Introduction
Lateritic soils are commonly used for road construction in Nigeria.
Lateritic soil in its natural state sometimes have low bearing capacity
and low strength due to high content of clay. When lateritic soil
contains a huge amount of clay materials, its strength and stability
cannot be guaranteed under load in presence of moisture[1]. Also, when a weak soil is encountered on a
site and sourcing for alternative soil proves economically unviable,
improving the soil by way of stabilization to meet the desired objective
becomes the viable option [2, 3, 4]. Popular
industrial stabilizers are cement, lime, flyash and bitumen.
Furthermore, the high cost of cement being used as binder, has led to
the search for natural materials as either alternative or complement.
Research on alternative or complement to cement has so far centered on
the partial replacement of cement with different materials[5]. The improvement in the strength and
durability of lateritic soil in recent times has become imperative, this
has geared researchers towards using stabilizing materials that can be
sourced locally at a very low cost [1]. These
local materials can be grouped as either agricultural or industrial
wastes [6]. In light of this, cheap agricultural
waste such as rice husk ash is being studied as replacements for the
more expensive cement.
Rice is one of the most cultivated and consumed cereal in the world. In
rice producing countries, a traditional waste material known as ‘rice
husk’ is obtained as a by-product in bulk amount from Rice mills.
Globally, approximate 600 million tonnes of rice paddies are produced
each year. On the average, 20% of the paddy is husk, giving an annual
total production of 120 million tonnes. [7,8].
Rice husk is a by-product from agriculture produce when it is harvested,
the outermost part of the paddy is the rice husk, also called the rice
hull. It is separated from the brown rice in rice milling. Complete
burning of rice husk results to rice husk ash (RHA), so for every 1000
kg of paddy milled, about 220 kg (22%) of husk is produced and when the
husk is burnt in boilers, about 55 kg (25%) of RHA is generated, if the
burning is incomplete, the carbonized rice husk (CRH) is obtained[9]. In line with the Federal Government’s drive
for Nigeria to be self-sufficient in rice production and to save
hundreds of billions of naira annually on rice importation, local rice
production has reached 15 million metric tonnes[10], this, in turn has resulted to increased
generation of rice husk as waste. Stabilization enhances the desired
qualities of a soil [11], chiefly among these, is
the California bearing ratio (CBR), a standard for measuring the
strength of a given soil in road construction. The design of flexible
pavement is much dependent on the CBR of subgrade. CBR values can be
measured in the laboratory test in accordance with BS 1377[12 13,14]. The CBR test
performed in the laboratory is time-consuming, a laboratory test
generally takes four or more days to measure the soaked CBR value for
each soil sample. The result of the tests is actually an indirect
measure, which represents comparison of the strength of subgrade
material to the strength of standard crushed rock referred in percentage
values. Instead, it can be predicted from properties of soils determined
in the laboratories. Several studies have been conducted to estimate CBR
from Liquid limit, Plasticity Index, standard proctor parameters, the
use of artificial neural network has so far held high promises in
achieving this [15, 16]. In light of this,
developing credible predictive models has been in the fore-burner, the
use of artificial neural network (ANN) is fast gaining ground especially
in the field of geotechnical engineering [17, 18,
19,20].
[15]. ANN is a massively parallel –distributed
information processing system that has certain performance
characteristics resembling biological neural networks of human brain[21]. ANNs have been developed as a generalization
of mathematical models of human cognition or neural biology. The key
element of ANN is the novel structure of its information processing
system. An ANN is composed of a large number of highly interconnected
processing elements called neurons working in unison to solve specific
problems. Neurons having similar characteristics in an ANN are arranged
in groups called layers. A way of classifying neural networks is by the
number of layers as single, bilayer and multilayer. ANNs can also be
categorized based on direction of information flow and processing The
main benefits of the ANN according to Khademikia et al.,[22] in comparison to other modeling programs are
the nonlinearity, adaptively, fault tolerance, uniformity and design.
In recent times, the increase in population has led to the generation of
more wastes such as the rice husk, thereby necessitating the need for
proper management of these wastes. It is however worthy of note that
there is yet to be adequate awareness on the usefulness of these
aforementioned wastes in Nigeria, in other words, little or no
importance is attached to them. The practice of incinerating them to ash
and adopting them as admixtures in stabilized soils due to their
pozzolanic values has enhanced their economic value[23]. Also, for greater efficiency in management
of time and manpower, the need for developing models in predicting
California bearing ratio (CBR) an important parameter in road
construction has become imperative. This is expected to address the
problems of unnecessary delays at the laboratories and human errors,
which can negatively impact on the project.
Materials and Methods
Materials The materials used were: rice husk ash, soil samples,
ordinary Portland cement and water.
Rice Husk Ash (RHA): The rice husk ash was burnt in open
atmosphere and the black ashes obtained were heated in an air tight
furnace for 6 hours at 10000C to obtain a white
coloured ash.
Soil Sample: Soil Sample was collected along Oye-Ekiti –
Isan-Ekiti Road, Nigeria at a depth not less than 1.2m below the ground
level at 5 different points of about 3m apart using the disturbed
sampling technique. It was brought to the soil laboratory and marked
indicating the soil description, sampling depth and date of sampling.
The soil sample was air-dried for two weeks to allow for partial
elimination of natural water content which may affect the analysis, then
sieved with sieve no 4 (4.75mm opening) to obtain the final soil sample
for the tests. After the drying period of two weeks, lumps in the sample
were pulverized under minimal pressure.
Ordinary Portland Cement: This was obtained from a cement
store.
Water: The water used was obtained from the running taps in the
laboratory, the source was borehole. Distilled water was not used so as
to obtain results that would reflect in-situ conditions.