In this study, the atmospheric electric charge changes were examined using an FET sensor. As is known, there are many resources that affect the global atmospheric cycle. The source is the sun in the most important of these resources. This study examined the effects of the sun on global atmospheric circuit.
Controlling the heat during cutting operations are an important factor in improving the quality of the product and performance of the machining. For controlling the heat, there are a lot of methods. One of this is Vortex Tube Cooling System. In this study, the Vortex tube cooling system was used to control heat during the turning operation. In the design of experiment, cutting speed, cooling temperature, feed rate, and cutting tool corner radius were selected as input parameters. Surface roughness and cutting force was selected as output parameters. The input and output parameters were modeled by using Artificial Neural Network, the results of experiment were optimized.
In this study boron carbide based sandblasting nozzles were produced by Low Pressure Powder Injection Molding (LPPIM) method, and wear behaviors of the nozzles were examined. The addition powder, addition ratio and sintering temperature were used as input parameters while density, micro hardness and wear rate were used as output parameters in the experimental design. This study consists of 3 steps: 1) production of standard samples and characterization, 2) modeling of proses parameters using Artificial Neural Network (ANN) method, 3) selection of nozzle material and production of nozzle, and testing. As a results of this study, ANN method can be used for modeling of process parameters of powder injection molding since the average value of the prediction error is below 7%, and boron carbide based products can be produced by using LPPIM method.