Journal of Civil and Environmental Engineering

The strengthening of RC structures with fiber reinforced polymer (FRP) materials has demonstrated enormous potential as a repairing material. However, their thermal and mechanical behaviors after exposure to elevated temperature remain an obstacle due to FRP’s sensitivity to high temperatures as compared with order structural materials. In this paper an experimental works was conducted to study the behavior of RC beam with NSM CFRP with different adhesive materials exposed to elevated temperature of 550°C for different periods of time and cooling schemes. In this experimental study 6 beams were cast, one beam (BN) was not exposed to elevated temperature as a control beam and the remaining beams were exposed to elevated temperature. These beams were tested under four-point loading. The effect of variables was studied in terms of ultimate failure load, maximum deflection and failure mode. From the test results, it could be concluded that ready-mix mortar could be as an alternative adhesive material. The ultimate load-carrying capacity of the RC beam was reduced for longer duration of elevated temperature.

The gathering systems in the production wells are very crucial in the transportation of produced liquids from production wells to collection points such as the processing plant or central processing facilities. Liquid transmission pipelines are a part of the energy industry which involves the transportation of natural crude oil through pipelines. In this research the pipeline costs, material costs are proportional to pipeline diameter, whilst construction and design costs are approximately constant. The research shows that the bigger the length of the flow line, the bigger the total pressure drop, per unit length of the flow line for a given size and the type of pipe, the total pressure drop increases with length, whilst the pressure increases from 100 kpa to 250 kpa, and the length of the flow lines increases from 5.4 km to 12.5 km. The inlet pressure of 600 psig was used, as maximum inlet pressure with a design pressure of 1215 psig, with the assumption that protection against closed in tubing head pressure (CITHP) was protected. The investigation shows that a single flow line or trunk lines are not economical in transporting the fluids from the production wells, due to high -pressure drop in the flowline segments and it can affect pipeline diameters since pressure drop can lead to excess inlet pressure to push the liquid through the flow line and the operating costs can be excessive and result in insufficient pressure to pump or transport the fluids to the central processing facility. The modeling of the pressure drop in the flowline at different rates and for different sizes of nominal pipeline in the gathering systems was achieved.

In microsimulation models, the behaviours of agents as intelligent objects are modeled through various behavioral modeling techniques, which give rise to uncertainties in the modeling workflow and predicted outputs. ILUTE (Integrated Land Use Transportation Environment model) is an agent-object-based microsimulation model system designed to simulate different activities in a city, in which many agents (persons, families, households, firms, etc.) intelligently and/ or randomly act and interact in a complex way. A 150,000 (150K) synthetic base year (1986) household sample of the Greater Toronto and Hamilton Area (GTHA) population is used as the starting point for undertaking twenty-year historical simulations (1986-2006). In order to analyze the uncertainty associated with stochastic behaviours in the ILUTE model system, a 1000 independent runs using different initial random number seeds are generated and tested through parallel programming and using high performance cloud computing (HPC). In this paper, the behaviour of the demographic updating module is tested by examining the variability and the distribution of its outputs including births, deaths, families, and households across simulation runs. The test results show that all the simulated outputs’ distributions are generally normally, or very close to normally, distributed. In general, ILUTE can simulate demographic updating process with considerable reliability and confidence.

The main purpose of this study is comparing two methods to get the convergence of two series nonlinear spring system. The key method is Broyden’s method which based on the Jacobian matrix to update the inverse of the secant stiffness matrix and the results are compared with the Newton–Raphson’s method. A constant force is applied to the second node in the system of two degrees of freedom (DOF). The results are compared with the first and second degree of nonlinear springs displacements differences that serially connected. The displacements at the first node are smaller than the second node and the number of iterations to reach the convergence for the second degree of difference displacements are greater than for the first degree. The main disadvantage of Broyden’s method is that it becomes unstable when the number of iterations increases.

The stability of the gully erosion slopes in this work is analyzed using PLAXIS2D (a finite element based program) and checked with Slide of Rocscience Inc utilizing the Ordinary Method of Slices, Bishop’s Method and GLE/ Morgensten-Price Method. The finite element program uses the phi-c reduction method. The phi-c method is based on the reduction of the shear strength (c) and the tangent of friction angle (tan∅) of the soil. Results from laboratory tests of the soil samples have geotechnical properties which by all indications denote the problematic nature of the slope as the soil samples had very low plasticity and the cohesion intercept are considerably low. The soil is classified as Clayey Sand. The various slope sections have been analyzed and apparently, slope sections A, B, and C are unsafe as they possess low factors of safety in the range of 0.6 – 0.8. Generally, a study of the erosion site shows that the area is poorly drained as the entire area has only one drainage channel leading to the main erosion gully. Recommendations have been proffered which includes retaining structure, cement grouting and more drains to improve the drainage around the eroding area which leads to the gully.

Emission factors are very important measures for developing an emission inventory, making decisions, designing control strategies, mitigating climate change, and even improving public health, in terms of respiratory system diseases. The emission factors could be either measured from field tests or estimated by an emission model. Existing models seldom consider the impacts of some special factors such as pavement roughness. As the impacts of the pavement roughness on emissions are very complicated, a linear model or physical model may not depict the mappings from affecting factors to resulted emission factors. In this paper, two non-linear models, including K-Nearest Neighbor (KNN) and Neural Network (NN) were built to estimate vehicle emission factors using roughness involved input data. A best fitted model was identified to illustrate the emission pattern along a wide range of pavement roughness. Multiple field tests were conducted in five regions of the State of Texas, United States, with a total of 1,609 km test length. One dedicated test vehicle was employed throughout the test. Pavement roughness was tested using a smartphone based application. All tested data were separated into four groups, each representing a different range of roughness, while the modeling was conducted within each group. The predictive performance of each model was evaluated by (1) correlation coefficient; (2) relative errors; and (3) two tailed unequal variance t-test. Results suggest that, K-NN can be better than NN to model the emission factors for the Texas highway system, and driving on a smoother and rougher pavement result in higher vehicle emissions.