Civil Engineering

Owing to the fact that corrosion of steel is the key concern of service life of reinforced concrete structures, researchers have been dealing with this subject for many years. Pozzolanic materials, most of which are by products of industries, are widely used in concrete production, especially to increase the durability properties. Fly ash, ground granulated blast furnace slag (GGBS) and silica fume are the most common pozzolans together with natural pozzolans used in concrete technology. In this experimental research, resistance to chloride induced corrosion of reinforcing steel bars embedded in GGBS concrete has been studied. Two classes of concrete have been prepared; such as C25 and C35 at two different binder ratios. Cement in the concrete was replaced with GGBS at the ratios of 30%, 50% and 70%. Lollipop specimens with steel bars located in the center were prepared and stored in 1M NaCl solution for corrosion testing. Two levels of continuous potential difference, i.e. 6V and 1...

In order to reduce the cement content used in concrete production utilization of waste materials for substitution of a part of cement can be considered. In this study, two pozzolanic-waste materials, silica fume and fly ash, are used as a part of cement up to 12% and 40%, respectively in concrete and compressive strength as well as permeability properties were determined. The test results were evaluated by using the response surface method. By keeping the cement content in concrete constant at 300 kgm-3 , the variation of strength grade and permeability properties were investigated. It was found that it is possible to obtain the same or better strength grades by replacing cement with silica fume or fly ash up to 12% and 40%, respectively in concrete. Besides, the impermeability properties of pozzolan replaced concretes were superior than those of plain concretes without pozzolan.

Resumen-Los profesores han incrementado el uso de herramientas en la nube, como una opción para gestionar el aprendizaje digital pues generan datos que se utilizan para la toma de decisiones en la tutoría virtual. En este sentido se torna indispensable identificar los recursos interoperables que pueden vincularse con un entorno virtual para mejorar el proceso educativo. Este trabajo se desarrolló en un contexto universitario, participaron 35 estudiantes y se utilizaron únicamente recursos que cumplen con el estándar LTI (interoperabilidad de herramientas del aprendizaje Es importante destacar que las herramientas con este estándar permiten a los tutores identificar las huellas digitales que se generan con herramientas externas, consolidarlas al sistema de gestión de aprendizaje donde se desarrolla el hecho educativo y tomar decisiones a partir de las analíticas de aprendizaje.

This paper presents a triple diagram method (TDM) based on the Kriging technique for predicting future lake levels from two antecedent measurements, which are considered as independent variables. The experimental semivariograms (SV) for three lags are obtained, and the most suitable theoretical SV for the three cases is the Gaussian type. Based on these theoretical SVs, the contour lines of the dependent variable are constructed by Kriging. The resulting maps are referred to as the TDM model for lake level fluctuation. It is expected that this model will be used more extensively than the Markov or ARIMA (AutoRegressive Integrated Moving Average) models commonly available for stochastic modelling and predictions. The TDM does not have restrictive assumptions such as the stationarity and ergodicity which are preliminary requirements for the stochastic modelling. The TDM is applied to monthly level fluctuations of Lake Van in eastern Turkey. In the prediction procedure lags, one, two and three are considered. Interpretations from these three basic diagrams help to identify properties of lake level fluctuations. It is observed that the TDM preserves the statistical properties. These diagrams also help to make predictions with less than 10 % relative error.

The statistical behavior of wave energy at a single site is derived by considering simultaneous variations in the period and wave height. In this paper, the general wave power formulation is derived by using the theory of perturbation. This method leads to a general formulation of the wave power expectation and other statistical parameter expressions, such as standard deviation and coefficient of variation. The statistical parameters, namely the mean value and variance of wave energy, are found in terms of the simple statistical parameters of period, significant wave height and zero up-crossing period. The elegance of these parameters is that they are distribution free. These parameters provide a means for defining the wave energy distribution function by employing the ChebyschevÕs inequality. Subsequently, an approximate probability distribution function of the wave energy is also derived for assessment of risk and reliability associated with wave energy. Necessary simple charts are given for risk and reliability assessments. Two procedures are presented for such assessments in wave energy calculations and the applications of these procedures are provided for wave energy potential assessment in the regions of the Pacific Ocean off the west coast of U.S.

The statistical behavior of wave energy at a site strongly depends on the wave characteristics. Wave energy converters fail to produce energy when there are no sufficiently available wave heights. Hence, evaluation of return periods and risk values of the minimum wave height becomes important for wave energy studies. A time index representing the minimum wave height is proposed here for ocean wave applications. Persistence plays a significant role in the calculation of return period and risk. Although ignoring the serial independence makes calculations easy, it leads to overestimations of the real status. In this paper, return periods and risk values are compared with each other by taking into consideration independent and dependent situations. Application of the study is achieved for the stations located in the Pacific Ocean and Gulf of Mexico.

The quality of ground water in any aquifer takes its final form due to natural mixture of waters, which may originate from different sources. Water quality varies from one aquifer to another and even within the same aquifer itself. Different ground water quality is obtained from wells and is mixed in a common reservoir prior to any consumption. This artificial mixing enables an increase in available ground water of a desired quality for agricultural or residential purposes. The question remains as to what proportions of water from different wells should be mixed together to achieve a desired water quality for this artificial mixture. Two sets of laboratory experiments were carried out, namely, the addition of saline water to a fixed volume of fresh water. After each addition, the mixture volume and the electric conductivity value of the artificially mixed water were recorded. The experiments were carried out under the same laboratory temperature of 20˚C. A standard curve was developed first experimentally and then confirmed theoretically. This curve is useful in determining either the volume or discharge ratio from two wells to achieve a predetermined electrical conductivity value of the artificial mixture. The application of the curve is given for two wells within the Quaternary deposits in the western part of the Kingdom of Saudi Arabia. (KEY TERMS: artificial mixing; electrical conductivity; ground water; fresh water; saline water; volume ratio.) Sen, Zekai, Abdulaziz Abo Saud, Abdüsselam Altunkaynak, and Mehmet Özger, 2003. Increasing Water Supply by Mixing of Fresh and Saline Ground Waters.

In this paper, a technique is proposed in order to study triple time series. It combines the variable of interest, sulfur dioxide (SO 2 ) with two related meteorological variables. Hence, three variables measured at the same time points are jointly analyzed. Instead of using classical multiple time series analysis, it is suggested to consider the measurements of the two meteorological variables as coordinates of a two-dimensional space and the simultaneous observation of the third variable (associated SO 2 concentrations) at each pair of coordinates. Subsequently, well-known optimum interpolation is used for predicting the SO 2 concentrations on the basis of six meteorological variables. All the variables of the study are measured at the same times (all days in 2000) around the city of Istanbul, Turkey. The triple diagrams, in the form of contour maps, help to answer various questions concerning the SO 2 concentration variability with respect to meteorological variables. The same diagrams also provide a basis for the prediction of SO 2 concentrations. It is shown that the relative prediction error is less than 10%, which is acceptable for the practical studies.

Wave heights and periods are the significant inputs for coastal and ocean engineering applications. These applications may require to obtain information about the sea conditions in advance. This study aims to propose a forecasting scheme that enables to make forecasts up to 48 h lead time. The combination of wavelet and fuzzy logic approaches was employed as a forecasting methodology. Wavelet technique was used to separate time series into its spectral bands. Subsequently, these spectral bands were estimated individually by fuzzy logic approach. This combination of techniques is called wavelet fuzzy logic (WFL) approach. In addition to WFL method, fuzzy logic (FL), artificial neural networks (ANN), and autoregressive moving average (ARMA) methods were employed to the same data set for comparison purposes. It is seen that WFL outperforms those methods in all cases. The superiority of the WFL in model performances becomes very clear especially in higher lead times such as 48 h. Significant wave height and average wave period series obtained from buoys located off west coast of US were used to train and test the proposed models.

The purpose of this study is to investigate the relationship between wind speed, previous and current wave characteristics. It is expected that such a non-linear relationship includes some uncertainties. A fuzzy inference system employing fuzzy IF-THEN rules has an ability to deal with ill-defined and uncertain systems. Compared with traditional approaches, fuzzy logic is more efficient in linking the multiple inputs to a single output in a non-linear domain. In this paper, a sophisticated intelligent model, based on Takagi-Sugeno (TS) fuzzy modeling principles, was developed to predict the changes in wave characteristics such as significant wave height and zero up-crossing period due to the wind speed. Past measurements of significant wave height values and wind speed variables are used for training the adaptive model and it is then employed to predict the significant wave height amounts for future time intervals such as 1, 3, 6 and 12 h. The verification of the proposed model is achieved through the wave characteristics time series plots and various numerical error criterias. Also the model results were compared with classical Auto Regressive Moving Average with exogenous input (ARMAX) models. For the application of the proposed approach the offshore station located in the Pacific Ocean was used.

Many formulations have been developed so far to predict the wave height and period from fetch length and wind blowing duration for a constant wind speed. This study aimed to predict wave parameters from fetch length and meteorological factors by using triple diagram methodology based on Kriging principles. Proposed model results were compared with Joint North Sea Wave Project (JONSWAP) model which is used so commonly in the ocean and coastal engineering studies. For the implementation of the methodology hourly wave and wind data were obtained from a buoy located in Lake Ontario. Numerical and graphical comparisons demonstrated that the proposed method outperforms the classical formulation. r

This study aims to investigate the effectiveness of the low impact development (LID) practices on sustainable urban flood storm water management. We applied three LID techniques, i.e. green roof, permeable pavements and bioretention cells, on a highly urbanized watershed in Istanbul, Turkey. The EPA-SWMM was used as a hydrologic-hydraulic model and the model calibration was performed by the well-known Parameter ESTimation (PEST) tool. The rainfall-runoff events occurred between 2012 and 2020. A sensitivity analysis on the parameter selection was applied to reduce the computational cost. The Nash-Sutcliffe efficiency coefficient (NSE) was used as the objective function and it was calculated as 0.809 in the model calibration. The simulations were conducted for six different return periods of a storm event, i.e. 2, 5, 10, 25, 50 and 100-years, in which the synthetic storm event hyetographs were produced by means of the alternating block method. The results revealed that the combination...