Periodic Reporting for period 2 - DESTINATE (Decision supporting tools for implementation of cost-efficient railway noise abatement measures)
Période du rapport: 2017-11-01 au 2018-10-31
The project DESTINATE aims to develop methodologies and tools that facilitate informed decisions on cost-efficient rail noise mitigation options. This main objective is supported by five technical objectives.
1. Development of an improved methodology and algorithm for assessing the cost-effectiveness of noise mitigation and sound design including human perception.
2. Development of a novel simulation model of interior noise, based on operational transfer path measurements.
3. Identification of relevant source and sub-assembly input data for noise simulation and development of a systematic methodology for source and sub-assembly characterisation.
4. Development of auralisation and visualization of noise scenarios to support the demonstration of mitigation methods’ efficiency.
5. Analysis and assessment of the effectiveness of new noise control technologies on noise-proof windows.
Operational transfer path analysis (OTPA) was used to identify and rank main railway noise sources for the TramLink prototype of Stadler Rail Valencia. These were measured for real operation conditions on the Valencia network. Based on these measurements a model was built with the capability to predict design changes. To validate the model, a second measurement campaign was carried out in Gmunden on a TramLink. It was shown that the model is capable to predict certain design changes for trains of the same family. As OTPA works in the time domain, the data could be used directly for auralisation.
Within the project, different experimental source characterisation methods were investigated when applied at train-level in real-life conditions. It was found that in-situ structure-borne sound source characterisation is a useful method for application in the railway industry.
The first A&V (auralisation and visualisation) model for railway noise based purely on physical processes was developed. Four different output modes are supported by the A&V system: classroom presentation, spatial video and audio for web-sharing platforms, presentation in a studio with loudspeaker array and rendering for virtual reality with a head-mounted display. Several demonstration scenarios were developed for freight and regional trains. The model allows varying different parameters like rail and wheel roughness in a controlled way. Listening tests can be carried out to research the effect of mitigation options before implementing them. Interior railway noise A&V was investigated using binaural replay of spatially placed sound sources. Visualisation of the train interior was achieved by a combination of 3D modelling of the train structure and passengers and videos of the moving landscape. The applicability was demonstrated through a listening test (speech intelligibility) in virtual reality using a head-mounted display. The complementary project FINE 1 supported this task by delivering valuable input data for both auralisation and visualisation.
An analysis of the technical feasibility of selected new technologies to improve sound insulation of windows was carried out. Applicability and benefits were discussed.
All public results and further information can be found on the project website. A&V demonstration videos were put on YouTube so that everyone can experience the project outcome at home: www.youtube.com/playlist?list=PLFHEzMwLXvjGY4KUMNR1PWGPWXj40jXnk. Project results were presented at several scientific conferences (e.g. Internoise 2017, Euronoise 2018 and ICSV 2018) and in articles and conference papers. A&V scenarios were demonstrated at Innotrans 2018 at the Shift2Rail stand. The project results will mainly be exploited in PhD theses and future research at universities, for improved services of consultancies and improved acoustic design of trains. The A&V demonstrator will be used as:
1. A communication tool, which is made available to public authorities for information purposes,
2. A research tool to provide audio samples for psychoacoustic listening test to explore the effectiveness of noise mitigation measures from a subjective point of view and
3. A service for rail vehicle manufacturers and infrastructure operators to support noise related issues.
For interior noise, the OTPA based approach providing frequency and time signals that may readily be auralised helps to enhance the state of the art of interior noise prediction modelling. Taking into account not only sound levels but also sound composure in the development and redesign of trains for an improved hearing experience will be key to raise the attractiveness of the railway public transport sector.
A versatile, physics-based auralisation tool was developed for train pass-bys and is ready for application, making audio recordings for auralisations obsolete. Earlier developed technology from the aerospace domain was used and adapted for use in the rail domain. In particular, the use of virtual reality glasses and binaural headsets was applied for research that can now be done for the interior of a train cabin. A listening test for cabin comfort, successfully used in assessing cabin comfort for a business jet, was translated to the rail domain. In DESTINATE, this test was integrated in the virtual reality world, where a non-intrusive evaluation can take place for different audio scenarios in the train.
The main impacts are:
1. Improved attractiveness and comfort for rail users through improved noise prediction and perception-based evaluation of mitigation measures with innovative approaches like auralisation & visualisation.
2. Reduced exposure to noise and vibration through improved noise prediction and cost-efficiency assessment of mitigation measures.
Both an increased acoustic comfort in trains and a decrease of railway exterior noise in general and more importantly of annoying components helps to raise the quality of life in Europe and minimise adverse health effects.