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International Journal of Civil Engineering and Technology (IJCIET)

Volume 9, Issue 7, July 2018, pp. 1962–1974, Article ID: IJCIET_09_07_209

Available online at http://www.iaeme.com/ijciet/issues.asp?JType=IJCIET&VType=9&IType=7

ISSN Print: 0976-6308 and ISSN Online: 0976-6316

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GEOPOLYMER EFFECT IN MODELLING

HYDRAULIC CONDUCTIVITY FOR

DESIGNING SOIL LINER OF LATERITE SOIL

M. Mukri

Civil Engineering Department, UiTM Shah Alam - 41450, Shah Alam, Malaysia

N. N. S.Aziz

Faculty of Civil Engineering, UiTM Shah Alam- 41450, Shah Alam, Malaysia

N. Khalid

Civil Engineering Department, UiTM Shah Alam - 41450, Shah Alam, Malaysia

ABSTRACT

Soil liners are commonly used in the base of waste containment facilities and it

has been used for many years. The previous studies revealed that the soil liner should

have a hydraulic conductivity lower than 1x10-9

m/s. Laterite soil is the main material

used for soil liner. However, the use of laterite soil associated with difficulties in

compacting to achieve the acceptable hydraulic conductivity. Laterite soil was

modified with the chemical stabilizer which is fly ash based geopolymer. Laterite soil

was mixed with different percentages of geopolymer which are 5%, 10%, 15% and

20% by weight. The NaOH in pellets form was added to water in order to obtain the

alk ali solution and fly ash was added to the solution to form a material in a binder

state k nown as geopolymer. The soil properties were also determined for all soil

samples. The hydraulic conductivity of soil was determined by using a falling head

permeability test subjected to BSL test only. All compacted samples were performed at

dry, optimum and at wet of optimum moisture content. The hydraulic conductivity for

the soil sample that compacted with RBSL test and BSH were determined by using

Benson and Trast’s formula. According to the results, it was found that the soil

mixture with 15% of geopolymer gives the best value of hydraulic conductivity of the

soil. Subsequently, models of estimating hydraulic conductivity, k from an empirical

formula based on soil parameter measured in the laboratory were established. The

models were developed by using MINITAB software. There are a few parameters that

were used in developing the models. A model was developed based on physical

properties parameters to predict the hydraulic conductivity of the modified soil based

geopolymer. Further adding geopolymer in the soil mixes was found decreased the

hydraulic conductivity of the resulted liner.

Key words: Laterite Soil, Geopolymer, Hydraulic Conductivity and Empirical

Formula.

M. Mukri, N. N. S.Aziz and N. Khalid


Cite this Article: M. Mukri, N. N. S.Aziz and N. Khalid, Geopolymer Effect in

Modelling Hydraulic Conductivity for Designing Soil Liner of Laterite Soil.

International Journal of Civil Engineering and Technology, 9(7), 2018, pp. 1962-

1974.

http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=9&IType=7

1. INTRODUCTION

Soil liners are generally used in the base of waste containment facilities and it has been as

such for many years. There are three (3) types of soil liners normally applied, which are

natural undisturbed clayey deposits, compacted soil liners and geosynthetic clay liners [29]. A

low hydraulic conductivity is a key parameter in the design of liner to prevent the downward

migration of contaminants into aquifers. Besides that, Stewart and Nolan, [31] explained a

landfill liner should have low hydraulic conductivity, good resistant to shrink age crack ing

and have suitable mechanical properties for structural integrity during construction and

operation. Benson et al. [8] from their studies suggested that the soil liner should have a

hydraulic conductivity lower than 1x10-9

m/s. The thickness of compacted soil liners usually

0.6 m to 3 m, consisting natural soil. This natural soil is recompacted in the field to obtain the

desired hydraulic strength properties.

Good engineering practice and quality assurance program can result in good quality and

low hydraulic conductivity soil liners [29, 37]. The hydraulic conductivity of compacted soil

liners depends on the soil mineralogy and the mode of placement of the liner. Examples of

soil liners and cover system used in the liner are shown in Figure 1 and Figure 2. Based on

Figure 1, Rowe [29] and Mukri [38] stated that liners may be described as single composite

liner systems and double composite liner. Single composite liner system consists of

geomembrane in combination with a compacted soil liner. This type of liner system is

required in a municipal waste landfill because it is effective at limiting leachate migration into

the subsoil. Other than that, double composite liner system consists of either two single liners,

two composite liners or both single and composite liners. The functions of upper and lower

liners are different. On the other hand, Figure 2 shows the typical cover system. This system

is important to cover the waste in order to prevent water ingress into the waste and therefore

to limit future leachate generation. The topsoil that covers the waste comprises of compacted

soil with low permeability.

Figure 1 Examples of compacted soil liners (typical liner system) [29].

Geopolymer Effect in Modelling Hydraulic Conductivity for Designing Soil Liner of Laterite Soil


1.1. Laterite Soil

Laterite soil is one of the residual soils. Gidigasu and Kuma [14] stated the term

“Laterization” describes the processes that produce laterite soils. Lateritic soils usually

develop in tropical and other regions with similar hot and humid climate, where heavy

rainfall, warm temperature and well drainage lead to the formation of thick horizons of

reddish lateritic soil profiles rich in iron and aluminium [23, 32, 7]. According to Gidigasu

and Kuma [14], a lateritic soil profile is characterized by the presence of three major horizons

include the sesquioxide rich lateritic horizon, the mottled zone with evidence of enrichment of

sesquioxide and the pallid or leached zone overlying the parent rock . Lateritic soils have a

varieties colour from ochre through red, brown and violet to black . According to Safiuddin et

al. [30], the colour of the soils depends largely on the concentration of iron oxides and the

presence of hematite and goethite. If soil sample consists high amount of iron oxides, the

sample of laterite gives reddish to brown in colour. Figure 2 show the profile of laterite soil.

Figure 2 Profile of Laterite Soil (Encyclopedia Britannica)

In addition, Maigien [20] and Gidigasu [13] stated laterite soil are weathered under

conditions of high temperatures and humidity resulting in poor engineering properties such as

high plasticity, tendency to retain moisture and high natural moisture content.

Frempong and Yanful [12]; Osinubi and Nwaiwu [25] ; Ahmad et al. [39] and Osinubiet

et al. [26] mentioned that when laterite soil was compared with active clay soils, it presents

attractive option because of its greater shear strength properties, chemical resistance, better

work ability and availability where they occur in abundance. In addition, the positive and

extensive experience of using lateritic soil in several geotechnical structures such as highway

embankments, road bases, airport runways, earth dams etc for several decades has encouraged

research in the use of the soil as material for soil liners [4]. However, the soil has high

hydraulic conductivity apparently due to the predominance of inactive and non-expanding 1:1

kaolinite clay mineral in the soil [20, 13, 4].

Laterite soils in the landfill area cannot perform satisfactorily as a barrier because of its

high hydraulic conductivity. Hence, modification of soils to improve their engineering

properties becomes necessary. Numerous studies have been conducted on the permeability of

the lime-treated soil, cement-treated soil and fly ash-treated soil but data on the use of

geopolymer is still lacking. The focus of this study is to examine the suitability of geopolymer

to enhance lateritic soils as soil liner.

https://global.britannica.com/editor/The-Editors-of-Encyclopdia-Britannica/4419



2. MATERIAL AND EXPERIMENTAL PROCEDURES

2.1. Geopolymer

Douglas et al. [10] and Cristelo, Glendinning, Fernandes and Pinto [9] mentioned that

geopolymers are inorganic binders consisting of two components which are very fine and dry

powder and syrupy, highly alkaline liquid. In order to produce a mixture of molasses-like

consistency which is then reacted with the desired waste or aggregate, the liquid and powder

portions are mix together [10].

Cristelo et al. [9], stated that in geotechnical applications, alkaline activation which is a

geopolymeric binder of fly ash was tested for soil improvement since the waste material was

obtained as a binder in most of the other geopolymer applications. Alkaline-activated

materials showed better performance since durability and stability can be increased, an

improvement from a mechanical aspect compared to cement and also improved the bond

between the soil particles and binder [27, 34]. Alkaline activation generally was a reaction

concerning alumina-silicate materials and alkali or earth substances alkali. At a molecular

level to natural rocks, materials formed from reactions between silica, alumina and alkali

cations were very alike in term of stiffness, durability and strength (Cristelo et al., 2012) [9].

Referring to Hamidi et al. [16], based on Zhang et al. [36], they mentioned that research

on this inorganic polymer widens where it shows promising use in various application namely

toxic metal immobilization, waste management, fire resistance, construction repair and

coatings. Moreover, it is a green material because it comes from industrial waste and natural

resource. Furthermore, the other advantages of geopolymer are that their product is very

economical and cost-effective because the waste is available at low cost and the process is

hassle-free [17].

According to Komnitsas [19], any aluminosilicate source (such as metak aolin, kaolin,

slag and fly ash) that can dissolve in alkaline activator solution (such as NaOH or KOH) will

act as geopolymer precursor and geopolymerise. Most of the researchers more interest to

utilize industrial byproduct material such as slag and fly ash as the source materials for

geopolymer because they have high silica and alumina contents which also abundantly

available in landfill site [24]. Whereas, the alkaline solutions play role in geopolymerization

at the early stage as it dissolves the active aluminosilicate species in the reaction [18].

Nikolic et al. [22] reported that fly ash is of coal fire by-product material from the coal-

fired power station. Ansary et al. [5] acknowledged that fly ash is regularly used as a partial

replacement for cement in concrete because of its pozzolanic properties. Besides that, it is

also the form of ash, which has the greatest potential for use in the ground modification.

There are two classes of fly ash are defined by ASTM C618 which is Class F fly ash and

Class C fly ash. The differences between these classes of fly ash are the amount of calcium,

silica, alumina, and iron content in the ash. The chemical properties of the fly ash are largely

influenced by the chemical composition of the coal burned. The additions of a chemical

activator such as sodium silicate (water glass) to a Class F ash can lead to the formation of a

geopolymer. Furthermore, class C fly ash is produced from the burning of younger lignite or

subbituminous coal. Unlike Class F, self-cementing Class C fly ash does not require an

activator. Alkali and sulfate (SO4) contents are generally higher in Class C fly ashes.

Sodium hydroxide is one of the materials that are used to produce geopolymer binder. It

consists of two different states which are in solution form or in pallet form. In a solution form,

sodium hydroxide is a white, odorless, and non-volatile solution. It is highly reactive but does

not burn. It reacts violently with water and numerous commonly encountered materials,



generating enough heat to ignite nearby combustible materials [3]. The advantages of

geopolymer are it can easily react with water which results in a powerful compaction aid thus

giving a higher density for the same compaction effort. Sodium hydroxide reacts very

effectively with soil rich in aluminum [3].

Harditjo et al. [15] stated that an alkaline activator that commonly used in producing

geopolymer is a combination of sodium hydroxide (NaOH) or potassium hydroxide (KOH)

and sodium silicate or potassium silicate. This alkaline solution plays an important role [21].

An alkaline solution is chosen depends upon various factors such as the cost and the reactivity

of the alkaline solutions [21]. The dissolution of fly ash is affecting due to the type and

concentration of alkaline solutions. Generally, the Al3+ and Si4+ ions are leaching highly

with sodium hydroxide solution compared to the potassium hydroxide solution. Duchesne,

Duong, Botrom and Frost [11] mentioned that in presence of NaOH in the activating solution,

the reaction proceeds more rapidly and the gel is less smooth. The gel composition analyzed

in the sample activated with the mixture of sodium silicate and sodium hydroxide is enriched

in Na and Al [2].

Xu and Van Deventer [35] studied a wide range of aluminosilicate minerals to make

geopolymers. They found that generally, the sodium hydroxide solution caused a higher

extent of dissolution of minerals than the potassium hydroxide solution [21].

2.2. Experimental Procedure

This study involves with several laboratory works. First, the laterite soil was collected at

Damansara Perdana area. Then, the geopolymer was produced by mixing fly ash with an

alkali activator, sodium hydroxide (NaOH). Sodium hydroxide was purchased from the

supplier and the fly ash was collected from Kapar Energy Ventures Sdn. Bhd. Kapar

Selangor. The sodium hydroxide (NaOH) in pellet form was added to water in order to obtain

the alkali solution and fly ash was added to the solution to form a material in a binder state

known as geopolymer.

Next, the soil properties were determined by conducting Atterberg limit, particle density,

particle size distribution, pH, and shrink age limit test to determine the physical properties of

laterite soil before and after mixing with different percentage of geopolymer. From this

preliminary laboratory works, the parameters collected include liquid limit (LL), plastic limit

(PL), plasticity index (PI), specific gravity of soil (Gs) and pH of the soil. Then, shrinkage

limit test was carried out to identify the shrinkage index of laterite soil.

The next test was falling head permeability test. This test was carried out to determine the

hydraulic conductivity of soil mixed with different proportions of geopolymer subjected to

British Standard Light (BSL) of compaction. There were 15 samples prepared, and these

compacted soil samples were performed at dry, optimum and at wet of optimum moisture

content. The hydraulic conductivity of soil that had been compacted with Reduced British

Standard Level (RBSL) and British Standard Heavy (BSH) test was determined using the

empirical models that had been developed by the previous researcher. The falling head

permeability test was not carried out on laterite soil that had been compacted with Reduced

British Standard Level (RBSL) and British Standard Heavy (BSH) tests because of time

constraint. In this study, one (1) soil sample required about four (4) months to saturate and

can be used to determine its hydraulic conductivity.

Last but not least, the collected laboratory data were analyzed using MINITAB 14. This

software was used to develop a model of hydraulic conductivity effected by geopolymer, k(%

geopolimer). These models were identified to design a new soil liner system. In the process of



developing models, there are some parameters that were used based on the physical and

engineering properties of the soil. For example energy of compaction (E), plasticity index

(PI), plastic limit (PL), liquid limit (LL) optimum moisture content (OMC), maximum dry

density (MDD), clay content (C), initial saturation (Si) and percentage of geopolymer (%

Geo). The parameter that has a strong relationship and can effect hydraulic conductivity of

soil were chosen. All hypothesis leading to the relationships of the statistical simulation must

be defined clearly before running the test. The values of k , R2, P and T shows a good

relationship with the parameter that was used. The results of all samples were analyzed and an

extensive research had been carried out to improve landfill system through the establishment

of new soil liner. The test was done on the compacted remolded soil and the experiment was

conducted in regards to the objectives of this research.

3. RESULTS AND DISCUSSION

3.1. Soil Physical Properties

It is important to determine the percentage of different particle sizes in a soil in order to

identify the characteristics of the soil. From the sieve analysis test, the laterite soil used in this

research consisted of about 25.98% of gravel, 35.55% of sand and 38.47% of fine size grain.

Therefore, this laterite soil was classified under very silty SAND. The average percentage of

liquid limit (LL) for these three samples was 57.28%. Meanwhile, their average percentages

of plastic limit (PL) and plasticity index (PI) were 52.46% and 4.82% respectively. Based on

the results, the laterite soil examined in this study had a slightly plastic soil characteristic

because its plasticity index (PI) value was in a range of 3% to 15%. The specific gravity value

for this residual soil fell within the range specified by previous researchers which were 2.59.

On the other hand, the specific gravity test for soil mix with geopolymer also had been

determined which are within 2.60-2.66. Different percentage of geopolymer with soil were

tested which were 5% geopolymer, 10% geopolymer, 15% geopolymer and 20% geopolymer.

The plain laterite soil produced a pH of 4.44 and followed at 10.24, 10.95, 11.69 and 11.83

for 5%, 10%, 15% and 20% of geopolymer, respectively. For natural laterite soil, the average

shrinkage of the soil was taken as 7.38% as it was reduced to 4.05%, 3.34%, 2.86% and

2.14% as it had been added with 5% geopolymer, 10% geopolymer, 15% geopolymer and

20% of geopolymer.

3.2. Engineering Properties

The results for standard Proctor compaction test of plain laterite soil show the optimum

moisture content (OMC) of the soil had a range between 17% to 35% and maximum dry

density (MDD) range between 1.3 Mg/m3 to 1.7 Mg/m3 respectively. Table 1 showed the

range value of MDD and OMC for Reduced British Standard Level (RBSL) test, British

Standard Level (BSL)test and British Standard Heavy (BSH) test with different percentage of

geopolymer

Table 1 Compaction results for RBSL test, BSL test and BSH test for appearance of 0-20% geopolymer

Compaction Energy

Maximum Dry

Density, MDD

(Mg/m3)

Optimum

Moisture Content,

OMC (%)

Reduced British Standard Level (RBSL) 1.71-1.86 15.40-11.36

British Standard Light (BSL) 1.74-1.85 15.16-13.87

British Standard Heavy (BSH) 1.92-2.02 12.87-11.38



3.3. Hydraulic Conductivity

Hydraulic conductivity, k test was carried out for plain laterite soil and soil with different

percentage of geopolymer. This test was important to determine the ease of water to pass

through the particle of the soil. Performing laboratory test was very time-consuming

especially in the case of permeability tests on samples with high portions of fine particles

content. For example, in this study, one sample took four (4) months to be fully saturated for

the use of the permeability test. Because of this difficulty and to save more time, the test was

only carried out for British Standard Light (BSL) test. Meanwhile, for Reduced British

Standard Level (RBSL) test and British Standard Heavy (BSH) test, the value of hydraulic

conductivity, k was predicted using the suitable empirical model developed from previous

studies which are Benson and Trast [6] model. Based on the results of hydraulic conductivity,

k using this model, it displayed a small amount of difference when compared with results

from laboratory test. The graph was shown in Figure 3 exhibited a small difference between

Benson and Trast model with the laboratory results. Because of such minor difference, this

model was the best estimator among the studied equations to predict the hydraulic

conductivity for soil samples that compacted with Reduced British Standard Level (RBSL)

and British Standard Heavy (BSH) condition.

Figure 3 Comparison of hydraulic conductivity, k of laterite soil with different percentage of

geopolymer and different compaction energy based on empirical formula from Benson and Trast, [6]

The hydraulic conductivity, k test also had been carried out to plain laterite soil mix with

different percentage of geopolymer (5%, 10%, 15% and 20%). The samples of soil were

prepared and molded based on optimum moisture content (OMC) value from British Standard

Light (BSL) test. From the results, the hydraulic conductivity, k of plain laterite soil mix with

different percentage of geopolymer decreased nonlinearly with the addition of geopolymer. It

indicated the soil mix with 15% of geopolymer gave the low reading of hydraulic

conductivity,k and followed by 10%, 20% and 5% of geopolymer for Reduced British

Standard Level (RBSL) test and British Standard Light (BSL) test. Meanwhile, for British

Standard Heavy (BSH) test, it had shown slightly different results in which the smallest value

of hydraulic conductivity, k was 15% of geopolymer and followed with 10%, 5% and 20% of

geopolymer.

From the results, the soil samples were compacted using the British Standard Light (BSL)

compaction energy, yielded hydraulic conductivity, k 1.96 x10-9

m/s to 3.69 x10-10

m/s. In



order to predict the hydraulic conductivity, k of the sample for Reduced British Standard

Level (RBSL) test and British Standard Heavy (BSH) test, Benson and Trast empirical model

was selected because of the results from the laboratory for British Standard Light (BSL)

exhibit the closer value of hydraulic conductivity, k . The other empirical model from

previous studies did not fit well with the value from laboratory test. Referring the models by

Benson and Trast [6] the soil samples compacted with Reduced British Standard Level

(RBSL) compaction energy contributed hydraulic conductivity, k value ranging from 8.28 x

10-9

m/s to 8.69 x 10-10

m/s while the soil samples compacted with British Standard Heavy

(BSH) compaction energy, gave lower hydraulic conductivity, k ranging from 1.17 x 10-9

m/s

to 1.33 x 10-10

m/s. It can be said that the hydraulic conductivity of soil was decreased with

increasing percentage of geopolymer. The results are based on the immediate mixture which

is the sample does not expose to the curing period. It is believed that when the soil sample

was allowed to cure for a few days, it will produce the better results of hydraulic conductivity

as compared to results of the immediate mixture.

According to Benson and Trast [6], the effectiveness of liners and covers for waste

containment was often measured in terms of the possibility of achieving hydraulic

conductivity ≤ 1 x 10-9

m/s. In general, based on the results of this study, the hydraulic

conductivity of the soil samples decreased with an increase in the certain percentages of

geopolymer. The similar observation had been carried out by previous studies [33, 40]. They

observed a decrease in hydraulic conductivity due to the precipitation of new minerals as a

result of chemical interactions between additive and soil. The results of their findings also

suggested the pozzolanic and self-cementing properties of fly ash have resulted in the

formation of hydration products that could possibly block void spaces and reduced the

interconnection between fly ash particles. It could be said that geopolymer was a material that

is able to fill in the gaps between the soil particles and could ensure low hydraulic

conductivity, k of soil. Table 2, Table 3 and Figure 4presented the results of hydraulic

conductivity, k from this study.

Table 2 Summary results of hydraulic conductivity (After Benson and Trast, 1995) for Reduced

British Standard Level (RBSL), British Standard Light (BSL) and British Standard Heavy (BSH) test.

Compaction

Energy

Hydraulic Conductivity, k (m/s)

0% of

Geopolymer

5% of

Geopolymer

10% of

Geopolymer

15% of

Geopolymer

20% of

Geopolymer

RBSL

BSL

BSH

8.46 x 10-9

2.34 x 10-9

1.33 x 10-9

8.47 x 10-10

3.31 x 10-10

1.31 x 10-10

8.44 x 10-10

3.24 x 10-10

1.29 x 10-10

8.28 x 10-10

3.73 x 10-10

1.17 x 10-10

8.44x 10-10

3.26 x 10-10

1.32 x 10-10

Table 3 Summary results of hydraulic conductivity based on falling head permeability test for British

Standard Light (BSL) test

Compaction

Energy

Hydraulic Conductivity, k (m/s)

0% of

Geopolymer

5% of

Geopolymer

10% of

Geopolymer

15% of

Geopolymer

20% of

Geopolymer

K labOMC

(-5%)-BSL 3.22 x 10

-9 3.45 x 10

-10 3.10 x 10

-10 3.02 x 10

-10 3.11x 10

-10

K labOMC

-BSL 1.96 x 10

-9 3.46 x 10

-10 3.39 x 10

-10 3.22 x 10

-10 3.42 x 10

-10

K labOMC

(+5%)-BSL 2.98 x 10

-9 3.06 x 10

-10 3.01 x 10

-10 3.28 x 10

-10 3.21 x 10

-10



Figure 4 Hydraulic conductivity, k of laterite soil with different percentage of geopolymer based on

Benson and Trast [6] empirical formula and falling head test

3.2. Modelling of Hydraulic Conductivity with Various Variables

The suitable parameter such as energy of compaction (E), percentage of geopolymer,

plasticity index (PI), plastic limit (PL), liquid limit (LL), percentage of clay (C), optimum

moisture content (OMC), maximum dry density (MDD) and initial saturation (Si) were chosen

to be used for producing new empirical formula in determining hydraulic conductivity of soil.

This study successfully produces eight (4) empirical formula to determine the hydraulic

conductivity of laterite soil with geopolymer. This equations produces a high regression

coefficient, R2 which is 99.7% [41]. The best equations is;

* (

)+

(1)

Table 4 Empirical formula from this study with percentage of geopolymer

Variables Empirical Formula Equation

E, OMC, LL

and % Geo

(

) 4

E, Si, PL and

% Geo

(

)

3

E, OMC, LL,

MDD and %

Geo

*

(

) +

2

E, OMC, LL

MDD, C and %

Geo

*(

)(

)+

1

Meanwhile, the other equations that also can be used to determine the hydraulic

conductivity of soil with % geopolimer are tabulated in Table 4. Other equations, 2,3 and 4



are successfully developed and can be used in order to predict hydraulic conductivity of

laterite soil with geopolymer depends on what parameter that available.

From the developed models, it is show that the values of T, P and R2 shows the good

relationship with the parameters that were used which are liquid limit (LL), plastic limit (PL),

plasticity index (PI), percentage of clay (%C), percentage of geopolymer (% Geo), optimum

moisture content (OMC) and maximum dry density (MDD).

4. CONCLUSIONS

The results that were obtained from the preliminary and main laboratory tests enable to

provide a satisfactory prediction of physical and engineering properties of the laterite soil with

different percentage of geopolymer. This will also enhance the knowledge and understanding

of the behavior of additive which is geopolymer on how it reacts with laterite soil and its

effects on the permeability of laterite soil. The hydraulic conductivity of soil also affected

when geopolymer is mix with soil. The results revealed that the geopolymer helps reduced the

hydraulic conductivity of plain laterite soil. The hydraulic conductivity of plain laterite soil

compacted with British Standard Light (BSL) test gives a lower value of hydraulic

conductivity when geopolymer was added to the soil. At 5%, 10% and 15% of geopolymer,

the hydraulic conductivity of soil were decreased to 3.46 x10-10

m/s and followed with 3.39

x10-9

m/s and 3.22 x10-10

m/s. When 20% of geopolymer was mixed with soil, the hydraulic

conductivity of soil shows a little increment which is 3.42x10-10

m/s. Comparing the results

from permeability laboratory test of British Standard Light (BSL) effort, it is present that the

value of hydraulic conductivity of samples is more accurate with the empirical model by

Benson and Trast, 1995. Therefore, the empirical model from Benson and Trast, (1995) was

chosen to predict the value of hydraulic conductivity for Reduced British Standard Level

(RBSL) and British Standard Heavy (BSH) of soil samples. Based on the results, it is seen

that the hydraulic conductivity of plain laterite soil compacted with Reduced British Standard

Level (RBSL), British Standard Level (BSL) and British Standard Heavy (BSH) did not meet

the requirement in designing a soil liner. However, after 5%, 10%, 15% and 20% of

geopolymer were mixed with all soil samples, the range value of hydraulic conductivity of

soil between 3.46 x10-10

m/s to 3.22 x10-10

m/s which are less than 1 x10-9

m/s as a requirement

in designing a soil liner. Besides that, the new empirical formula was developed in order to

determine the hydraulic conductivity of laterite soil in designing a compacted soil liner. The

formula can be used directly to determine the hydraulic conductivity of laterite soil by

entering the suitable parameter without the need to conduct the permeability test. This study

successfully produces eight (8) empirical formula to determine the hydraulic conductivity of

laterite soil without and with geopolymer. All of these equations produces a high regression

coefficient, R2 which are 98.8% and 99.7%. In a nutshell, it can be said that the developed

models in this study are able to provide a good prediction of hydraulic conductivity, k for

laterite soil and laterite soil mixed with a different percentage of geopolymer. On the other

hand, the used of additive which is geopolymer are economically advantage and environment-

friendly compared to another additive such as bentonite, lime, and extra. Last but not least, it

is hoped that the results of this study can be used as a guideline in designing a soil liner

system at landfill area.

ACK NOWLEDGEMENTS

The authors thank to all staff in the Faculty of Civil Engineering, UiTM for permission and

encouragement to conduct such studies for the benefit of science and society. The authors

would like to acknowledge that this research has been carried out funded by Universiti



Teknologi MARA (UiTM), Institute of Quality and Knowledge Advancement (InQKA) and

support from Faculty of Civil Engineering, Universiti Teknologi MARA (UiTM).

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