Nebojša Bogojević

The proposal of validation metrics for the assessment of the quality of simulations of the dynamic behaviour of railway vehicles

This paper introduces new validation metrics that may be used for the validation of models of railway vehicles. The proposed validation metrics are based on a comparison between the cumulative distribution functions of selected parameters obtained by simulation and measurements. A model of a freight railway vehicle has been developed and the proposed validation metrics were used in model validation. The results of the validation were compared with the results of validation metrics used in the ‘DynoTRAIN’ project. It was shown that the proposed metric is more severe than the metrics used in the project; a result of it comparing the complete domains of the cumulative distribution functions and not only the selected characteristic values.

Application of Artificial Neural Network to Prediction of Traffic Noise Levels in the City of Niš, Serbia

Road traffic noise is one of the main sources of environmental pollution in urban areas. Since the early 1950s many mathematical models for traffic noise prediction have been developed. Available models are usually based on regression analysis of experimental data. This paper presents the application of multilayer feedforward neural network in prediction of equivalent continuous level of road traffic noise in urban areas of the city of Nis, Serbia. Predictions of developed neural network are compared to data collected by traffic noise monitoring, as well as to predictions of commonly used traffic noise models. Obtained results show that the application of artificial neural network may improve accuracy of traffic noise prediction.

DMLS Built Maraging Steel Fatigue Response Investigated for Different Build Orientations and Allowance for Machining

This work derives its motivations from the increasing interest towards Additive Manufacturing and the lack of studies, mainly in the field of fatigue. The effect of build orientation and of allowance for machining on DMLS produced Maraging Steel MS1 has been assessed. The experimental results, properly set up by tools of Design of Experiment, have been statistically processed and compared. The outcomes were that, probably due to effect of the thermal treatment, machining and material properties, the aforementioned factors do not have a significant impact on the fatigue response. This made it possible to work out a global curve, accounting for all the result. Fracture surfaces have been carefully studied as well.

Effects of Machining and Heat and Surface Treatments on as Built DMLS Processed Maraging Steel

The main motivations for this study arise from the need for an assessment of the fatigue performance of DMLS produced Maraging Steel MS1, when it is used in the “as fabricated” state. The literature indicates a lack of knowledge from this point of view, moreover the great potentials of the additive process may be more and more incremented, if an easier and cheaper procedure could be used after the building stage. The topic has been tackled experimentally, investigating the impact of heat treatment, machining and micro-shot-peening on the fatigue strength with respect to the “as built” state. The results indicate that heat treatment significantly enhances the fatigue response, probably due to the relaxation of the post-process tensile residual stresses. Machining can also be effective, but it must be followed (not preceded) by micro-shot-peening, to benefit from the compressive residual stress state generated by the latter.

Comparative analysis of European models for railway noise prediction

According to Directive 2002/49/EC relating to environmental noise assessment and management, all EU countries are obliged to make strategic noise maps for heavily populated areas. Some countries developed their own national method for noise prediction. In addition to road traffic, a railway traffic is, also, significant noise source in urban areas. This paper provides an overview of several models used in European countries for prediction of sound power of railway noise sources and attenuation due to sound propagation between noise source and receiver point.

Influence of Heavy Data Transmission Losses on Spectra of Signals

Measurements of machine vibrations are often influenced by heavy data losses during wireless transmission of signals, which arise because of electromagnetic interference of electric motors. In this paper, authors present an analytic calculation of distortions introduced in spectra of harmonic signals by heavy data transmission losses, which are characterized by the loss ratio and frequency of losses. The results may be used to reduce errors that arise during spectral analysis of signals in conditions of heavy spectral losses.