Current railway track work machinery is mainly operated with diesel fuel. As a result, track maintenance of Austrian Federal Railways (OeBB) amounts to nearly 9000 t CO₂ equivalent per year according to calculations from Graz University of Technology. OeBB’s total length of railway lines only accounts for 0.56% of the world’s length of lines. This indicates huge potential for mitigating greenhouse gas emissions considering the need for track maintenance worldwide. Environmental concerns have led to the introduction of alternative drives in the transport sector. Until now, R&D (Research & Development) of alternative propulsion technologies for track work machinery has been widely neglected. This paper examines the possibility of achieving zero direct emissions during maintenance and construction work in railways by switching to alternative drives. The goal is to analyze alternative propulsion solutions arising from the transport sector and to assess their applicability to track work machinery. Research results, together with a calculation tool, show that available battery technology is recommendable for energy demands lower than 300 kWh per construction shift. Hydrogen fuel cell technology is an alternative for energy demands higher than 800 kWh. For machinery with energy requirements in between, enhancements in battery technology are necessary and desirable for the coming years.

This study assesses and compares lifecycle (LC) greenhouse gas (GHG) emissions from the two main railway track construction types: ballasted track and slab track. In this study, preexisting soil conditions are considered, as they significantly influence necessary measures during the construction phase for each type. This study is executed for Austrian boundary conditions with speeds up to 250 km/h. The results show that ballasted track is associated with 11–20% lower LC GHG emissions, whereby the variation in relative emission reduction is associated with additional soil reinforcement treatments due to varying preexisting soil conditions. Poor preexisting soil conditions increase LC GHG emissions by 26%, underlying the necessity to integrate this parameter into the lifecycle assessment of railway track. In contrast to the higher service life of slab track construction, this type amounts to higher masses of concrete and demands more extensive measures for soil enhancement due to the higher stiffness of the track panel. Only in tunnel areas does slab track cause lower GHG emissions since soil reinforcements are not necessary due to an existing concrete base layer after tunnel construction. For both construction types, over 80% of the GHG emissions stem from material production. Hence, circular economy as well as innovations within steel and concrete production processes hold significant potential for reducing GHG emissions.

Managing head checks is a crucial task for an infrastructure manager as in case of deep cracks, rails can break and, thus, accidents might be the consequence. Many infrastructure managers use vehicle-mounted eddy-current testing for detecting cracks. This is sufficient for guaranteeing safe railway operation in applying a reactive maintenance regime removing cracks of a pre-defined depth. Moving this towards a predictive maintenance regime is only possible through assessing the crack growth. Establishing a stable deterioration function needs a sound data basis including a proper re-positioning of the test results of consecutive testing campaigns. This paper presents the results achieved from analysing the eddy-current testing campaigns of 10 years on a main line of the Austrian railway network and calculating a crack growth function as regression to field data. While it is possible to derive stable functions, the testing frequency needs to be shortened in order to move further to predictive maintenance.

Track deterioration models (TDMs) help to allocate maintenance work (direct costs) to vehicle runs. Furthermore, these models demonstrate the impact of rolling stock properties on infrastructure. This paper review provides an overview of the state of the art in railway track deterioration modelling and outlines the research potential in this domain. The main focus lies on ballast degradation, rail surface wear and fatigue, and their description in an empiric analytic wear formula. The basis for discussion is the wear formula of the Graz University of Technology. While the TDM demonstrates effectiveness, enhancements are sought, particularly with regard to adjusting the track parameters that vary across railway networks. Further exploration aims to refine the description of rail surface wear and rolling contact fatigue (RCF), incorporating factors such as traction energy and short-wave effects and adapting mathematical functions such as the t-Gamma function. This review underscores the need for ongoing research to develop TDMs that are both simple and detailed enough to encourage track-friendly rolling stock design.