engleski

Input data complexity in railway traffic noise modeling: Case Study of Railway line M604 Oštarije – Gospić – Knin – Split

Many sources of error can influence traffic noise modeling results: choice of calculation method, applied software, and input data complexity. In addition, when large areas need to be analyzed, noise calculations usually get time-consuming and costly very fast. At the same time, the required input data needed for these calculations might not be available. In the Republic of Croatia, a uniform database for noise models preparation and the analysis of railway noise emission is not yet developed. In order to prepare a sufficiently accurate model of the area under study, a large quantity of data obtained from various sources must be used for each analysis. Therefore, the designer must be aware that a trade-off between the required accuracy of the results and the time and cost needed to perform the analysis will always be present in this process. In this paper, the influence of input data complexity in railway traffic noise modeling will be presented on an example of a railway line M604 Oštarije – Gospić – Knin – Split in Croatia. In order to upgrade the track structure for train speed of up to 160 km/h, approximately 62 km long section of this railway line was reconstructed. As a part of the reconstruction project, railway noise analysis was conducted. Because a large part of the analyzed area is contaminated with landmines, noise levels were defined by means of several field measurements in the close proximity of the tracks, and noise modeling. The purpose of the analysis presented in this paper was to determine which adjustments of available input data can be made in order to reduce model preparation and noise calculation time, without influencing the accuracy of the results.

noise modeling, input data, rail traffic

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