Spatial variability of precipitation regimes over Turkey

Abstract

This study aims to predict the daily precipitation from meteorological data from Turkey using the wavelet—neural network method, which combines two methods: discrete wavelet transform (DWT) and artificial neural networks (ANN). The wavelet—ANN model provides a good fit with the observed data, in particular for zero precipitation in the summer months, and for the peaks in the testing period. The results indicate that wavelet—ANN model estimations are significantly superior to those obtained by either a conventional ANN model or a multi linear regression model. In particular, the improvement provided by the new approach in estimating the peak values had a noticeably high positive effect on the performance evaluation criteria. Inclusion of the summed sub-series in the ANN input layer brings a new perspective to the discussions related to the physics involved in the ANN structure.     

Oreganum Stalks as a New Biosorbent to Remove Textile Dyes from Aqueous Solutions

In the present study, Oreganum onites L. stalks in natural and chemically modified with HNO³ and H³PO⁴ used as adsorbent for removal of both acidic and basic dyes from waters. The adsorption was studied as a function of pH and contact time by batch method. All tested biosorbents were characterized by FT‐IR, scanning electron microscopy, and measuring the pH dependence of the zeta potential. The adsorption isotherms were fitted to Langmuir isotherm. The maximum adsorption capacity of dyes was 280.73 mg g^?1 for Basic Red 18, 147.06 mg g^?1 for methylene blue and 112.36 for Acid Red 111, which is comparable to that of other lignocellulosic materials. The modification process was considerably increased the biosorption capacity of lignocellulosic material, resulting in a 56–63% increase in the biosorption capacity of basic dyes and a 125% increase in the biosorption capacity of acidic dye. The present study illustrated that the most effective factors in the adsorption of basic dye were surface charge and acidic groups on lignocellulosic biosorbents, while non‐electrostatic forces as well as electrostatic forces were also effective in the adsorption of acidic dye. In conclusion, Oreganum stalks can be considered as a very prospective adsorbent for the removal of tested basic and acidic dyes.     

Soil Strength Improvement by Microbial Cementation

The biologically induced cementation (BioGrout) method has been used in this study to improve engineering properties of soil. Laboratory tests have been carried out to quantify the effect of BioGrout treatment on the strength of two types of sand by using Sporosarcina pasteurii bacteria. Bearing strength and other parameters, such as colony forming units (number of bacteria), pH level, temperature, and amount of CaCO₃, have also been studied. Calcification (cementation) through precipitation of CaCO₃ on the mineral surfaces has been clearly observed from the images of a scanning electron microscope (SEM). Finally, the effect of sand material on the effectiveness of biocementation was investigated via employement of different sand types.     

Spectral-based Probabilistic Seismic Hazard Analysis for Fethiye, Muğla

Fethiye is an important region located in the eastern part of the Mediterranean Basin.This region which is the most active part of the south-western Anatolia ex...     

The interannual precipitation variability in the southern part of Iran as linked to large-scale climate modes

The interannual variation of precipitation in the southern part of Iran and its link with the large-scale climate modes are examined using monthly data from 183 meteorological stations during 1974–2005. The majority of precipitation occurs during the rainy season from October to May. The interannual variation in fall and early winter during the first part of the rainy season shows apparently a significant positive correlation with the Indian Ocean Dipole (IOD) and El Ni?o-Southern Oscillation (ENSO). However, a partial correlation analysis used to extract the respective influence of IOD and ENSO shows a significant positive correlation only with the IOD and not with ENSO. The southeasterly moisture flux anomaly over the Arabian Sea turns anti-cyclonically and transport more moisture to the southern part of Iran from the Arabian Sea, the Red Sea, and the Persian Gulf during the positive IOD. On the other hand, the moisture flux has northerly anomaly over Iran during the negative IOD, which results in reduced moisture supply from the south. During the latter part of the rainy season in late winter and spring, the interannual variation of precipitation is more strongly influenced by modes of variability over the Mediterranean Sea. The induced large-scale atmospheric circulation anomaly controls moisture supply from the Red Sea and the Persian Gulf.     

An empirical attenuation relationship for Northwestern Turkey ground motion using a random effects approach

Using a random effects model that takes into consideration the correlation of data recorded by a single seismic event, a database consisting of 195 recordings from 17 recent events is employed to develop empirical attenuation relationships for the geometric mean of horizontal peak ground acceleration and 5-percent damped spectral acceleration (S_a). The recordings employed are obtained from strong motion stations operating in Northwestern Turkey and resulted from events that include the Kocaeli (M_w=7.4) and the Düzce (M_w=7.1) earthquakes and their aftershocks as well as other events. By studying differences in standard errors, the random effects model is compared with a fixed effects model that does not account for distinctions between intra- and inter-event variability. Effects of local site conditions are included in the empirical relationships developed. The dependence on frequency of the various model parameters is also studied. Frequency-dependent attenuation coefficients for the proposed random effects models developed are summarized in tables to facilitate their use.     

A successive elimination method for one-dimensional stock cutting problems in ship production

One-dimensional stock cutting problems can be encountered at the production stage of many areas of engineering as well as in shipbuilding and coastal structures. In this paper, a novel approach is proposed to solve the problem directly by using the cutting patterns obtained by the analytical methods at the mathematical modeling stage. By minimizing both the number of different cutting patterns and material waste, the proposed method is able to capture the ideal solution of the analytical methods. The main advantage of the method comes from the fact that an integer solution is guaranteed. However, in analytical methods it is not always possible to produce integer solutions and the linear programming algorithm must be run repeatedly to select integer solutions from the alternatives to get practical results. The proposed nesting algorithm is a low-cost and efficient tool. Minimizing the number of cutting patterns contributes to time and material savings. Also, by using this method trim loss is minimized and stock usage is maximized. The efficiency of the proposed method is demonstrated by extensive numerical results.