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1. TITLE:

Sand Testing Preparation (GFN)

2. OBJECTIVES:

2.1.To measure the sand grain size and calculate the Grain Fineness Number (GFN).

2.2.To understand the advantages and disadvantages of sieve analysis and its applications.

2.3.To study the causes of different value of GFN in the casting processes.

2.4.To enhanced knowledge about suitability of the sand for castings.

2.5.To study the necessary precaution needed for this experiment.

3. INTRODUCTION:

A system has been developed to rapidly express the average grain size of a given and

sample. The Grain Fineness Number (GFN) is the quantitative indication of the grain size

distribution of the sand sample by carrying out a sand sieve analysis. GFN is important

because it provides the foundry a way to verify that its sand is within specification for the

castings being produced and helps avoid conditions that could lead to potential casting

problems. Sand that is too fine (higher GFN) or too coarse (lower GFN) can affect the

quality of castings produced. Sand that is too fine can create low permeability and result

in casting gas defects. Sand with high permeability (too coarse) can create problems with

metal penetration, rough surface finish, burn-in and burn-on. The grain fineness of sand is

measured using a test called Sieve Analysis.

A sieve analysis is a practice or procedure used to assess the particle size distribution

of a granular material. Sand sieve analysis is a method for determining the grain size

distribution of particles typically between 1.0mm and 0.062mm. It is a relative accurate

method for determining depositional hydrology and for refining sedimentary

environments. With experience, most geologists can visually measure grain size within

accuracy of the Wentworth grade scale at least down to silt grade. Silt and clay can be

differentiated by whether they are crunchy or plastic between one’s teeth. Clay stones and

siltstones are not amenable to size analysis from an optical microscope. Their particle size

can be measured individually by electron microscope analysis. Boulder, cobbles, and

gravel are best measured manually with a tape measure or ruler. Sands are most generally

measured by sieving.

Both graphic and statistical methods of data presentation have been developed for the

interpretation of sieve data. The percentage of the samples in each class can be shown

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graphically in bar charts or histogram. Another method of graphic display is the

cumulative curve or cumulative arithmetic curve. Cumulative curves are extremely useful

because many sample curves can be plotted on the same graph and differences in sorting

are at once apparent. The closer a curve approaches the vertical the better sorted it is, as a

major percentage of sediment occurs in one class. Significant percentages of coarse and

fine end-members show up as horizontal limbs at the ends of the curve.

Figure 3.1: Example of Graphical Interpretation of Sieve Data

The four statistical measurements for sieved samples consist of a measure of central

tendency (including median, mode, and mean); a measure of the degree of scatter or

sorting; kurtosis, the degree of peakedness; and skewness, the lop-sidedness of the curve.

Various formulae have been defined for these parameters.

Figure 3.2: Skewness Analysis

Within geology accurate sieve analyses are required for petrophysical studies which

relate sand texture to porosity and permeability. The distribution of sediment for water

wells also requires a detailed knowledge of the sediment of aquifers. Sieve analysis data

can be used as an interpretive tool to determine the depositional environment of ancient

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sediments. The philosophy behind this approach is that modern environments mold the

distribution of sediment and these differences can be quantitatively distinguished. Thus,

by comparing the sieve analysis data from modern depositional environments with

samples from the geologic past the depositional environment for these ancient samples

can be determined.

The size distribution is often of critical importance to the way the material performs in

use. A representative sample of the sand is weighed and passed through a series of

progressively finer sieves (screens) while being agitated for a 15-min test cycle. The sand

retained on each screen is weighed and the weights are recorded. The weight retained on

each sieve is divided by the total sample weight to arrive at the percent retained on each

screen. In economics, a numerical coefficient showing the effect of a change in one

economic variable on another. One macroeconomic multiplier, the autonomous

expenditures multiplier, relates the impact of a change in total national investment on the

nation's total , for that particular screen and these values then are added together to find

the GFN of the sand (Table 1). The factors for the sieves are based on the fact that the

sand that is retained on a particular sieve such as 50 mesh is not all 50 mesh in size, but

rather it is smaller than 40 mesh (passed through 40 mesh screen), but larger than 50 mesh

(won't pass through 50 mesh screen). The result should be rounded to one decimal place

decimal place. The position of a digit to the right of a decimal point, usually identified by

successive ascending ordinal numbers with the digit immediately to the right of the

decimal point being first. This number is the weighted mathematical average of the

particle size particle size, also called grain size, refers to the diameter of individual grains

of sediment, or the lithified particles in clastic rocks. After performing the sieve analysis

test, the distribution of sand grains on the screens can be just as significant as GFN. The

distribution refers to how much is retained on each sieve, rather than the average of all of

the sieves. Formula below used to calculate Grain Size Fineness;

∑ F GFN = X 1

∑ C

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4. APPARATUS:

Figure 4.1: Set of Sieves and Sieve Shaker

Figure 4.2: Apparatus and Materials

4.1.Materials

Silica Sand,

4.2.Equipment

1 set of 9 sieves (53,75,106,150,212,300,425,600,850) plus the sieve pan, Sieve

Shaker, Digital Scale Balance

4.3.Hand Tools

Brush

Sieves

Sieve Shaker

Sieve Pan

Digital Scale

Balance

Hand Brushes

Silica Sand

Container

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5. EXPERIMENTAL PROCEDURE:

i. The screens on the sieves wan clean carefully by turning the sieves face down and

striking the rim evenly on the table. The screen must not touch with fingers. The

sieves should not beat hard to avoid damage on the rim.

ii. The sand sample was weight 100 grams to accuracy of 0.01 grams.

Figure 5.1: A student weighed the silica sand

iii. The stack of sieves was placed on the Sieve Shaker Octagon 2000 machine. The top

sieve of the sieves shaker contains the bigger mesh size which is 850.

Figure 5.2: Put the sieves on the Sieve Shaker

iv. The weighing sand sample was poured into the top sieve of the sieve s shaker.

Figure 5.3: Pour the sand

v. The sieves were shaken continuously for a period of 15 minutes.

vi. After the shaking operations, the top sieve was taken apart and left over sand of the

sieves was wiped using brush and carefully weighed. The weight was recorded in

column C of Table 1.

Figure 5.4: Take apart the left over sand

vii. Step VI was repeated until the left over sand in the last sieve was weighed and the

value was recorded.

viii. The Grain Fineness Number (GFN) was calculated using the formula below;

∑ F GFN = X 1

∑ C

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6. RESULTS AND DATA ANALYSIS:

Table 1: Sieve Analysis Data and Calculations

A B C D E F

No. Opening

(Mic)

Sand Mass

(g)

Sample

(%)

AFS

Multiplier

AFS Product

(C x E)

1 20 850 0.00 0 10 0.00

2 30 600 0.00 0 20 0.00

3 40 425 0.00 0 30 0.00

4 50 300 0.03 0.03 40 1.20

5 70 212 5.16 5.19 50 258.00

6 100 150 35.13 35.35 70 2459.10

7 140 106 33.62 33.83 100 2262.00

8 200 75 16.03 16.13 145 2324.35

9 270 53 8.03 8.08 200 1606.00

10 PAN 1.38 1.39 300 414.00

Total accumulated sand mass (g) ∑C = 99.38 100% ∑F = 10424.65

Original mass of sample before

Sieving (g) 100

Calculation;

∑ F GFN = X 1

∑ C

10424.65 = X 1

99.38

= 104.89

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Table 2: Percentage of Mass Retained in Each Sieve

SIEVE NUMBER PERCENTAGE OF MASS

RETAINED IN SIEVE (%)

CUMULATIVE

PERCENTAGE OF MASS

LEFT IN SIEVE (%)

1 0 0 2 0 0 3 0 0 4 0.03 1.39 5 5.19 9.47 6 35.35 25.6 7 33.83 59.43 8 16.13 94.78 9 8.08 99.97 10 1.39 100

TOTAL = 100 100

Plotting the graph;

a. Graph between sieve numbers and percentage of mass retained in each sieve.

Sieve Number versus Percentage of Mass Retained

0

5

10

15

20

25

30

35

40

0 1 2 3 4 5 6 7 8 9 10 11

Sieve Number

Percenatge of Mass Retained (%)

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b. Graph between sieve numbers and cumulative percentage of mass left in sieve.

Sieve Numbers versus Cumulative Percentage of Mass Left

0

10

20

30

40

50

60

70

80

90

100

110

0 1 2 3 4 5 6 7 8 9 10 11

Sieve Numbers

Cumulative Percentage of Mass Left

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7. DISCUSSION:

From the experiment, the value of GFN we get for the sand silica sample in sieve

analysis is 104.89. The GFN value is very high. So, the silica sand sample has fine grain

since the value of GFN is above 100. The total accumulated mass of the sand sample is

only 99.38g. It is slightly different from the mass we were weighed before the sieve

testing. The early sand mass before sieve shaking is 100g. The different is about 0.62g.

There are different in the mass value of the sand because some errors occur during the

testing. Student did not wipe all the left over sand in each sieve and error also occur

during reading the value at digital balancing scale. The environment condition also will

influence the reading of the result. The digital balancing scale is the sensitive instrument,

so it must be carefully handle to avoid the error from occur.

We have plotted graph of sieve numbers versus the percentage of mass retained in

each sieve from the data calculated. The graph is a quadratic graph. We can say that the

value of sand mass retained in each sieve has greater increase for a moment before

decrease until the last sieve. From the graph, we can see that the percentage of mass is

higher at the middle sieve. But, at the sieve number 1 until 3, there is no percentage of left

over sand. Then, we also plot graph of sieve number versus the cumulative percentage of

the sand mass retained in the sieves. From the data interpreted, we got a sinusoidal graph.

The sand mass value is increase with the increasing in the sieve number. However, there

are some constants values at the early and final stage of the graph.

In this experiment, there are several precaution we must take to avoid and prevent

errors from occur. The screen on the sieves should be clean carefully in order to remove

all grain sands. The stack of sieves on the Sieve Shaker must be locked tidily to avoid

them from moving away during shaking process. Student should make sure that all the left

over sand in each sieve is transferred to the container use in weighing process. We also

must clean the area around digital scale balance to get accurate readings and avoid the

environmental effects. Student also can use a soft bristle brush to gently wipe the screen.

i) Explain briefly what is GFN?

GFN or ‘Grain Fineness Number’ is a system developed by AFS for rapidly expressing the average grain size of given sand. It approximates the number of meshes per inch of that sieve that would just pass the sample if its grains of uniform size. It is approximately proportional to the surface area per unit of weight of sand, exclusive of

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clay. For the different value of GFN will be used for different applications (e.g. 40: large casting, 70: small casting, 100: non-ferrous alloy cast, 150: aluminium alloy casting). GFN as known as the grain fineness number is quantitative indication of the grain size and grain size distribution

ii) Based on GFN value and the distribution obtained, suggest the suitability of the sand for castings.

The quality of castings produced depends largely upon the properties of the sand utilized. To ensure good castings, the sand must satisfy specifications: 1. Refractoriness. 2. Bond strength. 3. Permeability. 4. Collapsibility 5. Grain fineness and size 6. Grain shape and roundness The sand which is suitable for casting should has good strength to avoid the mould from broken during the process. It also has high refractoriness to withstand the high temperature of the molten metal. The sand also must have good permeability. The sand must be porous so that the gases generated are allowed to escape. Size of the sand and its shape it’s depend on the materials and casting process. The small size provide better surface finish but the large grain size is more permeable. The sand should have good thermal conductivity, so that the heat from casting is quickly transferred.

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8. CONCLUSION:

From this experiment, we found that the value of the GFN of the silica sand specimen

by using sieve analysis is 104.89. The sand sample used in this experiment is too fine

since we got the higher value of GFN. However some errors occur during this experiment.

The total accumulates sand mass is differ from original mass which is 99.38 while the

original mass is 100g. We must take some precaution in order to get the accurate data in

this experiment and avoid the errors. As conclusion, this experiment has achieved its

objective which is to measure the grain size of silica sand sample and calculate the value

of GFN.

9. RECOMMENDATION:

i. The screen on the sieves should be clean carefully in order to remove all grain

sands.

ii. Do not touch the sieves screen with the fingers.

iii. Avoid beat the sieves hard to prevent it from damage.

iv. The stack of sieves on the Sieve Shaker must be locked tidily to avoid them from

moving away during shaking process.

v. Make sure that all the left over sand in each sieve is transferred to the container

use in weighing process.

vi. Clean the area around digital scale balance to get accurate readings and avoid the

environmental effects.

vii. Use a soft bristle brush to gently wipe the screen.

10. REFERENCES:

i. Serope Kalpakjian, Steven R. Schmid, Manufacturing Technology and

Fundamental, 5th Edition, Prentice Hall, 2004.

ii. Serope Kalpakjian, Steven R. Schmid, Manufacturing Processes for Engineering

Materials, 4th Edition, Illinois Institute Of Technology, Prentice Hall, 2003.

iii. http://www.wikipedia.com/foundry_sand_testing

iv. http://www.engnet/glossary_GFN

v. http://www.sfsa.org/sfsa/glossary/deftrmgg.html