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Jilai Zeng,Zailun Liu,Hui Quan,Ancan Shao,Sanzhen Wang 한국유체기계학회 2022 International journal of fluid machinery and syste Vol.15 No.1
The pressure distribution law and calculation of impeller side cavity is one of the important topics in the pump industry, but there is no more accurate calculation method at present. On this basis, a mathematical model of pump cavity pressure distribution and balance cavity pressure under design conditions was derived in this paper. By changing the radial clearance of front and back sealing rings and the diameter of the balance hole on the same impeller, the pressure distribution of front and rear cavities and the balance cavity pressure of the pump were systematically tested by a specially designed device. In the test, the curve of pressure loss coefficient and relative radius of pump cavity under different sealing ring radial clearance was obtained, which could solve the calculation problem of the pressure distribution of front and rear pump cavities. The test curve of the relationship between flow coefficient ratio and specific surface area essentially reflected the coupling regulation effect of balance holes and the rear sealing ring on the balance cavity pressure, which could not only solve the calculation problem of the balance cavity pressure, but also provide the theoretical basis for controlling the pressure and cover force of balance cavity and select different combinations of the radial clearance of the rear sealing ring and the diameter of balance holes. The results showed that the theoretical prediction value was more consistent with the actual measured value, which proved that the proposed mathematical model has high accuracy and universality. This study provides a new way to more accurately calculate the pump cavity pressure distribution and balance cavity pressure and laid a theoretical basis for the study of impeller cover force with significant academic and application value.
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How much information can soil solute profiles reveal about groundwater recharge?
Tianming Huang,Shuo Yang,Jilai Liu,Zhi Li 한국지질과학협의회 2016 Geosciences Journal Vol.20 No.4
The unsaturated zone is an important link between groundwater and the land surface, and can provide storage capacity for both water and contaminants. Consequently, the solute profile of the unsaturated zone can provide much information on groundwater recharge using tracers. This study takes a rain-fed agricultural area (Luochuan loess plain) in the Chinese Loess Plateau as an example to demonstrate how much recharge information in the thick unsaturated zone can be obtained from the solute profile. The results show that the recharge rate is 36–67 mm yr–1 and infiltration rate is 0.19 to 0.30 m yr–1, as obtained using three methods, i.e., evaluating the Cl-peak, chloride mass balance, and nitrate levels. The amount of time needed for annual precipitation to reach the water table is 133–316 years, and the groundwater is tritium free. The nitrate introduced by human activities is mainly distributed in the upper unsaturated zone (above 6 m), and the groundwater nitrate content (3.7 to 9.6 mg l–1 as NO3) remains at baseline level. The storage capacity of the unsaturated zone is found to delay the entrance of pollutants into the aquifer.
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Assessment of Wind Power Prediction Using Hybrid Method and Comparison with Different Models
Mohammed Eissa,Yu Jilai,Wang Songyan,Peng Liu 대한전기학회 2018 Journal of Electrical Engineering & Technology Vol.13 No.3
This study aims at developing and applying a hybrid model to the wind power prediction (WPP). The hybrid model for a very-short-term WPP (VSTWPP) is achieved through analytical data, multiple linear regressions and least square methods (MLR&LS). The data used in our hybrid model are based on the historical records of wind power from an offshore region. In this model, the WPP is achieved in four steps: 1) transforming historical data into ratios; 2) predicting the wind power using the ratios; 3) predicting rectification ratios by the total wind power; 4) predicting the wind power using the proposed rectification method. The proposed method includes one-step and multi-step predictions. The WPP is tested by applying different models, such as the autoregressive moving average (ARMA), support vector machine (SVM), and artificial neural network (ANN). The results of all these models confirmed the validity of the proposed hybrid model in terms of error as well as its effectiveness. Furthermore, forecasting errors are compared to depict a highly variable WPP, and the correlations between the actual and predicted wind powers are shown. Simulations are carried out to definitely prove the feasibility and excellent performance of the proposed method for the VSTWPP versus that of the SVM, ANN and ARMA models.
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