Maher Omar

Compaction characteristics of granular soils in United Arab Emirates

Most of the topsoils encountered in United Arab Emirates and in the Arabian Peninsula are granular soils with small percentages of silt and clay. Determination of the compaction characteristics of such soils is an essential task in preparing for construction work. The accumulating experience over many years of soil testing in our laboratories suggested that there exists an underlying trend that governs the compaction characteristics of such soils. As such, a study was undertaken to assess the compaction characteristics of such soils and to develop the governing predictive equations. For the purposes of this study, 311 soil samples were collected from various locations in the United Arab Emirates, and tested for various including grain-size distribution, liquid limit, plasticity index, specific gravity of soil solids, maximum dry density of compaction, and optimum moisture content following ASTM D 1557-91 standard procedure C. Following the development of the predictive equations, a new set of 43 soil samples were collected and their compaction results were used to test the validity of predictive model. The range of variables for these soils were as follows: percent retained on US sieve #4 (R#4): 0–68; Percent passing US sieve #200 (P#200): 1–26; Liquid limit: 0–56; Plasticity index: 0–28; Specific gravity of soil solids: 2.55–2.8.Based on the compaction tests results, multiple regression analyses were conducted to develop mathematical models and nomographic solutions to predict the compaction properties of soils. The results indicated that the nomographs could predict well the maximum dry density within ±5% confidence interval and the optimum moisture content within ±3%.

Modeling Time Dependent Swell of Clays Using Sequential Artificial Neural Networks

This work attempts to implement sequential artificial neural networks (SANN) for modeling time dependent swell of expansive soils. Forty soils with varying properties were selected and tested for expansion under three different initial applied pressures (25, 100, and 200 kPa) to develop the database used for training and testing the neural network. Consequently, a total of 120 swell tests were performed to produce over 1800 data points. The input parameters used in the network included the soil initial dry unit weight and water content, initial applied pressure, percent clay content, plasticity index and the percent swell at time i. The network was programmed to process this information and produce the percent swell at time i + 1. The study demonstrates that there is a possibility to develop a general SANN model that can predict time dependent swell, based on basic soil properties, with relatively high accuracy (correlation r2 = 0.975 between predicted and observed data).

Empirical correlations for predicting strength properties of rocks – United Arab Emirates

In United Arab Emirates (UAE) and the Arabian Peninsula, most of the rocks are sedimentary in nature and mainly consist of sandstone, mudstone and crystalline gypsum. The identification of rock properties is beneficial for the construction work and design projects. Unconfined compressive strength (UCS) is the most frequently used method and is usually determined from laboratory tests, among the different strength parameters. A study was undertaken to assess estimating strength parameters from empirical correlations of such rocks and to develop the governing predictive equations. In order to conduct this study, 420 soil samples were collected from various locations in the UAE and were tested for various observations including point load test (Is(50)) and ultrasonic velocity (USV) through its pulse velocity. The results indicated that the nomographs could predict well the unconfined compressive strength within ± 10% confidence interval for both Is(50) and USV. The accumulating experience over many years of rock testing in our laboratories and other geotechnical investigation laboratories in the area suggested that there exists an underlying trend that governs the strength characteristics of such rocks.

Analysis of strip footings resting on reinforced granular trench by the finite element method

Abstract Numerous methods have been used in the past and recent time to enhance the bearing capacity of the soils, depending on the type of the structure, available equipments, and the properties of the soil. The use of granular trench (two-dimensional plane strain condition of stone column) is one of these methods. This paper provides a finite element method to model soft cohesive soil, granular trench soil, and the reinforcement material by using a computer program called (SIGMA/W). The behavior of both cohesive and granular soils is simulated by nonlinear-elastic soil model (hyperbolic model), while the linear-elastic model was used to simulate the reinforcement material.The angle of friction of trench soil, modulus of elasticity of reinforcement material, depth, width and shape of the granular trench, locations, and number of the reinforcement layers were varied. The sloped granular trench was analyzed in two cases; lined and unlined conditions. The results showed that use of granular trench beneath foundations will increase the bearing capacity and reduce the settlement. Moreover, using of polymers as a reinforcement material has a significant effect on both bearing capacity and settlement.For both reinforced and unreinforced granular trenches, the depth ratio has an important effect on the settlement ratio, which decreases with the increase of depth ratio. The best practical value for the depth ratio was found to be equal to 2. Making a trench with a width (X) larger than the foundation width (B) also decreases the settlement, and the best effect occurs when the width ratio (X/B) equals to 0.75.

Evaluation of Methods Used for Reducing Heavy Metal Leaching from Sandy Soil

Excessive heavy metal content in sandy soils poses risk to human health and the environment. The rapid expansion of urban areas makes it imperative to manage contaminated sites so that land can be reclaimed for beneficial purposes. Several methods have been proposed to control the leaching of heavy metals from contaminated soils. In this study, four techniques for mobilization and immobilization of metals in sandy soil were compared. The assessed mobilization techniques included chemical extraction using aqueous solutions of acids and chelating agents as well as biochemical extraction using sulfur-oxidizing microorganisms. The evaluated immobilization techniques included lime-cement-pozzolan stabilization and natural-zeolite stabilization. The immobilization techniques do not involve removing metals from soil and instead focus on addition of substances to the soil that alter its composition, volume, and properties. On the other hand, mobilization techniques entail the removal of metals from soil and changes in the soil properties. The findings confirmed that both mobilization and immobilization are effective in controlling the leaching of metals from sandy soils and thereby minimize the risk to the environment and human health. However, the appropriate technique for application at a given site should be chosen on a case-by-case basis, while accounting for the economic and technical feasibility, the necessary level of cleanup, and effect of residual metals on human health and the environment.

Impact of surface ocean acidification on the CO2 absorption rate

The rising level of atmospheric CO2 and consequently the acidification of the surface ocean affect the CO2 absorption rate. However, there are no mathematical models to describe the impacts of acidification on the rate of CO2 absorption. Therefore, the objective of this study was to develop simple mathematical models to describe the dependence of the CO2 absorption rate on the pH of the surface ocean. The developed models predict that the CO2 absorption rate is enhanced with acidification directly proportional to the increase in the abundance of * 23 H CO in the surface ocean. In addition, the models predict that the increasing rate of CO2 absorption reflects the increasing rate of increase of CO2 in the atmosphere.

Probabilistic-based assessment of the bearing capacity of shallow foundations

In this paper, a probabilistic distribution for the bearing capacity and safety factor of shallow foundations is proposed to account for the variability and randomness of the soil strength properties and applied loads. A probabilistic-based model is developed to assess the bearing capacity of shallow foundations. A Monte Carlo simulation is performed to infer probabilistic descriptions of the bearing capacity of shallow foundations. The effects of the variation in strength and load random variables on the variation of the bearing capacity and the safety factor are studied. The generalized extreme value reduced to type II extreme distribution was proved to be best suited in describing the variability in both the bearing capacity of shallow foundations and the safety factor. The reliability index and the deterministic safety factor are compared. A risk-based safety factor for the ultimate bearing capacity of shallow foundations is proposed and assessed.

Perceptions on effective engineering education

In the context of engineering education, excellence is that quality which gives a special value and worth to a particular program. Excellence in engineering education (EEEdu) means different things to different people, but in this paper, EEEdu is considered to be a quality that is achievable through geniune commitment to teacher and student development, program development, teaching innovations, and community service. Using the broad definition of EEEdu, certain perceptions and perspectives of EEEdu from the points of view of: (1) the teacher; (2) the student; (3) the community; (4) the employers; and (5) professional engineering organizations were assessed using a survey designed for this purpose. The results support the idea that engineering programs need to be developed and delivered in view of the various opinions on what makes a program distinct, rather than relying solely on the professional and academic views. The results of the survey and study suggest that excellence, in its wider definition, must be pursued as a higher goal and that sustaining excellence requires developing a culture of excellence at the organization level.

Advanced Mathematical Models to Predict the Compaction Properties of Coarse-Grained Soils from Various Physical Properties

An essential task in the process of construction is the determination of compaction properties of soils. Many years of laboratory test experience strengthen our belief in the existence of predictive equations that govern the compaction characteristics of soils. An advanced mathematical model developed in this research in order to uncertain the governing equations. An advanced mathematical model developed in this research in order to uncertain the governing equations. Through a comparative study among a Multiple Linear Regression (MLR) model, an Artificial Neural Network (ANN) model, Extreme Learning Machine (ELM) and a Support Vector Machine (SVM) model, the best predicting model was determined. For this purpose, Six hundred and six (606) samples collected and split into a dataset used for training the models and another used for validation of the derived model. 8 neural networks with a varying number of hidden layers and a varying number of nodes in hidden layers were employed. In ELM 1 hidden layer with varying number of units were employed. It was found that the equations derived from the ELM models described the relationship with superiority over multiple regression, ANN and SVM models for Maximum Dry Density and MLR models described the relationship with superiority over ANN, ELM and SVM models for Optimum Moisture Content.

Macro and micro geo-spatial environment consideration for landfill site selection in Sharjah, United Arab Emirates

Waste management involves various procedures and resources for proper handling of waste materials in compliance with health codes and environmental regulations. Landfills are one of the oldest, most convenient, and cheapest methods to deposit waste. However, landfill utilization involves social, environmental, geotechnical, cost, and restrictive regulation considerations. For instance, landfills are considered a source of hazardous air pollutants that can cause health and environmental problems related to landfill gas and non-methanic organic compounds. The increasing number of sensors and availability of remotely sensed images along with rapid development of spatial technology are helping with effective landfill site selection. The present study used fuzzy membership and the analytical hierarchy process (AHP) in a geo-spatial environment for landfill site selection in the city of Sharjah, United Arab Emirates. Macro- and micro-level factors were considered; the macro-level contained social and economic factors, while the micro-level accounted for geo-environmental factors. The weighted spatial layers were combined to generate landfill suitability and overall suitability index maps. Sensitivity analysis was then carried out to rectify initial theoretical weights. The results showed that 30.25% of the study area had a high suitability index for landfill sites in the Sharjah, and the most suitable site was selected based on weighted factors. The developed fuzzy-AHP methodology can be applied in neighboring regions with similar geo-natural conditions.