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CHAPTER ONE
INTRODUCTION
In the field of civil engineering, nearly all projects are built on to, or
into, the ground. Whether the project is a structure, a roadway, a tunnel, or a
bridge, the nature of the soil at that location is of great importance to the
civil engineer.
Geotechnical engineers are not the only professionals interested in the
ground: soil physicists, agricultural engineers, fanners and gardeners all take
an interest in the types of soil with which they are working. These workers,
however, concern themselves mostly with the organic top soils found at the
soil surface. In contrast, the geotechnical engineer is mainly interested in the
engineering soils found beneath the topsoil. It is the engineering properties
and behavior of these soils which are their concern.
Different soils with similar properties may be classified into groups
and sub-groups according to their engineering behavior. Classification
systems provide a common language to concisely express the general
characteristics of soils, which are infinitely varied, without detailed
descriptions.
Most of the soil classification systems that have been developed for
engineering purposes are based on simple index properties such as particle-
size distribution and plasticity. Although several classification systems are
now in use, none is totally definitive of any soil for all possible applications
because of the wide diversity of soil properties.
Soils in nature rarely exist separately as gravel, sand, silt, clay or organic
matter, but are usually found as mixtures with varying proportions of these
components. Grouping of soils on the basis of certain definite principles
would help the engineer to rate the performance of a given soil either as a
sub-base material for roads and airfield pavements, foundations of
structures, etc.
Following some types of different soils in nature shown in figures 1-1 to 1-?
Figure 1-1: associated surface environment and profile of a brunisol soil.
Figure 1-2: associated surface environment and profile of a chernozem soil.
Figure 1-3: associated surface environment and profile of a Cryosol soil.
Figure 1-4: associated surface environment and profile of a gleysol soil.
Figure 1-5: associated surface environment and profile of a luvisol soil.
Figure 1-6: associated surface environment and profile of an organic soil.
Figure 1-7: associated surface environment and profile of a podzol soil.
Figure 1-8: associated surface environment and profile of a regosol soil.
Figure 1-9: associated surface environment and profile of a solonetzic soil.
1.1 Project Objectives
The objective of this project is to design a computer program to classify
and maintain a database for Iraqi soils.
CHAPTER TWO
LITERATURE REVIEW AND THEORY
Soil can be described as gravel, sand, silt and clay according to grain
size. Most of the natural soils consist of a mixture of organic material in the
partly or fully decomposed state. The proportions of the constituents in a
mixture vary considerably and there is no generally recognized definition
concerning the percentage of, for instance, clay particles that a soil must
have to be classified as clay, etc.
When a soil consists of the various constituents in different proportions, the
mixture is then given the name of the constituents that appear to have
significant influence on its behavior, and then other constituents are
indicated by adjectives. Thus a sandy clay has most of the properties of a
clay but contains a significant amount of sand.
The individual constituents of a soil mixture can be separated and identified
as gravel, sand, silt and clay on the basis of mechanical analysis. The clay
mineral that is present in a clay soil is sometimes a matter of engineering
importance. According to the mineral present, the clay soil can be classified
as kaolinite, montmorillonite or illite. The minerals present in a clay can be
identified by either X-ray diffraction or differential thermal analysis.
Buildings, bridges, dams etc. are built on natural soils (undisturbed soils),
whereas earthen dams for reservoirs, embankments for roads and railway
lines, foundation bases for pavements of roads and airports are made out of
remolded soils. Sites for structures on natural soils for embankments, etc,
will have to be chosen first on the basis of preliminary examinations of the
soil that can be carried out in the field. An engineer should therefore be
conversant with the field tests that would identify the various constituents of
a soil mixture.
The behavior of a soil mass under load depends upon many factors such as
the properties of the various constituents present in the mass, the density, the
degree of saturation, the environmental conditions etc. If soils are grouped
on the basis of certain definite principles and rated according to their
performance, the properties of a given soil can be understood to a certain
extent, on the basis of some simple tests. The objectives of the following
sections of this chapter are to discuss the following:
1. Field identification of soils.
2. Classification of soils.
2.1 FIELD IDENTIFICATION OF SOILS
The methods of field identification of soils can conveniently be
discussed under the headings of coarse-grained and fine-grained soil
materials.
2.1.1 Coarse-Grained Soil Materials
The coarse-grained soil materials are mineral fragments that may be
identified primarily on the basis of grain size. The different constituents of
coarse-grained materials are sand and gravel. The size of sand varies from
0.075 mm to 4.75 mm and that of gravel from 4.75 mm to 80 mm. Sand can
further be classified as coarse, medium and fine. The engineer should have
an idea of the relative sizes of the grains in order to identify the various
fractions. The description of sand and gravel should include an estimate of
the quantity of material in the different size ranges as well as a statement of
the shape and mineralogical composition of the grains. The mineral grains
can be rounded, subrounded, angular or subangular. The presence of mica or
a weak material such as shale affects the durability or compressibility of the
deposit. A small magnifying glass can be used to identify the small
fragments of shale or mica. The properties of a coarse grained material mass
depend also on the uniformity of the sizes of the grains. A well-graded sand
is more stable for a foundation base as compared to a uniform or poorly
graded material.
2.1.2 Fine-Grained Soil Materials
Inorganic Soils: The constituent parts of fine-grained materials are the silt
and clay fractions. Since both these materials are microscopic in size,
physical properties other than grain size must be used as criteria for field
identification. The classification tests used in the field for preliminary
identification are:
1. Dry strength test.
2. Shaking test.
3. Plasticity test.
4. Dispersion test.
Dry strength: The strength of a soil in a dry state is an indication of its
cohesion and hence of its nature.
It can be estimated by crushing a 3 mm size dried fragment between thumb
and forefinger. A clay fragment can be broken only with great effort,
whereas a silt fragment crushes easily.
Shaking test: The shaking test is also called as dilatancy test. It helps to
distinguish silt from clay since silt is more permeable than clay. In this test a
part of soil mixed with water to a very soft consistency is placed in the palm
of the hand. The surface of the soil is smoothed out with a knife and the soil
pat is shaken by tapping the back of the hand. If the soil is silt, water will
rise quickly to the surface and give it a shiny glistening appearance. If the
pat is deformed either by squeezing or by stretching, the water will flow
back into the soil and leave the surface with a dull appearance. Since clay
soils contain much smaller voids than silts and are much less permeable, the
appearance of the surface of the pat does not change during the shaking test.
An estimate of the relative proportions of silt and clay in an unknown soil
mixture can be made by noting whether the reaction is rapid, slow or
nonexistent.
Plasticity test: If a sample of moist soil can be manipulated between the
palms of the hands and fingers and rolled into a long thread of about 3 mm
diameter, the soil then contains a significant amount of clay. Silt cannot be
rolled into a thread of 3 mm diameter without severe cracking.
Dispersion test: This test is useful for making a rough estimate of sand, silt
and clay present in a material. The procedure consists in dispersing a small
quantity of the soil in water taken in a glass cylinder and allowing the
particles to settle. The coarser particles settle first followed by finer ones.
Ordinarily sand particles settle within 30 seconds if the depth of water is
about 10 cm. Silt particles settle in about 1/2 to 240 minutes, whereas
particles of clay size remain in suspension for at least several hours and
sometimes several days.
Organic soils
Surface soils and many underlying formations may contain significant
amounts of solid matter derived from organisms. While shell fragments and
similar solid matter are found at some locations, organic material in soil is
usually derived from plant or root growth and consists of almost completely
disintegrated matter, such as muck or more fibrous material, such as peat.
The soils with organic matter are weaker and more compressible than soils
having the same mineral composition but lacking in organic matter. The
presence of an appreciable quantity of organic material can usually be
recognized by the dark-grey to black color and the odor of decaying
vegetation which it lends to the soil.
Organic silt: It is a fine grained more or less plastic soil containing mineral
particles of silt size and finely divided particles of organic matter. Shells and
visible fragments of partly decayed vegetative matter may also be present.
Organic clay: It is a clay soil which owes some of its significant physical
properties to the presence of finely divided organic matter. Highly organic
soil deposits such as peat or muck may be distinguished by a dark-brown to
black color, and by the presence of fibrous particles of vegetable matter in
varying states of decay. The organic odor is a distinguishing characteristic of
the soil. The organic odor can sometimes be distinguished by a slight
amount of heat.
2.2 Textural Classification
In a general sense, texture of soil refers to its surface appearance. Soil
texture is influenced by the size of the individual particles present in it.
Table 2.1 divided soils into gravel, sand, silt, and clay categories on the basis
of particle size. In most cases, natural soils are mixtures of particles from
several size groups. In the textural classification system, the soils are named
after their principal components, such as sandy clay, silty clay, and so forth.
Table 2.1 Soil Fractions as per U.S. Department of Agriculture
A number of textural classification systems were developed in the past by
different organizations to serve their needs, and several of those are in use
today. Figure 2.1 shows the textural classification systems developed by the
U.S. Department of Agriculture (USDA). This classification method is based
on the particle-size limits as described under the USDA system in Table 2.1;
that is:
• Sand size: 2.0 to 0.05 mm in diameter
• Silt size: 0.05 to 0.002 mm in diameter
• Clay size: smaller than 0.002 mm in diameter
The use of this chart can best be demonstrated by an example. If the particle-
size distribution of soil A shows 30% sand, 40% silt, and 30% clay-size
particles, its textural classification can be determined by proceeding in the
manner indicated by the arrows in Figure 2.1.
This soil falls into the zone of clay loam. Note that this chart is based on
only the fraction of soil that passes through the No. 10 sieve. Hence, if the
particle-size distribution of a soil is such that a certain percentage of the soil
particles is larger than 2 mm in diameter, a correction will be necessary. For
example, if soil B has a particle size distribution of 20% gravel, 10% sand,
30% silt, and 40% clay, the modified textural compositions are:
Figure 2.1 U.S. Department of Agriculture textural classification
On the basis of the preceding modified percentages, the USDA textural
classification is clay. However, because of the large percentage of gravel, it
may be called gravelly clay.
Several other textural classification systems are also used, but they are no
longer useful for civil engineering purposes.
2.3 Classification by Engineering Behavior
Although the textural classification of soil is relatively simple, it is
based entirely on the particle-size distribution. The amount and type of clay
minerals present in fine-grained soils dictate to a great extent their physical
properties. Hence, the soils engineer must consider plasticity, which results
from the presence of clay minerals, to interpret soil characteristics properly.
Because textural classification systems do not take plasticity into account
and are not totally indicative of many important soil properties, they are
inadequate for most engineering purposes. Currently, two more elaborate
classification systems are commonly used by soils engineers. Both systems
take into consideration the particle-size distribution and Atterberg limits.
They are the American Association of State Highway and Transportation
Officials (AASHTO) classification system and the Unified Soil
Classification System.
The AASHTO classification system is used mostly by state and county
highway departments. Geotechnical engineers generally prefer the Unified
system.
2.3.1 AASHTO Classification System
The AASHTO system of soil classification was developed in 1929 as
the Public Road Administration classification system. It has undergone
several revisions, with the present version proposed by the Committee on
Classification of Materials for Subgrades and Granular Type Roads of the
Highway Research Board in 1945 (ASTM designation D-3282; AASHTO
method M145).
The AASHTO classification in present use is given in Table 2.2. According
to this system, soil is classified into seven major groups: A-1 through A-7.
Soils classified under groups A-1, A-2, and A-3 are granular materials of
which 35% or less of the particles pass through the No. 200 sieve. Soils of
which more than 35% pass through the No. 200 sieve are classified under
groups A-4, A-5, A-6, and A-7. These soils are mostly silt and clay-type
materials. This classification system is based on the following criteria:
1. Grain size
a. Gravel: fraction passing the 75-mm (3-in.) sieve and retained on the
No. 10 (2-mm) U.S. sieve.
b. Sand: fraction passing the No. 10 (2-mm) U.S. sieve and retained
on the No. 200 (0.075-mm) U.S. sieve.
c. Silt and clay: fraction passing the No. 200 U.S. sieve.
2. Plasticity: The term silty is applied when the fine fractions of the soil have
a plasticity index of 10 or less. The term clayey is applied when the fine
fractions have a plasticity index of 11 or more.
3. If cobbles and boulders (size larger than 75 mm) are encountered, they are
excluded from the portion of the soil sample from which classification is
made. However, the percentage of such material is recorded.
To classify a soil according to Table 2.2, one must apply the test data from
left to right.
By process of elimination, the first group from the left into which the test
data fit is the correct classification. Figure 2.2 shows a plot of the range of
the liquid limit and the plasticity index for soils that fall into groups A-2, A-
4, A-5, A-6, and A-7.
To evaluate the quality of a soil as a highway subgrade material, one must
also incorporate a number called the group index (GI) with the groups and
subgroups of the soil.
This index is written in parentheses after the group or subgroup designation.
The group index is given by the equation
Table 5.1 Classification of Highway Subgrade Materials
Figure 2.2 Range of liquid limit and plasticity index for soils in groups A-2,
A-4, A-5, A-6, and A-7
2.3.2 Unified soil classification system
The original form of this system was proposed by Casagrande in 1942
for use in the airfield construction works undertaken by the Army Corps of
Engineers during World War II. In cooperation with the U.S. Bureau of
Reclamation, this system was revised in 1952. At present, it is used widely
by engineers (ASTM Test Designation D-2487). The Unified classification
system is presented in Table 2..
This system classifies soils into two broad categories:
1. Coarse-grained soils that are gravelly and sandy in nature with less than
50% passing through the No. 200 sieve. The group symbols start with a
prefix of G or S. G stands for gravel or gravelly soil, and S for sand or sandy
soil.
2. Fine-grained soils are with 50% or more passing through the No. 200
sieve. The group symbols start with prefixes of M, which stands for
inorganic silt, C for inorganic clay, or O for organic silts and clays. The
symbol Pt is used for peat, muck, and other highly organic soils.
Other symbols used for the classification are:
• W—well graded
• P—poorly graded
• L—low plasticity (liquid limit less than 50)
• H—high plasticity (liquid limit more than 50)
Figure2-3 Plasticity Chart
For proper classification according to this system, some or all of the
following information must be known:
1. Percent of gravel—that is, the fraction passing the 76.2-mm sieve and
retained on the No. 4 sieve (4.75-mm opening)
2. Percent of sand—that is, the fraction passing the No. 4 sieve (4.75-mm
opening) and retained on the No. 200 sieve (0.075-mm opening)
3. Percent of silt and clay—that is, the fraction finer than the No. 200 sieve
(0.075-mm opening)
Figure 2-4
4. Uniformity coefficient (Cu) and the coefficient of gradation (Cc)
5. Liquid limit and plasticity index of the portion of soil passing the No. 40
sieve.
The group symbols for coarse-grained gravelly soils are GW, GP, GM, GC,
GC-GM, GW-GM, GW-GC, GP-GM, and GP-GC. Similarly, the group
symbols for fine-grained soils are CL, ML, OL, CH, MH, OH, CL-ML, and
Pt.
More recently, ASTM designation D-2487 created an elaborate system to
assign group names to soils. These names are summarized in Figures 5.4,
5.5, and 5.6. In using these figures, one needs to remember that, in a given
soil,
• Fine fraction _ percent passing No. 200 sieve
• Coarse fraction _ percent retained on No. 200 sieve
• Gravel fraction _ percent retained on No. 4 sieve
• Sand fraction _ (percent retained on No. 200 sieve) _ (percent retained on
No. 4 sieve)
Figure 2-5
Figure 2-6
Figure 2-7
Figure 2-8
CHAPTER THREE
CASE STUDY
Three different soil samples were taken for analysis and classification
using the unified soil classification system.
Soil A, B, and C where taken as samples of different types. Experiments
were conducted on these soils to determine their class.
Soil A has a silty nature, soil B has a clayey nature, and soil C has sandy
nature.
Many tests were conducted in addition to the required tests to determine the
proper classification of these soils, these tests were:
1. Specific gravity.
2. Water content.
3. Sieve analysis.
4. Liquid limit.
5. Plastic limit.
The results are shown below.
3.1 Specific Gravity
Weight of every soil sample = 5 gm.
USoil A
Wt. sample (water + soil) = 96.97 gm
Wt. sample (water) = 93.82 gm
( ) 703.297.9682.935
5=
−−=sG
2.7 ≤ GRsR ≤ 2.703
silty soil
USoil B
Wt. sample (water + soil) = 88.71 gm
Wt. sample (water) = 85.55 gm
( ) 72.271.8855.855
5=
−−=sG
2.7 ≤ GRsR ≤ 2.74
USoil C
Wt. sample (water + soil) = 93.96 gm
Wt. sample (water) = 90.83 gm
( ) 67.296.9383.905
5=
−−=sG
2.65 ≤ GRsR ≤ 2.69
Sandy soil
3.2 Water content %
USoil A
WRwetR =61 gm
WRdryR =49 gm
W% = (61– 49)/49 *100% = 24.49%
USoil B
wRwetR=36
wRdryR=27
w% =(36–27)/27 *100% = 33.33%
USoil C
Dry
3.3 Liquid limit tests
Soil A:-
W% Wt. dry Wt. wet No. of blows
29.52 13.01 16.85 24
32.37 14.24 18.85 16
27.65 12.73 16.25 27
L.L =48
Soil B:-
W% Wt. dry Wt. wet No. of blows
50.09 11.06 16.6 21
45.92 7.23 10.55 29
53.68 7.34 11.28 16
L.L =28.5
Soil C
No liquid limit
3.4 Plastic Limit tests
U Soil A
Wt. container= 10.72 gm
Wt. (cont.+water+soil)= 17.41 gm
Wt. (cont.+dry soil)= 16.15 gm
Wt. (wet soil)= 17.41-10.72= 6.69 gm
Wt. dry soil= 16.15-10.72= 5.43 gm
W%=[(6.69-5.43)/5.43]*100%
PL=23.2%
USoil B
Wt. container=11.52 gm
Wt. (cont.+soil+water)=20.71 gm
Wt. (cont.+dry soil)=18.76 gm
Wt. wet soil=20.71-11.52=9.19 gm
Wt. dry soil=18.76-11.52=7.24 gm
W%=[(9.91-7.24)/7.24]*100%
PL=26.43%
USoil C
Non Plastic
3.5 Plasticity index
USoil A
PI = LL – PL
= 48.0 – 23.2 = 24.8
USoil B
PI = LL – PL
= 28.5 – 26.43 = 2.07
USoil C
Non Plastic
3.6 Sieve analysis tests
USoil A
Wt. of the total sample = 200 gm
%
passing
%
cumulative
% wt.
retained
Wt.
retained
Opening
dia. mm
Sieve no.
100 0 0 0 4.75 4
100 0 0 0 2.38 8
100 0 0 0 0.71 25
100 0 0 0 0.3 50
91.39 8.61 8.61 17.5 0.15 100
89.14 10.86 2.25 4.5 0.075 200
0 100 89.13 178 Pan
∑ of retained soil= 200.0 gm
USoil B
Wt. of the total sample = 200 gm
All passed sieve 200
USoil C
Wt. of the total sample = 200 gm
% passing %
cumulative
% wt.
retained
Wt.
retained
Opening
dia.
Sieve no.
92.1 7.9 7.9 16 4.75 4
79.8 20.2 12.3 25 2.38 8
44.64 55.36 35.16 70 0.71 25
31.59 68.41 13.05 26 0.3 50
3.56 96.44 28.03 56 0.15 100
1.05 98.95 2.51 5 0.075 200
0.045 99.955 1.005 2 Pan
∑ retained soil= 200.0 gm
10 1 0.1 0.01
0
20
40
60
80
100
Form graph
DR10 R= 0.178
DR30 R= 0.34
DR60R = 1.2
74.6178.02.1
10
60 ===DD
Cu
541.0178.02.1
34.0 2
1060
230 =
×=
×=
DDDCc
3.7 Soil classification according to USCS
USoil A
F200 = 89.14 > 50
It's Silty clay
L.L = 48 < 50
It's ML or CL or CL-ML
PI = 24.8
It's CL
USoil B
F200 = 100.00 > 50
L.L = 28 < 50
PI = 2.07
ML
USoil C
F200 = 1.05 < 50
It's Gravel or Sand
5.008.005.1100
1.92100
200
4 ≤=−−
=RR
It's sandy soil
F200 = 1.05 < 5
CRuR = 6.74 ≥ 6
CRc R= 0.541 ≤ 1
It's SP
CHAPTER FOUR
COMPUTER PROGRAM
A computer program using MATLAB 2009 program was designed
especially for soil classification using the unified soil classification system.
The computer program has the following user interface as shown in fig. 4.1.
Figure 4-1 user interface
Through the user interface, the necessary data are obtained and the sieve
data are loaded from an excel sheet file containing sieve number, opening
diameter, and weight of retained soil.
A sample of an empty excel sheet is shown in table 4-1.
Table 4-1 Excel sheet content Sieve no. Dia. mm Wt. retained gm
4 4.75 5 4 6 3.35 7 2.8 8 2.36
10 2 12 1.7 14 1.4 16 1.18 18 1 20 0.85 25 0.71 30 0.6 35 0.5 40 0.425 50 0.355 60 0.25 70 0.212 80 0.18
100 0.15 120 0.125 140 0.106 170 0.09 200 0.075 270 0.053
The results data obtained from a sieve analysis test are entered to an empty
excel sheet, the unwanted empty rows are omitted and the file is saved with
a unique name.
The weight of the soil retained on the pan is entered in the textbox in the
user interface in addition to the liquid limit (L.L.), plasticity index (P.I.).
The (Get Data) button then is clicked and the required excel sheet file is
selected.
The program uses these data to draw the original particle size distribution,
and also find the best fit curve to obtain D R60R, DR30R, and DR10R from the best fit
curve.
The computer program uses two best fit functions:
1. Exponential function DxBX CeeAy +×=
2. Power function 21 DxCxBxA+−+
Many functions were tested to see the most appropriate function to give the
best fit curve using trial and error method of sample sieve test results.
These two functions were found to give the best results for fitting the
particle distribution curves for the sieve analysis.
The computer program chooses the best fit function according the minimum
residual between the two functions using Minimum Square of residuals
regression.
Then the computer program draws the two best fit curves in addition to the
original curve.
The usual calculations are made to classify the soil as mentioned in chapter
two.
DR60R, DR30R, and DR10 Rare obtained and accordingly C RuR, CRcR are calculated and
showed in the user interface.
A table in the user interface also shows the results of the calculations needed
to obtain the percentage passing each sieve number.
There is a filed in the user interface also shows the residual of the two
functions and the best one to be used for this particular problem.
The last two fields in the user interface shows the classification of the soil
and the description of the soil.
The computer program was tested in solving an example of classification
problem as shown below.
Classification problem after (Das. 2006)
Sieve analysis problem is shown after (Das, 2006) was also analyzed using
the new program, the results of the computer program is show in figure 4.2.
Figure 4-2
Figure 4-3 user interface showing the results of classification problem
after (Das, 2006)
This is a good verification for the computer program that shows the way it
works.
The computer program now is used to classify the three soil samples
mentioned in chapter three.
1. USoil sample A
The sieve analysis results (as shown in chapter three) are entered in an excel
sheet as shown in table 4-2
Table 4-2 sieve analysis results for soil A Sieve no. Dia. mm Wt. retained gm
4 4.75 0 8 2.36 0.00
25 0.71 0.00 50 0.355 0.00
100 0.15 17.50 200 0.075 4.50 Pan - 178
Figure 4-4 user interface results for soil A classification
Since the soil is fine, no particle size distribution curve is drawn. Other
calculations are conducted and the soil was found to be CL with the soil
description as (The Soil is Fine, Clayey Soil, Low Plasticity) is shown in
the user interface, as shown in figure 4-4.
2. USoil sample B
Soil B has a particle size all passing no. 200 sieve. Which means that it is all
clay with L.L. = 28.5, and P.I. = 2.07.
Figure 4-5 user interface results for soil B classification
The soil classification is found by the computer program to be ML as
classified earlier in chapter three. The results are shown in figure 4-5 with
soil description as (The Soil is Fine, Silty Soil, Low Plasticity).
3. USoil sample C
Soil C sieve analysis results are entered in an excel sheet with data as shown
in table 4-3 below.
Table 4-2 sieve analysis results for soil C Sieve no. Dia. mm Wt. retained gm
4 4.75 16 8 2.36 25.00
25 0.71 70.00 50 0.355 26.00
100 0.15 56.00 200 0.075 5
Soil C is non plastic which means that liquid limit and plastic limit indices
could not be obtained. This is obvious since the soil is coarse and sandy in its
nature.
Figure 4-6 shows the user interface for Soil C with the plot of the original
particle distribution curve in addition to the best fit functions.
As could be seen, that the power function is the most suitable function for this
problem and has the less residual value, so it was used automatically by the
computer program to calculate the values of DR60R, DR30R, DR10R, CRcR, and C RuR as
shown below.
DR60R = 1.1164
DR30R = 0.39532
DR10R = 0.14797
CRuR = 7.5443
CRcR = 0.94605
Figure 4-6 user interface results for soil C classification
Comparing these values to the values obtained from the manual
classification method, it was found an acceptable agreement between the two
sets of values
DR60R = 1.2
DR30 R= 0.34
DR10 R= 0.178
CRuR = 6.74
CRcR = 0.541
The soil classification was obtained from the computer program as SP and
the soil description was (The Soil is Coarse, Sand, Poorly Graded).
CHAPTER FIVE
RESULTS AND DISCUSSION
Results obtained from the application of the computer program
reveals that soil classification can be easily made using a computer program.
The three types of soils chosen in this project were classified by using the
appropriate laboratory tests, then the same data were used as input data for
the computer program and the results were identical for the two
classifications, the manual classification and the classification by the
computer program.
The two curve fit functions gave a good smooth curve for the particle size
distribution when the most appropriate one is chosen.
CHAPTER SIX
CONCLUSIONS AND RECOMMENDATIONS
It is concluded that:
1- The computer program gave very good results on soil classification.
2- Using curve fit functions gave a smooth curve for the particle size
distribution which facilitates the estimation of D R60R, DR30R, DR10R, CRcR, and
CRuR.
3- The computer program could be used to classify various types of soils.
Recommendations for further studies are:
1- Other types of classification systems could be programmed to obtain
more general program.
2- Languages other than MATLAB could be used in the computer
programming.
3- Other curve fit functions could be used to enhance the particle
distribution curve.
References
1- R.F. Craig,2004, “Craig’s Soil Mechanics”, Spon Press.
2- Das, BRAJA M., 2006, “Principles of Geotechnical Engineering”,
FIFTH EDITION, Nelson, a division of Thomson Canada Limited.
3- Lambe, T. W., and R. V. Whitman, 1979, “Soil Mechanics”, John Wiley & Sons.
