Journal of Engineering Research, Vol. 14, No. l , March 2009. A.L. Ayodele, FA. Falade andM. O. Ogedengbe

EFFECTS OF FIl't~S CONTENT ON SOME ENGINEERING PROPERTIES OF LATERITESOILS IN ILE-IFE, NIGERIA

By

A. L. AYODELE*, F.A. FALADE** and M. O. OGEDENGBE*

"Department of Civil Engineering. Obafemi Awolowo University. Ile-Ife, Nigeria.

**Department of Civil and Environmental Engineering. University of Lagos. Lagos. Nigeria

ABSTRACTOne of the factors which affect road failure (which is a common feature of the tropical environment) isthe soil used as sub-base material. Soils (usually obtained from borrow pits) used as sub-base materia!contain a certain amount of particles passing sieve si:e 7 urn which is referred to as fines (silt and elm).This work studied the effect of varying fines content on the engineering properties of selected soilsmples. Lateritic soil samples were collected from three selected borrow pits ill Ile-Ife, the samples wereseparated into fines and coarse content by wet sieving through sieve size 75Jlm. Laboratory indexproperties. compaction and California Bearing Ratio (CBR) tests revealed that the soil samples werenot suitable as sub-base material in their natura! states. but Oil reconstituting the fines and coarsecontents together at different ratios. it was observed that the engineering properties of the reconstitutedsoils increase as the fines content reduce. Regression analysis showed linear relationship with thecompaction characteristics and non linear relationship with the CBR. The study showed that the natureof coarse content and the fraction of fines present are interdependent and significant factors in lateriticsoil for use as sub-base material in road construction.

Keywords: Fines content. CBR. Sub-base. and Road Construction.

1.0 INTRODUCTIONSoil with particle size smaller than 75 urn, isreferred to as fines according to the Unified SoilClassification System ASTM, (2000) andAmerican Association of State Highway andTransportation Officials AASHTO, (1986)classification systems. The level of fines contentin any soil has been found to affect importantproperties of the soil including soil composition,particle friction, compaction, moisture and typeof soil Hveern, (2000).These properties in turn affect the performanceof the soil when used as a sub-base materialalthough the actual effects vary from soilsample to sample. The fines content in soil alsoplays an important role in phase problems

including minimum and maximum void ratios andporosity Lade et al. (1998). Fines have also beenfound to affect liquefaction potential,Compressional characteristics and stress strainbehaviour of soil Georgiannou et al, (1990);Salgado et al, (2000); Naeini and Baziar, (2004);Cabalar, (2008). Tatlisoz et al (1997) studied theeffect of fines on mechanical properties of soi l-tyrechip mixtures and found that the fines havesignificant effect on the mechanical properties ofthe soil-tyre mixture.Falade (l991) established that the differences instrength values between laterite fines collectedfrom nine difference sources were statisticallyinsignificant at 5% level irrespective of the locationfrom which the samples were procured.

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Journal of Engineering Research, Vol. 14, No.1, March 2009. A.L. Ayodele, FA. Falade andM.O.Ogedengbe

Soil chosen for a particular road work must besuitable for the environment and must have,enough strength to bear the load the road isintended for. The strength of the soil isexpressed in terms of the California BearingRatio (CBR). The soaked 'CBR (CBRs) isusually obtained for a sub-base material in thelaboratory, by soaking the compacted soilsample in water. This is because water has beenfound to contribute to the reduction of strengthof lateritic soil insitu (Ampadu, 2007). TheAtterberg limits (liquid limit and plasticityindex) are also considered along the CBR. Thestandard specifications employed depend on thecountry and region, Table 1 gives therequirements in Nigeria. The most common soiltype in use for the construction of road in thetropics is lateritic soil because they are the mostcommon naturally occurring materials, .and inthe tropics weathering is intense, and hencethere is lack of good quality crushed aggregates(Makasa, 2007)

2.0 MATERIALS AND METHODSThe lateritic soil samples for this study areborrow materials for the construction of stateroads in Ile-Ife, Osun State, Nigeria. Table 2gives the general description of the soil samplesincluding, the co-ordinates andelevationsheights relative to mean sea levelobtained from GeographicaJ Positioning System(GPS) and the approximate estimated areas ofthe borrow pits. As shown in Table 2, samplescollected from Ede Road are referred to as ERIand ER2 while the sample collected fromMokuro Road is termed MR.Classification and identification tests whichinclude natural and moisture include naturalmoisture content (w),Table 1: General Requirements for Subgrade,Sub-base and Base Course in Nigeria

Subgrade Sub Base- coursebase

Fines content(%) J35 035 J35Liquid Limit 080 J35 035(%)Plasticity 055 ~12 J12% .index (%)Soaked CBR NA J 080(24hrs.) 30%Relative 0100 0 J100compaction 100(%)

Source: Federal Republic of Nigeria highwaymanual (1992)

Table2: Description of Soil Samples from SelectedBorrow Pits

Soil Sample I MR ERI ER2IdentificationGeographi Mokuro Ede Ede Roadc Road Road

Latitu 7°30.133' 7u30.851 7°31.208'de ,Loca

G Longit 004u35.66 004u39.3tion 004°29.100'P ude 2' 84'S Elevat

IOn 326 314 316(m)

Approximate 28,800 21,600 23,200Area (m')

specific gravity (G), sieve analysis, hydrometeranalysis of particles passing sieve No. 200,Atterberg limits tests (plastic and liquid limit) ofparticles passing sieve size 42511IDwere carried outon the soil samples in their natural states.Laboratory compaction tests using standard proctormethod, Unconfined Compressive Strength (UCS)test, California bearing ratio (CBR) test were alsocarried out on the soil samples both in their naturalstates and after reconstitution. The fines contentswere separated from the coarse contents by soakingthe soil samples in water containing 4% sodiumhexametaphosphate, a dispersing agent

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Journal of Engineering Research, Vol. 1-1,No.1, March 20()9. A.L Ayodele. F.A. Falade andM.O. Ogedengbe

(commercially named Calgon) in the laboratoryfor between 12 and 24 hours. The soil was thenwashed through sieve No. 200 with 75f.-lmopening. The soil passing 75f.-lm sieve size wasoven dried and referred to as lOO% fines. Thesoil sample retained on sieve 75pm opening wasalso oven dried and referred to as lOO% coarse.In order to avoid non homogenei y of specimen.it was ensured that the fines content werethoroughly mixed together before oven dryingand after pulverization according to Lade andYamarnuro (1997).The pulverized fines and the coarse fractionswere 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: 100because, laboratory compaction test could notbe carried out on the sample containing 0%fines (i.e. 100% coarse) and thus purelycohesion less. This is because the process oflubrication which aids compaction is limited tosoils containing fines and cohesionless soils arecompacted or densified by vibration and not byimpact which laboratory compaction utilizes.

3.0 RESULTS AND DISCUSSIONTable 3 gives the summary of the results ofpreliminary tests on the three soil samples aresummarized in Table 4.2. Based on theseresults, the AASHTO classifications and thegroup indices of the samples indicate that therating of the samples as subgrade material is fairto poor for samples ER1 and ER2 and good toexcellent for sample MR. The values of thespecific gravities conform to the specificzravities of lateritic soils which are usuallyo

between 2.6 and 3.4 (De Graft-Johnson andBhatia, 1969).

if' 1 S '[ STable 3: Index Properties 0 I ie 01 amp es! MR ERI ER:2 I

i Natural Moisture 116.:23 I 18.15 20.6-1-I

i IContent (0/,..)

I 2.60Specific Gravrty (G<;) I 2.88 2.6~Liquid Limit LL ('Ie) 38 39 SOPla~tIc Limn PL ((i; ) 20 I 2-1- 20 iPlasncitv Index PI (0/0) IS IS 21 I

J

, Percentage passing ,I 39.90 /48.10

;ieve 32.60 I

No. 200 (Fines content) i(t, clay sized particles 10 0 27 I

(j( silt sized particles 4 II 10 IAASHTO Classification A-2-6 A-6 A-7-S IUSCS Classification CL MLor OHar I

OL ME i

Colour [Red Brown Yell~wish I

Idish

brownbrown

3.1 Effect of Fines Content on theCompaction Characteristics of the Soil Samples.The summary of the compaction characteristics ofthe soil samples 111 their natural states are presentedin Table 4.

Table=l: Compaction parameters of [he sodsamples ill their natural states,

Compaction MR ERI ER2ParametersMaximum dry 1.95 1.83 1.76

IDensity, MOD I

(Mg/rrr')Optimum Moisture 16.5 18.0 20.2Content, OMC (%)

The compaction curve WIth the zero air void(ZA V) curve is also shown in Figure 1. Thecompaction curves indicate that sample MRexhibits best compaction characteristics i.e. it hasthe highest Maximum Dry Density (MOD) andlowest Optimum Moisture Content (OMC), whilesample ER2 has the lowest MOD value and highestOMC value.These results imply' that when subjected to thesame compaction method (i.e. same cornpactiveeffort and number of passes) on the field, sample\-1,R would have the highest dry density whilesample ER2 would have the lowest dry density.

12

Journal of Engineering Research, Vol. 14, No.1, March 2009. A.L. Ayodele, F.A. Falade andM.O. Ogedengbe

2.1 '

1.1} "

'"E 1.8-<"~2 1.7

g l~ ~2 1.5 ~

1.4

1.3 .• , .._._._,._-_ ..__ .__ .'.- ..

o 10 j) 20 2)

-[i.'10 air \'010 hnc

WJter content 1%)

Figure 1: Compaction curves of soil samples intheir natural states

3.1.1 Correlations between the OptimumMoisture Content and the Fines ContentThe summary of the result of compaction testson the different percentage of fines to coarsecontent are given in Table 5. The OMCincreases with increasing fines content whichagrees with the findings of Bloomfield andJermy (2003) for all the soil samples.

Table 5: OMC and MDD of the Samples at DifferentFines Contents

f Sample("fr') MR ERI ER2

OMC MDD OMC MDD OMC MDD10 10.0 2.02 12.0 2.12 10.0 2.0720 12.0 1.95 12.5 2.06 12.0 1.9930 14.0 1.94 15.0 2.00 14.2 1.9340 17.0 1.90 16.8 1.84 17.8 1.7950 18.5 1.89 17.0 1.82 20.5 1.7360 19.5 1.87 20.5 1.67 20A 1.6370 23.5 1.84 26.0 1.61 22.8 1.5380 26.0 1.73 28.1 1.56 30.0 1.4490 zs.o 1.70 28.8 1.51 :n.O U7100 30.5 1.62 31.2 1.38 40.5 1.19.. ,OMC IS 111'1" MDD IS III Mg/m

The increments in OMC are more pronouncedin sample ER2 with OMC of 10% at 10% finesand OMC of 40.YYr, at 100% fines (42.5%increment). The high plasticity 01" sample ER2explains the more pronounced increments inOM(' when compared to any 01" the other twosamples (Raymond, 1(97). The results showIhal sample ER2 h.rx the strongest affinity for

water and that the lowest OMC of sample MR(Table 4) in its natural state is due to the fact that itpossesses the lowest fines content (32.6%) whilethe highest OMC in sample ER2 is due to the factthat it possesses the highest fines content (48.1 %).The regular increase in OMC with increase in finescontent is shown in Figure 2. A linearrepresentation of the data is used rather than usinga polynomial which gives a better coefficient ofdetermination (R2) value, because most correlationof compaction properties are done linearly inliterature e.g. Croft, (1968). Regression analyses ofthe data give equations 4.3 - 4.6 for samples MR,ER1 and ER2 respectively.

45

40

35

~O'-'r.J5

~O

y = 0.232x + 8.006R2=0.962

y = 0.228x + 7.333R2= 0.992

15y = 0.329x + 4A06

R2= 0.9355

10 20 30 40 50 60 70 80 90 100

Fines Content (%)

• Sample MR • Sample ER I •. Sample ER2 x General

Figure 2: Relationship between OMC and finescontent

The R2 values obtained from linear regression areas shown on Figure 2 while the correlationcoefficient (r) are 0.996, 0.981 and 0.967 forsamples MR, ER 1 and ER2 respectively.Correlation coefficient of the three data setsobtained from multiple regressions is 0.946. Based., .on the W values, the models generated (Equations1 - 3) give good representations of the relationshipbetween the OMC and the fines content. The lineof best fit through regression is given in Equation4.y = 0.228x + 7.333 (I)Y= O.232x + 8.006 (2)

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Journal of Engineering Research, Vol. 14, No. I, March 2009. A.L. Ayodele, FA. Falade andM.a. Ogedengbe

y = 0.329x + 4.406OMC = O.2S3f + 6.866f is fines content in %

(3)(4)

3.1.2 Correlations between the MaximumDry Density and the Fines ContentThe variations in MOO with fines content aresummarized in Table 5, while graphicalrepresentation of the data set is given in Figure3. It can be observed from the figure that theMOO generally reduces as the fines contentincreases. The changes in the MOO values aremore pronounced in samples ER I and ER2.

22 1

2.12-. 1.9

~ 1.8

6 1.7

01.6

0 1.5~ 1.4

1.31.21.1

10 20 30 40 50

y = -0.004x + 2.066R2 = 0.9.35

60 70 80 90 100

Fines content (%)

.Sample MR -Sample ERI -"'Sample ER2 X General

Figure 3: Relationship between the optimummoisture content and fines content

Figure 3 also shows that the values droppedsteadily with increase in fines content from avalue of 2.02Mg/m3 and 2.07Mg/IlY' for 10%fines to 1.62Mg/m3 and 1.19Mg/m' at 100(};,fines for samples ERI and ER2 respectively. Itis inferred from this that the changes in finescontent have more effect on the two samples.Sample MR's MOOs change rather gently asseen in Figure 3.This result is however, contrary to that obtainedby Bloomfield and Jermy (2003) who showedthat the MOD increased with increase in finescontent from lor;;, fines content to 1 ()l}{, fincscontent before it started reducing based on thefact that as the fines content increases the gapsbetween the sand grains arc filled, until ;1 point

where the percentage of fines begins to push thesand grains apart. These opposing results can heattributed to the type of samples used in bothstudies. Bloomfield and Jerrny (2003) employedcoastal sand, whereas this study employs lateriticsoil samples which have more tendency ofprogressive breakdown of panicles under theimpact of the rarnmer, thereby making workabilityof soils easier (Gidigasu, 1976). The progressivebreakdown of particles rules out the effect of fi ncsfilling the voids between coarser particles.Linear regression analyses of the MOD data giveequation 5 with r =-0.967. equation 6 with r = -0.993 and equation 7 with r =-0.996 for samplesMR. ER 1. and ER2 respectively. The r values(which are very close to -I). indicate that equationsgive good correlations between the fines contentand the MOD. The correlation coefficient (r) of thethree data sets through multiple regressions is -0.917 and the general equation of line of best fitthrough regression is given in equation 4.10.y = -0.004x + 2.066 (5)y = -0.008x + 2.209 (6)

_ Y = -OJ)09x + 2.187 (7)MOD = -0.0071" + 2.152 on3.1.3 Correlation between the MDD and OMCCorrelations between the Maximum Dry Density(MOD) and the Optimum Moisture Content(OMe) for the threesoil samples are shown in Figure 4. Therelationships between the two parameters arc alsoshown graphically in Figure 4. Multiple regressionanalysis of the data gives <111 r value of -0.94 and ageneral equation given ill Equation 4.11.

MDJ) = 2.312 - 0.026 OMC (9)Equation 10 (which is similar to Equation 9) wasobtained by Ackroyd (IW»)), who determined therelationships between the OMC and MDJ) of sometropical soils. These results show th.u a goodcorrelation exists between the OMC .uu] MI)J) oftropical soi Is.MDO = 2.56 - (U)445 OMC ( IOj

]11

Journal of Engineering Research, Vol. 14, No.1, March 2009. A.L. Ayodele, F.A. Falade andM.O.Ogedengbe

L;

- 1.5

'"~ J 7<,oc~ J6c 1)0s 1;:

Ij

12

1.1

;. .I '.

" 1 ,,', \ .'". .,

\,. .A~y: {J.034x t 2.464

R': 0.950 't• ISJi1lpi('MP.

y: ·0.027!· 2 n:p,:: 0.942

y: {J,017x t 2.196•RJ = 0.950

11 16 21 26 31 36 •

OMC(%JFigure 4: Relationships between MDD and

OMC of the soil samples

3.2 Effects of Fines Content on theEngineering Properties of the Soil SamplesThe results from CBR and UCS tests aresummarised in Table 6. These results show thatsample MR has a higher CBR value of 12%,than either of samples ER 1 and ER2 which havesame CBR value of 5%. The subgrade strengthof sample MR is good while that of samplesERI and ER2 is normal (source). This showsthat the CBR values of the soil samples wouldhave to be improved before they can be used assub-base materials.

Table 6:S I

Engineering Properties of the Soilh . N l Samptes 111 t eir atura tares

Engineering Property MR ERI ER2California Bearing Ratio, CBR 12 5 5(%)Unconfined Compressive Strength, 102 63 58UCS (kN/m2

)

Table 6 also shows that sample MR has thehighest Unconfined Compressive Strength(UCS) of 102kN/m2,while the UCS of sampleER I is 63kN/m2 and sample ER2 has the lowestUCS of 58kN/m2

.

3.2.1 Correlations between the CaliforniaBearing Ratio and the Fines ContentTable 7 gives the results of both soaked CBR(CBRs) and Un soaked CBR (CBRu) tests of thesoil samples. The results of the CBRu are furtherpresented graphically in Figure 5. It can beobserved from the results that both CBRu andCBRs decrease with increase in fines content forall the samples.

Figure 5: Relationship between the CBR and thefines content

These results agree with the findings of Curtis et al.(2004) which indicate that increased fines contentand moisture reduced the mechanical behaviour ofgranular materials. The effect is however morepronounced in the CBRs.At 10% fines content, sample ER2 has a higherCBRu (64%) than sample ERI (30%) despite thefact that both samples have a CBR of 5% in theirnatural states. The higher CBRu in ER2 is probablydue to the nature of the coarser particles i.e. thecoarser particles in ER2 have more strength thanthat of ERI (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 ER Irespectively. This result shows that the effect offines on the CBRu is more pronounced in samples

Journal of Engineering Research, Vol. 14, No.1, March 2009. A.L. Ayodele, F.A. Falade andM.O. Ogedengbe

ER2 and MR. the values of the CBRu of sampleMR are consistently higher than any ofcorresponding CBRu of samples ERI and ER2as shown in Figure 4.9. The CBRu of sampleER2 tends to zero from 40% fines content,while that of ERI and MR tends to zero from70% fines. This shows that the fines content ofsample ER2 has more affinity for water which isalso reflected in its highest PI. Sample ER2 hasmore affinity for water because it contains thehighest amount of clay sized particles (Table 3).The CBRu for each of the samples at 40% fineswas almost zero. The percentage loss in CBRdue to soaking is also given in Table 7. Theeffect of soaking is more pronounced in sampleER 1; this could be due to the fact that water hasa significant effect on the coarser particle whichis reflected to be the weakest among the threesamples. The results also show that there is littleloss in CBR for sample ER2 at 10% fines, whilesamples MR and ERI have 23% and 27% lossrespectively. This implies that even though thefines content of sample ER2 has more affinityfor water, the strength of the coarser contentsoutweighs the effect of water on the finescontent. However at 20% fines, the effect ofsoaking on ER2 reflects the nature of its finescontent. The percentage loss in CBR due tosoaking is more pronounced in sample MR from40% fines. Sample MR can be said to havecoarse particles of high strength and finescontent of moderate affinity for water.

on-linear regression analysis of the data producesequations 11 - 14, with R2 values 0.9854, 0.9814and 0.9616 for samples MR, ERI and ER2respectively. Equation 14 is the general equationfor the three soil samples. The r value obtainedfrom multiple regressions of the three sets of datais 0.9096.y = -0.0004x3 + 0.0866x2 - 5.8798x + 132.2333(11)Y = -0.0001x3 + 0.0183x2 - 1.4044x + 41.3333(12)y = -0.0004x3 + 0.0768x2 - 4.9412x + 101.433(13)CBR = -0.0004e + 0.0759f2

- 4.6629f + 97.4206(14)

3.2.2 Correlations between the UnconfinedCompressive Strength and the Fines ContentThe results of the UCS show a deviation from thenorm when compared to those of other engineeringparameters' results. These results are shown inTable 8 and Figure 6. The UCS increases withincreasing fines content to a certain point afterwhich it starts decreasing. This is because increasein fines content causes increase in the cohesion andtherefore the bonding of the soil increases, thusincreasing the UCS (Alao, 1983). However, as thefines content increases the water content of the soilincreases, causing a decrease in the UCS valuesafter peak strength is reached due to the adverseeffect of water on the bonding forces betweenparticles.

H;

Journal of Engineering Research, Vol. 14, No.1, March 2009. A.L. Ayodele, F.A. Falade andM.O. Ogedengbe

t. bl 7 S k d d U k d CBR if h S I Diffi Ca e oa e an nsoa e o t e amptes at l erent znes ontentsFines MR ERI ER2

Content(%)Unsoaked Soaked lossin Unsoaked Soake lossin Unsoaked Soaked % loss

CBR d CBR inCBR(%) (%) (%)

10 85 65 23 30 22 27 64 57 820 42 30 29 19 7 63 23 9 5730 19 13 32 12 3 75 10 6 2540 10 4 60 9 1 89 5 1 6750 8 2 75 8 0 100 3 0 10060 5 0 100 7 0 100 3 0 10070 3 0 100 3 0 100 2 0 10080 3 0 100 3 0 100 2 0 10090 2 0 100 2 0 100 2 0 100100 2 0 100 2 0 100 2 0 100

Table 8: UCS of Soil Samples at DifferentFinesContents

FinesContent Sample(%) MR ERI ER2

DCS (kN/mL)10 15 12 1020 25 44 1930 65 48 5340 79 51 1850 95 81 6360 85 144 2670 llO 43 17480 95 48 13990 30 26 20100 2 2 2

180 •160

~140 • A...E120Z100 'e 80 -~ 60;:;J 40 A.

20 Ao ---.,----.-~--.- ..--, -, -.--~10 20 30 40 SO60 70 80 90 10

oFines content (% )

Figure 6: Relationship between UCS and finescontent

17

Journal of Engineering Research, Vol. 14, No.1, March 2009. A.L. Ayodele, F.A.Falade and

M.O.Ogedengbe

Nishimura and Fredlund (1999) found thatthe unconfined compressi ve strength is afunction of the water content in the void ofthe soil. This explains why ER2 at samefines content (70%) with sample MR has ahigher ues because at 70% fines OMC ofER2 is 22.8% while that of MR is 23.5%.The optimum result is obtained at between50% and 80% fines content for each of thesoil samples.The results were almost zero at 10% and100% fines. These can also be explainedwhen one considers the general equationfor determining the shear strength of soilas given in Equation 2.2. As fines contenttends to zero, the shear strength tendsto o 'tan0, while as the fines content tendsto 100% the shear strength tends to C. Soilwith almost 50% fines has the twocomponents of shear strength present (i.e.C and (3) thus the higher value of the shearstrength. The correlations of UCS for eachsoil sample are given in Equations 15 - 17.The R2 values are 0.917, 0.602 and 0.523for samples MR, ERI and ER2respectively. The regression is not helpfulin predicting a Y value because of the lowvalues of the R2 especially for samplesER 1 and ER2, thus a general equationcannot be obtained from the sets of data.y = -0.OOOx3 + O.033x2 + 1.53lx - 6.066(15)Y = -0.OOOx3

- 0.018x2 + 3.285x - 20.76(16)y = -O.OOlxJ + 0.211x2

- 6.918x + 73.9(17)

4.0 CONCLUSIONSIt is concluded from the findings of this workthat:

1. the engineering properties of thestudied soil samples generall y reducewith increase in fines content;

11. linear and non-linear relationshipshave been generated between finescontent and the engineeringproperties through regression analysis;

Ill. a soil of high plasticity can be madesuitable for use as sub-base material ifthe fines content can be reducedconsiderably.

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r Iournal of Engineering Research. l '01. 1-1.No.1. March 2009. A.L Ayodele, F.A.Falade and

M. O. Ogedengbe

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