Effect of Fines Content on Some Engineering Properties of Lateritic Soil in Ile-libre

8/12/2019 Effect of Fines Content on Some Engineering Properties of Lateritic Soil in Ile-libre

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Table 2.3: General Requirements for Subgrade, Sub-base and Base Course in Nigeria

Subgrade Sub-base Base course

Proportion

passing BS

sieve No. 200(Amount of

fines, %)

35 35 35

Liquid Limit

(%)

80 35 35

Plasticity index

(%)

55 12 12%

Soaked CBR

(24hrs.)

NA 30% 80

Relative

compaction

(%)

100 100 100

Source: Federal Republic of Nigeria highway manual (1992)

consists of clay and silt, while the coarse content consists of sand and gravel. These soil types

Most soils used for road construction are not completely

granular (i.e. cohesionless); they usually contain varying percentages of fines content. Soil

with particle size smaller than 75 m, is referred to as fines according to the Unified Soil

Classification System (ASTM, 2000) and American Association of State Highway andTransportation Officials (AASHTO, 1986) classification systems. The level of fines content

in any soil has been found to affect important properties of the soil including soil

composition, particle friction, compaction, moisture and type of soil (Hveem, 2000). Theseproperties in turn affect the performance of the soil when used as a sub-base materialalthough the actual effects vary from soil sample to sample.

Soil with particle size larger than 75 m is referred to as coarse content. The fines content

consists of clay and silt, while the coarse content consists of sand and gravel. These soil types

resist deformation and support loads by different means or mechanisms, depending on thebasic properties of the soil. These means are interparticle friction and cohesive resistance.

Interparticle friction, which is internal friction among the aggregate particles, is the principalproperty which permits coarse soils or granular materials to resist load without deformation

and it is related to aggregate characteristics such as shape and surface texture. Cohesiveresistance is induced almost entirely by the fines content. However, cohesion is mostly

provided by the clay content, because silt, even though is referred to as fines, is relatively nonplastic and non cohesive. However, cohesive soils, which do not normally derive any

significant engineering strength from interparticle bonds or cohesive forces, possess frictional

strength because they exhibit a property known as plasticity. Plasticity which is defined as the

ability of soil to be worked and remoulded in the hand, allows cohesive soil to sustain large

pore water suctions which may result in large effective stresses and hence frictional strength

even if the total stress is zero (Powrie, 1997; Woodward et al., 2002).

A proper degree of both internal friction and cohesion in a soil prevents the aggregate

particles from being moved past each other by the forces exerted by traffic. It is realized that

if the cohesive strength could be made sufficiently high, internal friction would not be

necessary (Woodward et al., 2002). But cohesion of soil is a function of water content and

time (Kemper and Rosenau, 1984), therefore as the water content increases the cohesionincreases.However, natural soils containing appreciable amounts of water are not capable of


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pavement, the higher the expected CBR value, thus, the CBR of road base material should be

higher than that of sub-base material, while the CBR of sub-base material should be higher

than that of subgrade material. Table 2.4 gives the typical CBR range for different soil types.

Capping layers are introduced to help solve the problem of sub-grades wetting up and losing

strength during construction by protecting the subgrade from the worst of the damage caused

by site traffic. Capping layers are laid on top of the subgrade, such that the top of the cappinglayer becomes the formation level.

Madu (1980) noticed a positive correlation between iron sesquioxide content (a measure of

the degree of laterization) and the CBR values of some Eastern Nigeria laterite soils. The

CBR characteristics of some Western Nigeria residual laterite soils were found to be affected

by geological factors of parent material and degree of weathering. The values of the CBR

increase with the degree of laterization.

The duration of soaking is usually between 24 and 48 hours. A shorter soaking period is

permissible for A-1-a and A-3 soils if tests show that a shorter period does not affect the test

results, but in no case shall the soaking period be less than 24 hours (AASHTO, 1993).

Surcharge weights, in the form of annular discs with a mass of 2 kg are placed on top of the

soil test sample before the sample is soaked. Each 2 kg disc is roughly equivalent to 75 mmof surcharge material. The surcharge weights allow for the increase in strength due to road

construction material placed above the subgrade or the sub-base. The plunger penetratesthrough a hole in the disc to reach the soil.

2.6.1.2 Shear strength of soilThe shear strength of a soil mass is the internal resistance per unit area that the soil

mass can offer to resist failure along any plane inside it (Das, 1990). When this resistance isexceeded failure occurs. The shear strength is usually made up of:

(a) Internal friction or the resistance due to interlocking of the particles, represented by anangle .

(b) Cohesion or the resistance due to the forces tending to hold the particles together in asolid mass. The cohesion of a soil is generally symbolized by the letter C.

The law governing the shear failure of soils was first put forward by Coulomb and it is givenin Equation 2.4:

S = C + tan (2.4)Where:

S is the shear strength and is the normal stress

Soil composition (mineralogy,grain size distribution, and pore water

content), initial state (defined by initial void ratio and stress history), structure (arrangement

of particle within soil mass) and Loading conditions (stress path, type of loading and time

history) are found to affect the shear strength of soil (Poulos, 1989; Nishimura and Fredlund,

1999; Sridharan and Prakash, 1999). It was found out that the shear strength characteristics ofsandy soil are affected by textural and grain size characteristics (Charles, 1992) and soil

plasticity (Lambe and Whitman, 1979). When the soil is loaded to failure without pore water

dissipation (i.e. drainage is prevented) the shear strength obtained is referred to as undrained

shear strength (Su) otherwise drained shear strength is obtained. The unconfined compressive

strength (UCS) of soil is usually measured in the laboratory by the Unconfined Compressive

Test (UCT) and it is related to the undrained shear strength by Equation 2.5.

Su=UCS

2 (2.5)

Soil strength and stiffness behaviour are related to the range of plastic

consistency. The consistency of most soils in the ground will be plastic or semi-solid. The

shear strength and unconfined compressive strength of soil are related to the consistency of
http://en.wikipedia.org/wiki/Mineralogyhttp://en.wikipedia.org/wiki/Mineralogy


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the soil as shown in Tables 2.5 and 2.6. The tables show that the harder the soil the higher the

value of the shear strength and the UCS.

Table 2.3: General Requirements for Subgrade, Sub-base and Base Course in Nigeria

Subgrade Sub-base Base courseProportion

passing BS

sieve No. 200

(Amount of

fines, %)

35 35 35

Liquid Limit

(%)

80 35 35

Plasticity index

(%)

55 12 12%

Soaked CBR

(24hrs.)

NA 30% 80

Relative

compaction

(%)

100 100 100

Source: Federal Republic of Nigeria highway manual (1992)

Materials and MethodsSamples of lateritic soil were collected from three selected lateritic soil deposits (one onMokuro road and two on Ede road in IleIfe) with descriptions as given in Table 1.

Classification and identification tests which include natural moisture content (w),specific gravity (G), sieve analysis, hydrometer analysis of particles passing sieve No.200, atterberg limits tests (plastic and liquid limit) of particles passing sieve size 425 m

were carried out on the soil samples in their natural states.Laboratory compaction tests using standard proctor method, Unconfined Compressive

Strength (UCS) test, California bearing ratio (CBR) test were also carried out on the soil

samples both in their natural states and after reconstitution.

The fines contents were separated from the coarse contents by soaking the soil samples

in water containing 4% sodium hexametaphosphate, a dispersing agent (commercially namedCalgon) in the laboratory for between 12 and 24 hours. The soil was then washed through

sieve No. 200 with 75 m opening. The soil passing 75 m sieve size was oven dried and

referred to as 100% fines. The soil sample retained on sieve 75 m opening was also ovendried and referred to as 100% coarse. In order to avoid non homogeneity of specimen, it wasensured that the fines content were thoroughly mixed together before oven drying and after

pulverization according to Lade and Yamamuro (1997).

The pulverized fines and the coarse fractions were added together in varying ratios (fines:coarse) from 10:100 to 100:0 in 10% increment. The ratio started with 10: 100 and not 0:100

because, laboratory compaction test could not be carried out on the sample containing 0%fines (i.e. 100% coarse) and thus cohesionless (put source). This is because the process of

lubrication which aids compaction is limited to soils containing fines and cohesionless soilsare compacted or densified by vibration and not by impact which laboratory compaction

utilizes.


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Results and Discussions

Table 4.2 gives the summary of the results of preliminary tests on the three soil

samples. Based on these results, the AASHTO classifications and the group indices of the

samples indicate that the rating of the samples as subgrade material is fair to poor for samples

ER1 and ER2 and good to excellent for sample MR according to source .

The values of the specific gravities conform to the specific gravities of lateritic soils whichare usually between 2.6 and 3.4 (De Graft-Johnson and Bhatia, 1969).

Table 4.2: Index Properties of the Soil Samples

MR ER1 ER2

Natural Moisture Content (%) 16.23 18.15 20.64

Specific Gravity (GS) 2.60 2.88 2.69

Liquid Limit LL (%) 38 39 50

Plastic Limit PL (%) 20 24 29

Plasticity Index PI (%) 18 15 21

Percentage passing sieve

No. 200 (Fines content) 32.60 39.90 48.10% clay sized particles 10 9 27

% silt sized particles 4 11 10

AASHTO Classification A-2-6 A-6 A-7-5

USCS Classification CL ML or OL OH or MH

Colour Reddish brown Brown Yellowish brown

Group Index 1 3 7

Effect of Fines Content on the Compaction Characteristics of the Soil Samples.The summary of the compaction characteristics of the soil samples in their natural states are

presented in Table 4.3. The compaction curve with the zero air void (ZAV) curve is also

shown in Figure 4.3. The compaction curves indicate that sample MR exhibits bestcompaction characteristics i.e. it has the highest Maximum Dry Density (MDD) and lowestOptimum Moisture Content (OMC), while sample ER2 has the lowest MDD value and

highest OMC value.These results imply that when subjected to the same compaction method (i.e. same

compactive effort and number of passes) on the field, sample MR would have the highest drydensity while sample ER2 would have the lowest dry density.

4.3.1 Correlations between the optimum moisture content and the fines content

The summary of the result of compaction tests on the different percentage of fines to coarse

content are given in Table 4.4. The OMC increases with increasing fines content which

agrees with the findings of Bloomfield and Jermy (2003) for all the soil samples. Theincrements in OMC are more pronounced in sample ER2 with OMC of 10% at 10% fines and

OMC of 40.5% at 100% fines (42.5% increment). The high plasticity of sample ER2 explains

the more pronounced increments in OMC when compared to any of the other two samples

(Raymond, 1997). The results show that sample ER2 has the strongest affinity for water and

that the lowest OMC of sample MR (Table 4.3) in its natural state is due to the fact that it

possesses the lowest fines content (32.6%) while the highest OMC in sample ER2 is due to

the fact that it possesses the highest fines content (48.1%).

The regular increase in OMC with increase in fines content is shown in Figure 4.4. A

linear representation of the data is used rather than using a polynomial which gives a better

coefficient of determination (R2) value, because most correlation of compaction properties

are done linearly in literature e.g. Croft, (1968). Regression analyses of the data giveequations 4.3 - 4.6. Equations 4.3 - 4.5 represent the relationship between the OMC and fines


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Figure 4.3: Compaction curves of soil samples in their natural states

content for samples MR, ER1 and ER2 respectively.The R

2values obtained from linear regression are as shown on Figure 4.4 while the

correlation coefficient (r) are 0.996, 0.981 and 0.967 for samples MR, ER1 and ER2

respectively. Correlation coefficient of the three data sets obtained from multiple regressionsis 0.946. Based on the R2 values, the models generated (Equations 4.3 - 4.5) give good

representations of the relationship between the OMC and the fines content. The generalequation which is the addition of Equations 4.3, 4.4 and 4.5 is given in Equation 4.6

y = 0.228x + 7.333 (4.3)

y = 0.232x + 8.006 (4.4)

y = 0.329x + 4.406 (4.5)

OMC = 0.253f + 6.866 (4.6)

f is fines content in %

Table 4.3: Compaction Parameters of the Soil Samples in their Natural States

Compaction Parameters MR ER1 ER2

Maximum dry Density, MDD (Mg/m ) 1.95 1.83 1.76

Optimum Moisture Content, OMC (%) 16.5 18.0 20.2

Table 4.4: OMC of the Samples at Different Fines Contents

Fines

Content

(%)

Sample

MR ER1 ER2

OMC* MDD** OMC* MDD** OMC* MDD**

10 10.0 2.02 12.0 2.12 10.0 2.07

20 12.0 1.95 12.5 2.06 12.0 1.9930 14.0 1.94 15.0 2.00 14.2 1.93

40 17.0 1.90 16.8 1.84 17.8 1.7950 18.5 1.89 17.0 1.82 20.5 1.73

60 19.5 1.87 20.5 1.67 20.4 1.6370 23.5 1.84 26.0 1.61 22.8 1.53

80 26.0 1.73 28.1 1.56 30.0 1.4490 28.0 1.70 28.8 1.51 37.0 1.37

100 30.5 1.62 31.2 1.38 40.5 1.19* OMC in % ** MDD in Mg/m

3

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2

2.1

0 5 10 15 20 25

MDD(Mg/m

3)

Water content (%)

Sample ER2

Sample MR

zero air void line

Sample ER1


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Bloomfield and Jermy (2003) employed coastal sand, whereas this study employs lateritic

soil samples which have more tendency of progressive breakdown of particles under the

impact of rammer, thereby making workability of soils easier (Gidigasu, 1976). The

progressive breakdown of particles rules out the effect of fines filling the voids between

coarser particles.

Linear regression analyses of the MDD data give r

values of -0.967, -0.993 and -0.996for samples MR, ER1, and ER2 respectively. The r values (which are very close to -1),

indicate that equations 4.7 - 4.9 give good correlations between the fines content and the

MDD. Equations 4.7 - 4.9 give the relationship between the MDD and the fines content for

samples MR, ER1, and ER2 respectively. The correlation coefficient (r) of the three data sets

through multiple regressions is -0.937 and the general equation of line of best fit through

regression is given in equation 4.10.

y = -0.004x + 2.066 (4.7)

y = -0.008x + 2.209 (4.8)

y = -0.009x + 2.187 (4.9)

MDD = -0.007f + 2.152 (4.10)

4.3.3 Correlation between the MDD and OMC

Correlations between the Maximum Dry Density (MDD) and the Optimum Moisture Content(OMC) for the three soil samples are shown in Figure 4.6, The relationships between the two

parameters are also shown graphically in Figure 4.6. Multiple regression analysis of the datagives an r value of -0.94 and a general equation given in Equation 4.11.

MDD = 2.312 - 0.026 OMC (4.11)

Figure 4.6: Relationships between MDD and OMC of the soil samples

Equation 4.12 (which is similar to Equation 4.11) was obtained by Acroyd

(1963), who determined the relationships between the OMC and MDD of some tropical soils.

These results show that a good correlation exists between the OMC and MDD of tropical

soils.

MDD = 2.56 0.0445 OMC (4.12)

y = -0.0271x + 2.2762

R = 0.9428

y = -0.034x + 2.4648

R = 0.9506

y = -0.0176x + 2.1961

R = 0.9509

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2

2.1

1 6 11 16 21 26 31 36 41

MDD(Mg/m3)

OMC (%)

Sample ER2

Sample ER1

Sample MR


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4.4 Effects of Fines Content on the Engineering Properties of the Soil Samples

The results from CBR and UCS tests are summarised in Table 4.6. These results show that

sample MR has a higher CBR value of 12%, than either of samples ER1 and ER2 which have

same CBR value of 5%. The subgrade strength of sample MR is good while that of samples

ER1 and ER2 is normal (source). This shows that the CBR values of the soil samples would

have to be improved before they can be used as sub-base materials.Table 4.6 also shows that sample MR has the highest Unconfined Compressive

strength (UCS) of 102kN/m2, while the UCS of sample ER1 is 63kN/m

2and sample ER2 has

the lowest UCS of 58kN/m2.

Table 4.6: Engineering Properties of the Soil Samples in their Natural States

Engineering Property MR ER1 ER2

California Bearing Ratio,

CBR (%)

12 5 5

Unconfined CompressiveStrength, UCS (kN/m2)

102 63 58

4.4.1 Correlations between the California bearing ratio and the fines content

Table 4.7 gives the results of both soaked CBR (CBRs) and Unsoaked CBR (CBRu) tests of

the soil samples. The results of the CBRu are further presented graphically in Figure 4.9. It

can be observed from the results that both CBRu and CBRs decrease with increase in fines

content for all the samples. These results agree with the findings of Curtis et al. (2004) which

indicate that increased fines content and moisture reduced the mechanical behaviour of

granular materials. The effect is however more pronounced in the CBRs.At 10% fines content, sample ER2 has a higher CBRu (64%) than sample ER1 (30%) despite

the fact that both samples have a CBR of 5% in their natural states. The higher CBRu in ER2

is probably due to the nature of the coarser particles i.e. the coarser particles in ER2 have

more strength than that of ER1 (Acroyd, 1963). There is a 64%, 51% and 37% decrease in the

CBRu from 10% to 20% fines and 56%, 55% and 37% decrease from 20% to 30% fines for

samples ER2, MR and ER1 respectively. This result shows that the effect of fines on the

CBRu is more pronounced in samples ER2 and MR. the values of the CBRu of sample MR

are consistently higher than any of corresponding CBRu of samples ER1 and ER2 as shown

in Figure 4.9. The CBRu of sample ER2 tends to zero from 40% fines content, while that ofER1 and MR tends to zero from 70% fines. This shows that the fines content of sample ER2

has more affinity for water which is also reflected in its highest PI. Sample ER2 has moreaffinity for water because it contains the highest amount of clay sized particles (Table 4.2).

The CBRu for each of the samples at 40% fines was almost zero. The percentage loss in CBRdue to soaking is also given in Table 4.7. Effect of soaking is more pronounced in sample

ER1; this could be due to the fact that water has a significant effect on the coarser particlewhich is reflected to be the weakest among the three samples. The results also show that there

is little loss in CBR for sample ER2 at 10% fines, while samples MR and ER1 have 23% and27% loss respectively. This implies that even though the fines content of sample ER2 has

more affinity for water, the strength of the coarser contents outweighs the effect of water onthe fines content. However at 20% fines, the effect of soaking on ER2 reflects the nature of

its fines content. The percentage loss in CBR due to soaking is more pronounced in sampleMR from 40% fines. Sample MR can be said to have coarse particles of high strength and

fines content of moderate affinity for water.


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Table 4.7: Soaked and Unsoaked CBR of the Samples at Different Fines Contents

Fines

Content(%)MR

Unsoaked Soaked

% loss in

CBR (%)ER1

Unsoaked Soaked

% loss in

CBR (%)

ER2

Unsoaked Soaked

% loss in

CBR (%)

10 85 65 23 30 22 27 64 57 8

20 42 30 29 19 7 63 23 9 57

30 19 13 32 12 3 75 10 6 25

40 10 4 60 9 1 89 5 1 67

50 8 2 75 8 0 100 3 0 100

60 5 0 100 7 0 100 3 0 100

70 3 0 100 3 0 100 2 0 100

80 3 0 100 3 0 100 2 0 100

90 2 0 100 2 0 100 2 0 100

100 2 0 100 2 0 100 2 0 100


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Non-linear regression analysis of the data produces equations 4.13 - 4.15, with R2 values

0.9854, 0.9814 and 0.9616 for samples MR, ER1 and ER2 respectively. Equation 4.16 is the

general equation for the three soil samples. The r value obtained from multiple regressions of

the three sets of data is 0.9096.

y = -0.0004x3+ 0.0866x2- 5.8798x + 132.2333 (4.13)

y = -0.0001x3

+ 0.0183x2

- 1.4044x + 41.3333 (4.14)y = -0.0004x3+ 0.0768x2- 4.9412x + 101.4333 (4.15)

CBR = -0.0004f3+ 0.0759f

2- 4.6629f + 97.4206 (4.16)

Figure 4.9: Relationship between the CBR and the fines content

4.4.2 Correlations between the unconfined compressive strength and the fines contentThe results of the UCS show a deviation from the norm when compared to those of other

engineering parameters results. These results are shown in Table 4.8 and Figure 4.10. The

UCS increases with increasing fines content to a certain point after which it starts decreasing.

This is because increase in fines content causes increase in the cohesion and therefore the

bonding of the soil increases, thus increasing the UCS (Alao, 1983). However, as the fines

content increases the water content of the soil increases, causing a decrease in the UCS values

after peak strength is reached due to the adverse effect of water on the bonding forces

between particles. Nishimura and Fredlund (1999) found that the unconfined compressive

strength is a

y = -0.0004x3+ 0.0866x2- 5.8798x + 132.2333

R = 0.9854

y = -0.0001x3+ 0.0183x2- 1.4044x + 41.3333

R = 0.9814

y = -0.0004x3+ 0.0768x2- 4.9412x + 101.4333

R = 0.9616

-10

0

10

20

30

40

50

60

70

80

90

10 20 30 40 50 60 70 80 90 100

CBR(%)

Fines content (%)

Sample MR

Sample ER1

Sample ER2

General


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Table 4.8: UCS of Soil Samples at Different Fines Contents

Fines Content (%) SampleMR ER1 ER2

UCS (kN/m )

10 15 12 10

20 25 44 19

30 65 48 53

40 79 51 18

50 95 81 63

60 85 144 26

70 110 43 174

80 95 48 139

90 30 26 20

100 2 2 2


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function of the water content in the void of the soil. This explains why ER2 at same

fines content (70%) with sample MR has a higher UCS because at 70% fines OMC of ER2 is

22.8% while that of MR is 23.5%. The optimum result is obtained at between

50% and 80% fines content for each of the soil samples.

The results were almost zero at 10% and 100% fines. These can also be explained when one

considers the general equation for determining the shear strength of soil as given in Equation2.2. As fines content tends to zero, the shear strength tends totan, while as the fines

content tends to 100% the shear strength tends to C. Soil with almost 50% fines has the two

components of shear strength present (i.e. C and ) thus the higher value of the shearstrength. The correlations of UCS for each soil sample are given in Equations 4.17 - 4.19.

The R2values are 0.917, 0.602 and

0.523 for samples MR, ER1 and ER2 respectively. The regression is not helpful in predicting

a Y value because of the low values of the R2especially for samples ER1 and ER2, thus a

general equation cannot be obtained from the sets of data.

y = -0.000x3+ 0.033x2+ 1.531x - 6.066 (4.17)

y = -0.000x3- 0.018x

2+ 3.285x - 20.76 (4.18)

y = -0.001x3+ 0.211x2- 6.918x + 73.9 (4.19)

4.5 Establishment of the optimum fines content

The variations of soil parameters for each soil samples MR, ER1 and ER2 are given inTables 4.11, 4.12 and 4.13, while graphical representations on a logarithmic scale are

presented in Figures 4.11, 4.12 and 4.13 respectively. The figures show that the soilproperties reduce as the fines content increase, except for the UCS for which a model cannot

be generated. Though the optimum result for the UCS is obtained at between 60% and 80%fines content, the result cannot be used because at these fines

Documents

Effect of Fines Content on Some Engineering Properties of Lateritic Soil in Ile-libre