In this study, engine performance and exhaust emission of a Diesel engine (CI) at full load and various speeds conditions using only Diesel fuel and five different blends with butanol (3, 6, 9, 12 and 15 v/v %) were modeled by using Artificial Neural Network (ANN). A single-cylinder diesel engine was used in the experimental studies. Single layer, logistic sigmoid transfer function Scaled Conjugate Gradient and Levenberg–Marquardt algorithms were used in the presented ANN model. Input layer includes engine speed and blending ratio. Output layer includes parameters of brake specific fuel consumption, effective efficiency, NOx emission and CO emission. Mean absolute percentage error (MAPE) data and mean square error (MSE) and were calculated for performance of the networks. It was obtained that there was a consistency among the presented ANN model and the data obtained from experiments.

In this paper, flow changes were observed via Particulate Image Velocimetry (PIV) technique in shallow water flow for two side by side circular cylinders which a vertically placed splitter plate (VSP) was placed between them. The circular cylinders made of acrylic material have a diameter of D=40mm. Throughout the experiments water height was hw=20 mm and flow images were taken at the elevation of hL=10 mm. The free stream velocity was U∞=125 mm/sec and Reynolds Number was ReD=5000 based on diameters of circular cylinders. Five different VSPs varied from heights of H=2 mm to 10 mm with an increment 2 mm were used to control unsteady flow. The gap/diameter ratio was G/D=1.25 for all cases. Dimensionless Turbulence Kinetic Energy and time-avaraged velocity values were acquired by processing experimentally obtained data on a computer. As a result, the usage of splitter plate has shown its effectiveness on flow control. After the plate height of H=6mm, TKE values were decreased significantly. The most effective plate height on the flow control was seen as H=10mm.

In this study, an air filter was manufactuted and variation of temperature and vibration magnitude on filter paper were investigated experimentally by inverse pulse cleaning. For this purpose, compressed clean and dried air was released throughout in the inverse direction of the flow for 10 msec under 827 kPa constant pressure. The effect of nozzle and pulse distance for pulse cleaning of filter paper were observed experimentally under different nozzle-filter distance and different nozzle positions. The magnitude of vibrations and variation of temparature obtained using accelerometers and thermal camera respectively. The usage of nozzle within the different positions and distance effect vibration and tempapature patterns. As a result of experimental study, it was determined the most homogeneous vibration and temperature distributions were at vertical position of nozzle.

During the winter months, the soil temperature increases as the soil depth increase, and after a certain depth it does not change. In this study, the prevention of icing on pavements by heat pipes which uses the energy of the ground has been investigated. Firstly, the variation of the soil temperature is investigated when the ambient temperature varies between -1 to -7 °C and the wind speed 0 and 3 m/s. For anti-icing, the evaporator, condenser and adiabatic section lengths of the heat pipe to be used were chosen as 3 m, 1 m and 0.1 m respectively and diameters of the heat pipe were determined as 25 mm and 50 mm. The heat pipe material was selected as stainless steel and the working fluid as ammonia. In the study, first it is assumed that the soil temperature is 8 oC at 3 m depth. If the wind speed and outdoor temperature are assumed to be 0 m/s and -1 °C respectively, icing for 1.2 m2 area was prevented by the 25 mm diameter heat pipe. At the same conditions, icing prevented areas by 25 mm and 50 mm heat pipes were calculated as 2 m2 and 2.7 m2 respectively for 3 m depth and with 12 oC soil temperature. Heat transfer rate was increased by the increase of the heat pipe diameter and ground source temperature, consequently it was seen that the heat pipe was more effective to prevent icing.

In this study, the heat transfer characteristics and friction factor of nanofluids under laminar pulsating inlet flow conditions in a tube with circular rings are investigated numerically. In investigations, the governing equations are solved with FLUENT ANSYS 15.0 package program, along with boundary conditions using the finite volume approach (FVM) by SIMPLE algorithm. Firstly, the effects on heat transfer of different nanofluid types with varying particle volume fractions and Reynolds numbers under steady flow conditions are analyzed. Then, these nanofluids parameters are kept constant and the effects on heat transfer under pulsating flow conditions of nanofluids are investigated. The average Nusselt number and friction factor are calculated for different pulsating parameters. The numerical results indicate that the heat transfer performance enhances with increase in particle volume fraction and Reynolds number in steady regime. It is observed that the heat transfer performance increases with increasing pulsating amplitude in pulsating nanofluid flow, and there is a slightly increase in pressure drop. The computed results reveal that there is a good potential in promoting the heat transfer enhancement by using the nanoparticles under pulsating flow in a tube with circular rings.

Thermoelectric generators are long-life electricity generators that operate according to the Seebeck thermoelectric effect and produce DC voltage by utilizing the temperature difference on hot and cold surfaces, without moving parts. The ability to generate electricity directly in any situation where the temperature difference between the surfaces of the thermoelectric modules arises makes it possible to generate electricity from the first time in the exhaust systems of the internal combustion engines. It is very important to examine the recovery of the thermoelectric generators in the heating process in the internal combustion engines due to the reduced generator efficiency at low revs. In this study, thermoelectric generators were used to provide exhaust heat recovery in heating process of an internal combustion gasoline engine, electrical gains obtained at three different temperature averages were investigated and experimental and simulated results were compared. A maximum ΔT = 165 ° C temperature difference was obtained between the module surfaces. In the experiments performed, ΔT = 165 ° C, RL = 10 Ω load resistance, maximum 6.75 V voltage, 0.65 A current is obtained. Experimental and simulation results are generally in coherence.

In this study, flue gases from natural gas-fired industrial furnaces were thermodynamically investigated. In the analysis, the experimentally measured values of concentration of the flue gas components, i.e. O2, CO2, H2O and N2, the flue gas temperature and the flue gas outlet rate were used. The usable amount of energy (exergy) released to the environment by flue gases in terms of different output parameters was calculated, then effects of physical and chemical properties of flue gases on the exergy losses were investigated. In addition, the calculated exergy data were modeled by Artificial Neural Network (ANN) method, besides that ANN model with best accuracy was determined by altering the number of neurons in the hidden layer. With the help of ANN model as well as concentration, temperature and rate of flue gases, it has been shown that the exergy of flue gases value can be estimated with high accuracy.

The using areas of composite materials in mainly aerospace sector and other industry have been increased due to their more light, high fatigue strength, impact strength and specific strength properties than metals. The critical factor in fiber reinforced laminate composites from composite materials is to crack formation on interface matrix structure and fibers carrying loads and distributing forces to matrix structure. Also, the cracks on interface matrix structure and fibers cause decreasing the composite structure strength with crack propagations under loads. In this study, the effect of location and angle of the crack in the laminate hybrid composite material reinforced with glass-epoxy, boron-epoxy, carbon-epoxy, glass-boron-carbon-epoxy fibers at different angles on mechanical behaviors is determined with finite element analyses. In analyses, the different located crack and crack angles (0° ve 30°) inside the laminate composite structure with different fiber materials reinforced at different angles (0°,15°,30°,45°,60°,75° ve 90°) with 1.5 mm of total composite thickness were formed and applied tensile forces. Afterwards, stress and displacement values were obtained in the cracked fiber reinforced structures. According to results, Decrease in stress at top and bottom aluminium plate was observed in case of parallel fiber orientation to the applied forces. Beside, shear stresses increase with increasing the crack angle.

In this study, the effects of hot dip galvanizing treatment on the fatigue strength of the hot rolled and quenched-tempered AISI 4340 steel were examined. The phase structure, phase thicknesses, surface hardness and roughness values of the galvanized coating were also examined.
While the reduction in surface roughness of the part due to the high surface tension of the liquid zinc after galvanization has a positive effect, the decrease in the surface hardness due to the low hardness of the zinc and the decrease in the fatigue resistance are adversely affected. The surface hardness, surface roughness, coating thicknesses and the morphologies of constituent phases of coating obtained in both groups are similar, irrespective of the treatments seen before galvanizing the AISI 4340 steel. Although the decrease in fatigue strength after galvanization is higher in QT steel, the positive contribution to fatigue resistance of the quenced and tempered process still continues.

The aim of this study is the fabrication of submicron and nano Al2O3 ceramic powders from coarse Al2O3 ceramic powders by mechanical milling method. The effect of mechanical milling parameters such as milling time, milling speed and ball to powder weight ratio on the morphology, particle size, specific wear rate, apparent density and microstructure of milled coarse Al2O3 powders is also investigated. Scanning electron microscope is used for morphology examination. The average particle size and specific surface area are investigated by a particle sizer. The apparent density values are measured by using a hall flowmeter. Morphology examinations showed that the polygonal morphology of Al2O3 powders is changed to irregular and spherical morphology with increasing milling speed. When the particle size values investigated, it is found that the most effective parameter for particle size refinement is the milling speed. The lowest particle size of Al2O3 powders is 320 nm which is obtained with 300 rpm of milling speed, 5h of milling time and 15: 1 of ball to powder weight ratio. When the initial size of the Al2O3 powders with 48 micron and 320 nm of final particle size at obtained at the 5h of milling are compared, the effect of mechanical milling on the milling process of ceramic powders is clearly demonstrated.

In this study, fracture behavior of bolted joints in composite plates containing cracks repaired with single-sided composite patch was numerically investigated. The effects of variation of parameters such as plate and patch materials, pin diameter and adhesive properties on stress intensity factor ate crack tip were investigated. In the solution, the plate repaired with the patch was modeled as three-dimensional and the crack displacement at the edge of the pin hole was found by the finite element method. Stress intensity factor is obtained by DCM (Displacement Correlation Method) which can be applied to three dimensional crack problems for homogeneous ortotropic materials and the results are presented in graphical form. It has been found that for the crack tips at the same distance from the center of the pin hole, larger hole diameters are a more effective parameter on the stress intensity factor than the larger crack length. It has been found that the effect of the patch material variation on the stress intensity factor is increased at large pin diameters.

The aim of this work is to optimise the welding parameters of electrical resistance spot welded TWIP steel sheets using a Taguchi method. The welding parameters, such as weld current, welding time and electrode force, were determined according to the Taguchi orthogonal array L9 using a randomised approach. The optimum welding parameters for the peak tensile shear load of the joints were predicted, and the individual importance of each parameter on the tensile shear load of the resistance spot weld was evaluated by examining the signal-to-noise (S/N) ratio and analysis of variance (ANOVA). The optimum weld current, welding time and electrode force were found to be 12 kA, 300 ms and 3000 N, respectively. The ANOVA results indicated that the weld current has the highest statistical effect with 78.73% on the tensile shear load, followed by the welding time and electrode force. The tensile shear load of the resistance spot welding joints increased with increasing weld current and electrode force. But, higher welding time led to relatively lower tensile shear load. In addition, the fracture surface characterisation of the selected joints was conducted using scanning electron microscopy (SEM) technique. In this examination, it has been found that the joints having higher weld strength exhibited a relatively more ductile fracture characteristic.

The intense competition in the production of particleboard in the world requires minimization of process times which is one of the important parameters effective on costs. In this study, it is aimed to minimize the press time in order to increase the production speed by using the mathematical sub-structure of the response surface method (RSM) which is one of the well-known design of experiments techniques. For this purpose, optimum levels of the factors those have effect on press time namely humidity of the particleboard, bath gel time, gravure gel time for the bottom of the particleboard, gravure gel time for the top of the particleboard, flow, final weight, humidity of the paper, amount of urea-formaldehyde (UF), amount of melamine formaldehyde (MF), press density, press pressure and press temperature were investigated. In this case, It is aimed to increase the production amount and productivity of the line while decreasing the press time. For the purpose of modeling, the mathematical relationship between the factors and the press time was determined by using 56 observation values of 5 repetitions each and then optimization was performed. At the end of the study, the press time is reduced to 11 seconds from 13.57 seconds – which is the lowest press time observed for the currently selected item type.

In this study, we address a production scheduling problem. The scheduling problem is encountered in a job-shop production type. The production system is discrete and dynamic system in which jobs arrive continually. We introduce a simulation model (SM) to identify several situations such as machine failures, changing due dates in which scheduling rules (SRs) should be selected independently. Three SRs, i.e. the earliest due date rule (EDD), the shortest processing time first rule (SPT) and the first in first out rule (FIFO), are incorporated in a SM. A simulated annealing heuristic (SA) based simulation-optimisation approach is proposed to identify the unknown schedules in the dynamical system. In the numerical analysis, the performance of SRs and SA are compared using the simulation experiments. The objective functions minimising the mean flowtime and the mean tardiness are examined with varying levels of shop utilization and due date tightness. As an overall result, we observe that the proposed SA heuristic outperforms EDD and FIFO, the well-known SPT rule provides the best results. However, SA heuristic achieves very close results to the SPT and offers a reasonable computational burden in time-critical applications.

Particle Swarm Optimization (PSO) is a well-known swarm intelligence-based algorithm that simulates the movements of school or bird flocks in problem solving. Although it is first introduced to solve unconstrained global optimization problems, there are numerous reported publications of PSO involving various types of problems. However, as one can see from the related literature, compared to other types of implementations, discrete and binary PSO applications are relatively fewer in number. In this context, in the present work, a 0-1 PSO modification enhanced with a quantum-based local search procedure is developed. The mentioned quantum-based procedure generates randomly scattered particles referred to as quantum particles located within a sphere that is generated around the best-found solution by the algorithm. Next, these particles are used for local search to achieve possible improvements on the best-found solution. The performance of the proposed approach is tested by using a 0-1 problem suite consisting of the commonly used One-Max, Deceptive, Plateau and Royal Road functions. Experimental study shows the effectiveness of the proposed approach in 0-1 problems.

The Teaching-Learning Based Optimization (TLBO) algorithm is a population-based optimization technique that has been shown to be competitive against other population-based algorithms. The main purpose of this paper is to solve the balancing problem of mixed-model two-sided assembly lines by using TLBO algorithm first time in the literature. Most recently, hybrid teaching-learning-based optimization (HTLBO) algorithm is proposed by [1] for solving the balancing of stochastic simple two-sided assembly line problem. The HTBLO algorithm is compared with the well-known 10 different meta-heuristic algorithms in the literature in [1]. The tests performed underlined that HTLBO algorithm presented more outstanding performance when compared to other algorithms. In this paper, HTLBO algorithm is also adapted for solving the problem of balancing mixed-model two-sided assembly line and its performance is analysed. The objective function of this study is to minimize the number of mated-stations and total number of stations for a predefined cycle time. A comprehensive computational study is conducted on a set of test problems that are taken from the literature and the performance of the algorithms are compared with existing approaches. Experimental results show that TLBO algorithm has a noticeable potential against to the best-known heuristic algorithms and HTLBO algorithm results show that it performs well as far as the best-known heuristic algorithms for the problem in the literature.

Electrical-electronic waste (WEEE) is generated from electric and electronic devices at the end of their lifecycles. When WEEEs are disposed, burned or disassembled for recycling, they are transformed into products containing hazardous substances and harm the environment and human health. Therefore WEEEs should be collected, transported and processed properly during their recycling operations by municipality authority in order to minimize their damage and maximize their economic benefit. In this paper, a study is carried out for the WEEE management of Çankaya Municipality by the cooperation of Environmental Conservation and Control Department of Çankaya. For this purpose first WEEE with a focus on television, refrigerator, washing machine, oven and vacuum cleaner are estimated based on the electronic device usage behavior of residents in Çankaya. Secondly, the WEEE collection points’ location problem is solved considering set covering problem.

Due to global warming in recent years, using natural resources in an effective way has become more and more important for our world. Decreasing natural resources are pushing agriculture and food chains to adopt more efficient management strategies. The first condition for a successful management is to make plans based on accurate and reliable forecasts. In this study, using real-world data forecasting models are developed for the products of a feed company, which is the first chain of agriculture and food chain systems. The traditional statistical time series methods are compared to two popular and effective computational intelligence techniques, i.e. artificial neural networks and support vector regression. The accuracy of the forecasts is calculated by different measures. The results show that the proposed artificial neural network model produces significantly better results with high R-squared values, comparing to both time series methods and support vector regression.

Nowadays, computer technology is rapidly advancing and computer capacities are increasing, which makes it easier to reach the database by increasing the number of information recording areas. Although the produced and recorded data are meaningless on their own, they become meaningful when they processed for a certain purpose. Converting raw data to meaningful information can be done by data mining. In this study, rule extraction is realized in a yarn production facility by classification which is one of the data mining methods. Prior to classification, the features that affect the yarn quality are determined, and feature selection is realized by choosing the effective features by Taguchi experimental design method. Rule extraction phase is applied for both cost-insensitive classification that aims to minimize the number of misclassification errors and cost-sensitive classification that aims to minimize the expected misclassification cost. For rule extraction Weka 3.8.1 and MT-VeMa 1.0 package programs are utilized. The resulting rules guide the firm for producing qualified yarns. By this study how to achieve data mining and experimental design applications at a yarn production facility with actual data is presented and the current application is contributed to the processes of the facility.

Although several substantial attempts, there is still a lack of research investigating of how employee characteristics and performance are integrated into a wage structure. In this study, it is intended to develop a salary model that creates a wage level from overall score consisting of job evaluation, employee characteristics and job performance in order to ensure wage fairness and also enhance employee’ satisfaction. In the first phase, a point factor job evaluation system including sixteen factors was adapted to determine the job scores of the white-collar jobs within a company. The score generates a basic payment. There will be extra pay for the staff who are well educated and experienced for the job. A method producing a score from employee characteristics in terms of “education” and “experience” factors was developed. Job performance was measured with how an employee achieves the task activities for eleven job evaluation factors. These three components were integrated to a composite score to translate a wage level. The system was implemented in a middle sized manufacturing company for white-collar jobs. The results indicated that the job point has significantly greater influence on wage level.

Ports and Waterways Safety Assessment (PAWSA) is a comprehensive and sophisticated AHP-based Delphi method in which risk analysis and risk management are handled simultaneously. PAWSA has primarily developed for maritime domain, and there is a need to extend such risk analyses to the other fields. First aim of this study is to introduce PAWSA process and to add its methodology to existing academic literature. Significance of PAWSA is exhibited and innovative suggestions for further developments are given in this study. Secondly, PAWSA method is employed for Istanbul Strait to obtain the levels of navigational risks and to measure effectiveness of counter actions. It analyses risks of navigation situations, the conditions of vessels, traffic intensity and waterway characteristics. Ultimately, it is aimed to minimize the marine incidents and increase navigational safety by introducing new counter actions. The Istanbul Strait is one of the most difficult-to-navigate and the narrowest international waterway in the world. The Istanbul Strait has a dense traffic because of its geographical and strategic location. According to annual statistics, traffic density is two times more than the Suez Canal and three times more than the Panama Canal. Besides the heavy local traffic, the Strait is used by approximately 50.000 international vessels with a total gross tonnage of 600 million. 15 million people live in Istanbul and 300.000 people are transported daily from Asia to Europe using Istanbul Strait. A comprehensive risk analysis by a convenient method for the Istanbul Strait is therefore required for safe maritime transportation.

Hastalar saðlýk hizmetlerindeki israf ve deðiþkenlik nedeniyle bakým süreçlerinde sorunlar yaþamaktadýr. Hastalarýn bu problemler nedeniyle yaþadýklarý rahatsýzlýða raðmen, hizmet saðlayýcýlar aþýrý iþyükü ve örgütsel kargaþa nedeniyle þikayetler ile ivedilikle ilgilenememektedir. Bu çalýþmanýn amacý Türkiye’de Eskiþehir ilinde hizmet veren bir kamu hastanesinin Fizik Tedavi ve Rehabilitasyon servisinde yaþanan operasyonel problemlerin çözümünde yalýn tekniklerin uygulanmasýdýr. Süreç, yalýn tüketim baðlamýnda hem hasta hem de hizmet saðlayýcý bakýþ açýsýndan eþ zamanlý olarak analiz edilmiþtir. Genchi gembutsu, deðer akýþ haritalama (DAH), bütünleþik tüketim ve tedarik haritasý, A3 ve heijunka bu çalýþma kapsamýnda kullanýlan yalýn tekniklerdir. Sistemin haritalandýrýlmasý örgütsel karmaþýklýðýn çözülmesi için fýrsat sunmaktadýr. Sonuç olarak, heijunka uygulamasý kapsamýnda tasarlanan günlük ve haftalýk atama algoritmalarý ile hemþirelerin biliþsel yükü azaltýlmýþtýr. Ayrýca gerçekleþtirilen iyileþtirmeler sonucunda hasta akýþ süresinde %26.84, süreç adýmlarýnda ise %14.28 azalma kaydedilmiþtir.

Determining positions and counting of actors, amount of product flow between and decreasing transportation costs are handled as a network design problem in supply chain management. Supply chain network design (SCND) problem belongs to the class of NP-hard problems. It has therefore appealed to a number of researchers’ close attention. However, existing literature lacks of common benchmark instances for forward SCND problems so as to make a fair comparison between developed and applied heuristic approaches. To this end, 450 new benchmark instances ranging from small to large size for forward SCND problems with two, three and four-echelon are generated and a mathematical model for each of the problems is formulated. Due to the complexity issues, we develop two heuristic solution approaches, genetic algorithm (GA) and hybrid heuristic algorithm (HHA), and we apply them to the large pool of benchmark instances. Comparative experiments show that both the GA and HHA can yield feasible solutions in much less computational time and, in particular, outperforms CPLEX regarding the solution quality as the number of echelon grows.

Supply chain risk management (SCRM) is crucial for a long-term profitable, competitive and sustainable supply chain. Many destructive risk incidents that have affected the global scale have come into play in the historical process. The losses, occurred due to these risk incidents, revealed how the supply chains are fragile against the risks.
In this study, a comprehensive supply-side literature review has been conducted on SCRM. In order to define the conceptual framework of SCRM, 59 studies from the years 1999-2016, and 137 supply-side studies from the years between 2003 and 2016, in which quantitative methods had been utilized, have been determined. All 196 studies have been reviewed, and analyses and suggestions have been provided.
This study, in general terms, differs from the previous review studies by outlining all aspects of the conceptual framework of SCRM, surplus of the reviewed paper, including papers published after 2013, and extend of review coverage.