Abstract

A significant stage in geotechnical engineering is to establish geotechnical properties of soil models to predict the most important soil properties such as unconfined compressive strength (UCS) and compression index (Cc) because they are the main parameters in the state design of the footings, pavements, or stability assessment of existing structures or slopes. This study is focused on developing models to predict the compressive strength and Cc for the clay soils as a function of Atterberg limits, natural moisture content, dry density, void ratio, and fine content (passing ≤ 0.075 mm). The UCS of the soils ranged from 24 to 340 kPa and was quite accurately quantified using the laboratory-tested data and data collected from published research studies. The Cc of the soils varied between 0.0878 to 0.8317, which was also correlated as a function of easy measurable soil properties such as Atterberg limits, natural moisture content, density, void ratio, and fine contents (percentage passing sieve number 200). A wide experimental test results (a total of 253 tested soils) were combined with more than 350 data collected from different academic research studies, and total data were statistically analyzed and modeled. In the modeling process, the most relevant parameters affecting the compressive strength and Cc of soils incorporation ratio (6–41 % of moisture content), plasticity index (7–72 %), dry density (11–19 kN/m3), and fine content (0–100 %). According to the correlation determination, mean absolute error, and the root mean square error, the compressive strength and Cc of soil can be well predicted in terms of liquid limit, plasticity index, moisture content, dry density, void ratio, and percentage passing sieve No. 200 (75 µm) using linear simulation techniques. The sensitivity investigation concludes that the dry density and moisture content are the most important parameters for the prediction of the compressive strength and Cc, respectively, with the training data set.

References

1.
Surendra
R.
and
Gurcharan
D.
, “
Statistical Models for the Prediction of Shear Strength Parameters at Sirsa, India
,”
International Journal of Civil and Structural Engineering
4
, no. 
4
(September
2014
):
483
498
, https://doi.org/10.6088/ijcser.201404040002
2.
Ojuri
O. O.
, “
Predictive Shear Strength Models for Tropical Lateritic Soils
,”
Journal of Engineering
2013
(February
2013
): 595626, https://doi.org/10.1155/2013/595626
3.
Cao
J.
,
Gao
J.
,
Rad
H. N.
,
Mohammed
A. S.
,
Hasanipanah
M.
, and
Zhou
J.
, “
A Novel Systematic and Evolved Approach Based on XGBoost-Firefly Algorithm to Predict Young’s Modulus and Unconfined Compressive Strength of Rock
,”
Engineering with Computers
(January
2021
):
1
17
, https://doi.org/10.1007/s00366-020-01241-2
4.
O’Neill
M. W.
and
Yoon
G.
, “
Engineering Properties of Overconsolidated Pleistocene Soils of Texas Gulf Coast
,”
Transportation Research Record
1479
(November
1995
):
81
88
.
5.
Mohammed
A. S.
and
Vipulanandan
C.
, “
Compressive and Tensile Behavior of Polymer Treated Sulfate Contaminated CL Soil
,”
Geotechnical and Geological Engineering
32
, no. 
1
(September
2014
):
71
83
, https://doi.org/10.1007/s10706-013-9692-9
6.
Mohammed
A.
, “
Property Correlations and Statistical Variations in the Geotechnical Properties of (CH) Clay Soils
,”
Geotechnical and Geological Engineering
(November
2017
):
1
16
, https://doi.org/10.1007/s10706-017-0418-2
7.
Sivaruban
N.
, “
Construction and Maintenance Issues Related to Transportation Infrastructure
” (PhD diss.,
University of Houston
,
2008
).
8.
Park
H. I.
and
Lee
S. R.
, “
Evaluation of the Compression Index of Soils Using an Artificial Neural Network
,”
Computers and Geotechnics
38
, no. 
4
(June
2011
):
472
481
, https://doi.org/10.1016/j.compgeo.2011.02.011
9.
Mohammadzadeh
D. S.
,
Kazemi
S.-F.
,
Mosavi
A.
,
Nasseralshariati
E.
, and
Tah
J. H. M.
, “
Prediction of Compression Index of Fine-Grained Soils Using a Gene Expression Programming Model
,”
Infrastructures
4
, no. 
2
(May
2019
): 26, https://doi.org/10.3390/infrastructures4020026
10.
Mousavi
S. M.
,
Alavi
A. H.
,
Gandomi
A. H.
, and
Mollahasani
A.
, “
Nonlinear Genetic-Based Simulation of Soil Shear Strength Parameters
,”
Journal of Earth System Science
120
, no. 
6
(January
2011
):
1001
1022
, https://doi.org/10.1007/s12040-011-0119-9
11.
Westerberg
B.
,
Müller
R.
, and
Larsson
S.
, “
Evaluation of Undrained Shear Strength of Swedish Fine-Grained Sulphide Soils
,”
Engineering Geology
188
(April
2015
):
77
87
, https://doi.org/10.1016/j.enggeo.2015.01.007
12.
Obasi
N. L.
and
Anyaegbunam
A. J.
, “
Correlation of the Undrained Shear Strength
,”
Nigerian Journal of Technology
24
, no. 
2
(
2005
):
1
11
.
13.
Goktepe
A. B.
,
Altun
S.
,
Altintas
G.
, and
Tan
O.
, “
Shear Strength Estimation of Plastic Clays with Statistical and Neural Approaches
,”
Building and Environment
43
, no. 
5
(May
2008
):
849
860
, https://doi.org/10.1016/j.buildenv.2007.01.022
14.
Jain
R.
,
Jain
P. K.
, and
Bhadauria
S. S.
, “
Computational Approach to Predict Soil Shear Strength
,”
International Journal of Engineering Science and Technology
2
, no. 
8
(
2010
):
3874
3885
.
15.
Hossain
M. S.
and
Kim
W. S.
, “
Estimation of Subgrade Resilient Modulus for Fine-Grained Soil from Unconfined Compression Test
,”
Transportation Research Record
2473
, no. 
1
(January
2015
):
126
135
, https://doi.org/10.3141/2473-15
16.
Mozumder
R. A.
and
Laskar
A. I.
, “
Prediction of Unconfined Compressive Strength of Geopolymer Stabilized Clayey Soil Using Artificial Neural Network
,”
Computers and Geotechnics
69 (September
2015
):
291
300
, https://doi.org/10.1016/j.compgeo.2015.05.021
17.
Zaimoglu
A. S.
, “
Optimization of Unconfined Compressive Strength of Fine-Grained Soils Modified with Polypropylene Fibers and Additive Materials
,”
KSCE Journal of Civil Engineering
19
, no. 
3
(February
2015
):
578
582
, https://doi.org/10.1007/s12205-015-1425-6
18.
Sharma
L. K.
and
Singh
T. N.
, “
Regression-Based Models for the Prediction of Unconfined Compressive Strength of Artificially Structured Soil
,”
Engineering with Computers
34
, no. 
1
(July
2018
):
175
186
, https://doi.org/10.1007/s00366-017-0528-8
19.
Linares-Unamunzaga
A.
,
Perez-Acebo
H.
,
Rojo
M.
, and
Gonzalo-Orden
H.
, “
Flexural Strength Prediction Models for Soil–Cement from Unconfined Compressive Strength at Seven Days
,”
Materials
12
, no. 
3
(January
2019
): 387, https://doi.org/10.3390/ma12030387
20.
Ahmed
C.
,
Mohammed
A.
, and
Saboonchi
A.
, “
ArcGIS Mapping, Characterisations and Modelling the Physical and Mechanical Properties of the Sulaimani City Soils, Kurdistan Region, Iraq
,”
Geomechanics and Geoengineering
(May
2020
):
1
-
14
, https://doi.org/full/10.1080/17486025.2020.1755464
21.
Ahmed
C.
,
Mohammed
A.
, and
Tahir
A.
, “
Geostatistics of Strength, Modeling and GIS Mapping of Soil Properties for Residential Purpose for Sulaimani City Soils, Kurdistan Region, Iraq
,”
Modeling Earth Systems and Environment
6
(January
2020
):
1
15
, https://doi.org/10.1007/s40808-019-00659-y
22.
Tiwari
B.
and
Ajmera
B.
, “
A New Correlation Relating the Shear Strength of Reconstituted Soil to the Proportions of Clay Minerals and Plasticity Characteristics
,”
Applied Clay Science
53
, no. 
1
(July
2011
):
48
57
, https://doi.org/10.1016/j.clay.2011.04.021
23.
Azzouz
A. S.
,
Krizek
R. J.
, and
Corotis
R. B.
, “
Regression Analysis of Soil Compressibility
,”
Soils and Foundations
16
, no. 
2
(June
1976
):
19
29
, https://doi.org/10.3208/sandf1972.16.2_19
24.
Yu
C.
,
Koopialipoor
M.
,
Murlidhar
B. R.
,
Mohammed
A. S.
,
Armaghani
D. J.
,
Mohamad
E. T.
, and
Wang
Z.
, “
Optimal ELM–Harris Hawks Optimization and ELM–Grasshopper Optimization Models to Forecast Peak Particle Velocity Resulting from Mine Blasting
,”
Natural Resources Research
(February
2021
):
1
16
, https://doi.org/10.1007/s11053-021-09826-4
25.
Mohammadzadeh
S. D.
,
Bazaz
J. B.
,
Vafaee Jani Yazd
S. H.
, and
Alavi
A. H.
, “
Deriving an Intelligent Model for Soil Compression Index Utilizing Multi-Gene Genetic Programming
,”
Environmental Earth Sciences
75
, no. 
3
(January
2016
): 262, https://doi.org/10.1007/s12665-015-4889-2
26.
Mohammadzadeh
D.
,
Bazaz
J. B.
, and
Alavi
A. H.
, “
An Evolutionary Computational Approach for Formulation of Compression Index of Fine-Grained Soils
,”
Engineering Applications of Artificial Intelligence
33
(August
2014
):
58
68
, https://doi.org/10.1016/j.engappai.2014.03.012
27.
Sridharan
A.
and
Nagaraj
H. B.
, “
Compressibility Behaviour of Remoulded, Fine-Grained Soils and Correlation with Index Properties
,”
Canadian Geotechnical Journal
37
, no. 
3
(June
2000
):
712
722
, https://doi.org/10.1139/t99-128
28.
Yoon
G. L.
and
Kim
B. T.
, “
Regression Analysis of Compression Index for Kwangyang Marine Clay
,”
KSCE Journal of Civil Engineering
10
, no. 
6
(November
2006
):
415
418
, https://doi.org/10.1007/BF02823980
29.
Ozer
M.
,
Isik
N. S.
, and
Orhan
M.
, “
Statistical and Neural Network Assessment of the Compression Index of Clay-Bearing Soils
,”
Bulletin of Engineering Geology and the Environment
67
, no. 
4
(October
2008
):
537
545
, https://doi.org/10.1007/s10064-008-0168-8
30.
Standard Test Method for Particle-Size Distribution (Gradation) of Fine-Grained Soil Using the Sedimentation (Hydrometer) Analysis
, ASTM D7928-17 (
West Conshohocken, PA
:
ASTM International
, approved May 1,
2017
), https://doi.org/10.1520/D7928-17
31.
Vipulanandan
C.
and
Mohammed
A. S.
, “
3-Dimension Stresses and New Failure Model to Predict Behavior of Clay Soils in Various Liquid Limit Ranges
,”
Arabian Journal of Geosciences
14
, no. 
3
(January
2021
):
1
13
, https://doi.org/10.1007/s12517-021-06553-1
32.
Mahmood
W.
and
Mohammed
A.
, “
Hydraulic Conductivity, Grain Size Distribution (GSD) and Cement Injectability Limits Predicted of Sandy Soils Using Vipulanandan Models
,”
Geotechnical and Geological Engineering
38
, no. 
2
(December
2020
):
2139
2158
, https://doi.org/10.1007/s10706-019-01153-z
33.
Mahmood
W.
and
Mohammed
A.
, “
New Vipulanandan p-q Model for Particle Size Distribution and Groutability Limits for Sandy Soils
,”
Journal of Testing and Evaluation
48
, no. 
5
(September
2020
):
3695
3712
. https://doi.org/10.1520/JTE20180606
34.
Mohammed
A.
and
Vipulanandan
C.
, “
Testing and Modeling the Short-Term Behavior of Lime and Fly Ash Treated Sulfate Contaminated CL Soil
,”
Geotechnical and Geological Engineering
33
, no. 
4
(May
2015
):
1099
1114
, https://doi.org/10.1007/s10706-015-9890-8
35.
Mohammed
A.
and
Mahmood
W.
, “
Vipulanandan Failure Models to Predict the Tensile Strength, Compressive Modulus, Fracture Toughness and Ultimate Shear Strength of Calcium Rocks
,”
International Journal of Geotechnical Engineering
15
, no. 
2
(May
2021
):
129
139
, https://doi.org/10.1080/19386362.2018.1468663
36.
Standard Test Methods for One-Dimensional Consolidation Properties of Soils Using Incremental Loading
, ASTM D2435/D2435M-11(2020) (
West Conshohocken, PA
:
ASTM International
, approved May 1,
2011
), https://doi.org/10.1520/D2435_D2435M-11R20
37.
Standard Test Methods for Laboratory Determination of Density and Unit Weight of Soil Specimens
, ASTM D7263-21 (
West Conshohocken, PA
:
ASTM International
, approved January 21, 2009), https://doi.org/10.1520/D7263-21
38.
Standard Test Methods for Laboratory Determination of Water (Moisture) Content of Soil and Rock by Mass
, ASTM D2216-19 (
West Conshohocken, PA
:
ASTM International
, approved March 19,
2019
), https://doi.org/10.1520/D2216-19
39.
Standard Test Method for Unconfined Compressive Strength of Cohesive Soil
, ASTM D2166/D2166M-16 (
West Conshohocken, PA
:
ASTM International
, approved July 1,
2016
), https://doi.org/10.1520/D2166_D2166M-16
40.
Standard Test Methods for Liquid Limit, Plastic Limit, and Plasticity Index of Soils
, ASTM D4318-17e1 (
West Conshohocken, PA
:
ASTM International
, approved April 17,
2018
), https://doi.org/10.1520/D4318-17E01
41.
Yılmaz
I.
, “
Evaluation of Shear Strength of Clayey Soils by Using Their Liquidity Index
,”
Bulletin of Engineering Geology and the Environment
59
, no. 
3
(December
2000
):
227
229
, https://doi.org/10.1007/s100640000056
42.
Mohammed
A.
,
Rafiq
S.
,
Sihag
P.
,
Kurda
R.
,
Mahmood
W.
,
Ghafor
K.
, and
Sarwar
W.
, “
ANN, M5P-Tree and Nonlinear Regression Approaches with Statistical Evaluations to Predict the Compressive Strength of Cement-Based Mortar Modified with Fly Ash
,”
Journal of Materials Research and Technology
9
, no. 
6
(December
2020
):
12416
12427
, https://doi.org/10.1016/j.jmrt.2020.08.083
43.
Sihag
P.
,
Tiwari
N. K.
, and
Ranjan
S.
, “
Modelling of Infiltration of Sandy Soil Using Gaussian Process Regression
,”
Modeling Earth Systems and Environment
3
, no. 
3
(August
2017
):
1091
1100
, https://doi.org/10.1007/s40808-017-0357-1
44.
Mohammed
A.
,
Mahmood
W.
, and
Ghafor
K.
, “
TGA, Rheological Properties with Maximum Shear Stress and Compressive Strength of Cement-Based Grout Modified with Polycarboxylate Polymers
,”
Construction and Building Materials
235
(February
2020
): 117534, https://doi.org/10.1016/j.conbuildmat.2019.117534
45.
Usluogullari
O. F.
and
Vipulanandan
C.
, “
Stress-Strain Behavior and California Bearing Ratio of Artificially Cemented Sand
,”
Journal of Testing and Evaluation
39
, no. 
4
(July
2011
):
637
645
, https://doi.org/10.1520/JTE103165
46.
Vipulanandan
C.
,
Ahossin Guezo
Y. J.
, and
Bilgin
Ö.
, “
Geotechnical Properties of Marine and Deltaic Soft Clays
,”
Advances in Measurement and Modeling of Soil Behavior
(October
2007
):
1
13
, https://doi.org/10.1061/40917(236)5
47.
Edil
T. B.
,
Benson
C. H.
,
Li
L.
,
Mickelson
D. M.
, and
Camargo
F. F.
,
Comparison of Basic Laboratory Test Results with More Sophisticated Laboratory and In Situ Tests Methods on Soils in Southeastern Wisconsin, No. WHRP 09–02
(Madison, WI: University of Wisconsin,
2009
).
48.
Qadir
W.
,
Ghafor
K.
, and
Mohammed
A.
, “
Characterizing and Modeling the Mechanical Properties of the Cement Mortar Modified with Fly Ash for Various Water-to-Cement Ratios and Curing Times
,”
Advances in Civil Engineering
2019
(June
2019
): 7013908, https://doi.org/10.1155/2019/7013908
49.
Vipulanandan
C.
and
Mohammed
A. S.
, “
Hyperbolic Rheological Model with Shear Stress Limit for Acrylamide Polymer Modified Bentonite Drilling Muds
,”
Journal of Petroleum Science and Engineering
122
(October
2014
):
38
47
, https://doi.org/10.1016/j.petrol.2014.08.004
50.
Vipulanandan
C.
and
Mohammed
A.
, “
Effect of Drilling Mud Bentonite Contents on the Fluid Loss and Filter Cake Formation on a Field Clay Soil Formation Compared to the API Fluid Loss Method and Characterized Using Vipulanandan Models
,”
Journal of Petroleum Science and Engineering
189
(June
2020
): 107029, https://doi.org/10.1016/j.petrol.2020.107029
51.
Burhan
L.
,
Ghafor
K.
, and
Mohammed
A.
, “
Enhancing the Fresh and Hardened Properties of the Early Age Concrete Modified with Powder Polymers and Characterized Using Different Models
,”
Advances in Civil Engineering Materials
9
, no. 
1
(April
2020
):
227
249
, https://doi.org/10.1520/ACEM20190087
52.
Ghafor
K.
,
Mahmood
Q.
,
Qadir
W.
, and
Mohammed
A.
, “
Effect of Particle Size Distribution of Sand on Mechanical Properties of Cement Mortar Modified with Microsilica
,”
ACI Materials Journal
117
, no. 
1
(
2020
):
47
60
, https://doi.org/10.14359/51719070
53.
Vipulanandan
C.
and
Mohammed
A.
, “
XRD and TGA, Swelling and Compacted Properties of Polymer Treated Sulfate Contaminated CL Soil
,”
Journal of Testing and Evaluation
44
, no. 
6
(November
2016
):
2270
2284
, https://doi.org/10.1520/JTE20140280
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