Industrial Double-Suction Centrifugal Pump

Unsteady flow characteristics and cavitation prediction in the double-suction centrifugal pump using a novel approach

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