Tatyana Bedych’s scientific contributions

In fuel economy, a rising level of interest in heavy duty diesel engines that industry has witnessed over the last few years continues to go up and this is not likely to change. Lowering the fuel consumption of all internal combustion engines remains a priority for years to come, driven by economic, legislative, and environmental reasons. According to statistics, the share of operating expenses to ensure transport operations in industrial production is 15-20%, wherein 16-30% of the total volume of transport operations concerns a car, tractor, and trailer. During transport operations, the engine load by the torque, in most cases, does not exceed 40-50%. The paper investigates the increase in fuel efficiency of cars and tractors by disconnecting some of the engine cylinders operated in low-load and idling modes. The research has led to the establishment of the theoretical dependencies between the effective power, engine efficiency, mass of the transported cargo, speed of the car (tractor) and the number of disconnected engine cylinders. Results of experiments suggest the interdependencies of the performance parameters of the car (tractor) when disconnecting some of the engine cylinders. It has also been established that the maximum reduction in the hourly fuel consumption occurs in the idling mode while it decreases along with an increase in the load.

This paper presents the application of simulation to assess and predict the influence of random factors of pedestrian flow and its continuity on the traffic capacity of a signal-controlled intersection during a right turn. The data were collected from the surveillance cameras of 25 signal-controlled intersections in the city of Chelyabinsk, Russia, and interpreted by a neural network. We considered the influence of both the intensity of the pedestrian flow and its continuity on the traffic capacity of a signal-controlled intersection in the stochastic approach, provided that the flow of vehicles is redundant. We used a reasonably minimized regression model as the basis for our intersection models. At the first stage, we obtained and tested a simulated continuous-stochastic intersection model that accounts for the dynamics of traffic flow. The second approach, due to the unpredictability of pedestrian flow, used a relevant method for analysing traffic flows based on the fuzzy logic theory. The second was also used as the foundation to build and graphically demonstrate a computer model in the fuzzy TECH suite for predictive visualization of the values of a traffic flow crossing a signal-controlled intersection. The results of this study can contribute to understanding the real conditions at a signal-controlled intersection and making grounded decisions on its focused control.