Presents here in the results of comparison between the theoretical equation stated by Huang and Menq and laboratory model tests used to study the bearing capacity of square footing on geogrid-reinforced loose sand by performing model tests. The effects of several parameters were studied in order to study the general behavior of improving the soil by using the geogrid. These parameters include depth of first layer of reinforcement, vertical spacing of reinforcement layers, number of reinforcement layers and types of reinforcement layers The results show that the theoretical equation can be used to estimate the bearing capacity of loose sand.

Bearing capacity of soil is an important factor in designing shallow foundations. It is directly related to foundation dimensions and consequently its performance. The calculations for obtaining the bearing capacity of a soil needs many varying parameters, for example soil type, depth of foundation, unit weight of soil, etc. which makes these calculation very variable–parameter dependent. This paper presents the results of comparison between the theoretical equation stated by Terzaghi and the Artificial Neural Networks (ANN) technique to estimate the ultimate bearing capacity of the strip shallow footing on sandy soils. The results show a very good agreement between the theoretical solution and the ANN technique. Results revealed that us

Abstract The present work aims to study the performance of reinforced compacted clay soil by sand columns stabilized with sodium silicate to obtain more solid columns than the surrounding soil. The experimental work was carried out by using a lab model to evaluate the performance of both the floating and end bearing sand columns. The results showed that the improvement ratio for the soil reinforced with sand columns stabilized with sodium silicate reached 390% for the type of floating columns and 438% for end bearing columns.

In real conditions of structures, foundations like retaining walls, industrial machines and platforms in offshore areas are commonly subjected to eccentrically inclined loads. This type of loading significantly affects the overall stability of shallow foundations due to exposing the foundation into two components of loads (horizontal and vertical) and consequently reduces the bearing capacity.

Based on a numerical analysis performed using finite element software (Plaxis 3D Foundation), the behavior of model strip foundation rested on dry sand under the effect of eccentric inclined loads with different embedment ratios (D/B) ranging from (0-1) has been explored. The results display that, the bearing capacity of st

Gypseous soils are distributed in many regions in the world including Iraq, which cover more than (31%) of the surface area of the country. Existence of these soils, always with high gypsum content, caused difficult problems to the buildings and strategic projects due to dissolution and leaching of the gypsum caused by the action of water flow through soil mass. For the study, the gypseous soil was brought from Bahr Al-Najaf, Al-Najaf Governorate which is located in the middle of Iraq. The model pile was embedded in gypseous soil with 42% gypsum content. Compression axial model pile load tests have been carried out for model pile embedded in gypseous soil at initial degree of saturation of (7%) before and after soil satu

In this paper, a shallow foundation (strip footing), 1 m in width is assumed to be constructed on fully saturated and partially saturated Iraqi soils, and analyzed by finite element method. A procedure is proposed to define the H – modulus function from the soil water characteristic curve which is measured by the filter paper method. Fitting methods are applied through the program (SoilVision). Then, the soil water characteristic curve is converted to relation correlating the void ratio and matric suction. The slope of the latter relation can be used to define the H – modulus function. The finite element programs SIGMA/W and SEEP/W are then used in the analysis. Eight nodded isoparametric quadrilateral elements are used for modeling

This research presents a method of using MATLAB in analyzing a nonhomogeneous soil (Gibson-type) by
estimating the displacements and stresses under the strip footing during applied incremental loading
sequences. This paper presents a two-dimensional finite element method. In this method, the soil is divided into a number of triangle elements. A model soil (Gibson-type) with linearly increasing modulus of elasticity with depth is presented. The influences of modulus of elasticity, incremental loading, width of footing, and depth of footing are considered in this paper. The results are compared with authors' conclusions of previous studies.

ABSTRACT: Ultimate bearing capacity of soft ground reinforced with stone column was recently predicted using various artificial intelligence technologies such as artificial neural network because of all the advantages that they can offer in minimizing time, effort and cost. As well as, most of applied theories or predicted formulas deduced analytically from previous studies were feasible only for a particular testing environment and do not match other field or laboratory datasets. However, the performance of such techniques depends largely on input parameters that really affect the target output and missing of any parameter can lead to inaccurate results and give a false indicator. In the current study, data were collected from previous rel