Mechanical and microstructural properties of low-carbon steel-plate-reinforced gray cast iron

In the present experimental study, strengthening of gray cast iron by reinforcing with steel plates was investigated in the as-cast and normalized conditions. Normalizing heat treatments were applied to the specimens at temperatures of 800 °C and 850 °C. Three-point bend specimens were manufactured from gray cast iron and also from gray cast iron with reinforced steel plates. Flexural strengths of the steel-plate-reinforced cast iron were calculated for four distinct volume fractions (V_r = 0.04, 0.08, 0.12, and 0.16). The current study shows that the steel-plate-reinforced gray cast iron has higher flexural strength and flexural modulus than the cast iron without reinforcement. The flexural strength considerably increases with slight increase in normalization temperature. Optical and scanning electron microscopy analyses were used to examine flake morphology and microstructures of gray cast iron and steel-plate-reinforced gray cast iron. It is noted that carbon diffuses from the gray cast iron to the steel plates. A transition region containing partially dissolved graphite and having high hardness was observed due to the carbon diffusion.     

An analytic hierarchy process and two-sided matching based decision support system for military personnel assignment

Assignment of military personnel to positions is very demanding, primarily a manual process performed by detailers. Detailers try to satisfy needs and preferences of commands and personnel. In this paper, an analytic hierarchy process (AHP) and two sided matching based Decision Support System is proposed to assist detailers. The DSS is programmed to generate positions’ preferences from position requirement profiles and personnel competence profiles by using analytic hierarchy process and matches personnel to positions by using two-sided matching. The use of the proposed DSS is demonstrated with an example. Also, the effects of preference list length on two-sided matching are examined.     

Wear behavior of a crankshaft journal bearing manufactured by powder spraying

A new crankshaft bearing material that can be an alternative to the traditional material has been improved and its wear behavior studied experimentally. Crankshaft main bearings are subjected to various stresses. A new material supposed to be adapted these operating conditions was designed composing of Pb–Sn–Cu–ZrO₂ and manufactured by HVOF spraying technique. Wear behavior of the bearing was tested with the simulation of real operating conditions. An original bearing was used for comparison. After a trial of 500 h, the weight losses were measured. SEM micrographs of both original and new bearings were examined. The effect of microhardness was discussed. The new composition was seen as promising as a bearing material for automotive engines.     

Seismic microzonation of the historic peninsula of İstanbul

In this study, the geological and geotechnical conditions of old Istanbul (Fatih and Eminönü provinces) were investigated in detail and a seismic microzonation study was undertaken for this historical peninsula, which is the site of many ancient structures. Dynamic site response, liquefaction potential and slope stability analyses were carried out, based on field and laboratory tests and earthquake time histories computed with respect to probabilities of exceedance of 10 and 40% in 50 years. The output data obtained from the analyses were evaluated by GIS techniques, and ground shaking, liquefaction susceptibility and landslide hazard maps were prepared.     

Relationship among fecal coliforms and <Emphasis Type="Italic"> Escherichia coli </Emphasis>in various foods

For much of the twentieth century, coliform bacteria and especially Escherichia coli have been used as indicators of possible post-processing contamination and the presence of E. coli as an indicator of fecal contamination in foods. In this study, 500 foods in 10 different groups, mainly dairy products, delicatessen products, salads, spices, cream cakes and fresh fruit and vegetable samples, were analyzed for the natural contamination of fecal coliforms and E. coli by the standard most probable number (MPN) method. The difference between weighted means of fecal coliforms and E. coli counts were only 0.246 log₁₀ MPN/g-ml (MPN/gram for solid samples, and MPN/milliliter for liquids). Enumeration results were also evaluated by Pearson's correlation coefficient ( r), Cronbach's alpha (f) and determination coefficient ( r ²) analysis. According to results, although 33 samples contained only non- E. coli fecal coliforms, the results of reliability analyses indicated that fecal coliform counts and E. coli counts may be used interchangeably ( P <0.0001). It can be said that fecal coliform or, preferably E. coli analysis is sufficient for rapid routine determination of fecal contamination, at least for those food groups analyzed in this research.     

Neural network and fuzzy logic-based hybrid attitude controller designs of a fixed-wing UAV

Neural Computing and Applications - In this paper, a mini unmanned aerial vehicle (UAV) is planned to be used in applications such as spraying pesticide and weed control in agricultural areas....     

Atmospheric and anthropogenic deterioration of the İvriz rock monument: Ereğli-Konya,Central Anatolia,Turkey

Bulletin of Engineering Geology and the Environment - The aim of this study is to determine the extent of deterioration of the limestone on which the İvriz rock monument is engraved. This...     

Model Predictive Control Coupled with Artificial Intelligence for Eddy Current Dynamometers

The recent studies on Artificial Intelligence (AI) accompanied by enhanced computing capabilities supports increasing attention into traditional control methods coupled with AI learning methods in an attempt to bringing adaptiveness and fast responding features. The Model Predictive Control (MPC) technique is a widely used, safe and reliable control method based on constraints. On the other hand, the Eddy Current dynamometers are highly nonlinear braking systems whose performance parameters are related to many processes related variables. This study is based on an adaptive model predictive control that utilizes selected AI methods. The presented approach presents an updated the mathematical model of an Eddy Current Dynamometer based on experimentally obtained system operational data. Finally, the comparison of AI methods and related learning performances based on the assessment technique of mean absolute percentage error (MAPE) issues are discussed. The results indicate that Single Hidden Layer Neural Network (SHLNN), General Regression Neural Network (GRNN), Radial Basis Network (RBNN), Neuro Fuzzy Network (ANFIS) coupled MPC have quite satisfying performances. The presented results indicate that, amongst them, GRNN appears to provide the best performance.     

Increasing the conversion fraction of sulfur to sodium thiosulfate with the ultrasound energy

The usage of ultrasound has gained popularity in the recent years. Ultrasonic processing means blasting liquids, usually water, with very intense sound at high frequency, producing very well mixed powerful chemical and physical reactions. This paper deals with the investigation of the effect of ultrasonic energy on the conversion fraction of sulfur in the production reaction of sodium thiosulfate which was obtained from sulfur and Na₂SO₃ solution. Concentration of Na₂SO₃ solution parameter was chosen as the constant parameter. The experiments were performed with various amplitudes of ultrasound power and in the absence and presence of ultrasound energy in various temperatures with various particle sizes. The results indicate that the conversion fraction values increase in the presence of ultrasound energy and increase at high amplitude values.