The study was carried out to find out a suitable numerical procedure for establishing a graphical presentation of the soil profile of a site using SPT values and grain size analysis data. MATLAB numerical tool was used for this purpose and the soil properties was estimated using established empirical correlations. A computer Software was developed where SPT values at borehole locations, percent of grain sizes, water table and GPS coordinates of the site were used as inputs, Rectangular grids in 2-D or 3-D space were created for interpolation or extrapolation of the gridded data in ‘meshgrid’ format. The output yielded intermittent SPT profile and the contour plot matrix for subsoil soil condition of a site. The output soil-profile is presented by a 3-D shaded surface plot that would be useful for preliminary selection of a project site, land use planning, zoning ordinances, pre-disaster planning, capital investment planning, Fifteen borehole data of SPT values and grain sizes along a 20 km stretch of ongoing Janjira approach road project of Padma multipurpose bridge in Madaripur district were used to verify the usability of the developed Software. Disturbed soil sample were collected up to depths of 19.5m depth in every 1.5m interval to perform grain size analysis test. Excel spreadsheet was used where more than 500 data including SPT-N values, percent sand and fines at depths, GPS coordinated, reduce level and ground water table. The soils at the site were predominantly alluvial deposits. All these data were used in MATLAB interactive environment for numerical computation, visualization, and programming. The purposes of the study were to find SPT contour profile and soil-profile of a particular alignment of the site and to extract borehole Log form SPT profile and soil-profile of a specific location of the alignment. Outcome of this study can be used in microzonation studies, site response analysis, calculation of bearing capacity of subsoils in the region and producing a number of parameters which are empirically related to SPT values.

1. MATLAB MODELLING OF SPT AND GRAIN SIZE DATA IN
PRODUCING SOIL PROFILE
CE 400: PROJECT AND THESIS
Submitted by-
Debojit Sarker
Student ID: 0704015
Supervised by-
Dr. Md. Zoynul Abedin
Professor,
Department of Civil Engineering,
BUET.

2. Objectives:
To develop a MATLAB computer model that could produce the
soil-profile at a particular location using GPS coordinates or
chainage location.
To validate the model using known soil profile data.
To use predicted borehole log in case studies of designing
practical problems (e.g. Pile Capacity and Liquefaction).

3. Project Site
Jajira Approach Road of Padma Multipurpose
Bridge Project in Madaripur district

4. Subsurface Investigation:
• Determining the nature of soil at the site and its stratification.
• Obtaining disturbed and undisturbed soil samples for visual identification and
appropriate laboratory tests.
• Determining the depth and nature of bedrock, if and when encountered.
• Performing some in situ field tests, such as Standard Penetration Test (SPT)
• Assessing any special construction problems with respect to the existing
structure(s) nearby
• Determining the position of the R.L. & water table.

5. Planning for Soil Exploration
Table-1 gives guidelines for initial
planning of borehole spacing. In our
study 15 borings were conducted
within 20KM chainage at Jajira
approach road of Padma
multipurpose bridge project.
Table 1: Spacing of Borings

6. Position of Boreholes
APBH 05
APBH 06
APBH07
APBH08
APBH09
APBH10
APBH11
APBH12
APBH13
APBH14
APBH15
APBH16
APBH17
APBH18
APBH19
Bangladesh Geological Survey indicates that the project site Jajira of Madaripur district, in general, is
underlain by recent alluvium. The Padma superficial alluvial river deposits typically comprise normally-
consolidated, low strength compressible clays, or silts and fine sands of low density.

7. Applicability and Usefulness of In-situ Tests

8. Standard Penetration Test
The test consists of the following:
Driving the standard split-barrel sampler of dimensions a
distance of 460 mm into the soil at the bottom of the boring.
Counting the number of blows to drive the sampler the
last two 150 mm distances ( total = 300 mm) to obtain the N
number.
Using a 63.5-kg driving mass (or hammer) falling “free”
from a height of 760 mm. several hammer configurations
are available.
Standard Dimensions of Standard Split SpoonSPT arrangements

9. Correlations for Standard Penetration Test
Cohesive
Cohesionless

10. Correlations for Standard Penetration Test
Prediction of pile capacity by SPT (after Shoospasha et. at. 2013)

11. Correlations for Standard Penetration Test
Skin Friction of pile:
Cohesive (clay):
α Method
Qs=α*Cu*p*ΔL
Sladen (1992):
α=C * ( eff/ Cu)^0.45ϭ
C=0.5 for driven piles
Cohesionless (sand) according
to mayerhof,1976:
fav=0.02*Pa*N-avg (for high
displacement driven pile)
fav=0.01*Pa*N-avg (for low
displacement driven pile)
Qs=p*L*fav
(p=peremeter of pile)
Pile end bearing capacity:
Cohesive (clay):
(Mayerhof)
Qp=9*Cu*Ap
(Ap=area of pile tip)
Cohesionless (sand):
Meyerhof(1976)
Qp=qp * Ap
qp=0.4*Pa*N*L/D <=
4*Pa*N
(N= avg value of SPT)
For Foundation design and analysis purpose (pile foundation)
Clay:
Visic(1977)
Qp=Ap * Cu * Nc*
Nc*=4/3*(ln(Irr)
+1)+3.1416/2 +1
O'Neil & Reese (1999)
Ir=347*(Cu/Pa) - 33 <= 300
Sand:
Briaud et al. (1985)
Qp=qp*Ap
qp=19.7*Pa*(N60)^0.36
Clay:
λ method, Vijayvergiya and
focht (1972)
fav= λ*( effective avgϭ
+2*Cu)
Qs=p*L*fav
p= perimeter of pile section
Sand:
Briaud et al. (1985)
fav= 0.224*pa*(N60 avg)^0.29
Pa = atmospheric pressure=100
KN/m^2

12. Correlations for Standard Penetration Test
For Foundation design and analysis purpose (Seismic Soil Liquefaction)

13. Grain Size Distribution
Soil Type Particle Size
Range, mm
Retained on Mesh
Size/ Sieve No.
Boulder
Cobble
Gravel:
Sand:
Silt
Clay
Coarse
Medium
Fine
Coarse
Medium
Fine
>300
300-75
75-19
19-9.5
9.5-4.75
4.75-2.00
2.00-0.425
0.425-0.075
0.075-0.002
<0.002
12”
3”
¾”
3/8”
No. 4
No. 10
No. 40
No. 200
---
---
Engineering Classification (For particles smaller than 75mm and
based on estimated weights)
Coarse grained soils
(More than 50% of
the material
retained on No. 200
sieve (0.075 mm)
Gravels (More than
50% of coarse
fraction retained on
No. 4 sieve (4.75
mm)
Clean gravels
Less than 5% fines
Gravel with fines
More than 12% fines
Sands (over 50% of
coarse fraction
smaller than 4.75
mm)
Clean Sands
Less than 5% fines
Sands with fines
More than 12% fines
Fine grained soils
(Over 50% of the
material smaller
than 0.075 mm)
Silts & Clays
WL < 50
Inorganic
Organic
Silts & Clays
WL > 50
Inorganic
Organic
Soils of high organic origin

14. Particle Size Distribution of Soil
Typical sieve analysis Graph [at APBH 13]

15. MATLAB
MATLAB®
is a high-level language and interactive environment for
numerical computation, visualization, and programming. Using
MATLAB, you can analyze data, develop algorithms, and create
models and applications.
The language, tools, and built-in math functions enable you to
explore multiple approaches and reach a solution faster than with
spreadsheets or traditional programming languages, such as C/C++
or Java™
.

16. MATLAB R2013a Win8 screenshot:

17. Input method for SPT profile (MS Excel
Spreadsheet):
chainage
- depth
17600 18600 19600 20100 20600 21100 21600 24100 24582 25100 25600 26600 27100 27600
1.5 4 5 5 5 6 5 2 5 5 5 5 4 6 10
3 4 5 3 3 20 5 6 17 17 3 4 7 1 12
4.5 6 6 26 16 18 33 5 10 9 13 3 2 9 11
6 10 7 27 31 12 31 24 6 10 14 11 15 5 3
7.5 11 7 31 26 28 30 19 8 11 12 13 16 18 11
9 11 8 30 15 29 9 23 11 26 16 13 11 16 12
10.5 12 2 32 17 24 12 32 12 22 14 24 18 9 32
12 17 15 33 15 21 13 35 22 24 9 23 38 14 14
13.5 15 37 32 14 20 14 20 24 18 4 19 31 19 16
15 29 29 31 26 32 11 18 23 21 5 23 14 13 21
16.5 27 30 38 24 43 23 25 7
18 30 16 42 23 34 22 22 42
19.5 26 21 46 22 39 21 19 25

18. SPT contour profile:
Figure : SPT contour profile
from chainage 17600 [APBH 05] to 27600 [APBH 19], up to 19.5m depth

19. Input method for soil-profile (MS Excel
Spreadsheet):
APBH-05 APBH-06 APBH-07 APBH-08 APBH-09 APBH-10 APBH-11 APBH-12 APBH-13 APBH-14
Start End Avg
Chainage 17600 18600 19600 20100 20600 21100 21600 24100 24582 25100
Sand % Fine % Sand % Fine % Sand % Fine % Sand % Fine % Sand % Fine % Sand % Fine % Sand % Fine % Sand % Fine % Sand % Fine % Sand % Fine %
1.35 1.8 1.35 D1 86 14 92 8 94 6 90 10 86 14 94 6 15 85 18 82 8 92 14 86
2.85 3.3 3.075 D2 93 7 83 17 94 6 92 8 93 7 94 6 87 13 86 14 94 6 4 96
4.35 4.8 4.575 D3 94 6 84 16 86 14 93 7 87 13 82 18 94 6
5.85 6.3 6.075 D4 91 9 92 8 89 11 92 8 92 8 91 9 94 6 83 17
7.35 7.82 7.585 D5 84 16 88 12 88 12 94 6 90 10 94 6 93 7 87 13
8.85 9.3 9.075 D6 87 13 87 13 88 12 91 9 95 5
10.35 10.8 10.575 D7 88 12 89 11 91 9 87 13 90 10 92 8 88 12 2 98
11.85 12.3 12.075 D8 90 10 85 15 92 8 94 6 91 9 90 10 91 9 63 37 92 8 20 80
13.35 13.8 13.575 D9 85 15 89 11 87 13 89 11 91 9 86 14 63 37 17 83
14.85 15.3 15.075 D10 89 11 90 10 87 13 90 10 89 11 88 12 84 16 94 6 17 83
16.35 16.8 16.575 D11 92 8 90 10 92 8 90 10 90 10 84 16 10 90
17.85 18.3 18.075 D12 96 4 95 5 67 33 92 8 87 13 89 11 90 10
19.35 19.8 19.575 D13 94 6 88 12 88 12 92 8

20. Soil-profile
(from chainage 17600 to 27600, up to 19.5m depth)

21. Predicted Borehole Log
(At chainage 26100)
Location
Latitude (deg) 23.4009
Longitude (deg) 90.1735
0 0 cohesive very soft N/A 0 0
1.5 5 cohesive soft N/A 46.2 23
3 6 cohesive soft N/A 48.8 42
4.5 3 cohesive soft N/A 39.9 54
6 13 cohesionless medium 0.63 N/A 66
7.5 15 cohesionless medium 0.64 N/A 79
9 12 cohesionless medium 0.55 N/A 91
10.5 21 cohesionless dense 0.7 N/A 103
12 31 cohesionless dense 0.83 N/A 115
13.5 25 cohesionless dense 0.72 N/A 128
15 19 cohesionless medium 0.61 N/A 140
16.5
18
19.5
effectivestress
γ (kN/m^2) 15
γ sat
(kN/m^2)
18
RelativeDensity
UndrainedShear
Strength(kPa)
GraphicLog
Depth(meter)
SampleType
SampleNumber
BlowCounts
(blows/foot)
SoilType
Consistency
Groundwater Depth (m):
2.5
Elevation(m) PWD:
5.804
Total Depth of Boring:
15
Project Number:Project: Client: Boring No.
Address: Madaripur
Position:
Chainage: 26100
0
5
6
3
13
15
12
21
31
25
19
0
1.5
3
4.5
6
7.5
9
10.5
12
13.5
15
16.5
18
19.5

22. The ultimate load-carrying
capacity Qu of a pile is given
by the equation :
Qu = Qp +Qs
Where ,
Qp = Load carrying capacity
of the pile point
Qs = Frictional resistance
(skin friction) derived from
the soil-pile interface.
Allowable pile capacity,
Qa = Qu/ F.S.
Estimating pile capacity (at chainage 21100)

23. Liquefaction Potential Index (at chainage 21100)

24. Summary
 The developed MATLAB model can predict an intermittent borehole log with reasonable
accuracy.
 The developed model gives SPT contours that may be used to identify the soil spatial
stiffness.
 The program yields grain size surface plots that may be used to identify the soil profile.
 The estimation of pile capacity suggests that the predicted borehole estimates the SPT
values well.
 The variation in liquefaction potential suggests that the model be refined for grain size
estimation.

25. Thank You