Turkey is among the countries largely dependent on energy import. This dependency has increased interest in new and alternative energy sources. Installation of rooftop solar photovoltaic systems (RSPSs) in Turkey is increasing continuously regarding geographical and meteorological conditions. This paper presents an insight into the potential situation for Turkey and a simulation study for the RSPS designing and calculation for the faculty building at Marmara University in Istanbul. This simulation study demonstrates that 84.75-kWp grid-connected RSPS can produce remarkable power. The system is performed in detail with the PV*SOL software (Premium 2017 R8 - Test Version, Valentin Software GmbH, Berlin, Germany). Detailed financial and performance analysis of the grid-connected RSPS for faculty building with various parameters is also carried out in this study. According to the simulation results, the system supplies 13.2% of the faculty buildings’ annual electrical energy consumption. The annual savings value of faculty buildings’ electrical consumption is approximately 90,298 kWh energy which costs roughly $7296. A photovoltaic (PV) system installation for the faculty building, which has considerable potential for solar energy and sunshine duration, is indispensable for clean energy requirements and was supported by the simulation results. This paper can be considered to be a basic feasibility study prior to moving on to the implementation project.

Fuzzy group decision support system is an approach developed to assess the performance of engineering education students. This approach provides multiple perspectives of different people and prevents subjectivity in the evaluation process. It also enables students to take active roles in the assessment. Hence, unbiased evaluation is aimed to be promoted. The developed software for the specific purpose of this study is user-friendly and has multi-criteria decision dimension. The pedagogical implication and aspect of the study have also been displayed in the case study part. The results of the study reveal that fuzzy logic has been influential in increasing the quality of education facilities, motivation, reliability, consistency, and objectivity of the assessment. ß

In recent years, the importance of laboratory applications in engineering education has increased because, there is need for transferring the theoretical knowledge to empirical research and practice, which is particularly significant for the development of students in their career. Therefore, the evaluation of these laboratory applications should be effective. In this study, we propose a new approach to this assessment system. Our approach uses fuzzy decision support system and proposes a new approach that is called 'refinement process' on student grades. Fuzzy helps more reliable decision making and evaluation of applications using a pre-determined list of criteria. This model based on fuzzy multi criteria method, is developed for evaluating student performances in laboratory activities which consolidate theoretical knowledge with practical applications. In our approach, we use peer assessment, group assessment and personal assessment methods. This study shows that fuzzy system can provide a better evaluation system than classical systems.

Today’s automotive industry has focused its studies on electric vehicles (EVs) or hybrid electric vehicles (HEVs) rather than gasoline-powered vehicles. For this reason, more investment has been made in electric motors with high efficiency, high torque density, and high-power factor to be used in both EVs and HEVs. In this study, an outer-rotor permanent-magnet-assisted synchronous reluctance motor (PMaSynRM) with a new rotor topology was designed for use in an EV. The design has a transversally laminated anisotropic (TLA) rotor structure. In addition, neodymium-iron-boron (NdFeB) magnets were used in rotor topology. The stator slots were designed as distributed windings, so torque ripples are minimized. At the same time, the maximum electromagnetic torque was achieved. The analysis of the designed motor was carried out using the finite element method (FEM). Optimal values of motor parameters were obtained by improving the rotor geometry of the three-phase PMaSynRM in order to obtain maximum torque and minimum torque ripple in the design. The motor is in a 48/8 slot/pole combination, a speed of 750 rpm and a power of 1 kW. The simulation results showed that the design achieved maximum torque and minimum torque ripple.

Collision risk assessment and collision avoidance of vessels have always been an important topic in ocean engineering. Decision support systems are increasingly becoming the focus of many studies in the maritime industry today as vessel accidents are often caused by human error. This study proposes an anticollision decision support system that can determine surrounding obstacles by using the information received from radar systems, obtain the position and speed of obstacles within a certain time period, and suggest possible routes to prevent collisions. In this study we use a neural network to predict the subsequent positions of surrounding vessels, a fuzzy logic system to obtain the risk of collision, and a particle swarm optimization algorithm to find the safe and shortest path for collision avoidance.