Assets4rail develops an impact study (WP11) that reflects the socio-economic and wider social implications of the project:
WS1:
1.It is a goal of the A4R project to find the most suitable method(s) to inspect tunnel wall and subgrade condition.
2.It enables the integration of sensor data in a BIM system help to foster the inspection qualities. Furthermore, it enables monitoring data to be displayed side-by-side with all other relevant asset and maintenance information, 3D model data and properties, already present within the BIM environment. Different visualizations of the information is enhanced.
3. A4R project enables a deeper understanding of the “vibration to noise transmission” phenomena in bridges. Results of the project facilitate the introduction of technology to railway infrastructure managers and indirectly decrease noise levels near steel bridges.
4.Results enable to clean of tunnel drainages with high-pressure water for a length up to 1.500 m without the necessity to stop tunnel operations.
5.A4R develops a software tool for evaluation of fatigue consumption of structural components using robust algorithms which enable maintenance cost reduction and prolongation of life of structures.
WS2:
1.The values of the lateral displacement of the wheel relative to the rail can be measured in a real-time manner. These values are fused with acceleration monitoring, to calculate track geometry parameters such as longitudinal irregularity and lateral alignment.
2.A computer vision-based wayside train monitoring system (WTMS) that can automatically detect the critical failures on rolling stock bogies and identify the vehicle identity via RFID. Also, a methodology to assess and quantify the impacts of rolling stock failures on railway infrastructure. The proposed WTMS combines 3D stereo imaging, 2D imaging and RFID technologies for an end-to-end monitoring solution.
3.A modular system for data collection from signalling field elements such as point machines, incl. the on-site data collection device, SCADA system for data management, diagnostic algorithm. The diagnostic algorithm is more robust and allows domain adaptation for different field elements operated in various conditions.
A high-level socio-economic impact assessment was conducted, following the principles of cost-benefit analysis in line with European guidance for the appraisal of transport interventions (European Commission, 2014).
The assessment covers multiple and distinct innovations, and has consequently been structured as four separate impact assessments (or business cases). These four business cases cover innovations which are specific to each of the Work Streams (WS1 and WS2) of the project as well as the implementation of Building Information Modelling (BIM), a keystone of Assets4Rail which brings together aspects relevant to both WS1 and WS2.
Business Cases 1 and 2 assess the impact of the proposed innovations from WS1: i) technologies for the cleaning of long distance (tunnel) drainage pipes and ii) noise reduction measures. Business Case 3 focuses on measuring the impact from installing wayside 3D cameras to monitor the status of bogies of freight wagons, an innovation investigated under WS2. Finally, Business Case 4 provides a high-level impact assessment on the costs and benefits of adopting BIM in monitoring and maintaining railway infrastructure and assets, a technological innovation that is relevant and cross-cutting throughout the multiple tasks and objectives of the Assets4Rail project.
Active participation in international and European conferences, presentations, and events was performed. In addition, a mid-term conference and a final conference organised by the consortium has been the Assets4Rail milestones to deliver the results to specialized audiences of the project.
