Mehmet Saribiyik

Alkali silica reaction of BOF and BFS wastes combination in cement

Abstract This study reports the results of an experimental study conducted to determine composite cements manufactured with the combination of Basic Oxygen Furnace (BOF) Slag and Blast Furnace Slag (BFS). The overall objective of this work is to determine whether a combination of BOF slag and BFS can be used as a cementations material to produce Composite Portland Cement (CPC). Three groups of cement are produced for testing. The first group contains BOF slag, the second group contains BFS and the last group contains the mixture of BOF slag and BFS together. Physical properties and Alkali Silica Reaction (ASR) of these groups are also evaluated in this study. Maximum ASR expansion is observed from the sample of CPC created with BOF slag. On the other hand minimum ASR expansion value is located in the sample of CPC created with BFS only.

Lateral load estimation from visco-plastic mud-flow around cylindrical row of piles

In this paper, the influence of slow and creeping flow of mud/slurry is modelled as a visco-plastic fluid around cylindrical row of piles. The study is carried out theoretically using principles of applied fluid mechanics. The research initiates from actual requirement in using a series of piled columns as barrier(s) to stabilise such slopes considered to be at risk of land-slide due to reduced stability. It was thought that in the event of slope failure, the homogenised behaviour of the moving mass could be modelled as a fluid with appropriate inertial and mechanical properties. Parametric studies were carried out to estimate forces on a row of piles, considering visco-plastic fluids with different mechanical properties. The analysis focused on determining the variation of force per a unit distance with depth on piles, under the influences of a number of key parameters.

Design of permanent greenhouse structure by pultruded glass reinforced plastic

Research activities have been taking on place in many ports of the world to develop or produce new greenhouse construction materials in order to grow more economic agricultural products. One of the new technological materials is the glass fiber reinforced plastic (GFRP) materials. GFRP materials are basically constituted of resin and continuous or chopped fiber and they are manufactured by using various manufacturing methods. The pultrusion process is a proven manufacturing method for obtaining lengths of high quality GFRP and became a competitive alternative to traditional structural materials. Factors in choosing GFRP materials for greenhouse applications are: lightweight, non-corrosive, chemically resistant, possess good fatigue strength, provide electrical and flame resistance. In this study, the structural behavior of the greenhouse structure, which is constructed using pultruded GFRP structural element, has been investigated. The mechanical properties of the pultruded GFRP sections have been computed using national and international standards. The proposed structures have been modeled using well known finite element program (SAP, 2000) to investigate the structural behavior under the static and dynamic loads. The pultruded GFRP box section and three different connection details have also been developed. The advantages and importance of GFRP profiles used in the greenhouse structure have been demonstrated.

Design of a Short Tensile Coupon for Fiber Reinforced Plastic Using Artificial Neural Networks

The measurement of the mechanical properties of Fibre Reinforced Plastic (FRP) material is necessary for numerical structural analysis and design. The mechanical properties of the FRP materials may be determined by specific coupon test methods or by analytical calculation. However, pultruded or moulded FRP components may not possess the dimensions to permit the extraction of standard length coupons. The shape of the short tensile coupon has been established to circumvent this limitation using a Finite Element (FE) representation and Artificial Neural Network (ANN) including the effect of gripping length, coupon shape, width, length and thickness. The FE results have been used for the learning and testing sets of the ANN. The Multi-Layer Perceptron (MLP) has been employed in the modelling of the ANN. The MLP model has been trained using the Scaled Conjugate Gradient Algorithm (SCGA) and tested. The ANN results show that the correlation between targets and outputs are consistent. K e y w o r d s : Fibre reinforced plastic, mechanical properties, numerical analysis, tensile coupon, artificial neural network, scaled conjugate gradient algorithm.