Blade shape optimization of liquid turbine flow sensor

Suna Guo , Tao Zhang , Lijun Sun , Zhen Yang , Wenliang Yang

Transactions of Tianjin University ›› 2016, Vol. 22 ›› Issue (2) : 144 -150.

PDF
Transactions of Tianjin University ›› 2016, Vol. 22 ›› Issue (2) : 144 -150. DOI: 10.1007/s12209-016-2685-z
Article

Blade shape optimization of liquid turbine flow sensor

Author information +
History +
PDF

Abstract

Based on the characteristic curve analysis, the method using Δ(K 2) square difference of meter factor at different flow rates was developed to evaluate the performance of turbine flow sensor in this study. Then according to the distribution of entrance velocity, it was supposed that reducing the blade area near the tip could decrease the linearity error of a sensor. Therefore, the influence of different blade shape parameters on the performance of the sensor was investigated by combining computational fluid dynamics(CFD)simulation with experimental test. The experimental results showed that, for the liquid turbine flow sensor with a diameter of 10 mm, the linearity error was smallest, and the performance of sensor was optimal when blade shape parameter equaled 0.25.

Keywords

turbine flow sensor / performance evaluation method / parameter optimization / mathematical model / CFD simulation

Cite this article

Download citation ▾
Suna Guo, Tao Zhang, Lijun Sun, Zhen Yang, Wenliang Yang. Blade shape optimization of liquid turbine flow sensor. Transactions of Tianjin University, 2016, 22(2): 144-150 DOI:10.1007/s12209-016-2685-z

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Cheesewright R, Bisset D, Clark C. Factors which influence the variability of turbine flowmeter signal characteristics[J]. Flow Measurement & Instrumentation, 1998, 9(2): 83-89.

[2]

Dupuy P, Cao Y. Application of a new generation of spiral turbine flowmeter in the field of liquid measurement[C]. Proceedings of Chinese Society for Measurement Flow Professional Committee, 2002, China: Beijing 265-273.

[3]

Sun L, Zhou Z, Zhang T. Quantitative optimization method for rotor geometric parameters of liquid turbine flow sensor[J]. Chinese Journal of Scientific Instrument, 2007, 28(3): 493-498.

[4]

Wang J, Meng H. Numerical analysis of installation effects on the performance of turbine flowmeters[J]. Acta Metrologica Sinica, 2010, 31(1): 9-13.

[5]

Jia Y F, Wang Z, Jiang W W. Optimization and design of turbine flowmeter based on planning method of multivariable and nonlinear[J]. Control & Instruments in Chemical Industry, 2009, 5: 70-73.

[6]

Pope J G, Wright J D, Johnson A N, et al. Extended Lee model for the turbine meter & calibrations with surrogate fluids[J]. Flow Measurement and Instrumentation, 2012, 24: 71-82.

[7]

Sun L. Research on Reducing Turbine Flowmeter's Sensitivity to Viscosity Change [D], 2004, Tianjin, China: School of Electrical Engineering and Automation, Tianjin University.

[8]

Lavante E, Lazaroski N, Maatje U, et al. Numerical simulation of unsteady three-dimensional flow fields in a turbine flow meter[C]. Proceedings of the 11th FLOMEKOConference, 2003, the Netherlands: Groningen 12-14.

[9]

Guo S, Sun L, Zhang T, et al. Analysis of viscosity effect on turbine flowmeter performance based on experiments and CFD simulations [J]. Flow Measurement and Instrumentation, 2013, 34: 42-52.

[10]

Wang L H, Zhao H, Ming X, et al. An investigation on the behaviours of a turbine flowmeter under low flow rate condition[C]. Proceedings of 2011 World Congress on Intelligent Control and Automation, 2011, China: Taipei 285-290.

[11]

Wang Z, Zhang T. Computational study of the tangential type turbine flowmeter[J]. Flow Measurement and Instrumentation, 2008, 19(5): 233-239.

[12]

Saboohi Z, Sorkhkhah S, Shakeri H. Developing a model for prediction of helical turbine flowmeter performance using CFD[J]. Flow Measurement and Instrumentation, 2015, 42: 47-57.

[13]

Lavante E V, Humener T, Schieber W M. Numerical investigation of the flow field in a 2-stage turbine flow meter[C]. Proceedings of the 9th International Conference on Flow Measurement, 2001, UK: Glasgow.

[14]

Pei J H, Su Z D, Zhang K. Using numerical simulation to optimize the design of gas turbine flowmeter sensor[J]. Advanced Materials Research, 2013, 712: 1910-1913.

[15]

Tsukamoto H, Hutton S. Theoretical prediction of meter factor for a helical turbine flowmeter[C]. Proceedings of Conf Fluid Control and Measurement, 1985, Japan: Tokyo.

AI Summary AI Mindmap
PDF

139

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/