NUMERICAL ANALYSIS OF PERFORMANCE

CHARACTERISTICS OF GLOBE VALVE

A PROJECT REPORT

SUBMITTED BY

AJAY PRABHAKAR - CB.EN.U4MEE09003

NISHANTH G.L - CB.EN.U4MEE09018

SARATH V.J - CB.EN.U4MEE09046

VINAYAK V SHENOY - CB.EN.U4MEE09064

In partial fulfillment for the award of the degree

of

BACHELOR OF TECHNOLOGY

in

MECHANICAL ENGINEERING

DEPARTMENT OF MECHANICAL ENGINEERING

AMRITA SCHOOL OF ENGINEERING

AMRITA VISHWA VIDYAPEETHAM COIMBATORE – 641112

May, 2013

AMRITA SCHOOL OF ENGINEERING

AMRITA VISHWA VIDYAPEETHAM, COIMBATORE 641112. DEPARTMENT OF MECHANICAL ENGINEERING

BONAFIDE CERTIFICATE

This is to certify that the thesis entitled “Numerical Analysis of Performance

Characteristics of Globe Control Valve” submitted by AJAY PRABHAKAR

(CB.EN.U4MEE09003), NISHANTH G.L (CB.EN.U4MEE09018), SARATH V.J

(CB.EN.U4MEE09046), VINAYAK V SHENOY (CB.EN.U4MEE09064) for the award

of the Degree of Bachelor of Technology in Mechanical Engineering is a bonafide

record of the work carried out under my/ our guidance and supervision at Amrita School of

Engineering, Coimbatore.

Asst. Prof. A. S. Prakash

Project Advisor

Dept. of Mechanical Engineering,

Amrita School of Engineering.

Dr. V. Ratna Kishore

Project Co-Advisor

Dept. of Mechanical Engineering,

Amrita School of Engineering.

28

Dr. K. Rameshkumar

Chairman

Dept. of Mechanical Engineering,

Amrita School of Engineering This report was examined and the candidates underwent Viva-Voce examination

on

14th

May 2013

Internal Examiner External Examiner

AMRITA SCHOOL OF ENGINEERING

AMRITA VISHWA VIDYAPEETHAM, COIMBATORE

641112. DEPARTMENT OF MECHANICAL ENGINEERING

DECLARATION

We, AJAY PRABHAKAR (Reg. No.CB.EN.U4MEE09003), NISHANTH G.L

(Reg. No.CB.EN.U4MEE09018) , SARATH V.J (Reg.

No.CB.EN.U4MEE09046) , VINAYAK V SHENOY (Reg.

No.CB.EN.U4MEE09064) hereby declare that the project work entitled

“Numerical Analysis of Performance Characteristics of Globe Control Valve”, is

the record of the original work done by us, under the guidance of A.

S. Prakash, Asst. Professor, Department of Mechanical Engineering and Dr. V.

Ratna Kishore, Professor, Department of Mechanical Engineering, Amrita School

of Engineering, Coimbatore. To the best of my knowledge, this work has not

formed the basis for the award of any degree/ diploma/ associateship/ fellowship

or a similar award to any candidate in any University.

AJAY PRABHAKAR NISHANTH G.L

29

SARATH V.J VINAYAK V

SHENOY

Place: Coimbatore 112

Date:

COUNTERSIGNED

Prof. Dr. V. Ratna Kishore Asst. Prof. A. S.

Prakash

Project Co-Advisor Project Advisor

Dept. of Mechanical Engineering, Dept. of Mechanical

Engineering

Amrita School of Engineering. Amrita School of

Engineering

ACKNOWLEDGEMENT

Our whole hearted thanks to our project guide Mr. A. S. Prakash (Asst. Professor)

for giving us an opportunity to work on this project and for being supportive

throughout the project. He was a good friend to us and we have learnt a lot from

his guidance.

This project would not have been a success without the invaluable inputs and

suggestions by Dr. V. Ratna Kishore. It was his suggestions and practical

experience that had helped us to overcome most of the obstacles. We have learned

a lot from him and owe him a lot for developing passion in us for Computational

Fluid Dynamics.

Our sincere thanks to Dr.K.Rameshkumar, Chairman of Mechanical Engineering,

for motivating and providing support in all our efforts.

We would also like to express our thanks and gratitude to Mr. Vignesh (Fluid Lab

Asst.), Mr. Gireesh Kaimal (Fluid lab Asst.), Mr. Ravikumar (CAD lab Asst.) and

Mr. Venkitesh (CAD lab Asst.) for extending their helping hands whenever

needed.

We are indebted to Dr. M. Elangovan for reviewing and providing much useful

suggestions on our project report. We also take this opportunity to thank him for

permitting and ensuring that full facilities needed are well reached.

30

We would be failing in our duties if we do not thank the review panel for their

constructive comments which proved crucial at various stages.

We feel honored to have been part of Amrita School of Engineering that made our

B.Tech programme a highly memorable one.

31

ABSTRACT

A control valve is the most important single element in any fluid handling

systems, because it regulates the flow of fluid to the process. The comprehension

and better management of these hydraulic control valves along with

computational fluid dynamics (CFD) techniques have acquired a growing

significance due to their common usage in many automatic and manual industrial

processes. One of the most common types of control valves is the single seat

globe valve. Over the past few years, there has been an intense effort for knowing,

classifying, and analysing the characterization and classification of these valves.

In this work, the numerically predicted inherent valve characteristic of the 3 inch

globe control valve is qualitatively matched with the experimentally determined

characteristic. Also, the relationship between CV and the size of the valve will also

be analysed. The computational codes of the commercial CFD software FLUENT

14.0 and the validated standard results for a 3 inch globe control valve will be

used in the analysis. In addition, the influence of the turbulence model and grid

size will also be investigated. The knowledge of these effects on CV has an

enormous potential impact on the selection and performance of these control

valves.

32

TABLE OF CONTENTS

SL. NO

TOPIC

PAGE NUMBER

Acknowledgement

i

Abstract ii

List of Figures v

List of Tables vi

List of Symbols, Abbreviations & Nomenclature vii

1 Introduction 1

1.1 Valve 1

1.2 Classification of Valve 1

1.3 Control Valves 4

1.4 Terminology of Globe Control Valve 5

2 Literature Survey 8

2.1 Terminologies 8

2.2 Literature on Numerical Analysis of

Control Valves

10

2.3 Literature Survey Conclusion 15

3 Development of Numerical Model 16

3.1 Governing Equation 16

3.2 Valve Geometry 3D Design 18

3.3 Computational Domain and Grid 20

3.4 Boundary Conditions and Numerical

Simulation

24

3.5 Calculation of Flow Rate 24

4 Results and Discussions 28

4.1 Validation of Numerical Model 28

4.2 Turbulence Modelling and Grid

Independence

30

33

4.3 Effect of flow direction on flow

coefficient ( Cv)

32

4.4 Effect of Number of Holes on The

Cage

33

4.5 Effect of Scaling Globe Valves 35

5 Conclusion 40

5.1 Conclusions Arrived 40

5.2 Scope of Future Work 40

Appendix A 41

Appendix B 45

References 49

34

LIST OF FIGURES

FIGURE

NUMBER

DESCRIPTION PAGE NUMBER

1.2.1 Globe valve 2

1.2.2 Gate valve 2

1.2.3 Needle valve 2

1.2.4 Diaphragm valve 2

1.2.5 Ball valve 3

1.2.6 Plug valve 3

1.2.7 Butterfly valve 4

1.2.8 Safety valve 4

1.4.1 Cross sectional view of globe valve 5

2.1.1 Equal percentage plug 9

2.1.2 Linear plug 9

2.1.3 Flow direction along globe valve 10

3.2.1 Designed 3D geometry of valve 18

3.2.2 Cross sectional view of designed valve 18

3.2.3 Development drawing of 8 hole cage 19

3.2.4 Development drawing of 12 hole cage 19

3.2.5 Development drawing of 24 hole cage 20

3.3.1(a) Computational domain front view 20

3.3.1(b) Computational domain top view 20

3.3.2 Test valve for code validation 21

3.3.3(a) Grid structure of computational domain 22

3.3.3(b) Regions meshed with dead curvature

parameters

22

3.3.3(c) Grid structure of valve numerical analysis

model along a central plane

23

3.3.3(d) Grid structure showing prism layers 23

4.1.1 Validation of Numerical Models 29

35

4.2.1(a) Verification of Turbulence Model 30

4.2.1(b) Verification of Grid Independence 31

4.4.1 Effect of number of holes on FTC & FTO 34

4.4.2 Flow areas for different openings 34

4.5.1 Relationship between Cv and size of valves

for FTC & FTO

35

4.5.2 Relationship between Cv/Af and size of

valves for (a) FTC & (b) FTO

38

4.5.3 Relationship between Cv/Af for different %

stroke openings

38

A.A.1 Experimental Setup – CAD Drawing 42

A.A.2 Schematic Experimental Diagram

44

A.B.1 Cage Design: 8 hole cage,12 hole cage, 24

hole cage

45

A.B.2 Components of valve assembly 46

A.B.3 Valve Assembly 47

A.B.4 Flow path extract from ANSYS

Workbench

48

36

LIST OF TABLES

Table Number Description Page Number

4.1(a) Flow to Open Validation of 3 inch 12 hole

valve

29

4.1(b) Flow to Close Validation of 3 inch 12 hole

valve

29

4.2(a) Turbulence Modelling 30

4.2(b) Grid Independence 31

4.3 Comparison of mass flow rate through holes

of 12 hole cage

32

4.4(a) Effect of Cv for Flow to Open 33

4.4(b) Effect of Cv for Flow to Close 33

4.5(a) Effect of Scaling for FTO 36

4.5(b) Effect of Scaling for FTC 37

A.A.1 Bill of Materials 43

37

LIST OF ABBREVIATIONS AND NOMENCLATURES

SYMBOL DESCRIPTION

CFD Computational Fluid Dynamics

Cv Flow Coefficient

q Volume flow rate in m3/hr

FTO Flow to Open

FTC Flow to close

Fp Piping Factor

Gf Specific Gravity

P1 Inlet Pressure

P2 Exit Pressure

PIV Particle Image Velocity

SIMPLE Semi-Implicit Method for Pressure Linked Equation

NB Nominal Bore

RNG Re-Normalized Group

u Velocity in x-direction

v Velocity in y-direction

w Velocity in z-direction

ρ Density kg/m3

Divergence Vector

* Stress Tensor

Af Flow Area mm2

38

Chapter 1

INTRODUCTION

1.1 Valve

A valve is a device that regulates, directs or controls the flow of a fluid

(gases, liquids, fluidized solids, or slurries) by opening, closing, or partially

obstructing various passageways. They are found in virtually every industrial

process, including water & sewage processing, mining, power generation,

processing of oil, gas & petroleum, food manufacturing, chemical & plastic

manufacturing and many other fields.

1.2 Classification of Valves

1.2.1 Multi-turn or linear motion valves

1.2.1.1Globe Valve

A globe valve is a multi-turn valve in which closure is achieved by means

of a disk or plugs that seals or stops the fluid on a seat generally parallel to the

flow.

1.2.1.2Gate Valve

A gate valve is a multi-turn valve in which the port is closed by a flat-

faced vertical disk that slides at right angles over the seat.

1.2.1.3 Needle Valve

A needle valve is type of valve which has a port and threaded needle

shaped plunger which precisely regulates fluid flow.

1.2.1.4 Diaphragm Valve

39

A multi-turn valve in which the open-close element is a diaphragm.

40

Fig 1.2.1 Globe Valve Fig 1.2.2Gate Valve

41

Fig 1.2.3 Needle Valve Fig 1.2.4 Diaphragm Valve

1.2.2 Quarter-turn or rotary valves

1.2.2.1 Ball Valve

A ball valve is a valve in which a drilled ball rotates between seats,

allowing straight through flow in open position and shutting off when rotated 90°

and blocks the flow passage.

1.2.2.2 Butterfly Valve

A butterfly valve is a quarter-turn valve that controls flow by a circular

disk pivoted at its central axis.

1.2.2.3 Plug Valve

The plug valve is a quarter turn valve which controls flow by means of a

cylindrical or tapered plug with a hole through the centre, which can be positioned

from open to close by a 90° turn.

Fig 1.2.5 Ball Valve

42

Fig 1.2.6 Plug Valve

1.2.3 Special purpose valves

1.2.3.1 Safety Valves

A valve, when actuated above a predetermined level, opens and allows the

gas or vapour to escape out, bringing the valve back to the original state.

1.2.3.2 Pressure regulator

A pressure regulator is a valve that automatically cuts off the flow of a

fluid at a certain pressure.

43

Fig 1.2.7 Butterfly Valve Fig.1.2.8 Safety Valve

Valves may be operated manually, either by a handle, lever, pedal or

wheel. Valves may also be automatic, driven by changes in pressure, temperature,

or flow. These changes may act upon a diaphragm or a piston which in turn

activates the valve.

1.3 Control Valves

Control valves are valves that are used to control flow variables such as

mass flow, pressure, temperature, and liquid level. The controlling is achieved by

fully or partially opening or closing of the plug in response to signals received

from controllers. The controller compares a "setpoint" to a "process variable"

whose value is provided by sensors that monitor changes in such conditions.

A control valve consists of three main parts in which each part exist in several

types and designs:

Valve's actuator

Valve's positioner

44

Valve's body

The advantages of using globe valves are:

Efficient throttling with minimum wire drawing or seat erosion.

Accurate flow control.

Available in multi-ports.

Short disk travels and fewer turns to operate, saving time and wear on

stem and bonnet

1.4 Terminology of a globe control valves

Fig. 1.4.1 Cross-sectional view of a globe control valve

1.4.1 Body

The body is the main pressure containing structure of the valve that

provides a provision for connecting pipes, flow passageway, and supports the

seating surfaces and the valveclosure member.

45

1.4.2 Bonnet

Bonnet is the portion of the valve that contains the packing box and stem

seal. Packing maintains the seal between the bonnet and the stem during valve

cycles. Stem is the part that connects the actuator to the plug. The bonnet guides

the stem and provides a leak-proof closure for the valve body .

1.4.3 Ports

Ports are openings in the body for fluid to flow in or out. The ports may be

oriented straight across from each other or anywhere on the body oriented at any

angle (such as 90°).

1.4.4 Actuator

Actuator is a component which is used to control the position of the plug

or piston in a valve. The actuators can be classified based on the source of

mechanism which are mainly hydraulic, pneumatic, manual, solenoid and motor.

1.4.5 Plug

Plugs are the closure member of the valve. Plugs are connected to the stem

which is slid or screwed up or down to throttle the flow.

1.4.6 Seat

The seat ring provides a stable, uniform and replaceable shut off surface.

Seat rings are usually held in place by pressure from the fastening of the bonnet.

Thus pushing the cage down on the lip of the seat ring and holding it firmly to the

body of the valve.

Seat rings may also be threaded and screwed into a thread cut in the same

area of the body. This makes removal of the seat ring during maintenance difficult

if not impossible. They may also be bevelled at the seating surface to allow for

some guiding during the final stages of closing the valve.

1.4.7 Stem

46

The stem serves as a connector between the actuator and the inside of the

valve. The stem must be straight and have low run out, in order to ensure good

valve closure. It should also be able to withstand high compression and tensile

strengths. Stems are either smooth or threaded.

1.4.8 Cage

The cage is part of the valve that surrounds the plug and is located inside

the body of the valve. Typically, the cage is one of the greatest determiners of

flow within the valve. As the plug is moved up, the openings in the cage are

exposed thus increasing flow. The design and layout of the openings can have a

large effect on fluid flow. Cages are also used to guide the plug to the seat of the

valve for a good shutoff, substituting the guiding from the bonnet.

47

CHAPTER 2

LITERATURE SURVEY

2.1 Terminologies

2.1.1 Flow Coefficient (CV)

The valve flow coefficient is an inherent parameter which measures the

valve capacity. It depends on valve type, diameter of valve, opening rate of valve

and operating fluids.

CV is defined as the flow in cubic meter per hour of water at a temperature

5-400C with a pressure drop across the valve of 1 bar.

Where,

q is the volume flow rate in m3/hr

P1 and P2 are inlet and outlet pressures

Gf is the specific gravity

Correction Factor, Fp=1

Numerical Constant, N1 = 0.862

For example, CV value of 12 means the valve has an effective port area in

the full open position such that it passes 12gpm of water at a pressure difference

f

p

v

G

PPFN

qC

211 **

48

of 1 psi. The use of the flow coefficient offers a standard method of comparing

valve capacities and sizing valves for specific applications that is widely accepted

by industry.

2.1.2 Valve Characteristics

The valve characteristic is a plot of the CV versus percentage opening of

the valve. The plot is indicative of how the flow rate will change with a change in

percentage opening of the valve. The percentage opening of the valve is a measure

of how far the plug is stroked relative to its maximum stroke length.

Characterization is used in control applications to better linearize the control loop.

The two most commonly used characteristics are the linear, where flow

rate increases linearly with valve plug travel, and equal percentage, where flow

rate increases exponentially with valve plug travel. Linear characteristics are used

in applications where the majority of the system pressure drop occurs at the valve

and equal percentage characteristics are used where the pressure drop across the

valve could vary significantly.

49

Fig 2.1.1 Equal Percentage Fig 2.1.2Linear

2.1.3 Flow Direction

There are 2 types of control valve flow directions:

2.1.3.1 Flow to Close (FTC)

When the fluid flows over the plug, it gives a closing action to the plug.

This is called as FTC type flow direction. The effects of cavitation are less and it

requires more break away torque to open and less closing torque. This is mainly

used for low pressure applications.

2.1.3.2 Flow to Open (FTO)

When the fluid flow goes through and faces the plug directly, it gives an

opening action to the plug. This is called as FTO type flow direction. This

requires more closing torque and less opening torque and is mainly used for high

pressure applications.

50

Fig 2.1.3Flow direction along globe valves

2.1.4 Piping Factor (FP)

The FP factor is the ratio of the flow rate through a control valve installed

with attached fittings to the flow rate that would result if the control valve was

installed without attached fittings and tested under identical conditions which will

not produce choked flow in either installation. The piping geometry factor FP is

necessary to account for fittings attached upstream and/or downstream to a control

valve body.

2.2 Literature on Numerical Analysis of Control Valves

A generalised idea regarding control valves, its applications and

importance has been gained. To obtain the depth of work that has been done in

the analysis of control valves, different journal papers were surveyed.

Davis et al. [1] studied performance analysis of globe valves using

axisymmetric flow models for numerical analysis. Three globe control valves of

both linear and equal percentage valves with Cd ranging from 2.5 to 13 were

51

modeled. This simplified flow model predicted the Cv values and inherent valve

characteristics for all the three globe control valves accurately over most of the

plug opening. It was found that Cv values differed the most from the experimental

data in the final plug openings of control valves. The details of the flow field such

as pressure at a discrete point and jet behaviour are also studied. This study

demonstrates and proves the usefulness of simplified CFD analysis for relatively

complex three dimensional flows.

Davis et al. [2]also conducted performance analysis of globe control

valves experimentally to analyse the differences in axisymmetric flow modeling

and three dimensional flow field modeling. Experimental results were obtained by

conducting an axisymmetric flow field experiment. This model‟s actual

applications were then tested to actual three dimensional control valves by

studying the pressure and flow field through a three dimensional control valve.

The results of the experiment revealed that control valve have a predominantly

axisymmetric flow field for most of their plug travel, which makes them suitable

for the model.The agreement between the experimental and modelled values was

better at lower percentage opening.

Salvador et al. [3] emphasize the importance of proper 3D modelling for

analysing control valve performances in their study with CFD. Mike and Stewart

had said in their paper that axisymmetric modelling and geometric simplification

will yield to lower Cv values and accuracy. Thus they modelled in full 3D with

geometric smoothening to analyse the differences in accuracy. The velocity fields,

pressure distributions, and flow separations and reattachments in all piston

positions were studied. Comparison was carried out between numerical results

and experimental data using different piston positions.. A 2inch double chamber

globe control valve was studied in an experimental setup for different flow rates

ranging from 0 l/s to 20 l/s and for pressure differences from 0 MPa to 14 MPa.

With the experimental data the CFD model was validated within the error of 6%.

Certain geometrical modifications were made in the original geometry and it was

observed that the area distorted by turbulence was reduced. The valve

characteristics were obtained with better accuracy than from axisymmetric model.

52

In 3D modelling, even in 100% opening the values was matching with an error of

less than 4%. The CFD simulation reports that the Cv for the original geometry

was lower than the Cv for modified geometry for all percentage opening. This

reaffirms that original geometry produced larger distorted area and thus larger

pressure drop. This confirms that turbulence flow behaviour inside a control valve

is better predicted by 3D model.

Hailing et al. [4] studied flow along a co-axial control valve by both

experimental and computational investigation for various plug piston

configurations. Valve characteristics were obtained and were compared for two

different plug geometries. The results obtained prove that, axial flow valve with

both piston configurations performs more efficiently than the conventional valve,

resulting in less energy loss. Numerical analysis was successfully done using

commercially available CFD code such as FLUENT.

Kiesbaueret al. [5] conducted a set of experiments to determine the flow

coefficient of a control valve using numerical simulation methods. A geometric

model with proper calibrations was set up and flow coefficient was measured.

Then the same setup was modeled in a software program with appropriate

boundary conditions and the flow coefficient was determined. Two methods are

available for calculation of flow coefficient. In the first method, pressure at the

inlet and the outlet of the valve was defined and mass flow rate was used as the

converging parameter. In the second method inlet pressure and outlet mass flow

rate was defined and outlet pressure was used as the converging parameter.

Second method is applied when the first method fails to converge. The results

indicated that the values obtained from the simulation were within the ±5%

tolerance. However, the result was obtained by using an optimal mesh and not a

rough mesh, which increased the error to ±20%.

Jeon et al. [6] discuss the numerical analysis on butterfly valves using

commercial CFD code FLUENT. A comparative study was done on different

kinds of butterfly valves. The flow coefficient, loss coefficient and pressure

distribution of valves according to valve opening rate were compared to each

53

other to check the influence of these on design variables of valve performance.

They concluded that there was no much difference in valve performance between

single and double disk type butterfly valves, except that double disk type showed

more complex flow pattern and recirculating eddies at the rear of valve disk

compared to single disk type.

S.K.Kang et al. [7] discusses the effect of attached fitting on valve flow

coefficient by both numerical and experimental investigation. Experiments and

simulations were done for L, T, Y, and + type fittings under steady state

conditions. The pressure loss appeared to be 10% greater. This increase in the

pressure loss results in low performance of the valve and thus decreases the valve

flow coefficient. It was found out that valve flow coefficient must be corrected by

a piping geometry factor of 0.81 irrespective of the type of fitting used.

S.W.Kim et al. [8] investigated hydrodynamic characteristics of butterfly

valves and compared analysis results by PIV and CFD. Experimentation on

difficult conditions like cryogenic cargo transfer system is almost impossible to

conduct and analyse. This paper supports the usefulness of computational analysis

as a powerful tool for numerical analysis. Comparison of both analysis, PIV &

CFD using water, respectively vector velocities and pressure loss coefficients

have shown similar characteristic pattern. Thus the numerical analyses are

verified as a higher accurate tool and could be used for various applications for

analysis of flow fields in marine and industrial processes.

Moncalvo et al. [9] studied the flow of non-Newtonian fluids using

computational methods. Shear thinning fluids like aqueous solutions of polyvinyl-

pyrrolidine in LESER type safety valve were analysed. The calculations were

carried out assuming laminar, turbulent and transitional flows. The predicted mass

flow rates using CFD were close to each other and to the measured values, except

at relieving pressure close to ambient. This deviation is thought to be because of

the entrainment of air bubbles which makes for additional shearing in the

solutions.

54

Oza et al. [10] analysed performance of a globe valve in high pressure

oxygen environment using CFD. They used simplified axisymmetric numerical

model and predicted inherent valve characteristics using both k-ε and k-ω

turbulence models. The results showed that the k-ω turbulence model values

predicted higher values of velocity and turbulent kinetic energy than the k-ε

model since the latter captures lesser recirculation and is more suitable for

boundary level flow. It was found that k-ε model is more suitable for free stream

simulations.

Daines et al. [11] performed computational analysis of cryogenic flow

through a control valve. Study was done on the effect of change in plug/seat

region of the valve prior to testing. All the numerical values were verified

experimentally and the modelled results compared well qualitatively with

experimental trends. During verification process, they analysed that it was better

to use double precision accuracy and non-integer grid ratios to make coarser grid

and thereby to reduce computational time. Thus the grid dependence of the

solutions was quantified using CFD verification techniques which yielded a grid

convergence index, an indication in the error bounded on the numerical solution

and an extrapolated grid independent value for Cv at various plug positions.

Soorya et al. [12] studied the valve deformation and valve performance

which are obligatory for material and product design integration. CFD analysis

was carried out on ball and gate valves with different fluids. Pressure distribution

along the valve body was analysed. This study helps in product design of the

control valves which makes the use of CFD very prominent. With the help of

CFD, product design and material design were able to be integrated in valve

manufacturing in an economical and faster way.

Yang et al. [13] aims at detailed CFD analysis of the three dimensional

flow fields in the chambers of the stop valve. The model was simulated and

observedfor flow patterns and to obtain valve flow coefficient and flow

fluctuations when stop valves with different flow rate and uniform incoming

velocity were used in a valve system. RNG k-ε turbulence model was used to

55

simulate turbulent flows in valve body. This model was chosen since the flow

inside a hydraulic valve is characterised by the co-existence of “free shear flows”

due to the flow jet at the exit of the metering section and “wall bounded flows”

which are strongly influenced by wall effects. From this paper it was understood

that when the fluid flows in the throat path between the piston and its seat,

circulation area diminishes quickly, due to which fluid pressure falls and fluid

here has more velocity magnitude.

Young et al. [14] studies the flow characteristics of control valves with

complex flow fields including pressure drop, cavitation effect, and variation of

flow coefficient and correlation of discharge coefficient. Numerical analyses of

three dimensional turbulent flows with high pressure drop were modelled in CFD-

ACE code. After analysing the pressure distribution, velocity flow fields and

cavitation inception points, certain design changes was done in a new model at the

trim region, valve chamber, valve inlet and outlet and were simulated. The newly

designed valve model showed reduced cavitation and was found to be better than

conventional one resulting in superior friction of anti-cavitation trim.

2.3 Literature Survey Conclusion

The literature survey highlights the fact that determination and verification

of flow coefficient of a valve can be done by designing a numerical model and an

experimental setup respectively. The analysis can be extended further by studying

the pressure fields, thus, giving an insight on the cavitation effect in the valve.

The pressure losses resulting due to the addition of various fittings in the

experimental setup should also be accounted by considering the piping geometry

factor, Fp. Since the flow through pipes and control valves are generally boundary

layer problems, in most cases k-ε standard turbulence model are used. Whereas,

RNG k-ε turbulence model is used for free shear flow and wall bounded flow

conditions. It was also understood that flow coefficient can be calculated by two

methods, either by defining pressure at the inlet and the outlet of the valve and

56

mass flow rate was used as the converging parameter or by considering inlet

pressure and outlet mass flow rate and then using outlet pressure as the

converging parameter. Second method is applied when the first method fails to

converge. Most of the published papers prominently support the use of

computational fluid dynamics, such as commercial CFD code by FLUENT, as a

powerful robust tool for detailed flow analysis across control valves.

57

CHAPTER 3

DEVELOPMENT OF NUMERICAL MODEL

3.1 Governing Equation

The governing equations of fluid flow represent mathematical statements

of conservation law of Physics:

The mass of the fluid is conserved.

The rate of change of momentum equals the sum of the forces on a fluid

particle (Newton‟s second law).

The rate of energy is equal to the sum of the rate of heat addition to and

the rate of work done on a fluid particle.

A steady incompressible flow without heat addition is assumed, thus energy

equation is not considered in the present work. The governing continuity and

momentum equations are:

..(2)

where stands for the divergence of the stress tensor. Considering the above

equation, the number of unknowns are 13 (velocity components, pressure and

stress field), making it difficult to solve. To overcome this difficulty Navier-

Stokes equations are consider, where the stress field is related to the fluid

viscosity. Thus Reynolds-averaged form of the Navier-Stokes equations is

typically used for solving engineering flows problems.

..(1)

58

The widely used numerical procedure to solve Navier-Stokes Equations is

SIMPLE (Semi-Implicit Method Pressure Linked Equations) algorithm. An

approximation of the velocity field is obtained by solving the momentum

equation. The pressure gradient term is calculated using the pressure distribution

from the previous iteration or an initial guess. The pressure equation is formulated

and solved in order to obtain the new pressure distribution. Velocities are

corrected and a new set of conservative fluxes is calculated.

The solution of the governing equations in case of laminar or inviscid

flows can be easily solved. However the solution of turbulent flows presents a

significant problem. In order to predict the effects of turbulence, a turbulence

model has to be considered. The commercial CFD code FLUENT offers a wide

range of turbulence models, standard k-ε model is selected for the simulations in

this work, based on studied result.

The k-ε Standard model is a two- equation model which has two extra

transport equations apart from the governing equations. These extra equations are

used to find turbulence kinetic energy and turbulence dissipation rate.

The turbulence kinetic energy is the mean kinetic energy per unit mass is

associated with turbulent flow. It is governed by the equation,

The turbulence dissipation rate is the rate at which the turbulence kinetic

energy is converted into thermal energy. It is governed by the equation,

RNG k-ε model can be used to verify turbulence model independence. In

this model, the unknown Reynolds stresses are related to the known mean strain

rate via a turbulent viscosity which is calculated as:

..(3)

..(4)

..(5)

59

Specification of this viscosity requires solution to two additional modelled

transport equations for the turbulent kinetic energy and the dissipate rate.

60

3.2 Valve Geometry 3D Design

Globe control valve of 3 inch (80NB) was modelled for a 12 hole cage

profile using SolidWorks. The 3D geometry and cross sectional view of the valve

modelled are shown below:

Fig 3.2.1 Designed 3D geometry of globe valve

Fig 3.2.2 Cross Sectional View of designed globe valve.

61

The test section includes the inlet pipe, outlet pipe, valve body, plug, cage

and seat ring. The length of the inlet and outlet pipes is 18inch and 30inch

respectively. The design was done for both flow directions (FTO and FTC) of the

control valves. The 3D cad model for various plug openings at 20%, 50%, 70%

and 100% were also modelled by moving the plug in vertical direction.

3.2.1 Design of 8-hole and 24-hole cages

The experimentally validated 3 inch globe control valve with 12-hole cage

was used as a reference in this project. Cages with 8 and 24 holes respectively

were designed (within an error of 13%) by matching the flow areas at various

stroke lengths with the data from the 12 hole cage. These cages replaced the 12

hole cage in the test section. And the plug was positioned at vertical heights to

obtain 20, 50, 70 and 100 percentage opening for both FTO and FTC

configuration. The flow paths of all the designed test sections were extracted

using the commercial software ANSYS Workbench. (Details in appendix 1).

Fig 3.2.3 Development Drawing of 8 hole Cage

62

Fig 3.2.4 Development Drawing of 12 hole Cage

Fig 3.2.4 Development Drawing of 24 hole Cage

3.3 Computational Domain and Grid

The numerical grid for the valve body and upstream and downstream pipes

was generated by means of StarCCM software. The Computational domain of the

model is shown in Fig.3.3.a.

Along with structured grid, unstructured grid was also used, owing to

the complex nature of the geometry. The distinguishing feature of structured grid

is that, the computational space is mapped in a unique manner by the grid points

in the physical space. Unstructured grids mainly comprises of triangles in case of

2D and tetrahedral in case of 3D. The grid size for the computational domain of

12-hole caged globe valve was obtained in the range of 1.6 to 2.0 million cells.

Fig 3.3.b shows the test valve for code validation. Fig 3.3.c shows the grid

structure of valve numerical analysis model.

63

Fig 3.3.1(a) Computational Domain Front View

Fig 3.3.1(b) Computational Domain Top View

64

Fig 3.3.2 Test valve for code validation

65

Fig. 3.3.3(a) Grid structure of computational domain

66

Fig. 3.3.3(b) Regions meshed with dead curvature parameters

67

Fig. 3.3.3(c) Grid structure of valve numerical analysis model along a central

plane

Fig. 3.3.3(d) Grid structure showing prism layers

68

Initially, the grid size function was used to refine the grid in the area

where sudden changes occur, to ensure an adequate grid size where the maximum

velocity and pressure gradients occur. In particular, the grid is significantly

refined in the valve body section. Certain areas in the geometry where the flow

does not occur were termed as dead curvature. Those sections were given a coarse

mesh.

The surface remesher is used to re-triangulate an existing surface in order

to improve the overall quality of the surface and optimizes the volume mesh

model. The re-meshing is primarily based on a target edge length of a cell.

Localized refinements based on boundaries are defined.

The prism layer mesh is used in conjunction with a core volume mesh to

generate orthogonal prismatic cells near wall boundaries. In typical boundary

layers, the flow is aligned with the wall and the gradients vary largely normal to

the wall. When only tetrahedral cells are present, the gradients exist across the

tetrahedral cell leading to inaccuracy in the resolution of the boundary layer

phenomena across the cell. The inclusion of prismatic layers resolves this problem

by aligning the gradients along the mesh.

Tetrahedral model is preferred due to its following advantages:

For a given number of cells, tetrahedral mesh occupies less memory due to its

lesser number of faces per cell and for the same reason, it consumes lesser

computational time. Though polyhedral mesher can yield meshes with lesser cells,

it would compromise on the accuracy of the solution. The smoothness, i.e., the

difference in size between any two tetrahedral cells is also lesser compared to

other models.

The mesh parameters used are given below;

For Normal(Coarse) Grids

No. of prism layers : 3

69

Prism layer thickness : 0.2mm

Size of cell

Maximum : 2.5 mm

Target : 5mm

For Finer Grids

No. of prism layers : 7

Prism layer thickness : 0.2mm

Size of cell

Maximum : 2 mm

Target : 5mm

3.4 Boundary Conditions and Numerical Simulations

The second order upwind scheme was used to discretizes the governing

equations in a collocated grid node to ensure the accuracy of the simulation

results. Regarding the inlet and outlet boundaries (6D from the inlet and 10D

outlet of the valve), pressure conditions was specified. The inlet and outlet

pressure specified were 3 bar and 2 bar respectively. Water, at standard pressure

and temperature was chosen as the working fluid. A proper estimation of turbulent

phenomena has great importance to determine the valve flow features.

In particular, the flow inside a hydraulic valve is characterized by the

coexistence of „„free shear flows‟‟, due to the flow jet at the exit of the metering

section, and „„wall bounded flows‟‟, which are strongly influenced by the wall

effects. The most suitable turbulence model for this kind of problem appears to be

the Standard k-ε model. This model gives a reliable estimation of the turbulent

quantities upstream and downstream of the restricted sections and is able to

estimate properly both the free jet and the wall bounded region.

70

3.5 Calculation of Volume flow rate

The computational codes of commercial CFD software ANSYS FLUENT

14.0 were used.

Firstly, the numerical model for globe control valve was validated with

experimental results, for both FTC and FTO configuration. Then, the gird

independence and turbulence model were verified. This was done only for FTO

type valves.

3.5.1 Validation of experimental results

The numerical models for 3 inch globe control valve with 12-hole cage

were validated using the experimental results (courtesy FCRI Ltd., Kanjikode).

The volume flow rates of the numerical model for 30%, 40%, 50%, 60%, 70%,

80%, 90% and 100% opening were used to calculate corresponding flow

coefficients (CV) and compared with the experimental data.

3.5.2 Grid Independence

For verifying, grid independence, numerical model of 12-hole cage was

remeshed to finer grids. The volume flow rate of these numerical models was

calculated using the computational codes of ANSYS FLUENT 14.0 with standard

k- turbulence model and the same boundary conditions. The corresponding CV

values thus obtained were compared with the CV values of the numerical models

with coarser mesh.

3.5.3 Turbulence Model

So far, the turbulence model chosen was standard k- model. Now, by

choosing RNG k- model the volume flow rates of the same numerical model

(only the ones with coarser mesh) was calculated. The corresponding Cv values

were also noted down. These values were compared with that of the

corresponding numerical models in which standard k- was used.

71

In the standard k-epsilon model the eddy viscosity is determined from a

single turbulence length scale, so the calculated turbulent diffusion occurs only at

the specified scale, whereas in reality all scales of motion will contribute to the

turbulent diffusion. The RNG approach, which is a mathematical technique, is

used to derive a turbulence model similar to the k-epsilon, resulting in a modified

form of the epsilon equation which attempts to account for the different scales of

motion through changes to the production term.

3.5.5 Effect of number of holes

The numerical models with 8-hole and 24-hole cages were used to find

their corresponding volume flow rates. The volume flow rates and their

corresponding CV values of 20%, 50%, 70% and 100% openings were calculated.

The turbulence model used was standard k-ε model. The analysis was performed

for both FTO and FTC type configuration.

3.5.6 Effect of Scaling

The numerical models of 3 inch globe control valves for different

percentage openings were scaled to 4 inch, 5 inch and 6 inch. The volume flow

rates and corresponding CV values of these models were also found and a

relationship between CV and flow areas were tried to obtain.

72

CHAPTER 4

RESULTS AND DISCUSSIONS

Chapter Overview

This chapter explains in detail about the results obtained for the various

numerical models that were simulated.

Initially, the numerical models of 3 inch globe control valve with 12-hole

cage for various percentage openings are validated with the experimental data

obtained from FCRI, Kanjikode. This was done for both FTO and FTC flow

directions. Further, the results obtained for turbulence modelling and grid

independence verification are discussed. This is followed by the comparison of CV

values for the numerical models with 8-hole and 24-hole cage, with that of the

numerical models with 12-hole cage. Scaling effects of 3 inch globe control valve

to 4 inch, 5 inch and 6 inch are discussed in detail at later stages of the chapter.

4.1 Validation of numerical models

The CV values of the numerical models for 20%, 50%, 70% and 100%

openings of the 3 inch globe control valve with 12-hole cage are in close

agreement with the experimental results within an error of 7%. The following

graphs (Fig.4.1.1) would be helpful in explaining the above statement clearly. The

results for both FTC and FTO are illustrated in these graphs.

73

Table 1(a): Validation of numerical models for FTO

% Stroke Opening Computed Cv` Experimental Cv Error (%)

20 8.69 8.86 -1.9

30 21.3 20.33 4.9

`50 58.45 58.21 0.4

70 94.73 100.35 -5.6

100 111.7 114.39 -2.3

Table 1(b): Validation of numerical models for FTC

% Stroke Opening Computed Cv Experimental Cv Error (%)

20 9.20 9.39 -2.0

40 41.07 41.59 -1.2

50 60.05 61.53 -2.4

70 102.46 100.03 2.4

100 132.78 142.10 -6.6

(a) FTO (b) FTC

Fig. 4.1.1 Validation of Numerical Models for (a) FTO & (b) FTC

74

4.2 Turbulence modelling and grid independence

The numerical models simulated with standard k-ε model and RNG k-ε

model yielded similar results within an error of 2% as shown in the graph

(Fig.4.2.1(a)). This proves that the effects of turbulence models are negligible.

Table 2(a): Turbulence Modelling

% Opening k-ε Model Cv RNG k-ε Model Cv Error (%)

20 8.62 9.36 -0.74

50 58.90 58.74 0.16

70 97.54 98.17 -0.63

100 110.50 112.42 -1.92

Fig. 4.2.1(a) Verification of Turbulence Model

75

For grid independence, the numerical models with coarser and finer

meshes yielded equal CV values for corresponding percentage openings within an

error of 3%. Therefore, the effect of mesh size can be regarded as negligible. The

following graph (Fig.4.2(b)) illustrates these results.

Table 2(b): Grid Independence

% Opening Computed Cv

Error (%)

Original Refined

20 8.60 8.62 -0.02

50 58.45 58.90 -0.45

70 94.73 97.54 -2.81

100 111.70 110.50 1.20

Fig.4.2.1(b) Verification of Grid Independence

76

77

4.3 Effect of flow direction on flow coefficient ( Cv)

It is interesting to note that the flow coefficient values obtained for FTO

and FTC configuration vary by a certain degree, for large percentage openings

(above 50%). This variation was found to be arising due to the difference in mass

flow rates of fluid flowing through the holes in the cage. The mass flow rate

through each hole in both the configuration for 50% and 100% was computed

using CFD-Post (Post Processor). It was observed that for 50% opening of cage

the difference between the mass flow rates through each hole for FTO and FTC

were almost zero. At 100% opening a significant difference was observed for

these values between FTC and FTO conditions. The tabulated results shown in

Table (4.3) enumerates the above statements clearly. Hence, it can be concluded

that, these variations arise due to the difference in the nature of flow in both flow

Table 4: Comparison of mass flow rate through holes of 12 hole cage

Hole No.

100% mass flow rate 50% mass flow rate

FTO

mass flow

FTC

mass flow Δ

FTO

mass flow

FTC

mass flow Δ

1 1.228 3.090 1.862 4.274 4.610 0.336

2 1.500 1.691 0.192 0.000 0.000 0.000

3 0.615 1.166 0.551 0.000 0.000 0.000

4 1.672 2.987 1.315 2.006 2.129 0.123

5 1.122 1.454 0.332 0.000 0.000 0.000

6 2.639 2.384 -0.255 0.000 0.000 0.000

7 3.310 3.108 -0.202 4.756 4.718 -0.038

8 4.034 3.656 -0.378 0.000 0.000 0.000

9 2.709 2.225 -0.484 0.000 0.000 0.000

10 3.611 3.471 -0.140 2.075 2.113 0.038

11 2.053 1.656 -0.397 0.000 0.000 0.000

12 2.142 2.951 0.809 0.000 0.000 0.000

78

directions (FTO and FTC).

4.4 Effect of number of holes on the cage

The CV values for the numerical models with 8-hole and 24-hole cages for

various plug openings yielded results which matched with the corresponding CV

values of the numerical models of 12-hole cage within an error of 10%. Therefore,

it can be inferred that the effect of number of holes on the cage has little

significance on the CV values. The following tables (Table 4.4) and graphs

(Fig.4.4.1) illustrate these results for both FTO and FTC.

Table 4(a): Effect of cage design on Cv for FTO

% Opening Computed Cv Error (Cv) Error (%)

12hole 8 hole 24 hole 8 hole 24 hole 8 hole 24 hole

20.00 8.71 7.26 6.62 1.45 2.09 16.65 24.00

30.00 21.33 19.74 19.15 1.60 2.18 7.48 10.22

50.00 58.45 58.71 60.19 -0.26 -0.26 -0.44 -0.44

70.00 94.73 93.46 98.72 1.27 -3.99 1.34 -4.21

100.00 114.85 113.31 113.86 1.54 1.54 1.34 1.34

Table 4(b): Effect of cage design on Cv for FTC

% Opening Computed Cv Error (Cv) Error (%)

12hole 8 hole 24 hole 8 hole 24 hole 8 hole 24 hole

20.00 9.20 7.58 7.05 1.62 2.15 17.61 23.37

30.00 22.37 20.96 19.19 1.41 3.18 6.30 14.21

50.00 60.05 58.26 60.95 1.79 -0.90 2.98 -1.50

70.00 102.46 93.93 107.50 8.53 -5.04 8.33 -4.92

79

100.00 132.78 129.71 129.64 3.07 3.14 2.31 2.36

(a) FTC (b) FTO

Fig 4.4.1 Effect of number of holes on (a) FTC & (b) FTO

The discrepancies observed are due to the errors which had occurred in the

flow area comparison performed for cage design. Since, the cage was designed by

trial and error method (within an error of 6%) as explained in the previous

chapter, these unavoidable errors got reflected in the calculation of CV values as

well. In the following graph (Fig 4.4.2), the flow area for different plug openings

are plotted for 8-hole, 12-hole and 24-hole cages.

80

Fig 4.4.2 Flow areas for different openings

It can be observed that the graph (Fig 4.4.1) follows the same pattern as

that of the above graph (Fig.4.4.2) except at lower plug openings. At lower

percentage openings the effect of velocity fluctuations are dominant owing to the

transient nature of the flow. Since, steady state flow was assumed in this present

work, the errors due to these factors got added up while calculating the Cv values.

4.5 Effect of scaling globe control valve

The numerical models of 3 inch globe control valve were scaled to 2 inch,

4 inch, 5 inch and 6 inch for 20%, 50%, 70% and 100% plug openings. A

comparative study of these scaled models for 50% and 100% plug openings for

both FTC and FTO is illustrated in Fig 4.5.1.

81

(a) FTC (b) FTO

Fig 4.5.1 Relationship between Cv and size of valves for (a) FTC & (b) FTO

From the graph, a linear relationship can be approximated for both the

percentage openings, within the limits of computational error.

The obtained values for FTC and FTO are tabulated in the following tables

(Table4.5).

Table 4.5(a) Effect of Scaling for FTO

% opening

2 inch 3 inch 4 inch

Computed Cv

Flow area, Af(mm2)

Cv / Af

Computed Cv

Flow area, Af(mm2)

Cv / Af

Computed Cv

Flow area, Af(mm2)

Cv / Af

20 3.838 96.240 0.040 8.734 149.487 0.058 15.369 266.398 0.058

30 9.540 217.814 0.044 21.331 397.340 0.054 37.972 706.220 0.054

50 26.454 643.969 0.041 58.451 1302.928 0.045 107.077 2314.154 0.046

60 32.13 892.293 0.036 18.250 1814.201 0.042 134.711 3222.056 0.042

70 42.877 1309.053 0.033 94.732 2484.575 0.038 177.622 4416.233 0.040

100 50.141 2521.867 0.020 114.845 5386.406 0.021 202.737 9570.688 0.021

% Opening

5 inch 6 inch

Computed Cv Flow area, Af(mm2) Cv / Af Computed Cv Flow area, Af(mm2) Cv / Af

20 23.885 414.431 0.058 33.140 6.5173E+02 0.051

30 59.319 1103.927 0.054 80.980 1.5894E+03 0.051

50 166.345 3621.920 0.046 237.501 5.3017E+03 0.045

60 211.005 5043.446 0.042 305.778 7.2568E+03 0.042

70 283.826 6902.600 0.041 402.933 9.9383E+03 0.041

100 334.105 14968.669 0.022 489.661 2.1546E+04 0.023

Table 4.5(b) Effect of Scaling for FTC

% opening

2 inch 3 inch 4 inch

Computed Cv

Flow area, Af(mm2)

Cv / Af

Computed Cv

Flow area, Af(mm2)

Cv / Af

Computed Cv

Flow area, Af(mm2)

Cv / Af

20 4.082 96.240 0.042 9.196 149.487 0.062 16.230 266.398 0.061

30 9.939 217.814 0.046 22.369 397.340 0.056 39.555 706.220 0.056

50 26.446 643.969 0.041 60.047 1302.928 0.046 105.893 2314.154 0.046

60 32.795 892.293 0.037 75.164 1814.201 0.041 130.227 3222.056 0.040

70 45.199 1309.053 0.035 102.458 2484.575 0.041 183.551 4416.233 0.042

100 55.033 2521.867 0.022 132.775 5386.406 0.025 227.276 9570.688 0.024

% Opening

5 inch 6 inch

Computed Cv Flow area, Af(mm2) Cv / Af Computed Cv Flow area, Af(mm2) Cv / Af

20 25.287 414.431 0.061 35.593 651.731 0.055

30 61.636 1103.927 0.056 90.176 1589.362 0.057

50 165.570 3621.920 0.046 226.902 5301.690 0.043

60 202.212 5043.446 0.040 69.112 7256.815 0.040

70 288.232 6902.600 0.042 397.432 9938.319 0.040

100 359.186 14968.669 0.024 531.093 21545.622 0.025

Further, it was found that for different valve sizes, CV is a multiple of a constant and

flow area for a specific percentage opening. The CV / Af values are plotted against different

valve sizes, for 50% and 100% plug openings as shown in graph (Fig 4.5.2). Also, the CV / Af

values for different percentage openings for both FTO and FTC are shown in graph (Fig

4.5.3).

It can be observed that CV / Af values for FTO are more than that of FTC except at

50% opening were the values are equal.

It is interesting to note from the graph (Fig 4.5.2) that, for 2 inch valve models, CV/Af

values deviate from their counterparts. This may be due to the small computational domain of

(a) FTC (b) FTO

Fig 4.5.2 Relationship between Cv/Af and size of valves for (a) FTC & (b) FTO

Fig 4.5.3 Relationship between Cv/Af for different % stroke openings

2 inch valve model and the present criteria being insufficient for the analysis. Therefore, it

can be concluded that, the results obtained in the present section is valid only for valve sizes

between 3 inch and 6 inch, supported by verified numerical results for 3 inch, 4 inch, 5 inch

and 6 inch numerical models.

CHAPTER 5

CONCLUSION

5.1 Conclusions Arrived

The numerical models for 3 inch globe control valve for both FTO and FTC were

qualitatively matched with the experimental results within an error of ±6%. The effect of

turbulence model was found to be negligible by comparing results of numerical models

simulated with standard and RNG k-ε model. The grid independence was established by

comparing the results of numerical models simulated with fine and coarse meshes. Further,

the effect of number of holes of cage on flow coefficient (Cv) was found to be very less,

within an error of ±10%. Scaling of 3 inch numerical models to 2 inch, 4 inch, 5 inch and 6

inch highlighted on the relationship between size of valve, flow area and Cv. It was found that

for a specific plug opening, Cv/Af is a constant for different valve sizes. Another observation

was that Cv /Af values for FTC were more than that of FTO for all the plug openings except

for 50% plug opening, where the values were equal. Owing to the small computational

domain, there were discrepancies in the results obtained for 2 inch globe control valve.

Therefore, results obtained for scaling in this present study are valid only between the 3 inch

and 6 inch valve sizes.

5.2 Scope of future work

In this project, all the analyses were confined to globe control valve. As a scope for

future work, these analyses can be performed for other types of control valves as well.

Cavitation study and analysis of streamlines can be done for all these numerical models.

Further, scaling can be done for valve sizes above 6 inch for globe control valve. Also, a

better computational analysis can be followed for the scaling of 2 inch and other lower valve

sizes to obtain more accurate results. Additionally, studies can be conducted with different

working fluids as well. Further, CFD analysis can be supplemented by finite element

modelling in a more detailed way, and the results would help predict the behaviour of flow in

a more detailed and accurate manner.

APPENDIX A

1. Fabrication of Experimental Loop

As part of this present work, an experimental loop was proposed to be set up in the

Fluid Lab of Amrita School of Engineering, Coimbatore. But due to some unforeseen

circumstances the fabrication was not completed on time for the experiments to be conducted

for this project. So, the experimental results obtained from FCRI (Fluid Control Research

Institute), Kanjikode were used to validate the present numerical models. The details of the

experimental loop are explained briefly here.

2. Design

The experimental loop was designed to measure the flow coefficient of 3 inch valve is

shown in figure (Fig. A.A.1). Various components used in the loop are labelled in the figure

appropriately. The design was done in the commercial CAD modelling software SolidWorks

12.0.

3. Market Survey

A market survey was conducted to find about the available manufacturers and dealers

of pumps, pipes, fittings, gate valves etc. The prices of the all these items by different

manufacturers were compared. A bill of materials, thus prepared is given in Table A.A.1.

4. Schematic Diagram

All the components of the experimental loop are shown in this schematic diagram

(Fig. A.A.2) using the standard symbols.

Table A.A.1 Bill of Materials

Fig

. A

.A.1

Ex

per

imen

tal

Set

up –

CA

D D

raw

ing

DATE: 13/12/2012

Sl.No. Item Specifications Manufacturer Quantity

1 Pipe Scheduled 40 Steel Jindal Steels

Pvt. Ltd.

3 (x5m)

2 Manual Valves

(Upstream and

Downstream)

ANSI CLS150 Jindal Steels

Pvt. Ltd.

2

3 Flanges and

Gaskets

ANSI CLS150 Jindal Steels

Pvt. Ltd.

10

4 Nut & Bolt ANSI CLS150 Jindal Steels

Pvt. Ltd.

40

5 Pipe Bends ANSI CLS150 Jindal Steels

Pvt. Ltd.

7

6 Flow meter 3” (80NB),

ANSI B 16.5 150

Frehnig

Instruments

and Controls

Ltd.

1

7 Submersible

Pump

3 bar/ 30m , 3”, 2500lpm,

Submersible Monoblock

TEXMO

Industries

1

8 Differential

Pressure Gauge

Triplee

Engineering

Equipments

Enterprises.

1

9 Pneumatically

Actuated Control

Valve

3” Globe Style- CIRCOR D

SERIES

CIRCOR 1

Fig

. A

A.2

Sch

emat

ic E

xper

imen

tal

Dia

gra

m

APPENDIX B

1. Design of 8-hole and 24-hole cages

In this section, the design of 8-hole and 24-hole cages using the already available 12-

hole cage is discussed. In the 12-hole cage, one of the holes was assumed as the reference and

the angles of the other holes were measured with this reference. These angles, in radians,

along with the arc lengths were used to make the development drawing of the12-hole cage.

This development drawing was used to make the development drawings of 8-hole and 24-

hole cages as shown in chapter 3 (Fig 3.2.3-3.2.4), by matching the flow areas at 10, 20, 30,

40, 50, 60, 70, 80, 90, and 100 percentages plug openings. By this trial and error method, the

flow areas of all the three development drawings were matched within an error of 4%. The

development drawings were then converted into 3D models. The 3D models are shown in the

Fig A.B.1.

(a) (b) (c)

Fig A.B.1 Cage designs of (a) 8 hole cage (b) 12 hole cage (c) 24 hole cage

2. Valve Assembly Design

The valve assembly consists of valve body, seat, plug, cage and a bonnet as shown in

fig.A.B.2. It was designed and assembled using the design software SolidWorks 2012.

Fig. A.B.2 Components of valve assembly

Steps followed for valve assembly design:

1. A reference plane was made at the base of the seat ring.

2. The maximum height to which the plug can be moved was fixed to be 50.8 mm. So,

for 20% percentage opening, the plug was positioned at a distance of 10.16 mm

(50.8*(20/100)) from the base of the seat ring.

3. Similarly, numerical models were created for all the other required percentage

openings with the appropriate distances from the base of the seat ring.

4. A pipe of length 6*Diameter(D) (458.7mm) was placed upstream of the valve while a

pipe of length 10D (763.5mm) was placed downstream. The upstream and

downstream pipe lengths were given these values so as to attain a fully developed

flow.

5. Then, the pipe openings were covered with a cap. The caps were placed so as to

extract the fluid path fig.5 in ANSYS Workbench, which is discussed in the next

section. The design files were saved as Parasolid files.

Fig. A.B.3 Valve Assembly

3. Procedure for Extraction of Fluid Path

The fluid path was extracted in ANSYS 14.0 Workbench. The steps followed for the

extraction process are given below.

1. The Geometry tool was selected from Components Systems.

2. On right clicking the Geometry, a drop box was displayed from which Import was

selected. The required Parasolid file was chosen from the window appeared.

3. The Geometry was double-clicked and a new window appeared for the selection of

units. Millimetre was selected as the unit.

4. The Operation Type was made as Add Frozen and the path was generated using

Generate from the menu bar.

5. After generating, filling was done by Select-> Tools->Fill. From the window which

opened, By Cavity was changed to By Caps and No was selected for Preserving

Solids.

6. The generation of path was done again by clicking Generate. Thus, the fluid path was

fully generated. The file was saved as a Parasolid text file. The generated path is

shown in the fig.6. This file was then used for meshing.

Fig A.B.4 Flow path extract from ANSYS Workbench

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