Abstract: Assessment of geotechnical properties of the subsoil is necessary for generating relevant input for the design and construction of a foundation. It is significant for the future development in the area. The focus of this research is to investigate the preliminary geotechnical properties of the uncemented sandstone from Kati formation at Puncak Iskandar, Seri Iskandar. A series of basic soil tests, oedometer and direct shear box tests were carried out to obtain the soil parameters. The uncemented sandstone of Kati Formation was found to have well-graded and poorly graded sand distribution, depending on the location where the samples were obtained. The sand grains distribution was in a range of 82%-100% while, the specific gravity of the uncemented sandstone is in the range 2.65-2.86. The preconsolidation pressure for USB3 was 990 kPa indicating that the sandstone at USB3 sample had undergone 990 kPa of overburden pressure. The angle of friction for uncemented sandstone was ranging between 23.34°-32.92°.
Abstract: The Cone Penetration Test (CPT) is a common in-situ
test which generally investigates a much greater volume of soil more
quickly than possible from sampling and laboratory tests. Therefore,
it has the potential to realize both cost savings and assessment of soil
properties rapidly and continuously. The principle objective of this
paper is to demonstrate the feasibility and efficiency of using
artificial neural networks (ANNs) to predict the soil angle of internal
friction (Φ) and the soil modulus of elasticity (E) from CPT results
considering the uncertainties and non-linearities of the soil. In
addition, ANNs are used to study the influence of different
parameters and recommend which parameters should be included as
input parameters to improve the prediction. Neural networks discover
relationships in the input data sets through the iterative presentation
of the data and intrinsic mapping characteristics of neural topologies.
General Regression Neural Network (GRNN) is one of the powerful
neural network architectures which is utilized in this study. A large
amount of field and experimental data including CPT results, plate
load tests, direct shear box, grain size distribution and calculated data
of overburden pressure was obtained from a large project in the
United Arab Emirates. This data was used for the training and the
validation of the neural network. A comparison was made between
the obtained results from the ANN's approach, and some common
traditional correlations that predict Φ and E from CPT results with
respect to the actual results of the collected data. The results show
that the ANN is a very powerful tool. Very good agreement was
obtained between estimated results from ANN and actual measured
results with comparison to other correlations available in the
literature. The study recommends some easily available parameters
that should be included in the estimation of the soil properties to
improve the prediction models. It is shown that the use of friction
ration in the estimation of Φ and the use of fines content in the
estimation of E considerable improve the prediction models.
Abstract: Soft clays are defined as cohesive soil whose water
content is higher than its liquid limits. Thus, soil-cement mixing is
adopted to improve the ground conditions by enhancing the strength
and deformation characteristics of the soft clays. For the above
mentioned reasons, a series of laboratory tests were carried out to
study some fundamental mechanical properties of cement stabilized
soft clay. The test specimens were prepared by varying the portion of
ordinary Portland cement to the soft clay sample retrieved from the
test site of RECESS (Research Centre for Soft Soil). Comparisons
were made for both homogeneous and columnar system specimens
by relating the effects of cement stabilized clay of for 0, 5 and 10 %
cement and curing for 3, 28 and 56 days. The mechanical properties
examined included one-dimensional compressibility and undrained
shear strength. For the mechanical properties, both homogeneous and
columnar system specimens were prepared to examine the effect of
different cement contents and curing periods on the stabilized soil.
The one-dimensional compressibility test was conducted using an
oedometer, while a direct shear box was used for measuring the
undrained shear strength. The higher the value of cement content, the
greater is the enhancement of the yield stress and the decrease of
compression index. The value of cement content in a specimen is a
more active parameter than the curing period.