The adsorption behavior of cesium on poly(N-isopropylacrylamide/itaconic acid) copolymeric hydrogels

In this study, N-isopropylacrylamide/itaconic acid (NIPAAm/IA) hydrogels prepared by irradiating with γ radiation were used in experiments on cesium ion adsorption. The cesium ion adsorption capacity of the hydrogels was investigated as a function of Cs⁺ concentration, pH and temperature. The adsorption behavior of cesium was evaluated by using the radiotracer method. The adsorption isotherm models were applied to the experimental data, and it was seen that Freundlich isotherm explained the adsorption better than Langmuir isotherm. Two simplified kinetic models including pseudo-first-order and pseudo-second-order equation were selected to follow the adsorption processes. The Cs⁺ adsorption could be best described by the pseudo-first-order equation. The thermodynamic parameters including ΔG°, ΔH° and ΔS° for adsorption processes of Cs⁺ on the hydrogel were also calculated, and the negative ΔH° and ΔG° confirmed that the adsorption process was exothermic and spontaneous.     

DYNAMIC SIMULATION OF A DISTILLATION COLUMN SEPARATING A MULTICOMPONENT MIXTURE

In this work, a dynamic model was developed to simulate the transient behaviour of a pilot scale, continuous, siagewise, 15 plate distillation column separating a mixture of ethanol, iso-propanol and isobutanol. The accuracy of the predictions was assessed by transient response data collected during experiments under step changes in reflux ratio, feed flow rate and feed composition.

Results demonstrated the feasibility of simulating multicomponent distillation under unsteady state conditions with fairly good success. Further improvements were suggested for a better accuracy     

Use of Turkish huntite/hydromagnesite mineral in plastic materials as a flame retardant

In this study, the flame retardancy properties of huntite/hydromagnesite mineral in plastic compounds were investigated for potential electrical applications. Before the production of composite materials, huntite/hydromagnesite minerals were ground to particle sizes of 10, 1, and 0.1 μm. Phase and microstructural analysis of huntite/hydromagnesite mineral powders were undertaken using XRD and SEM‐EDS preceding the fabrication of the composite materials. The ground minerals with different particle size and content levels were subsequently added to ethylene vinyl acetate copolymer to produce composite materials. After fabrication of huntite/hydromagnesite reinforced plastic composite samples, they were characterized using DTA‐TG, FTIR, and SEM‐EDS. Flame retardancy tests were undertaken as a main objective of this research. The size distribution and the mineral content effects are measured regarding the flame retardancy of the polymer composites It was concluded that the flame retardant properties of plastic composites were improved as the mineral content increased and the size was reduced. POLYM. COMPOS., 31:1692–1700, 2010. © 2010 Society of Plastics Engineers.     

Casting properties of ASTM A128 Gr. E1 steel modified with Mn-alloying and titanium ladle treatment

This work aims to produce a high manganese steel with more refined austenite grains and better wear resistance without sacrificing the toughness and tensile properties by Mn alloying and Ti ladle treatment in comparision to ASTM A128 Gr. E1 steel (1.0C-13Mn) that is mostly used in the mining industry. The 1.0C-17Mn-xTi alloys (x=0, 0.05 and 0.1, in wt.%) were prepared. A relationship was established between the microstructures and mechanical properties of the as-cast and solution annealed alloys. Increasing Ti content increases the stable Ti(CN) phase on and beside the grain boundaries and decreases up to 37% the austenite grain size of the as-cast alloy with 0.10wt.% Ti. Correspondingly, after solution annealed, optimized titanium content (0.05wt.%) results in significant improvements in wear resistance, hardness, elongation, yield and tensile strengths by 44%, 31%, 30%, 8% and 12%, respectively, except 9% decrease in impact toughness compared to ASTM A 128 Gr. E1 steel without modification. These results show that 1.0C-17Mn-0.05Ti alloy can be used for parts exposed to high load wear and applied in conditions where relatively high tensile properties with sufficent ductility is needed.

     

Allochthonous blocks misidentified as the basement: Implication for petroleum exploration in the SW Thrace Basin (Turkey)

The sedimentary sequence of the SW Thrace Basin (NW Turkey) comprises of three major sedimentary packages: a) Cretaceous (Meastrichtien)–Early Eocene package formed as pelagic carbonate, turbidite, shelf and nearshore-fluvial deposits, b) Middle Eocene–Early Oligocene package formed as shallow marine, slope apron and turbidite sediments, c) Middle Miocene–Early Pliocene package formed as alluvial fan-fluvial and nearshore deposits. This basin is structurally complex and its southern margin is represented by a fold-thrust zone. The Westward Propagation of the North Anatolian Fault (WPNAF) intersects the Thrace Basin along its southwestern flank. In the SW Thrace Basin, there are ophiolite and limestone blocks in the sedimentary succession, which previously were interpreted as suture of the Intra-Pontide Ocean, Cretaceous aged Yeniköy Mélange or Olistostromal Unit in the Eocene sediments. In this study these rocks have been defined as allochthonous blocks facies of the Gaziköy Formation aged Middle–Late Eocene.In previous studies the Karaağaç Formation (Early Eocene) was considered to be within oil window and have an average potential for oil and gas generation. According to our data the Karaağaç Formation has a moderate TOC content, is mature and overmature. In the study area, there are potential stratigraphic traps (submarine fans and channels of the Karaağaç and Keşan Formations, fluvial channels of the Fıçıtepe Formation and reefs of the Soğucak Formation), potential fractured tuffs (the Gaziköy Formation) and, potential structural traps related to the folds, thrusts and the WPNAF. Although 17 exploration wells have been drilled in the study area and vicinity, no discovery has yet been made. The cause of this may be that the wells were terminated at depths shallower than potential targets or possibly drilling may have been terminated at the allochthonous block facies of the Gaziköy Formation, which is especially derived from ophiolite mélange and was misidentified as basement.     

SENDROM: Sensor networks for disaster relief operations management

SENDROM is a new sensor network architecture to manage the rescue operations after large scale disasters. This architecture mainly consists of sensor nodes deployed prior to a disaster and central nodes that can query sensor nodes. Central nodes are stored nearby the emergency operation centers and airports before a disaster. Following a disaster rescue teams are assigned one mobile central node and guided to a region based on the data in the SENDROM database. This paper explains the SENDROM architecture as well as our new task and data dissemination, localization of a detected person, and end-to-end reliable event transfer schemes introduced for SENDROM. Then it evaluates the performance of these schemes analytically and through simulation.     

A Comparison of Various Artificial Intelligence Methods in the Prediction of Bank Failures

The strong relationship between bank failure and economic growth attaches far more importance to the predictability of bank failures. Consequently, numerous statistical prediction models exist in the literature focusing on this particular subject. Besides, artificial intelligence techniques began to attain an increasing level of importance in the literature due to their predictive success. This study distinguishes itself from the similar ones in the sense that it presents a comparison of three different artificial intelligence methods, namely support vector machines (SVMs), radial basis function neural network (RBF-NN) and multilayer perceptrons (MLPs); in addition to subjecting the explanatory variables to principal component analysis (PCA). The extent of this study encompasses 37 privately owned commercial banks (17 failed, 20 non-failed) that were operating in Turkey for the period of 1997–2001. The main conclusions drawn from the study can be summarized as follows: (i) PCA does not appear to be an effective method with respect to the improvement of predictive power; (ii) SVMs and RBF demonstrated similar levels of predictive power; albeit SVMs was found to be the best model in terms of total predictive power; (iii) MLPs method stood out among the SVMs and RBF methods in a negative sense and exhibits the lowest predictive power.     

Harmony search based algorithm for the optimum design of grillage systems to LRFD-AISC

Harmony search based optimum design method is presented for the grillage systems. This numerical technique imitates the musical performance process that takes place when a musician searches for a better state of harmony. Jazz improvisation seeks to find musically pleasing harmony similar to the optimum design process which seeks to find the optimum solution. The design algorithm considers the serviceability and ultimate strength constraints which are implemented from Load and Resistance Factor Design—American Institute of Steel Construction (LRFD-AISC). It selects the appropriate W-sections for the transverse and longitudinal beams of the grillage system out of 272 discrete W-section designations given in LRFD-AISC. This selection is carried out such that the design limitations described in LRFD-AISC are satisfied and the weight of the system is the minimum. Many design examples are considered to demonstrate the efficiency of the algorithm presented.     

An artificial neural network model for the effects of chicken manure on ground water

In the areas where broiler industry is located, poultry manure from chicken farms could be a major source of ground water pollution, and this may have extensive effects particularly when the farms use nearby ground water as their fresh water supply. Therefore the prediction the extent of this pollution, either from rigorous mathematical diffusion modeling or from the perspective of experimental data evaluation bears importance. In this work, we have investigated modeling of the effects of chicken manure on ground water by artificial neural networks. An ANN model was developed to predict the total coliform in the ground water well in poultry farms. The back-propagation algorithm was employed for training and testing the network, and the Levenberg-Marquardt algorithm was utilized for optimization. The MATLAB 7.0 environment with Neural Network Toolbox was used for coding. Given the associated input parameters such as the number of chickens, type of manure pool management and depth of well, the model estimates the possible amount of total coliform in the wells to a satisfactory degree. Therefore it is expected to be of help in future for estimating the ground water pollution resulting from chicken farms.     

Single-step ahead prediction based on the principle of concatenation using grey predictors

In literature a number of different methods are proposed to improve the prediction accuracy of grey models. However, most of them are computationally expensive, and this may prohibit their extensive use. This paper describes a much simpler scheme, based on the principle of concatenation, in which unit step predictions are concatenated by replacing the missing outputs by their previously predicted values. Despite its extreme simplicity, it is shown that the predicted values thus derived results in a better performance than the methods proposed in the literature. Simulation studies show the effectiveness of the proposed algorithm when applied to nonlinear function predictions.