Prediction of Cavitation Performance of Radial  Flow Pumps

Kaya, M.; Ayder, Erkan

doi:10.18869/acadpub.jafm.73.242.27827

Cited by 8 publications

(4 citation statements)

References 13 publications

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“…The experimental value of minimum σ value, σFC is systematically higher compare to the numerical one, similarly to previous published results [19,44,65,70,73]. As it was presented in studies that included a parametric analysis regarding the effect of non-condensable gas [33,74], the effect of non-condensable gases that is not taken into account in the current simulation, can cause the head collapse to happen earlier, namely at higher σ values. Additional factors that may be responsible for the deviation between measured and computed σFC, are the values given to the vaporization and condensation constants of the cavitation model, the geometry inaccuracies, especially at the tip clearance area, and the fact that the impeller-volute dynamic interactions are not modelled here.…”

Section: Validation Of the Numerical Resultssupporting

confidence: 87%

Numerical simulation of the performance of a centrifugal pump with a semi-open impeller under normal and cavitating conditions

Mousmoulis

Aggidis

Anagnostopoulos

2021

Applied Mathematical Modelling

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An important flow mechanism that can affect the performance and efficiency, as also the maintenance cost of centrifugal pumps is cavitation. Scientific research has been focusing on the mechanisms that govern cavitation in order to develop experimental and numerical tools that are able either to detect the phenomenon or to anticipate its appearance. In this study, a computational model is used in order to study the cavitation performance of a radial flow centrifugal pump with a semi open impeller. The numerical model includes and studies the effects of the blade tip clearance and its thickness, and it is validated against corresponding laboratory measurements and visualization data obtained for this pump under normal and cavitating flow conditions. The total head drop variation curves versus cavitation parameter are extracted both numerically and experimentally, and compared for various pump loading conditions with satisfactory agreement. A non-periodic pattern of flow and cavitation bubbles between the impeller blades, which is caused by the inlet pipe bending, is also well reproduced by the model. The numerical results display in detail the complex flow field and the secondary flows developed in the tip clearance area, close to the blades leading edge. The effects of the latter on the onset and development of cavitation at the suction side of the impeller, as well as on the backflow cavitation phenomenon are presented and analyzed. Backflow cavitation is found to affect the suction ability of the pump, especially for moderate cavitation conditions, as far as the pressure differences between the two blade sides remain significant.

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Section: Validation Of the Numerical Resultssupporting

confidence: 87%

Numerical simulation of the performance of a centrifugal pump with a semi-open impeller under normal and cavitating conditions

Mousmoulis

Aggidis

Anagnostopoulos

2021

Applied Mathematical Modelling

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“…Notably, these sudden drops were more noticeable at flow rates of 11.1 and 9.7 l s -1 in our study. (Kaya, 2020) also reported that sudden drops were observed at low flow rates.…”

Section: Resultsmentioning

confidence: 87%

Machine Learning-Based Prediction of NPSH, Noise, and Vibration Levels in Radial Pumps Under Cavitation Conditions

ORHAN,

KURT,

KIRILMAZ

et al. 2024

Tekirdağ Ziraat Fakültesi Dergisi

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Cavitation, a physical phenomenon that detrimentally affects pump performance and reduces pump life, can cause wear on pump elements. Various engineering methods have been developed to identify the initiation and full development of the cavitation process. One such method is the determination of the net positive suction head (NPSH) through a 3% decrease in total head (Hm) at a constant flow rate. In radial pumps, commonly used in agricultural irrigation and industry, cavitation conditions result in a sudden drop in the Hm-Q curve, making it challenging to detect the 3% Hm value drop. This study differs from others in the literature by modelling NPSH, noise, and vibration levels using three machine learning models, specifically artificial neural networks (ANN), support vector machines (SVM), and decision tree regression (DTR). The best-performing model predicts NPSH, noise, and vibration levels corresponding to a 3% decrease in Hm level. The present study determined the NPSH values of a horizontal shaft centrifugal pump at different flow rates and constant operating speed, and the vibration and noise levels were measured for these NPSH values. For each of the NPSH, noise, and vibration levels, ANN, SVM and DTR models were created. The performances of these models were evaluated using criteria such as root mean squared error (RMSE), Mean Absolute Error (MAE) and mean absolute percentage error (MAPE). In addition, Taylor and error box diagrams were created. The ANN model and DTR yielded high accuracy predictions for NPSH values (R2 = 0.86 and R2 = 0.8, respectively). The ANN model provided the best prediction performance for noise and vibration levels. By entering the level of 3% drop in the Hm value of the pump as external data input to the ANN model, NPSH3, noise, and vibration levels were determined. The ANN models can be effectively employed to determine NPSH3, noise, and vibration levels, particularly in radial flow pumps, where detecting 3% reductions in manometric height value is challenging.

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“…Furthermore, Liang et al (2016) analyzed the relationship between inlet pressure fluctuations and unsteady cavitation process condition inside a water hydraulic poppet valve using a two-phase mixture model. Kaya et al (2017), considering cavitation is a major problem in pump design and operation, developed a systematic methodology to calculate the cavitation performance of radial flow pumps.…”

Section: Introductionmentioning

confidence: 99%

Analysis on the Performance Improvement of Reciprocating Pump with Variable Stiffness Valve using CFD

Zhu

Dong

2020

JAFM

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As a key component of reciprocating pump, the valve has a significant influence on its performance. However, it is difficult for the existing valve to simultaneously solve the problems such as fatigue, erosion and cavitation in engineering application. In this paper, a solution to these problems of using variable stiffness spring is proposed. And three new structures of the valve are designed. Furthermore, based on Computational Fluid Dynamics (CFD) method, a three-dimensional dynamic simulation model considering fluid-structure interaction in the suction stroke of reciprocating pump is established by using dynamic grid technique and User-Defined Functions (UDF). The performance of these new valves are compared with that of conventional valve respectively. The result shows that the new valves have significant influence on the motion characteristics of the valve disc, flow field distribution and cavitation. Besides, the simulation and experimental results of the maximum lift are compared, and it is found that they are basically in agreement. The new structures provide a new research direction for improving the performance of reciprocating pump. Simultaneously, the above simulation method can also provide guidance for valve design, structural optimization and service life improvement.

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Prediction of Cavitation Performance of Radial Flow Pumps

Cited by 8 publications

References 13 publications

Numerical simulation of the performance of a centrifugal pump with a semi-open impeller under normal and cavitating conditions

Numerical simulation of the performance of a centrifugal pump with a semi-open impeller under normal and cavitating conditions

Machine Learning-Based Prediction of NPSH, Noise, and Vibration Levels in Radial Pumps Under Cavitation Conditions

Analysis on the Performance Improvement of Reciprocating Pump with Variable Stiffness Valve using CFD

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