A Comprehensive Numerical Study on Thermohydraulic Performance of Fluid Flow in Triangular Ducts with Delta-Winglet Vortex Generators

Triangular ducts fitted with various kinds of delta-winglet type vortex generators (VGs) are commonly used to achieve compactness and heat transfer enhancement in many industries. Successive locations of VGs on the inner surfaces of the ducts can be arranged in Common Flow Up (CFU) and Common Flow Down (CFD) orientations. In the present numerical study simultaneous effects of orientation and streamwise distance between VGs on triangular fin performance is carried out considering both global and local flow and heat transfer fields. With the configurations considered in this study, a CFD–CFU orientation and a nondimensional streamwise distance of 0.5 is determined as the best configuration. “RNG k-?” turbulence model with “Enhanced wall treatment” option is determined as the best turbulence model to predict the flow fields inside the triangular duct with built-in VGs, for Reynolds number of 5000.     

Power quality assessment of grid-connected wind farms considering regulations in turkey

This paper presents measurement system and detailed analysis of power quality at the substation of two different wind farm sites which are of low and high power rate. Measurement system has been designed using a data acquisition board (DAQ), Labview software, Matlab programming and a portable PC. The system has been installed at medium voltage level at substation of both wind farms. The real measurement results at substations are compared to current regulations in Turkey.     

Decision Based Model for Real-Time IoT Analysis Using Big Data and Machine Learning

Use of internet of things (IoT) in different fields including smart cities, health care, manufacturing, and surveillance is growing rapidly, which results in massive amount of data generated by IoT devices. Real-time processing of large-scale data streams is one of the main challenges of IoT systems. Analyzing IoT data can help in providing better services, predicting trends and timely decision making for industries. The systematic structure of IoT data follows the pattern of big data. In this paper, a novel approach is proposed in which big data tools are used to perform real-time stream processing and analysis on IoT data. We have also applied Spark’s built-in support of the machine learning library in order to make real-time predictions. The efficiency of the proposed system is evaluated by conducting experiments and reporting results on the case scenario of IoT based weather station.

     

An Optimum Vertical Handoff Decision Algorithm Based on Adaptive Fuzzy Logic and Genetic Algorithm

Handoff decision making is one of the most important topics in wireless heterogeneous networks architecture as there are many parameters which have to be considered when triggering handoff and selecting suitable access point. More intelligent approaches which reckon user profiles, application requirements, and network conditions must be improved so that desired performance results for both user and network could be provided. In this paper we introduce a new adaptive vertical handoff decision making algorithm in which fuzzy membership functions are optimized by means of genetic algorithm. Genetic algorithm is an adaptive search technique based on natural selection and genetic rules. In addition to that, it takes places in various scientific applications and can be used to adjust the membership functions in fuzzy systems. The purpose of the study is to adjust the shape of fuzzy membership functions, properly, using genetic algorithm in order to achieve optimum handoff performance. The results show that, compared to the several different algorithms performance of the proposed approach with genetic algorithm is significantly improved for both user and network in terms of number of handoff while the other requirements are still satisfied.     

Biosorption of Pb(II) ions from aqueous solution by pine bark (Pinus brutia Ten.)

The biosorption potential of pine (Pinus brutia Ten.) bark in a batch system for the removal of Pb(II) ions from aqueous solutions was investigated. The biosorption characteristics of Pb(II) ions on the pine bark was investigated with respect to well-established effective parameters including the effects of solution pH, initial Pb(II) concentration, mass of bark, temperature, and interfering ions present, reusability, and desorption. Initial solution pH and contact time were optimized to 4.0 and 4 h, respectively. The Langmuir and Freundlich equilibrium adsorption models were studied and observed to fit well. The maximum adsorption capacity of the bark for Pb(II) was found to be 76.8 mg g⁻¹ by Langmuir isotherms (mass of bark: 1.0 g L⁻¹). The kinetic data fitted the pseudo-second-order model with correlation coefficient greater than 0.99. The thermodynamic parameters Gibbs free energy (ΔG°), enthalpy (ΔH°), and entropy (ΔS°) changes were also calculated, and the values indicated that the biosorption process was spontaneous. Reutilization of the biosorbent was feasible with a 90.7% desorption efficiency using 0.5 M HCl. It was concluded that pine bark can be used as an effective, low cost, and environmentally friendly biosorbent for the removal of Pb(II) ions from aqueous solution.     

A sensitivity analysis for the design of small-scale hydropower plant: Kayabogazi case study

In this study, the feasibility of hydroelectric power generation from the Kayabogazi dam, which was built by The State Hydraulic Works of Turkey (DSI) in 1987 in the town of Tavsanli, Kutahya, for irrigation and flood control purposes is investigated. Since a certain amount of water is supplied from the dam to the town of Tavsanli as drinking water, that amount is deducted from the total and is not allowed to be used in the process of electric power generation. By evaluating the amount of incoming water to the Kayabogazi dam in the period of 1995 and 2003 years, the most agreeable turbine type and size is decided for a small hydropower plant (SHP). In this purpose, seven different cases have been taken into consideration. As a conclusion, the case used three turbines which one of them is installed to utilize from the higher flow rates has been determined as the best configuration. In this study, a power generation ranging between 0.313 and 4.997 MW has been achieved in the viewpoint of installed capacity for Kayabogazi dam. Hence, it has been estimated an electricity generation up to 10,579 MWh per annum.     

A CAD Approach Based on Artificial Neural Networks for Shielded Multilayered Coplanar Waveguides

In this paper a computer-aided design (CAD) approach based on artificial neural networks (ANNs) was successfully introduced to determine the characteristic parameters of shielded multilayered coplanar waveguides (SMCPWs). ANNs are trained with four learning algorithms to obtain better performance and faster convergence with simpler structure. The best results for training and test were obtained from the models trained with Bayesian regularization and Levenberg-Marquardt algorithms. The neural model results are in very good agreement with the results available in the literature for SMCPWs and three other different shielded CPW structures. One can calculate the quasi-static parameters of these four different shielded CPW configurations using only one neural model proposed in this work, easily, simply and accurately.     

Neural models for coplanar waveguides with a finite dielectric thickness

This article presents a new approach based on artificial neural networks (ANNs) to determine the characteristic parameters of symmetric and asymmetric coplanar waveguides with a finite dielectric thickness. ANNs are trained with the use of five training algorithms. The results obtained from neural models are in very good agreement with the theoritical and experimental results available in the literature. © 2003 Wiley Periodicals, Inc. Int J RF and Microwave CAE 13: 438–446, 2003.     

Genetic Variation of the Nile Soft-Shelled Turtle (Trionyx triunguis)

We studied the genetic structure of Trionyx triunguis populations from the Mediterranean and African continent based on mtDNA D-loop (776 bp) and nine microsatellite loci. A total of 102 polymorphic sites and 13 mtDNA haplotypes were described. Nucleotide diversity and haplotypes diversity were 0.047 and 0.974 respectively. Both mtDNA and nDNA supported the existence of two main management units as the Mediterranean and Africa. Based on the mtDNA results, the Mediterranean can be divided into two subunits; western Turkey and the eastern Mediterranean.