chapter 3 experimental detailsshodhganga.inflibnet.ac.in/bitstream/10603/11705/8/08_chapter...

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CHAPTER 3

EXPERIMENTAL DETAILS

In this chapter, the experimental set up, design of experiments,

method of analysis and experimental details are discussed.

3.1 EXPERIMENTAL SET UP

Belt grinding machine used for the optimisation studies is shown in

Figure 3.1. An abrasive belt grinding machine uses coated abrasive belt as a

grinding tool. It is used to evaluate the performance of the abrasive belts.

Figure 3.1 Autobelt evaluator – abrasive belt grinding machine

Idle

rollContact

wheel

Workpiece

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Machine details are given below,

Grinding machine : Automatic Belt Grinding

Machine (ABGM)

Maximum speed : 50 m/s

Maximum belt width and length : 50 mm and 750mm

Diameter of contact wheel : 300 mm

Loading control : Pressure

Figure 3.2 depicts the experimental set up. Abrasive belt is

mounted on the contact wheel, which is normally a rubber coated metal

wheel. Nearly homogenous pressure was given between the work piece and

belt. At the microscopic scale, the contact is localized within the peaks of

abrasive grains. Abrasive belt is driven through the contact wheel which is

attached to the motor. The motor has variable drive to change the RPM of the

contact wheel.

Figure 3.2 Schematic view of experimental setup

3.2 CONTACT WHEEL

The contact wheel is a rubber backing wheel used for mounting the

abrasive belt. Three different backing wheels are used for varying the

gripping force of the belt, namely 1:1, 1:2 and 1:3(land to groove ratio)

serrated wheels. Figure 3.3 clearly shows the land to groove ratio of the

Idler wheel

Abrasive belt

Contact wheelWork piece

Feed

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respective serrated wheels. The land area of the wheels are calculated based

on the surface speed of the wheel and mentioned as contact area (mm2/rev).

The contact area is related to the dimension of the work material, land area

and surface speed of the wheel.

Figure 3.3 Serrated contact wheels

3.3 MATERIALS SELECTION

Belt grinding is used to grind variety of materials for different

applications. Applicable materials from industries and literature are stainless

steel, cast iron, wood, alloyed steel and tool steel. Stain less steel is widely

used in food processing, and chemical industries as material for structural,

equipments and containers. Mostly sheets and pipe form with mirror finish.

Hence stainless steel was used as a work material for all the studies. A

medium carbon steel and tool steel were used for selected experiments. Apart

from metals, belt grinding is also used to finish brittle materials such as

marble, granite and alumina. Among the three materials, alumina is used as

engineering material. Hence Alumina has been chosen for optimization

studies. Metallic specimens like AISI 304 stainless steel, EN8 steel and High

carbon and High chromium steel were used for different experiments. The

properties of the work materials used in the present research work are given

below.

Land Groove:

1: 3 serrated 1: 2 serrated

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AISI304 stainless steel

AISI 304 stainless steel materials of same heat number were

procured. The chemical composition of the material was found to be

Ni- 8.8%, Cr-19.8%, C-0.08% and Mn of 1.5%. The hardness of the material

is 30HRC.

EN8 stainless steel

EN8 steel of same heat number was procured in the form of rods of

diameter 30mm diameter with length of 300mm. The chemical compositions

of the material are C-0.4%, Si-0.25%, S- 0.015% and P- 0.015%. The

hardness of the material is 45HRC.

HCHCr steel

HCHCr steel materials was procured in the heat treated conditions.

The hardness of the material was 60 to 65 HRC. The typical chemical

composition of the material was C-2.2%, Mn-0.52%, Cr-12.2%, Si-0.5%, V-

0.69% and W-0.64%

Alumina ceramics

The work materials taken for this research are alumina ceramics

(Al2O3) of three different purity levels (90%, 92% and 94% pure alumina)

manufactured by Carborundum Universal. The specimens are in the form of

hollow tubes having dimensions of external diameter 30mm, 5mm wall

thickness and 100mm in length. The Al2O3 has the grain size, ranging from 2–

10 m. Figure 3.4 shows the typical samples of the alumina ceramic materials

used for this study. Density of the materials are 3.6, 3.65 and

3.7 gm/cm3

, for 90, 92 and 94% purity respectively. The compressive

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strengths are 1700, 1800 and 2000 MPa for the 90, 92 and 94% purity

respectively.

Figure 3.4 Alumina ceramic Specimen

3.4 OUTPUT PARAMETERS MEASURED

From the literature review, it is evident that belt wear of the

abrasive belt grinding reflects the tool wear on the whole. Therefore, in the

present study, abrasive belt wear was considered as direct indicator of tool

status. For each experiment, material removal was measured interms of

weight loss. A fresh work piece was used for grinding purpose. The size of

the workpiece used for the each experiment was kept constant to avoid the

variation in the application of grinding pressure. Wherever required the

surface finish of the work piece was measured at the end of the testing

processes. Depending on the type of studies, belt wear and material removal

were measured periodically for every two minutes. A detailed fractographic

study on worn out belts was carried out to understand the mechanism of tool

wear. Table 3.1 shows the output process parameters and methodology of

measurements to analyze the performance of grinding.

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Table 3.1 Methodology for Measuring the Output Parameters

S.NoOutput process

parametersMeasuring methodology

1. Material removal

By weighing the work piece before and

after grinding using electronic weighing

machine with accuracy of 0.01 gm.

2. Abrasive Wear

By weighing the belt before and after

grinding using electronic weighing

machine with accuracy of 0.01 gm

3. Surface RoughnessMeasured using Surfcoder(SE3500), a

stylus based surface roughness tester

3.5 GRINDING PARAMETERS

Abrasive belt grinding is relatively a complex process with large

number of interacting variables, which varies depending upon application. In

this research work the following factors are considered for the optimization,

Belt characteristics - bonding system, backing material, Abrasive

grit size, Flexing pattern

Operating conditions - Belt speed, grinding pressure, contact area

and coolant.

For optimization of the belt grinding process, operating parameters

are often determined with the aid of grinding tests. If more number of

parameters is there then, the conventional testing method becomes time

consuming process. Hence Taguchi methods of design of experiments are

used to select the significant grinding parameters.

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3.6 DESIGN OF EXPERIMENTS AND ANALYSIS OF DATA

3.6.1 Design of Experiments

Taguchi Experimental Design (TED) was used to find out the

influence of the experimental factors and their significance on the response.

Taguchi method uses signal-to-noise (S/N) ratio, value to interpret the

experimental results data and the evaluation of characteristics for desired

parameter settings (Rose, 1996). This is because the S/N ratio can reflect both

average and variation of the quality characteristics. Depending on the quality

characteristics involved, different S/N ratios may be applicable, including

smaller is better (SB), nominal is the best (NB), or greater is better (GB).

Regardless of the category of the performance characteristic, normally the

greater S/N ratio corresponds to the better performance characteristics.

Therefore, the best level of the factors is mostly the level with the highest S/N

ratio.

3.6.2 Application of Taguchi Method

The various steps in the application of the Taguchi method in the

present study are as follows;

Selection of the factors and their levels

The grinding parameters such as contact area, belt speed and

grinding pressure are, generally controllable in any grinding situation,

selected as factors for study. Factors such as bonding system, flexing, and

backing are available to the maximum of three levels of variants. Hence three

levels are selected for each factor, to study the non –linearity effects.

Selection of Orthogonal Array and assignment of factors

To conduct an optimization study a special set of arrays called

orthogonal arrays needs to be selected. These standard arrays stipulate the

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way of conducting the minimal number of experiments which could give the

full information of all the factors that affect the performance parameter.

Orthogonal Array (OA)

Orthogonal Arrays are a set of tables of numbers created by

Taguchi that allow experimenters to study the effect of a large number of

control and noise factors on the quality characteristics with a minimum

number of trials ( Law and Kelton 2000). The choice of OA depends on the

number of factors to be studied for optimization, number of interactions to be

examined, number of levels required for each factor.

The number of degrees of freedom for the OA should be greater

than or equal to the degrees of freedom required for studying the main and

interaction effects.

Minimum Number of experiments

or = ( No. of level-1) X No. of factors +1

Degrees of freedom for the study

Further to selection of appropriate OA the factors are assigned to

various columns of the array and subsequent interaction columns located. For

example, in an experiment with three factors and three levels, the degree of

freedom is 9 hence an L9 orthogonal array shall be chosen for the studies.

Table 3.2 shows typical orthogonal array of L9.

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Table 3.2 Orthogonal array

Vairable 1 Variable2 Variable3

1 1 1 1 p1

2 1 2 2 p2

3 1 3 3 p3

4 2 1 2 p4

5 2 2 3 p5

6 2 3 1 p6

7 3 1 3 p7

8 3 2 1 p8

9 3 3 2 p9

L9 (34) Orthogonal array

ExperimentIndependent variables

Performance

parameter value

The orthogonal arrays have the following special properties that

reduce the number of experiments to be conducted.

1. The vertical column under each independent variables of the

above table has a special combination of level settings. All the

level settings appear an equal number of times. For L9 array

under variable 3, level 1, level 2 and level 3 appears thrice.

This is called the balancing property of orthogonal arrays.

2. All the level values of independent variables are used for

conducting the experiments.

3. The sequence of level values for conducting the experiments

shall not be changed. This means one can not conduct

experiment 1 with variable 1, level 2 setup and experiment 4

with variable 1, level 1 setup. The reason for this is that the

arrays of each factor columns are mutually orthogonal to any

other column of level values. The inner product of vectors

corresponding to weights is zero. If the above 3 levels are

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normalized between -1 and 1, then the weighing factors for

level 1, level 2 , level 3 are -1 , 0 , 1 respectively. Hence the

inner product of weighing factors of independent variable 1

and independent variable 3 would be

(-1 * -1+-1*0+-1*1)+(0*0+0*1+0*-1)+(1*0+1*1+1*-1)=0

3.6.3 Analysis of Results

Experiments are conducted on random sequence to avoid any

unknown and uncontrolled factors that may vary during the entire experiment

and which may influence the results. Each experiment is repeated for three

times and average results taken up for analysis. The results of the experiments

were calculated for based on the following types of quality characteristics.

Evaluation of S/N ratios

Taguchi suggests the transformation of the data in a trial in to a

consolidated single value called S/N ratio. Here, the term ‘signal’ represents

the desirable value (mean) and the ‘noise’ represents the undesirable value

(standard deviation). Hence the S/N ratio represents the amount of variation

present in the out put. Depending upon the objective of the output, S/N ratios

are calculated in the following form

Smaller-the-better

Smaller-the-better characteristic is a non-negative measurable

characteristic that has an ideal state or target of zero. This is used to measure

characteristics such as belt wear and surface finish. Formula to calculate

smaller that better S/N ratio ( ) is

n2

i

i 1

10 Log y /n

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Larger-the-better

Larger-the-better characteristic is a non-negative measurable

characteristic that has an ideal state or target of infinity. This measures

characteristics such as material removal G-ratio and strength. Formula to

calculate larger the better S/N ratio ( ) is

n2

i

i 1

10 Log (1 / y ) x 1/n

where yi the measured output for the ith

experiment and n the number of

experiment in a trial.

3.6.4 Sequence of Analysis

Results of the experiments were analyzed in three stages namely

1. Level average response analysis based on Factor effect

diagram and Average signal to noise ratio.

2. Analysis of variance (ANOVA) based on Average S/N ratios.

3. Multiple regression analysis based on experimental results.

Factor effect diagram

The level average response analysis is based average on S/N data.

The analysis is done by averaging the S/N data at each level of each factor

and plotting the values in a graphical form called factor effect diagram. The

level average response plots based on S/N data help in optimizing the

objective function under study. The peak points in these plots correspond to

the optimum condition. From the plot the influence of individual factors and

its level are analyzed, based on the slope of the curve. The absolute difference

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between the average S/N ratio values of the two levels reveals the effect of

each factor. The larger the difference, the stronger is the influence to the

performance.

ANOVA and modeling of responses

ANOVA is a computational technique to estimate quantitatively the

relative contribution of each controlled parameter makes in the overall

measured response. An Analysis of Variance (ANOVA) is performed on S/N

ratios to obtain the contribution of each of the factor. This is performed by

separating the total variability of the response performance, which are

measured by the sum of the squared deviations from the total mean of the

response performance and into contributions by each of the factors under

investigations and the error.

When the saturated design type is chosen, where all columns in OA

are assigned with the factors; the variation due to error is estimated by

pooling the factors having less influence for correct interpretation of results.

By comparing the sum of squares values of each factor with the factor that has

the highest sum of squares, which is less than 10% or lower than the most

influential factor, then these factors are considered insignificant (Roy 2001).

Fisher test (F-test) factor for 90% confidence level also used to find out the

significant factor. ANOVA was calculated for all the out put.

Multiple non linear regressions

A multiple regression method was performed using a non-linear fit

between the response and the factors. Based on the observed results of the

trials, a mathematical equation was formulated using the multiple regression

method by using a non-linear fit between the response and the significant

parameters.

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Multiple regression analysis is practical and relatively easy for use

and widely used for analyzing experimental results. By using this method the

influence of individual parameters were defined in equation. In regression

equation apart from significant parameters, other factors are also considered.

The following mathematical models were formulated for all measured

performance.

Material Removal = K1.Sw

1.Rx1.A

y1.C

z1 (3.1)

Belt wear = K2.Sw

2.Rx2.A

y2.C

z2 (3.2)

G-Ratio = K3.Sw

3.Rx3.A

y3.C

z3 (3.3)

Surface finish = K3.Sw

3.Rx3.A

y3.C

z3 (3.4)

where K, w, x, y, z are constants and S, R, A and C are grinding variables

such as Belt Speed (S) (m/s), Rotation of the work piece (E) (rpm), Density of

Alumina (D) (g/cm3)., Contact area(C) (mm

2/rev), abrasive grit size (G) (no),

flexibility (F) (mg) and peel strength (B) (N/mm). The suitable variables are

used depends up on the design of experiment. Regression coefficient is

calculated for the each regression equation which is represented as R2 = 1 -

Residual SS / Corrected SS, where SS- sum of square. Higher the value of

regression coefficient means the effective correlation of non linear fit with

actual results.

Validation of findings

Confirmatory run was conducted for further analysis. The optimum

level of the each factors are performed as a validation test. The test results are

compared with values derived from the non linear fit.

Figure 3.5 shows the sequence of analysis followed in this work.

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Figure 3.5 Sequence Analysis

3.7 VARIABLE PARAMETERS

The following belt properties and machine variables were used in

the studies.

Identification of Quality characteristics (performance

measure)

Selection of factors and its levels

Select Orthogonal Array (OA)and assign the factors and its

levels to the OA

Analysis of experimental data using signal to noise ratio,

factor effect diagram and optimum levels

Apply ANOVA to identify the significant factors

Form multiple non linear Regression Equation

Verification of the optimal design parameters through

confirmation experiment and compare the values

calculated from regression equation

Conclude on influence of the factors

Conduct the test described by the trials in the OA

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1. Belt speed (m/sec) : 38, 41 and 44.

2. Rotation of the (specific to alumina grinding)

Workpiece (rpm) : 720, 840, and 960

3. Material : AISI 304 Stainless steel, EN8 Steel

HCHCr steel and alumina

4. Contact wheel serration : 1:1, 1:2 and 1:3 (land to groove ratio)

5. Flexing pattern : 900, 90

0+45

0and 90

0 +45

0-45

0

6. Grinding pressure (bar) : 0.5, 1.0 and 1.5

7. Bonding system : Resin over resin, resin over glue, and

glue over glue

8. Backing material : Cotton, polycot and polyester

3.8 EXPERIMENT DETAILS

The study is conducted in two phases. The first phase of five set of

experiments are conducted to select the belt and machine parameters which

have strong influence on the output.

In second phase optimization of belt grinding of alumina ceramics

and stainless steel has been carried out. Taguchi method is used in the

selection of process of strongly influencing, belt and machining parameters.

For optimization of belt grinding of stainless steel, was done with full

factorials to validate the findings of phase I study. Optimization study was

done for Alumina ceramic as per taguchi approach. The design of experiments

for different set of factors and levels is shown in Tables 3.3 - 3.15.

Experiment 1 - Effect of bonding system in abrasive belt grinding

Bonding system - The purpose of bonding system is to hold the

grains and backing material together. Among the three kinds of bonding

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system discussed in section 1.2.3, it is required to understand and select the

suitable bonding system for further studies. The strength of bond is measured

as peel strength. Peel strength is defined as an ability of the material to resist

forces that can pull it apart by separating a coated layer from the backing

material. Peel strength, belt speed and pressure are chosen as the factors in

this experiment. Peel strength of glue over glue, resin over glue and resin over

resin are 40, 50 and 65 N/mm respectively. The adhesive strength is

considered as the parametric value for the discussion.

Abrasive belt: Abrasive – Alumina, Grit number- 60, Workpiece –

stainless steel

Table 3.3 Bonding system and machining parameters

S.No Parameter unit Level 1 Level 2 Level 3

1 Bonding system -Peel strength N/mm 40 50 65

2 Speed m/s 38 41 44

3 Pressure bar 0.50 1.0 1.5

Table 3.4 Orthogonal array for the experiment 1

Ex.no Bonding systemBelt Speed

(m/s)

Grinding

pressure

(bar)

1 Glue over glue 38 0.5



4 Resin over glue 38 1.0



7 Resin over resin 38 1.5



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Experiment 2 Effect of backing material in abrasive belt grinding

Backing material - The backing materials (section 1.2.4) posses

having different kind of properties based on the yarn. Physical properties of

the belt vary with respect to type of backing material. The mechanical

properties such as tensile strength, stretch (elongation) and stiffness of the belt

were measured. The stretches of the belts at 590 N are 7mm, 10mm and 14

mm respectively for polyester, polycot and cotton. Each experiment was

performed until the grain was pulled out from the belt. Belt was visually

examined for every tow minutes for any grain shedding.

Abrasive belt used : Abrasive – Alumina, Grit number-60 and

Bonding system – Resin over resin. Work material- AISI 304SS.

Table 3.5 Backing materials and machining parameters

S.No Parameter Unit Level 1 Level 2 Level 3

1 Type of backing-stretch mm 7 10 14

2 Speed m/s 38 41 44

3 Pressure Bar 0.50 1.0 1.5

Table 3.6 Orthogonal array for the experiment 2

Ex.noBacking

material

Belt

Speed

(m/s)

Grinding

pressure

(bar)

1 Polycot 38 0.5

2 Polycot 41 1.0

3 Polycot 44 1.5

4 Polyester 38 1.0

5 Polyester 41 1.5

6 Polyester 44 0.5

7 Cotton 38 1.5

8 Cotton 41 0.5

9 Cotton 44 1.0

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Experiment 3 - Effect of abrasive grit on abrasive belt grinding

Abrasive grit size – Theoretic the size of abrasive has strong

influence in the grinding output. In order to understand the intensity of the

influence along with the machine parameters, grit size and contact areas are

considered as one of the factor.

Abrasive belt: Abrasive- Alumina, Bonding system- Resin over

resin, Backing materials – polyester. Work piece-AISI304 SS, EN8 and

HCHCr

Table 3.7 Abrasive grit and machining parameters


1 Contact area mm2/rev 4210 2826 2120

2 Abrasive grit number 24 36 60

3 Speed m/s 38 41 44


Table 3.8 Orthogonal array for experiment 3.

Ex.noContact Wheel

(mm2/rev)

Abrasive

grit

Belt Speed

(m/s)

Grinding

pressure (bar)

1 4210 24 38 0.5

2 4210 36 41 1.0

3 4210 60 44 1.5

4 2826 24 41 1.5

5 2826 36 44 0.5

6 2826 60 38 1.0

7 2120 24 44 1.0

8 2120 36 38 0.5

9 2120 60 41 1.5

The experiment was repeated for all the Workpieces.

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Experiment 4 - Effect of flexing pattern on belt grinding.

Flexing pattern - Flexing is the process to achieve the required and

uniform flexibility of coated abrasive belt. The hardened and rigid bond is

partially broken in a controlled manner in small area sections. Flexing is a

mechanical operation designed to break the adhesive bond at closely spaced,

predicted intervals. Mechanical flexing is capable of producing different

‘degrees’ of flexibility by varying the spacing between ‘breaks’, angle of the

break and number of flexing directions.

The flexing operation offers a degree of flexibility for coated

abrasive belts. A single flex (90o

degree) produces flex breaks perpendicular

to the grind direction. It is chosen where conformability is required in the

crosswise direction. Double flexing (45o

degree) produces a crosshatch of the

breaks that are 45o

degrees to the belt direction. A double flex adds moderate

conformability in all directions to the belt. Fully or triple (Figure 4.23) flexed

(90o+45

o-45

odegree) abrasives are combinations of single and double flexed.

The stiffness of the flexed belt differs with respect to type of flexing. The

schematic (Figure 3.5) of 90o , 90

o + 45

o and 90

o + 45

o- 45

o show the

flexing pattern in the belts. . The stiffness of different flexed 90o, 90

o +45

o

and 90o +45

o- 45

o are 220g, 195 g and 180 g respectively

Figure 3.5 Types of flexing

(a) 90o

(b) 90o+45

o( c ) 90

o +45

o-45

o

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Abrasive-alumina; Grit number-60, Bonding system- Resin over resin,

Backing materials – Polyester. Work piece- AISI304SS. The parameters

observed as the most significant grit 60, resin over resin and polyester

backing are chosen as parameters for the present study.

Table 3.9 Flexing and machining parameters


1 Flexing degree 90 90+45 90+45-45

2 Speed m/s 38 41 44



Table 3.10 Orthogonal array for Experiment 4

Ex.noFlexing

(degree)

Belt Speed

(m/s)

Grinding

pressure

(bar)

Contact Wheel

(mm2/rev)

1 90 38 0.5 4210

2 90 41 1.0 2826

3 90 44 1.5 2120

4 90+45 38 1.0 2120

5 90+45 41 1.5 4210

6 90+45 44 0.5 2826

7 90+45-45 38 1.5 2826

8 90+45-45 41 0.5 2120

9 90+45-45 44 1.0 4210

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Experiment 5 – Effect of coolant in belt grinding

Grinding coolant – Grinding is also influenced by the external

factors such as grinding environment. The effect of the coolants such as water

and oil based coolant need to be compared with dry grinding to understand

the effect of coolants in the belt grinding, hence above coolants are

considered as factors.

Abrasive- alumina; Grit number- 60; Work piece – AISI 306SS

Table 3.11 Coolant and machining parameters


1 coolant Dry water Oil

2 Belt speed m/s 38 41 44

3 Grinding pressure Bar 0.50 1.0 1.5


Table 3.12 Orthogonal array for experiment 5

Belt SpeedG rinding

pressureContact area

m /s bar m m2/rev

1 Dry 38.00 0.50 4210

2 Dry 41.00 1.00 2826

3 Dry 44.00 1.50 2120

4 W ater 38.00 1.00 2120

5 W ater 41.00 1.50 4210

6 W ater 44.00 0.50 2826

7 Oil 38.00 1.50 2826

8 Oil 41.00 0.50 2120

9 Oil 44.00 1.00 4210

Ex.no Coolant

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Experiment 6 - Optimization of belt grinding of Alumina ceramics

Alumina ceramics with different purity level was used as work

material. In grinding of alumina ceramics, silicon carbide abrasive was used

as per Abrasive index. Initial trials with constant pressure resulted in more

chipping of work material. In order to avoid chipping, belt grinding was done

with constant feed rate and work piece rotation.

Abrasive - Silicon carbide; Bonding system – Resin over resin,

Backing materials – Polyester, Flexing pattern – 900 ,Grit number - 60; feed

rate - 0.80mm/minute.

Table 3.13 Material and Machining parameters


1 Speed m/s 38 41 44

2 Rotation RPM 720 840 920

3 Material % of alumina 90 92 94


Table 3.14 Orthogonal array for experiment 6

Ex.noBelt Speed

m/s

Work piece

Rotation

rpm

Density of

Alumina

(g/cm3)

Contact area

mm2/rev

1 38 720 3.60 4210

2 38 840 3.65 2826

3 38 960 3.70 2120

4 41 720 3.65 2120

5 41 840 3.70 4210

6 41 960 3.60 2826

7 44 720 3.70 2826

8 44 840 3.60 2120

9 44 960 3.65 4210

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Experiment 7 – Optimization of belt grinding of stainless steel

For Optimization of machining parameters, full factorial

experiments were conducted. The most significant machining parameters

factors from the experiments 1 to 6 were used as the parameters. Abrasive belt

made with Alumina grit size of 60 is used. Machining parameters like belt

speed, contact area and grinding pressure are used as variables.

Table 3.15 Full factorial Experiments

Belt SpeedGrinding

pressureContact area

1 38 0.5 4210

2 41 0.5 4210

3 44 0.5 4210

4 38 1.0 4210

5 41 1.0 4210

6 44 1.0 4210

7 38 1.5 4210

8 41 1.5 4210

9 44 1.5 4210

10 38 0.5 2826

11 41 0.5 2826

12 44 0.5 2826

13 38 1.0 2826

14 41 1.0 2826

15 44 1.0 2826

16 38 1.5 2826

17 41 1.5 2826

18 44 1.5 2826

19 38 0.5 2120

20 41 0.5 2120

21 44 0.5 2120

22 38 1.0 2120

23 41 1.0 2120

24 44 1.0 2120

25 38 1.5 2120

26 41 1.5 2120

27 44 1.5 2120

Exp.no

m /s bar mm2/rev

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