Analysis of a proportional control valve flow coefficient with the usage of a CFD method

2017 ◽  
Vol 53 ◽  
pp. 269-278 ◽  
Author(s):  
E. Lisowski ◽  
G. Filo
1999 ◽  
Vol 1999 (4) ◽  
pp. 549-554 ◽  
Author(s):  
Tamami TAKAHASHI ◽  
Chishiro YAMASHINA ◽  
Simpei MIYAKAWA

2016 ◽  
Vol 114 ◽  
pp. 02008 ◽  
Author(s):  
Adam Bureček ◽  
Lumír Hružík ◽  
Martin Vašina

2014 ◽  
Vol 541-542 ◽  
pp. 1266-1270
Author(s):  
Wen Rui Wang ◽  
Yue Lei Yin

The proportional flow control valve is not only one of the key competent of vane damp,but also the execution unit of shock absorber damping force's regulation .The proportional flow control valves self-designed will combine the structural design of proportional control valve and crate CFD model . The thesis analyzes its distribution of flow field by CFD and acquires experimental validation .It analyzes dynamic characteristics and determine the relationship of flow and opening and drive current. The proportional control valve test verifies the correctness, finally. It is basis for analyzing of damping characteristics about vane damp, which can be used other proportional control valve CFD study.


2012 ◽  
Vol 510 ◽  
pp. 34-38
Author(s):  
Yun Li ◽  
Jin Wei Fan ◽  
Xing Li Gao ◽  
Xiao Feng Wang

According to the problems of hydraulic system of sway machine, such as commissioning and maintenance are inconvenient, impact of change direction is big, system speed is slow, production efficiency is low, etc. It used electro-hydraulic proportional control valve to improve design in hydraulic system of sway machine. Application of electro-hydraulic proportional control valve has realized automatic adjustment of the hydraulic motor speed; it is effective to solve variable speed movement of sway machine frame and no impact of changing direction smooth. Commissioning and maintenance of sway machine are more convenient, and it improves performance of sway machine.


2003 ◽  
Author(s):  
Hailing An ◽  
Jungsoo Suh ◽  
Michael W. Plesniak ◽  
Steven H. Frankel

An experimental and computational investigation of the complex flow inside a co-axial flow control valve with various piston configurations was performed. A transparent full-scale prototype of a control valve was installed into an instrumented flow loop. The acrylic test article allows optical access for diagnostics, such as flow visualization and Particle Image Velocimetry (PIV). Global performance was assessed in terms of the valve flow coefficient for various piston configurations in the control valve at various flow rates by measuring the pressure drop across the valve using an electronic manometer. These results were compared to those for conventional control valves, and as expected, the co-axial design exhibited considerably lower losses (up to 30 times lower). However, the differences in piston geometry designed for different valve characteristics, such as linear, fast-opening, etc. led to different flow coefficients. Investigation of the mechanisms leading to the differences in the global performance involved PIV measurements of the velocity field in several planes within the valve. Complex piston geometries caused regions of separated flow and vortical structures to form. Companion computational studies were performed for the same valve geometries as installed in the flow loop using a commercial CFD package, FLUENT. A fully 3-D Reynolds Averaged Navier-Stokes (RANS) model employing on the order of 800,000 cells was used with a Renormalized Group theory (RNG) k-ε turbulence model. The computational results were compared qualitatively to the experimental data. The CFD results were then used to investigate details of the flow that were not accessible to the experiments, including streamlines, distributions of the static pressure and turbulent kinetic energy throughout the flow field.


2002 ◽  
Vol 124 (3) ◽  
pp. 772-777 ◽  
Author(s):  
James A. Davis ◽  
Mike Stewart

Computational Fluid Dynamics (CFD) tools are evaluated for use in industrial design applications by predicting primary control valve performance characteristics. The performance parameter of primary interest to the manufacturer is the flow coefficient, Cv. Valves having relative valve capacity factors between 2.5 and 13 were modeled. The control valve Cv was experimentally measured and numerically predicted. Both equal percentage and linear characteristic valves were represented in the study. The numerical (simulation) study presented in Part 1 showed that the valve Cv and the inherent valve characteristic could be accurately predicted using axisymmetric flow models over most of the plug travel. In addition, the study demonstrates the usefulness of simplified CFD analysis for relatively complex 3-D flows.


Author(s):  
Guanwei Liu ◽  
Shunsen Wang ◽  
Hui Guo ◽  
Jingru Mao ◽  
Zhenping Feng ◽  
...  

Through-flow capability and flow stability of some steam turbine control valves were studied by experimental investigation and numerical simulation. Based on the analysis of thermodynamic process in control valve, the relationship of flow coefficient, area ratio of valve outlet section to seat diameter section, pressure ratio and total pressure loss coefficient was deduced, and the expression of polytropic exponent was obtained. The relative deviations between formula results and experimental results are within 3%. Both expressions can be used for design and optimization to determine control valve parameters quantitatively. The results of 3D numerical simulation indicate that the topological structure of flow fields in all control valves is similar. The results of valve stability show that the airflow force acted on the valve disc depends on the vortex strength of flow around valve stem bush and valve disc, the asymmetric transonic impinging jet under the valve disc and the diffusing action. The valve operates steadily when the inlet and outlet Mach number are less than 0.15. As the unload degree is about 85%, stem vibrates at the operating conditions when pressure ratio is less than 0.8 and opening ratio is from 10% to 18%. A multihole annular orifice can make flow steady at all operating conditions.


2009 ◽  
Vol 2 (2) ◽  
pp. 66-74 ◽  
Author(s):  
Davide Bottazzi ◽  
Federica Franzoni ◽  
Massimo Milani ◽  
Luca Montorsi

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