The Effect of Urmia-Lake Water on Tensional Strength Concrete with Various Admixtures

In this paper, the effect of admixtures on the tensional strength of concrete in Urmia-lake water have been investigated. We made different types of concretes with the ratio of w/c and replaced different percentages of micro-silica, air-entraining, super plasticizer, corrosion-inhibiting, and caulk with two types of cement I and II as well as investigating in both ordinary water and Urmia-lake water. The tensional strength was investigated on these samples

The Effect of Urmia-Lake Water on Tensional Strength Concrete with Various Admixtures

In this paper, the effect of admixtures on the tensional strength of concrete in Urmia-lake water have been investigated. We made different types of concretes with the ratio of w/c and replaced different percentages of micro-silica, air-entraining, super plasticizer, corrosion-inhibiting, and caulk with two types of cement I and II as well as investigating in both ordinary water and Urmia-lake water. The tensional strength was investigated on these samples

Estimation of the Local Scour from a Cylindrical Bridge Pier Using a Compilation Wavelet Model and Artificial Neural Network

In the present study, an artificial neural network and its combination with wavelet theory are used as the computational tool to predict the depth of local scouring from the bridge pier. The five variables measured are the pier diameter of the bridge, the critical and the average velocities, the average diameter of the bed aggregates, and the flow depth. In this study, the neural wavelet method is used as a preprocessor. The data was passed through the wavelet filter and then passed to the artificial neural network. Among the various wavelet functions used for preprocessing, the dmey function results in the highest correlation coefficient and the lowest RMSE and is more efficient than other functions. In the wavelet-neural network compilation method, the neural network activator function was replaced by different wavelet functions. The results show that the neural network method with the Polywog4 wavelet activator function with a correlation coefficient of 87% is an improvement of 8.75% compared to the normal neural network model. By performing data filtering by wavelet and using the resulting coefficients in the neural network, the resulting correlation coefficient is 82%, only a 2.5% improvement compared to the normal neural network. By analyzing the results obtained from neural network methods, the wavelet-neural network predicted errors compared to experimental observations were 8.26, 1.56, and 1.24%, respectively. According to the evaluation criteria, combination of the best effective hydraulic parameters, the combination of wavelet function and neural network, and the number of neural network neurons achieved the best results

One Typical Jacket Platform's Reactions in Front of Sea Water Level Variations

Demanding structural safety under various loading conditions, has focused attention on their variation and structural elements behavior due to these variations. Jacket structures are designed for a specific water level (LAT). One of the important issues about these kinds of structures is the water level rise. For example, the level of water in the Caspian Sea has risen by 2.5m in the last fifteen years and is continuing to rise. In this paper, the structural behavior of one typical shallow or medium water jacket platform (a four-leg steel jacket platform in 55m water depth) under water level rise has been studied. The time history of Von Mises stress and nodal displacement has chosen for evaluating structural behavior. The results show that dependent on previous water depth and structural elements position; different structural elements have different behavior due to water level rise

ANALYTICAL STUDY OF CONCRETE-FILLED DOUBLE SKIN STEEL TUBULAR COLUMNS UNDER INTERACTION OF BENDING MOMENT AND AXIAL LOAD

Concrete Filled Double Steel Tubular columns are from the concrete filled tubular columnsâ (CFT) family formed of two steel walls with square or circular sections. They are assembled concentrically and the space between the two walls is filled with concrete. Since CFDST columns do not need concrete casting and are easy to assemble and carried and are well protected against damages, they have some advantages over other columns. They are generally used in offshore structures, piers of the bridges with large openings, and nuclear canals in power plants. They have recently been used in the frames of high rising buildings in Japan as well. The present study attempts to investigate the behavior of these new columns under axial pressure forces and bending moment through finite element method and ABAQUS 6.10 program. In order to make sure the finite element modeling is correct, the results of numerical analyses of CFT columns were compared to the laboratory results and the results were satisfying. The present study also investigated the effects different parameters of column thinness, the cross sectionâs geometric features, and characteristics of strength of materials and found that these columnsâ capacity for load is more than CFT columns and are lighter and more economical compared to them

Static strength of collar plate reinforced tubular T/Y-joints under brace compressive loading

In the present paper, the static strength of steel collar plate reinforced tubular T/Y-joints is numerically investigated. A finite element (FE) model was developed and the results were verified against the experimental data. Afterwards, a set of 168 FE models of collar plate reinforced T/Y-joints was generated and analyzed under axially compressive loads. The effect of plate size and joint geometry on the ultimate strength and failure mechanism of the joints were investigated through a parametric study. Results showed that the ultimate strength of a collar plate reinforced T/Y-joint can be up to 270% of the strength of the corresponding unreinforced joint. Despite this significant difference between the static strength of unreinforced and collar plate reinforced T/Y-joints, studies on this type of reinforced joints have been limited to very few T-joint tests. Also, no design equation is available to determine the ultimate strength of T/Y-joints reinforced with collar plates. Hence, after the parametric study, a new equation is proposed, through nonlinear regression analysis, for determining the ultimate strength of collar plate reinforced T/Y-joints under axially compressive loads

Static performance of doubler plate reinforced tubular T/Y-joints subjected to brace tension

In the present study, data extracted from the finite element analysis of 210 models, which were verified against the data available from eight experimental tests, were used to investigate the geometrical effect on the ultimate strength, initial stiffness, and failure modes in doubler plate reinforced tubular T/Y under axially tensile load. Results indicated that the doubler plate can significantly increase the initial stiffness, ultimate capacity, and considerably improve failure modes. Also, the reinforcing effect of the doubler plate thickness and doubler plate length on the ultimate capacity becomes more remarkable when one of these parameters is big. Despite this significant difference between the static capacity of unreinforced and doubler plate reinforced T- and Y-joints subjected to brace tension, studies on these types of reinforced joints have been confined to very few T-joint tests. Moreover, no design formula is available to compute the ultimate capacity of doubler plate reinforced T/Y-joints. For these reasons, geometrically parametric investigation was followed by a set of nonlinear regression analyses to propose an ultimate capacity parametric formula for the static analyses of doubler plate reinforced tubular T/Y-joints under axially tensile load