Ferenc Horvat

56556762800

Publications - 4

Innovative Approaches in Railway Management: Leveraging Big Data and Artificial Intelligence for Predictive Maintenance of Track Geometry

Publication Name: Tehnicki Vjesnik

Publication Date: 2024-01-01

Volume: 31

Issue: 4

Page Range: 1245-1259

Description:

This paper introduces and describes a method for extracting, processing, and analyzing large amounts of track geometrical data. It allows for a more accurate description of the orbital deterioration correlations than currently applied procedures, and it seems to be more valuable and efficient in practice. The initial data were the track geometry measurement and classification data for the whole national network provided by the Hungarian State Railways, i.e., the MÁV PLC. The MÁV provided data for the whole Hungarian railway network for 27 half-years, measured and recorded by the FMK-004 type special diesel locomotive (i.e., track geometry measuring car). The paper discusses the development of a procedure to automatically compute important condition ratings from the available data set of millions of units according to the algorithms created for railway industry colleagues, thus helping the maintenance and renewal decision-making process. Functions have been developed to classify the track geometry condition of a given railway line, to predict how long the service level can be maintained without intervention (i.e., e.g., lining, leveling, and tamping with a mechanized maintenance train), to determine the time of the necessary maintenance intervention, the time of the upgrade (rehabilitation or modernization), and to develop a track geometry prediction procedure that makes full use of the mathematical and computational possibilities of the present day.

Open Access: Yes

DOI: 10.17559/TV-20240420001479

Head Checks and the Useful Life of Rails

Publication Name: Chemical Engineering Transactions

Publication Date: 2023-01-01

Volume: 107

Issue: Unknown

Page Range: 295-300

Description:

Transport systems, including railways, are an important part of everyday life in modern societies. Whether it is passenger or freight transport, railways are an environmentally friendly solution with their robust throughput capacity and modern electrified lines. The significant changes in transport needs over the last fifty years have partly modified its role, increasing both track speed and axle load. Head Checks (HC) appeared on the MÁV (Hungarian Railway Corporation) network in the early 2010s. This phenomenon had been an unknown problem in Hungary before. Several cases abroad (e.g., a train derailment at Hatfield station in 2000 with four fatalities) have highlighted the extreme danger of this phenomenon. Materials and railway track experts at Széchenyi University have been working on the subject of HC defects in rail heads for several years. The results of research work carried out for MÁV Zrt. form the base of this article. The novelty of this article is the complexity consideration. Not only the structural changes of the rail material were investigated, but also the time/traffic load-dependent crack evolution was mathematically described. Based on the strategy outlined in the report of the research work, MÁV has taken up the fight against HC cracks, which were initially proliferating. The modern laboratory test in this article is based on the tests of Csizmazia and Horvát (2014). The stresses causing damage were investigated previously by Horváth and Major (2023). The economic analysis is based on Róbert Horváth's own calculation results.

Open Access: Yes

DOI: 10.3303/CET23107050

Investigation of confinement effect by using the multi-level shear box test

Publication Name: 10th International Conference on Geosynthetics Icg 2014

Publication Date: 2014-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

The stabilisation and reinforcement of crushed stone aggregate in infrastructural applications using geogrid reinforcement is based on the phenomenon called the "interlocking effect". Through shear interaction of the aggregate with the geogrid, the aggregate is laterally restrained and tensile forces are transmitted from the aggregate to the geogrid. This interaction helps reducing lateral movement of the aggregate and optimises road/track performance. It is well known that this strengthening effect depends on several influencing factors. It is still difficult to quantify the true reinforcement efficiency with regard to the limit of the lateral restraint effect (or confining resistance) over the depth of the aggregate layer being placed on top of the geogrid. To be able to quantify the confining resistance efficiency of geogrids over the depth of the installed aggregate layer a laboratory test was developed (Multi-level shear box test) which allows measuring the shear resistance as a function of the distance from the geogrid layer (in vertical direction). This paper will describe the methodology of the so called "Multi-level shear box test" as well as the results of the confinement efficiency of different type geogrids in combination with railway ballast.

Open Access: Yes

DOI: DOI not available

Assessment of particle confinement within a mechanically stabilised layer

Publication Name: 10th International Conference on Geosynthetics Icg 2014

Publication Date: 2014-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

The effect of geogrids on unbound granular fill by the mechanism of mechanical interlock has been established with particle confinement identified as being an important component influencing the performance of the resulting mechanically stabilised layer. Evaluation of the influence of geogrids on particles through the thickness of the mechanically stabilised layer has been carried out using a large multi-level shear box. The results obtained from the programme of testing carried out at the University of Gyor will be discussed by reviewing measured shear resistance at several levels in the granular fill to characterise the influence of the geogrid on particle confinement through the granular layer thickness.

Open Access: Yes

DOI: DOI not available