ISSN: 2490-3477

E-ISSN: 2490-3485

TTTP

Traffic and Transport Theory and Practice

Journal for Traffic and Transport Research and Application

Vol. 2 No. 1-2 (2017): TTTP - APEIRON

Veljko Đukić

The possibilities of using biodiesel in service of reducing the urban air pollution

Original scientific paper

DOI: 10.7251/JTTTP1701005DJ

Abstract

Using renewable energy is in line with the global strategy of sustainable development. The use of biofuels in transport contributes to increasing security of supply and reducing dependence of the trans- port sector on oil, reducing the share of greenhouse gas emissions from road transport and sustainable development of urban areas. The advantage of biodiesel in comparison to other alternative fuels can be seen in use in existing vehicles without or with minor modification of existing motors, depending on the concentration of biofuels in combination with fossil fuels. This paper discusses the possibilities of reducing the air pollution by using biodiesel, pollutants arising as a result of combustion of fuel in internal com- bustion engines, as well as the possibility of using waste cooking oil to produce biodiesel. The presented results show the reduction of air pollution using biodiesel as an alternative fuel, as well as the possibilities of solving the problem of wasting edible oil by using it for biodiesel production.

Keywords : biodiesel, air pollution, edible oil.

Vol. 26 No. 2 (2023): JITA - APEIRON

Igor Shubinsky, Alexey Ozerov

Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures

Original scientific paper

Abstract

The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.

Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.

Vol. 26 No. 2 (2023): JITA - APEIRON

Igor Shubinsky, Alexey Ozerov

Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures

Original scientific paper

Abstract

The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.

Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.