experimental study a nd optimizing erosiv … journal of mechanical engineering and technology ... t...

http://www.iaeme.com/IJMET/index.

International Journal of Mechanical Engineering and Technology (IJMET)Volume 8, Issue 6, June 2017, pp.

Available online at http://www.iaeme.com/IJME

ISSN Print: 0976-6340 and ISSN

© IAEME Publication

EXPERIMENTAL STUDY A

EROSIVE WEAR RATE PARAMETE

A NOVEL ENT

PELTON TURBINE

Robin Thakur, Anil Kumar

School of Mechanical & Civil E

Department of Mechanical Engineering, OM Institute of Technology, Juglan (Hisar)

AP Goyal Shimla University, Himachal Pradesh, India

ABSTRACT

In this article, the effect of differe

concentration, and jet velocity has been

silt size (�) = 90-450, silt concentration (

25.492 and operating time (

a multi criteria decision making

experimental values achieved

agreement. Depend upon the Entropy

that experimental parameters

25.492 and 12 provided an best parameter

Key words: Energy, silt size, erosion, stream velocity

Cite this Article: Robin Thakur, Anil Kumar and Rahul Nadda, Sourabh Khurana,

Muneesh Sethi Experimental Study and Op

Using A Novel Entropy Vikor Approach in A Pelton Turbine Buckets

Journal of Mechanical Engineering and Technology

http://www.iaeme.com/IJME

NOMENCLATURE

� Average grain size coefficient of suspended sediment with a base of 0.05 mm

� Silt concentration

�� Fraction of silt by weight

� Particle size

� Jet diameter

IJMET/index.asp 27 [email protected]

International Journal of Mechanical Engineering and Technology (IJMET) 2017, pp. 27–43, Article ID: IJMET_08_06_004

http://www.iaeme.com/IJMET/issues.asp?JType=IJMET&VType=8&IType=6

6340 and ISSN Online: 0976-6359

Scopus Indexed

EXPERIMENTAL STUDY AND OPTIMIZING

E WEAR RATE PARAMETERS USING

A NOVEL ENTROPY VIKOR APPROACH

PELTON TURBINE BUCKETS

Robin Thakur, Anil Kumar and Rahul Nadda

School of Mechanical & Civil Engineering, Bajhol (Solan), (HP), India

Sourabh Khurana


Muneesh Sethi

AP Goyal Shimla University, Himachal Pradesh, India.

he effect of different experimental factors such as

jet velocity has been examined. The experimentation

450, silt concentration (�) = 2000 - 8000, jet velocity (

25.492 and operating time () = 9-12 respectively. Hybrid Entropy-VIKOR technique,

a multi criteria decision making method (MCDM) is consequently implimented

values achieved, which measures the variant responses

upon the Entropy-VIKOR analysis method, it has been

experimental parameters of �,�, and having mathematical value of 90, 8000,

an best parameter combination respectively.

Energy, silt size, erosion, stream velocity.

Robin Thakur, Anil Kumar and Rahul Nadda, Sourabh Khurana,

Muneesh Sethi Experimental Study and Optimizing Erosive Wear Rate Parameters

Using A Novel Entropy Vikor Approach in A Pelton Turbine Buckets

Journal of Mechanical Engineering and Technology, 8(6), 2017, pp. 27

aeme.com/IJMET/issues.asp?JType=IJMET&VType=8&IType=6

verage grain size coefficient of suspended sediment with a base of 0.05 mm

Silt concentration

raction of silt by weight

[email protected]

T&VType=8&IType=6

ND OPTIMIZING

RS USING

ROPY VIKOR APPROACH IN A

BUCKETS

(HP), India.


.

such assilt size, silt

. The experimentation involves the

8000, jet velocity () = 25.436-

VIKOR technique,

implimented to the

s the variant responses as a common

method, it has been obtained

value of 90, 8000,

Robin Thakur, Anil Kumar and Rahul Nadda, Sourabh Khurana,

timizing Erosive Wear Rate Parameters

Using A Novel Entropy Vikor Approach in A Pelton Turbine Buckets. International

27–43.

asp?JType=IJMET&VType=8&IType=6

verage grain size coefficient of suspended sediment with a base of 0.05 mm

Experimental Study and Optimizing Erosive Wear Rate Parameters Using A Novel Entropy Vikor Approach

in A Pelton Turbine Buckets

http://www.iaeme.com/IJMET/index.asp 28 [email protected]

�� Erosive wear

1 2 3 Coefficient of shape, hardness and abrasion resistance of base metal,

respectively

Normal component of particle impact velocity needed to initiate the erosion

� Silt size

�1 Coefficient of C

�2 Coefficient of silt hardness

�3 Coefficient of silt particle size

�4 Coefficient of silt particle shape

Operating time (h)

� Velocity of particle/Flow velocity (m/s)

Jet velocity

� Normalized wear rate (kg/h)

� Exponent for relative velocity

�, �, �� Constants whose values depend on the properties of the erodent as well

as the target material

Greek Letters

�� Loss in runner efficiency due to sediment erosion, %/year

� Impact angle

� Abrasion rate (mm/h)

� Deformation factor

� Exponent for annual suspended sediments content

Exponent for average grain size coefficient

1. INTRODUCTION

Energy emergency and a worldwide temperature alteration, for example, depletion of fossils

powers, have made it noteworthy to utilize renewable energy sources like hydroelectric

energy adequately [1]. For satisfying the request of energy, a worldwide level activity is

required to use renewable energy. Hydro power has been considered as a standout among the

most dependable and flexible type of renewable energy source which can satisfy both base

and pinnacle request. Hydro turbines are heart of hydro power plants and working of hydro

power plants primarily rely on upon turbine effectiveness. The variable which influences the

execution of hydro turbines is residue disintegration. Sediment disintegration is for the most

part considered as steady evacuation of material created by disfigurement and cutting activity

[2-3].The fundamental driver of disintegration in hydro turbine parts is the mix of high

grouping of residue with a higher rate of quartz substance in water which is a to a great degree

hard material [4-5]. Erosion in hydro turbines for the most part rely on upon different

variables like sediment size, sediment concentration, working hours, stream velocity, jet

diameter, residue shape and nozzle angle [6-7]. In case of impulse turbines buckets, nozzle,

blades and needle are affected due to silt erosion and in case of reaction turbines runner

blades, face plates and guide vanes are prone due to sediment erosion [8]. Because of

sediment disintegration stream design changes, loss in effectiveness, vibration delivered lastly

breakdown of hydro turbine happen [9]. A various research has been attempted to foresee the

conduct and to decrease the impact of disintegration in hydro turbines because of sediment.

[10-16].Bain et.al [17] built up a relationship to explore the disintegration rate by gathering

broad data from a bench scale test rig. The connection can be spoken to in the given shape as,

W = KVβdγCφ (1)

Robin Thakur, Anil Kumar and Rahul Nadda, Sourabh Khurana, Muneesh Sethi


where W is erosion rate, V is velocity of particle, d is particle size, C is solid

concentration, and K, β, γ and φ are constants whose values depend on the properties of the

erodent as well as the target material. Tsuguo [18] established a correlation of basic

parameters which are responsible for erosion of turbines based on erosion data of 18

hydropower plants of 8 years. He proposed following relation to estimate erosion in turbines.

W = β.Cx.a

y.k1.k2.k3.V

m [mm/year] (2)

Where W is loss of thickness per unit time, β is turbine coefficient at eroded part, V is

relative flow velocity. The term ! iscoefficient of average grain size on the basis of unit value

for grain size 0.05 mm. The terms k1 and k2 are coefficient of shape and hardness of sand

particles and k3 is abrasion resistant coefficient of material. The x, y are exponent values for

concentration and size coefficient respectively. Naidu [19] revealed a review that India is

confronting the issue of sediment in very nearly 22 substantial hydropower stations. These

power stations have been arranged into three classifications in view of level of harm:

impressive harm, which needs unmistakable endeavours and assets inside 15-20 years;

broadly high harm, which require change in at regular intervals; and serious harm which

requires repair each year. Thapa et al. [20] examined the impact of suspended residue in hydro

power ventures in view of a contextual analysis of 60MW Khimti hydro power plant. Because

of nearness of high measures of residue, the hydro power plant was composed with settling

bowls to screen 85% of all particles with a width of 0.13 mm and 95% of all particles with a

distance across of 0.20 mm. The plant was dispatched in July 2000 and the harm to the

turbine segments was explored in July 2003. The agents watched that a lot of disintegration

had showed up in the turbine bucket and needles. Chitrakar et al. [21] describes the

simultaneous nature of combine effect which contributes to vibration, losses, fatigue problems

and failure of Francis turbines. They have also discussed to minimize the combine effect by

controlling the erosion or secondary flow in the turbine.

The aim of this experimental study was to determine the normalized erosive wear for

Pelton turbine buckets made of Aluminium as a function of silt and operating parameters. In

current investigation Entropy-VIKOR technique has been used for calculating the best set of

experimental factors of erosive wear rate on Pelton turbine buckets which are designed with

Taguchi orthogonal array. Weight of responses i.e. W and efficiency has been determined via

Entropy weight production model and after that the alternatives of experimental sets have

ranked as per to VIKOR method.

2. EXPERIMENTATION ANALYSIS DETAILS AND GOVERNING

EQUATIONS

A trial set up has been composed and created by the Pelton turbine model design for 1 kW

control yield as appeared in Fig. 1. The runner of Pelton turbine having pitch circle diameter

145 mm, nozzle diameter 12 mm and having 20 quantities of buckets has been utilized for the

exploratory review. The heaviness of every basin is around 115 gm. The model of every

bucket and runner was made on AutoCAD and CREO version 2016 as appeared in Fig. 2. To

get the disintegration in limited ability to focus time, turbine buckets were made of

Aluminium. In this test work two tanks were made (650 mm × 520 mm × 800 mm). The

principal tank was utilized to store water and to flow sediment water blend to the runner of

Pelton turbine of various residue focuses. The second tank was utilized to quantify the release

by utilizing rectangular notch. Amid test work a stirrer was utilized constantly in order to

supply a uniform blend of sediment water to turbine runner. A penstock pipe having 70 mm

external width and 3 mm thickness was utilized for providing water to the turbine runner. A

monoblock having 40 m evaluated head and a release limit of 9 l/s was utilized to make hydro

potential. A computerized weight transducer of Yokogawa make having scope of 0.5 "� to




14 #"� and having exactness ± 0.065 % was fitted with penstock pipe to quantify the net

head at bay of Pelton turbine. A generator was straight forwardly coupled to the turbine shaft.

Electric knobs of various wattages were utilized as resistive load. The electric load was

measured to decide the yield of the turbine. The weight reduction of Pelton basins were

measured previously, then after the fact experimentation with the assistance of electronic

weight adjust having minimum tally of 0.1$�. Distinctive sorts of sifters of 90, 150, 300 and

450 microns were utilized so that reviewing of sediment should be possible.

2.1. Experimental Procedure

Before beginning the investigation, a trial test was directed to check the best possible working

of the entire set up. Legitimate working of the considerable number of instruments was

additionally confirmed. At first administration pump drew water from the capacity tank and

provided it to the turbine. Water from the turbine was permitted to move through second fitted

with rectangular score for release estimation. The height of water over the crest of the notch

was recorded by a pointer gauge and the release of the pump relating to every head was

resolved. The figuring of release will be made based on the height of water (h) streaming over

the peak. To examine the impact of residue disintegration on containers of Pelton turbine,

silty water of known focus was set up in the principal tank. For providing a uniform blend of

sediment and water ceaselessly to turbine a stirrer was turned with the assistance of engine.

Amid tests head and stream were kept steady. One arrangement of readings was taken at four

estimations of time interim of 2 h by keeping one parameter as fix and other parameter as

variable.

Figure 1 Schematic of experimental setup



(a)

(b) PCD φ145mm (c)

Figure 2 Design details of Pelton turbine blades and runner

To assess disintegration qualities an aggregate 192 arrangements of readings were

recorded by taking distinctive estimations of residue size four arrangements of trials, also for

sediment focus four arrangements of examinations and four stream speed three arrangements

of tests were directed. To explore disintegration in containers they were destroyed after at

regular intervals of investigation. An advanced adjust of Tapson make with traverse go from

10 g to 210 g and least count of 0.1 mg were utilized to gauge loss of weight. Be that as it

may, because of course of silty water to turbine runner the impeller of the pump got

disintegrated after certain time of operation so the impeller was supplanted with new impeller.

3. RANGE OF PARAMETERS

In this test work residue measure, sediment focus, stream speed and working hours were

researched parameters. For this, specimen of sediment was gathered from Chameralake,

Chamba (HP, India) in which the sediment concentration amid storm season was around




20000 ppm and the normal quartz substance was observed to be around 80%. Residue was

dried in the daylight for 3-4 days and sifters of various sizes were utilized to strainer the sand

before blending with water. The factors of experiment which has been studied contains four

values of �,four values of�, four values of and four values of respectively. The ranges of

different parameters are depicted in Table 1.

Table 1 Range of experimental parameters

Sr. No. Parameters Symbols Range

1. Silt size � 90-450

2. Silt Concentration � 2000-8000

3. Jet Velocity 25.436-25.492

4. Operational time 3-12

4. UNCERTAINTY ANALYSIS

Uncertainty in experimental measurements has been carried out. Let a set of measurement is

made and the uncertainty in each measurement may be expressed. These measurements are

then used to calculate some output of experiments. The result (R) is a given function of the

independent variables x1, x2, x3,………,xn. Hence,

),.......,,( 21 nxxxRR = (3)

Let WR be the uncertainty in the result and W1, W2, W3,……….,Wn be the uncertainties in

the independent variables. The resultant uncertainty (WR) is calculated as;

∂

∂++

∂

∂+

∂

∂=

22

2

2

2

1

1

............. n

n

R Wx

RW

x

RW

x

RW

(4)

Uncertainty calculation for S (S) is determined as follow:

21 SSS −=

Uncertainty of Particular size range is provided as follow:

( ) ( )[ ]S

WW

S

W SSS

5.02

2

2

1+

=

(5)

( ) ( )[ ]%57.10157.0

90

115.022

==+

=S

WS

The maximum possible measurement errors in the values of major parameters are given

below in Table 2:



Table 2 Uncertainty analysis of major Parameters

S.No. Parameters Range Uncertainty

1 Silt size 90, 150, 300, 450 µm 1.57%

2 Silt concentration 2000, 4000, 6000, 8000 ppm 0.25%

3 Jet velocity 115g 0.69%

4 Operating time 8 h 1.18%

5 Pressure 0.5 kPa to 14 MPa ± 0.065 %

6 Discharge H=45-90 mm 1.68%

5. OPTIMIZATION METHODOLOGY

VIKOR approach is one of the significant MCDM processes which ranks parameters and

conclude the optimal results. Results achieved are extremely nearer to optimal response and

away from the worst. Due to the fast raise in functioning of VIKOR, we have preferred this

approach for optimization in current study also.

5.1. HYBRID ENTROPY-VIKOR METHOD

In terms of combined entropy-VIKOR approach the weight of responses from entropy process

are combined among the other stages of VIKOR. The outline of process in form of flow chart

has presented in Fig. 3. Three steps of the process are as follow:

1. Step-1: Elementary formation

2. Step-2: Entropy weight creation method

3. Step-3: VIKOR

5.2. STEP-1: ELEMENTARY FORMATION

In current step, amount of alternatives and different responses employed in the performance

estimation of specified MCDM are calculated and a comparative result matrix is created.

Figure 3 Schematic of the estimation methodology for optimization




If ‘O’ signify number of alternatives and ‘P’, signify number of responses then result

matrix having an order of O × P is characterized as:

=×

MNMM

N

N

PO

bbb

bbb

bbb

A

…

�…��

…

…

21

22221

11211

(6)

Here, a parameterijb (for i=1, 2... O; j = 1, 2... P),stands for real data of the i

th alternative

with respect jth

response.

After the generation of results matrix, benefit ( )maxijb and cost ( )

minijb response has obtained

as:

( ) [ ]Oibbb ijijiij ...2,1,maxmax

max===

( ) [ ]Oibbb ijijiij ...2,1,minmin

min===

(7)

5.3. STEP-2: ENTROPY WEIGHT CREATION METHOD

In this step the weights of different responses are calculated with the entropy process.

Primarily, projection value (ijπ ) for every alternative is determined as follow:

∑=

=O

i

ij

ij

ij

b

b

1

π

(8)

After the calculation of (ijπ ), entropy of all responses is determined as follow:

)ln(1

ij

P

j

ijj ππςε ∑=

−=

(9)

Here, ς is alteration constant and determined as,

)ln(

1

O=ς

After that the dispersion value (jλ ) of every response is determined as follow:

jj ελ −= 1 (10)

At last the weight of every response is determined as follow:

∑=

=P

j

j

j

j

1

λ

λω

(11)



5.4. STEP-3: VIKOR

Normalize the result matrix. The method of normalization is prepared with supposing

arithmetical alternatives jon every response:

�%& = ()*+∑ ()*-.*/0

(12)

In this step alternatives are measured and ranking is achieved. Method is expressed as

below: The data of utility measure ( jS ) and regret measure ( jR ) are determined as:

[ ][ ] criteriabenefitisjwhen

mm

mmS

P

j ii

ijij

j ,1

∑=

+•

•

−

−=

ω

(13)

[ ] criteriatisjifmm

mmwR

iii

ijij

j cos,][

max+•

•

−

−= , for j = 1, 2. . . O (14)

VIKOR index ( iϑ ) is calculated as:

)(

))((1(

)(

)(•+

•

•+

•

−

−−+

−

−=

RR

RRv

SS

SSv jj

iϑ (15)

Here, ν and ( ν−1 ) are established as weight for the highest value of utility and weight of

the particular regret respectively. The value of ν is used as 0.5. jS ,•

S , jR , •R are the highest

and lowest values of utility and regret calculations.

At last, with iϑ values the alternatives has been ranked and the alternative among the

lowest value of iϑ will be ranked as optimal alternative.

6. EXPERIMENTAL RESULTS AND DISCUSSION

Testing has been performed forerosive wear rate on Pelton turbine among combinations of

experimental factors as depicted in Table 3. After the examination of each alternative which is

parametric set of erosive wear rate on Pelton turbine, the results has been noted and calculated

for� and efficiency loss. Table 3 depicts� and efficiency lossresponsesachieved for all

alternatives combinations. The surface conditions of bucket after the investigation are shown

in Fig. 4. The results of Table 3 have been presented graphically in Fig. 5 so as to observe the

inclination of � and efficiency loss difference concurrently. It has been found that where the

efficiency loss is improved, at the same time the �value has also improved.




Figure 4 Surface condition of bucket after experimentation

Table 3 Experimental results of variant parameters

Experimental Parameters Results

Alternatives S C V t W (C1) Efficiency loss

(C2)

A-1 90 2000 25.436 3 0.0002188 0.087

A-2 90 4000 25.452 6 0.0009835 0.314

A-3 90 6000 25.476 9 0.0025402 0.667

A-4 90 8000 25.492 12 0.0037861 1.129

A-5 150 2000 25.452 9 0.0008754 0.221

A-6 150 4000 25.436 12 0.0022773 0.594

A-7 150 6000 25.492 3 0.0007170 0.331

A-8 150 8000 25.476 6 0.0017790 0.758

A-9 300 2000 25.476 12 0.0013742 0.287

A-10 300 4000 25.492 9 0.0016786 0.505

A-11 300 6000 25.436 6 0.0016638 0.583

A-12 300 8000 25.452 3 0.0010410 0.477

A-13 450 2000 25.492 6 0.0006898 0.173

A-14 450 4000 25.476 3 0.0006130 0.225

A-15 450 6000 25.452 12 0.0038404 0.985

A-16 450 8000 25.436 9 0.0033419 1.082

7. NUMERICAL SIMULATION FOR OPTIMIZATION

The responses achieved from testing have been optimized by Entropy-VIKOR technique.

Variant steps of the evaluation processes are explained as below:



8. STEP-1: ELEMENTARY STRUCTURE

The set A-1 to A-16 are selected as alternatives and responses of W and efficiency loss are

considered as criterions (� as C-1 and efficiency loss as C-2) for performance estimation of

erosive wear rate on Pelton turbine.

Figure 5 Difference of experimental results with alternatives

A resultant matrix ( )POD × has been created in which alternatives stands for by O and criterions

for P. Concurrently, all constituents of the matrix are denoted by

( )PjOiford ij ....3,2,1;....3,2,1 == . Decision matrix is,

( ) ( )( ) ( )( ) ( )( ) ( )( ) ( )

( ) ( )

=×

MNM

NM

dd

dd

dd

dd

dd

dd

D

1.0820.0033419

0.2210.0008754

1.1290.0037861

0.6670.0025402

0.3140.0009835

0.0870.0002188

1

5251

4241

3231

2221

1211

��

After generation of resultant matrix, benefit ( )maxijd and cost ( )

minijd responses have been

determined as follow:

( ) [ ]0.0002188,0.0038404max

max== ijiij dd

( ) [ ]0.087,1.129min

min== ijiij dd

8.1. STEP-2: ENTROPY WEIGHT DETERMINATION MODEL

After operating the data of benefit and cost responses, weights of these responses have been

calculated by Entropy weight determination model. Projection results of every response and

alternatives have determined by equation (8)and are depicted in Table 4.




For determining entropy, alteration constant can be calculated as follow:

0.36067)16ln(

1==ς

Results of )ln(1

ij

N

j

ij ππ∑=

have been calculated in Table 4.

Table 4 Projection values of all alternatives and responses

Alternatives Projection Value, ijπ ( )

ijij ππ ln×

C-1 C-2 C-1 C-2

A-1 0.00798 0.010335 -0.03855 -0.04725

A-2 0.035868 0.037301 -0.11937 -0.12267

A-3 0.09264 0.079235 -0.22039 -0.20089

A-4 0.138078 0.134117 -0.27339 -0.26945

A-5 0.031926 0.026253 -0.10996 -0.09556

A-6 0.083053 0.070563 -0.20666 -0.18708

A-7 0.026149 0.039321 -0.09528 -0.12724

A-8 0.06488 0.090045 -0.17746 -0.21678

A-9 0.050117 0.034094 -0.15002 -0.11519

A-10 0.061218 0.05999 -0.171 -0.16879

A-11 0.060678 0.069256 -0.17003 -0.18491

A-12 0.037965 0.056664 -0.12419 -0.16266

A-13 0.025157 0.020551 -0.09264 -0.07984

A-14 0.022356 0.026728 -0.08497 -0.09681

A-15 0.140058 0.117011 -0.27531 -0.25105

A-16 0.121878 0.128534 -0.25652 -0.2637

Total 1 1 -2.56574 -2.58986

After that the entropy of all responses has been determined using equation (9):

( ) ( ) 0.92542.5657436067.01 =−×−=−Cε

Similarly,

( ) ( ) 0.93412.5898636067.02 =−×−=−Cε

Dispersive results of the all responses have been determined from equations (10) and after

that weights have been determined using equation (11)as follow:



0.5309580.14051

0.07461 ==−Cω

0.4690430.14051

0.06592 ==−Cω

The entropy, dispersion value and the weight particular response depend on Shannon

entropy model is depicted in Table 5. It has been obtained that the maximum disorder in

response means minimum weight and vice versa. In current examination, the W show s

minimum data of the entropy and hence it has higher weight as compared to efficiency loss.

Table 5 Response weight determined with entropy technique

Criteria C-1 C-2

Entropy 0.9254 0.9341

Dispersion

value 0.0746 0.0659

Weight 0.530958 0.469043

8.2. STEP-3: VIKOR

The method of normalization is prepared with supposing arithmetical alternatives jon every

response and determined by using equation (12) and presented in Table 6 respectively.

Table 6 Normalized decision matrix

Alternatives C-1 C-2

A-1 0.00798 0.010335

A-2 0.035868 0.037301

A-3 0.09264 0.079235

A-4 0.138078 0.134117

A-5 0.031926 0.026253

A-6 0.083053 0.070563

A-7 0.026149 0.039321

A-8 0.06488 0.090045

A-9 0.050117 0.034094

A-10 0.061218 0.05999

A-11 0.060678 0.069256

A-12 0.037965 0.056664

A-13 0.025157 0.020551

A-14 0.022356 0.026728

A-15 0.140058 0.117011

A-16 0.121878 0.128534




The utility measure, regret measure and VIKOR index has been calculated using equation

(13-15 respectively and after that characterized among ranking of the alternatives in Table 7.

The alternative among maximum range of VIKOR index has been ranked the optimal. It

has been found that A-4 has maximum range of VIKOR index and A-1 has minimum range of

VIKOR index therefore A-4 the most suitable alternative among every one of alternative.

Table 7 Utility measure, regret measure, VIKOR index and ranking of parameters

Alternatives Utility measure

( jS )

Regret measure

( jR )

VIKOR index

( jϑ ) Ranking

A-1 0.000176 0.00163 0.00181 16

A-2 0.214166 0.111985 0.205756 11

A-3 0.601391 0.340312 0.605129 4

A-4 0.992094 0.523052 0.963098 1

A-5 0.156448 0.09613 0.163396 13

A-6 0.52997 0.301751 0.534824 6

A-7 0.18273 0.109833 0.188809 12

A-8 0.530705 0.302042 0.535447 5

A-9 0.259318 0.16929 0.281303 10

A-10 0.402095 0.213938 0.391214 8

A-11 0.435035 0.223268 0.415654 7

A-12 0.295972 0.175553 0.304609 9

A-13 0.107619 0.068907 0.114518 14

A-14 0.119761 0.062119 0.113867 15

A-15 0.935239 0.531016 0.943644 2

A-16 0.905786 0.4579 0.860612 3

The experimental parameters of erosive wear rate on Pelton turbineat alternative A-4 are:

S, silt concentration, and with relevant values of 90, 8000, 25.492 and 12 respectively.

The combination of alternatives in the descending order of their position are A-4>A-15>A-16

>A-3>A-8 > A-6>A-11>A-10>A-12>A-9>A-2>A-7>A-5>A-13>A-14 > A-1.

The erosive wear rate on Pelton turbine has been studied for W and efficiency loss

descriptions. Increase in both the performance estimation response has been obtained. The

entropy-VIKOR technique proposes that erosive wear rate on Pelton turbines with alternative

combination are� of 90, � of 8000, of 25.492 and of 12 provides the highest overall

performance as clearly observed IN Figure 6&7.



Figure 6 Normalized wear loss vs silt size and silt concentration

Figure 7 Efficiency loss vs silt size and silt concentration

8. CONCLUSIONS

In this paper, experimental analysis and parameters optimization Entropy-VIKOR techniques

has been carried out to investigate the effects of effect wear rate on silt size and silt

concentration in a Pelton turbine bucket. Based on the experimental results, the following

conclusions are drawn:

1. Entropy-VIKOR has been used in many engineering applications as a multi criteria decision

making (MCDM) approach. Where entropy measures the weights of each of the performance

evaluation criterion towards overall performance, the VIKOR method provides ranking of the

alternatives by providing the best compromise solution which is nearest to the real and farthest

from the worst. The results obtained from this study will be useful for the designers and

researchers in the field of Pelton turbine bucket for performance evaluation and optimization

with desired evaluation criteria for maximum overall performance.

2. Entropy technique has been used to the combination of experimental factors as designed with

Taguchi design of experiments on every of the performance responses. It was found that the

efficiency loss has maximum disorder of 0.9341 as compared the normalized weight loss

among a value of 0.9254. The equivalent weights of the responses are 0.530958 and 0.469043

respectively. This proposes that the efficiency loss response has higher influence on the whole

performance of erosive wear rate on Pelton turbine than that of normalized weight loss

response.




3. The best factors combination which gives the optimal normalized weight loss and efficiency

loss performance based upon VIKOR method with normalized weight loss and efficiency loss

at the higher end concurrently is alternative A-4. The ranking of whole factors combination

refers the order: A-4 > A-15 > A-16 > A-3 > A-8 > A-6 > A-11 > A-10 > A-12 > A-9 > A-2 >

A-7 > A-5 > A-13 > A-14 > A-1.

4. The entropy-VIKOR technique proposes that erosive wear rate on Pelton turbines with

alternative combination are� of 90, � of 8000, of 25.492 and of 12 provides the highest

overall performance.

REFERENCES

[1] Y. Nishi, T.Inagaki, Y.Li, R.Omiya, and J.Fukutomi, Study on an undershoot cross flow

water turbine, Journal of Thermal sciences, 23, 2014, 239-245.

[2] R. Thakur, A. Kumar, S. Khurana, M. Sethi, Correlation development for erosive wear

rate on pelton turbine buckets, International Journal of Mechanical and Production

Engineering Research and Development, ISSN-22496890 (Accepted for publication).

[3] Pundir A, Kumar A. Technical feasibility study for power generation from a potential

mini hydro site nearby Shoolini University, Advances Energy Research, 4, 2014, 85-95.

[4] S.C. Singh, Operational Problems and Development of a New Runner for Silty Water.

International Water Power and Dam Construction, 4,1990,29-37.

[5] D.Tong, Cavitation and Wear on Hydraulic Machines, International Water Power and

Dam Construction, 2, 1981,30–40.

[6] S.Khurana, and Varun, Effect of jet diameter on erosion of turgo impulse turbine runner,

Journal of Mechanical Science and technology, 28(11), 2014, 4539-4546.

[7] S.Khurana, Varun, and A.Kumar, Effect of Nozzle Angle and Silt Parameters on Erosion

and Performance of Turgo Impulse Turbine, International Journal of Thermal

Technologies 2(4),2012, 204-208.

[8] S.Chitrakar, H.P.Neopane, and O.G.Dahlhaug, Study of simultaneous effects of secondary

flow and sediment erosion in Francis turbines, Renewable energy 34, 2016,1-16.

[9] B.S.Thapa, O.G.Dahlhaug, and B.Thapa, Sediment erosion in hydro turbines and its

effect on the flow around guide vanes of Francis turbine, Renewable and Sustainable

Energy Reviews, 12, 2008, 1974-1987.

[10] M.K.Padhy, and R.P.Saini, A review on silt erosion in hydro turbines, Renewable and

Sustainable Energy Reviews, 49, 2008,1100-1113.

[11] S.Derakshan, and A.Nourbakhsh, Experimental study of characteristics curves of

centrifugal pump working as turbines in different specific speeds, Experimental thermal

and fluid Science, 32, 2008, 800-807.

[12] B.S.K.Naidu, Addressing the problems of silt Erosion at Hydro Plants, International

Journal of Hydropower and Dams, 3,2009, 72-77.

[13] M.K.Padhy, R.P.Saini, Effect of size and Concentration of Silt Particles on Erosion of

Pelton Turbine Buckets, Energy, 34, 2009, 1477-1483.

[14] T.R.Bajracharya, C.B.Joshi, R.P.Saini, and O.G.Dahlaug, Sand erosion of Pelton Turbine

nozzles and buckets: A case study of Chilme hydropower plant, Wear, 264, 2008, 177-

184.

[15] J.G.A.Bitter, A Study of Erosion Phenomenon- Parts I and II, Wear, 6, 5-21, 1963, 169-

190.

[16] APundir, and AKumar,Technical feasibility study for power generation from a potential

mini hydro site nearby Shoolini University, Advances Energy Research, 4, 2014, 85-95.

[17] A.G.Bain, and S.T. Bonnington, The hydraulic transport of solids by pipeline, 1st ed.

Oxford: Pergamon Press, 13, 1970, 1-6.



[18] N.Tsuguo, Estimation of repair cycle of turbine due to abrasion caused by suspended sand

and determination of desilting basin capacity, In Proceedings of International Seminar on

Sediment handling technique NHA, Kathmandu, 1999.

[19] B.S.K. Naidu, Silting problem in hydro power plant & their possible solutions, Delhi,

India, NPTI, 2004.

[20] B.Thapa, R.Strestha, P.Dhakal, and B.S.Thapa, Problems of Nepalese hydropower

projects due to suspended sediments, Aquatic Ecosystem Health Manage, 8(3), 2005,

251–257.

[21] Sailesh Chitrakar, H.P.Neopane, and O.G.Dahlhaug, Study of simultaneous effects of

secondary flow and sediment erosion in Francis turbines, Renewable energy, 2016, 1-16.

[22] B. S.Thapa, B.Thapa, and O.G.Dahlhaug, Empirical Modelling of Sediment Erosion in

Francis Turbines, Energy, 41, 2012,386– 391.

[23] Bilal Abdullah Nasir Design Of High Efficiency Pelton Turbine For Microhydropower

Plant. International Journal Of Electrical Engineering & Technology, 4(1), 2013, pp.171-

183.

[24] Dr. U. Sathish Rao and Dr. Lewlyn L.R. Rodrigues. Enhancing the Machining

Performance of HSS Drill in the Drilling of GFRP Composite by Reducing Tool Wear

through Wear Mechanism. International Journal of Mechanical Engineering and

Technology, 8(1), 2017, pp. 120–131.

[25] T. Madhusudhan and M. Senthil Kumar. Experimental Study on Wear Behaviour of SiC

Filled Hybrid Composites Using Taguchi Method. International Journal of Mechanical

Engineering and Technology, 8(2), 2017, pp. 271–277.

experimental study a nd optimizing erosiv … journal of mechanical engineering and technology ... t...

Documents