RAIL4EARTH
Building a more attractive and resilient transport mode and contributing to the objectives of a climate neutral Europe for 2050.
Goal
The goal is to improve the existing sustainability performance of railways, to build a more attractive and resilient transport mode, and to contribute towards the objectives of a climate neutral Europe for 2050.
Scope
The scope of work of the four-year FP4-Rail4EARTH, under the HORIZON-ER-JU-2022-FA4-01 call topic, is to improve the existing sustainability performance of railways, to build a more attractive and resilient transport mode and to contribute towards the objectives of a climate neutral Europe for 2050. The activities are covering the Europe’s Rail Flagship Project 4 Sustainable and Green Rail Systems, including rolling stock, infrastructure, stations, and all their related sub-systems (traction, bogies, brakes, energy storage systems, HVAC, etc.).
Involvement
Within this project, the Division of Operation and Maintenance Engineering at Luleå University of Technology (LTU) is engaged in two work packages (WP).
WP2: Adaptation to climate change
The aim WP2 is to implement the EU adaptation strategy to the railway sector to make it resilient to climate changes and its impacts. Project objectives are:
- A smarter adaptation to the climate change
- A faster adaptation by identifying existing solutions.
- During the first year of project execution, LTU’s work in WP2 consists of the following activities.
- Exploring Impacts of climate change on railway assets
- Exploring Infrastructure top 10 weather-related failures
- Working on "Design and testing standards mapping
- Working on "Operation events mapping
- Identify the TRV’s return of experience in connection to this project.
- Furthermore, LTU aims to provide different KPI to assess the Rail4Earth project tasks and working packages. Defined KPI should answer the following preliminary questions as:
- How climate adaption activities and proposed measures in Rail4Earth project has impacts on “Asset utilisation”, “Service quality” and “Financial effectiveness”?
- How does spending for maintenance and renewals change over time based on different RCP’s Scenarios?
To address the questions there is need to assess different performance indicators, including RAMS and LCC aiming to provide continuous monitoring and support for long-term climate adaptation measures and actions planning.
WP3: Noise and Vibration
Curve squeal from railway vehicles creates noise problems in urban environments where residential areas are close to railway curves. Monitoring squealing noise is an important task in understanding how frequently and under what conditions squealing noise arises.
LTU will work with task 3.5.2 where a practical standalone wayside monitoring system for squealing noise is developed. This system will detect curve squeal events by monitoring rail vibration signals via sensors attached to the low and high rail in a curve. The system will be installed and tested on a curve where squealing noise is frequently generated in Södertälje Sweden. The traffic in the curve consists of suburban passenger trains with motorized bogies, see Figure 1.
Figure 1. Suburban passenger train negotiating the curve at the measurement site in Södertälje
The initial track side measurements performed by LTU were started in March 2023. The purpose with this initial installation was to test different setup and mounting of sensors. The final measurement setup was completed in October 2023, consisting of rail mounted accelerometers that measure rail acceleration and rail temperature, and additional sensors that measure the air temperature and relative humidity. The single axis accelerometers are mounted on the rail web of the high and low rail of the curve.
Figure 2 shows the principle of the measurement setup. The main measurement system unit (MS) stores the recorded pass-by measurements and uploads these to a web server for further processing.
Figure 2. Principle of the monitoring system setup.
A long-term monitoring campaign has been started for harvesting data on curve squeal from the curve. Squealing events are detected and analysed from the recorded rail vibration signals and the quality of the measurements is being inspected regularly. Algorithms for vibration signal analysis are being developed for automatic detection of curve squeal.
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