About this Research Topic
The expansion and improvement of the railway network requires the assessment and mitigation of the environmental impact, induced by implementing such infrastructures. Thus, the main purpose of this Research Topic is to systematize recent advances on the prediction of vibrations and noise induced by railway traffic, to analyze the efficiency that can be achieved by mitigation techniques liable to be applied, and the presentation of interesting experimental and numerical cases studies. Numerical, analytical, and empirical tools as well as data mining and intelligent prediction methodologies, using different kinds of machine learning techniques, are suitable for the development and submission of the most diverse applications in this Research Topic.
This Research Topic covers multiple topics related to the prediction and control of noise and vibrations induced by railway traffic:
- reliable prediction methodologies involving different types of models
- numerical and experimental studies conducted in order to discern the main sources of uncertainty in the system
- the performance of usual and innovative mitigation countermeasures
- discussions about the key parameters of the problem
- identification of performance indicators of the system.
Particularly, special attention is given to prediction models that would be applied by the end-user, creating considerable added value for engineering practitioners.
This Research Topic is widely open to research works developed within these topics. We invite the submission of new research, case studies, projects, reviews, and state-of-the-art discussions as well.
Keywords: Railway Traffic, Noise and Vibrations, Prediction Approaches, Mitigation Measures, Experimental Results, Comfort and Life Quality, Modern Cities
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.