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International Journal of Architectural, Civil and Construction Sciences

ISSN: 2415-1734

Total 24 content found

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International Journal of Architectural, Civil and Construction Sciences International Journal of Biological, Life and Agricultural Sciences International Journal of Chemical, Materials and Biomolecular Sciences International Journal of Business, Human and Social Sciences International Journal of Earth, Energy and Environmental Sciences International Journal of Electrical, Electronic and Communication Sciences International Journal of Engineering, Mathematical and Physical Sciences International Journal of Medical, Medicine and Health Sciences International Journal of Mechanical, Industrial and Aerospace Sciences International Journal of Information, Control and Computer Sciences

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Analytical Study on a Longitudinal Joints of the Slab-Type Modular Bridges

Year: 2012 Volume: 6 Issue: 2 93 - 98 Pages

Abstract: In this study, a longitudinal joint connection was proposed for the short-span slab-type modular bridges with rapid construction. The slab-type modular bridge consists of a number of precast slab modules and has the joint connection between the modules in the longitudinal direction of the bridge. A finite element based parameter analysis was conducted to design the shape and the dimensions of the longitudinal joint connection. Numbers of shear keys within the joint, height and depth of the shear key, tooth angle, and the spacing were considered as the design parameters. Using the local cracking load at the corner of the shear key and the cross-sectional area of the joint, an efficiency factor was proposed to evaluate the effectiveness of the longitudinal joint connection. The dimensions of shear key were determined by comparing the cracking loads and the efficiency factors obtained from the finite element analysis.

A Study for Carbonation Degree on Concrete using a Phenolphthalein Indicator and Fourier-Transform Infrared Spectroscopy

Year: 2012 Volume: 6 Issue: 2 86 - 92 Pages

Abstract: A concrete structure is designed and constructed for its purpose of use, and is expected to maintain its function for the target durable years from when it was planned. Nevertheless, as time elapses the structure gradually deteriorates and then eventually degrades to the point where the structure cannot exert the function for which it was planned. The performance of concrete that is able to maintain the level of the performance required over the designed period of use as it has less deterioration caused by the elapse of time under the designed condition is referred to as Durability. There are a number of causes of durability degradation, but especially chloride damage, carbonation, freeze-thaw, etc are the main causes. In this study, carbonation, one of the main causes of deterioration of the durability of a concrete structure, was investigated via a microstructure analysis technique. The method for the measurement of carbonation was studied using the existing indicator method, and the method of measuring the progress of carbonation in a quantitative manner was simultaneously studied using a FT-IR (Fourier-Transform Infrared) Spectrometer along with the microstructure analysis technique.

Artificial Neural Networks Modeling in Water Resources Engineering: Infrastructure and Applications

Year: 2012 Volume: 6 Issue: 2 77 - 85 Pages

Abstract: The use of artificial neural network (ANN) modeling for prediction and forecasting variables in water resources engineering are being increasing rapidly. Infrastructural applications of ANN in terms of selection of inputs, architecture of networks, training algorithms, and selection of training parameters in different types of neural networks used in water resources engineering have been reported. ANN modeling conducted for water resources engineering variables (river sediment and discharge) published in high impact journals since 2002 to 2011 have been examined and presented in this review. ANN is a vigorous technique to develop immense relationship between the input and output variables, and able to extract complex behavior between the water resources variables such as river sediment and discharge. It can produce robust prediction results for many of the water resources engineering problems by appropriate learning from a set of examples. It is important to have a good understanding of the input and output variables from a statistical analysis of the data before network modeling, which can facilitate to design an efficient network. An appropriate training based ANN model is able to adopt the physical understanding between the variables and may generate more effective results than conventional prediction techniques.

Design Alternatives for Lateral Force-Resisting Systems of Tall Buildings in Dubai, UAE

Year: 2012 Volume: 6 Issue: 2 73 - 76 Pages

Abstract: Four design alternatives for lateral force-resisting systems of tall buildings in Dubai, UAE are presented. Quantitative comparisons between the different designs are also made. This paper is intended to provide different feasible lateral systems to be used in Dubai in light of the available seismic hazard studies of the UAE. The different lateral systems are chosen in conformance with the International Building Code (IBC). Moreover, the expected behavior of each system is highlighted and light is shed on some of the cost implications associated with lateral system selection.