Rail roughness and rolling noise in tramways

Companies which manage railway networks have to cope continually with the problem of operating safety and maintenance intervention issues related to rail surface irregularities. A lot of experience has been gained in recent years in railway applications but the case of tramways is quite different; in this field there are no specific criteria to define any intervention on rail surface restoration. This paper shows measurements carried out on some stretches of a tram network with the CAT equipment (Corrugation Analysis Trolley) for the principal purpose of detecting different states of degradation of the rails and identifying a level of deterioration to be associated with the need for maintenance through rail grinding. The measured roughness is used as an input parameter into prediction models for both rolling noise and ground vibration to show the potential effect that high levels of roughness can have in urban environment. Rolling noise predictions are also compared with noise measurements to illustrate the applicability of the modelling approach. Particular attention is given to the way the contact filter needs to be modelled in the specific case of trams that generally operate at low speed. Finally an empirical approach to assess vibration levels in buildings is presented

The evolution of the Kazakhstani Silk Road section from a transport into a logistics corridor and the economic sustainability of regional development in Central Asia

Central Asian countries attract investment in transport infrastructure to rebuild the Silk Road paths and enjoy economic benefits from the participation in international trade. The Kazakhstani government approached the Russian and Chinese governments intending to join the Western Europe-Western China (WE-WC) initiative to boost the country's regional development. The paper aims to assess how the WE-WC transport corridor affected the economic potential of linking cities and regions starting from the quality of transport infrastructure and leading to their export potential. The study's findings showed that the Kazakhstan section of the WE-WC corridor was at an early stage of transformation from a transport into an economic corridor. While the Russia-Uzbekistan section continues to serve mainly a transit function and operate at the level of transport infrastructure, the China-Kyrgyzstan section has started evolving from the level of multimode transport corridor to the level of logistics corridor. The economic sustainability of the WE-WC linking mining and agricultural regions of Kazakhstan still comes into question and depends on the government's further region-specific policy actions

Temperature and moisture in highways in different climatic regions

The article represents the results of experimental research for temperature and moisture variations in pavements and subgrade of highways located in five different climatic regions, an analysis of cyclic freezing and thawing of a pavement. To measure temperature and moisture in pavements and subgrade the sensors have been used which allow making measurement of these characteristics simultaneously in the points of interest. The peculiarities of variation were analyzed for air temperature, temperature in pavements and subgrade in different regions in warm and cold 24 hours. The differences were established in distribution of temperature and moisture in pavements and subgrade in warm and cold 24 hours. To analyze cyclic freezing and thawing (FT) of a pavement the air temperature values have been used during twenty sequential winter seasons in six geographical points of Kazakhstan. The dependences were established for the number of FT cycles on duration and minimal temperature of the cycles

Analysis of enterrelation between economic, road, transport and logistic indicators

The purpose of this research is to identify interrelation analysis between economic, road, transport and logistics indicators. Retrospective research of the freight turnover dynamics was conducted, as well as roads length, number of transport companies and the Gross National Product (GDP) from 1993 to 2017 in the Republic of Kazakhstan. For transport field freight turnover was chosen as economic indicator, for logistics service-the number of transport companies and the length of the motorway-for the infrastructure development. The qualitative analysis of the condition of the road surface showed unevenness of the infrastructure development along the corridor. It was revealed that the increase of freight turnover and the number of companies lead to the growth of the regional economic indicator GDP. However, the transport criteria are significantly lagging behind of the GDP growth rate. The lag was caused by the prolonged period of logistics infrastructure formation. Given the positive dynamics at the time of the route launch, it can be assumed that the development of regional economics is associated with the process of region integration into the international transport system, where the corridor «WE-WC» can be one of integration mechanisms

Use of Hybrid Mineral Filler with High Emissivity in Asphalt Mixture for Cooling Road Pavements

Road asphalt pavements cover a high percentage of urban size and contribute to heat islands. This study proposed a new method to cool asphalt pavement by incorporating a kind of hybrid mineral filler (HMF) with high emissivity into a reference asphalt mixture prepared with limestone mineral filler (LMF). The physical, emissive, solar reflective, and rheological properties of asphalt mastic and the thermal performances of asphalt mixture were covered to investigate the possibility of the proposed strategy. From Fourier transform infrared spectrum test, it can be found that HMF was physically blended with asphalt. The emissivity results show that HMF increased the emissivity of asphalt mastic from 0.9204 to 0.9820. The asphalt mastic containing HMF had similar solar reflectance with the control one. In addition, HMF could enhance the rutting resistance of asphalt mastic according to the results of multiple stress creep recovery tests. When HMF replaced LMF, the thermal conductivity of the asphalt mixture with HMF increased by 0.26 W/(m·K) (the reference value was 1.72 W/(m·K)). The combined effect of high emissivity and thermal conductivity led to a lower surface temperature (i.e., −5.4 °C) in the tests. The results of this study demonstrate that HMF is a potential material to cool asphalt pavements

Ensemble of deep convolutional neural networks for automatic pavement crack detection and measurement

Automated pavement crack detection and measurement are important road issues. Agencies have to guarantee the improvement of road safety. Conventional crack detection and measurement algorithms can be extremely time-consuming and low efficiency. Therefore, recently, innovative algorithms have received increased attention from researchers. In this paper, we propose an ensemble of convolutional neural networks (without a pooling layer) based on probability fusion for automated pavement crack detection and measurement. Specifically, an ensemble of convolutional neural networks was employed to identify the structure of small cracks with raw images. Secondly, outputs of the individual convolutional neural network model for the ensemble were averaged to produce the final crack probability value of each pixel, which can obtain a predicted probability map. Finally, the predicted morphological features of the cracks were measured by using the skeleton extraction algorithm. To validate the proposed method, some experiments were performed on two public crack databases (CFD and AigleRN) and the results of the different state-of-the-art methods were compared. To evaluate the efficiency of crack detection methods, three parameters were considered: precision (Pr), recall (Re) and F1 score (F1). For the two public databases of pavement images, the proposed method obtained the highest values of the three evaluation parameters: for the CFD database, Pr = 0.9552, Re = 0.9521 and F1 = 0.9533 (which reach values up to 0.5175 higher than the values obtained on the same database with the other methods), for the AigleRN database, Pr = 0.9302, Re = 0.9166 and F1 = 0.9238 (which reach values up to 0.7313 higher than the values obtained on the same database with the other methods). The experimental results show that the proposed method outperforms the other methods. For crack measurement, the crack length and width can be measure based on different crack types (complex, common, thin, and intersecting cracks.). The results show that the proposed algorithm can be effectively applied for crack measurement

Experimental investigation on the use of multiple very low-cost inertial-based devices for comfort assessment and rail track monitoring

The periodic rail track inspection is mandatory to ensure ride comfort and operational safety. However, conventional monitoring technologies have high costs, stimulating research on low-cost alternatives. In this regard, this paper presents the first experimental results on the use of multiple very low-cost sensors aboard trains for vibration monitoring, proposing a collective approach to provide more accurate and robust results. Nine devices comprising commercial-grade inertial sensors were tested in different distributions aboard a high-speed track recording train. Frequency weighted accelerations were calculated in accordance with ISO 2631 standard as comfort and indirect track quality index. As expected, vertical and lateral results were correlated with, respectively, track longitudinal level (range D1, maximum correlation coefficient of 0.86) and alignment (range D2, maximum correlation coefficient of 0.60), with numerically similar results when considering the fused signal. The collective approach's potential was proven as a result of the noise reduction and the discrepant sensor identification

Automatic crack detection on road pavements using encoder-decoder architecture

Automatic crack detection from images is an important task that is adopted to ensure road safety and durability for Portland cement concrete (PCC) and asphalt concrete (AC) pavement. Pavement failure depends on a number of causes including water intrusion, stress from heavy loads, and all the climate effects. Generally, cracks are the first distress that arises on road surfaces and proper monitoring and maintenance to prevent cracks from spreading or forming is important. Conventional algorithms to identify cracks on road pavements are extremely time-consuming and high cost. Many cracks show complicated topological structures, oil stains, poor continuity, and low contrast, which are difficult for defining crack features. Therefore, the automated crack detection algorithm is a key tool to improve the results. Inspired by the development of deep learning in computer vision and object detection, the proposed algorithm considers an encoder-decoder architecture with hierarchical feature learning and dilated convolution, named U-Hierarchical Dilated Network (U-HDN), to perform crack detection in an end-to-end method. Crack characteristics with multiple context information are automatically able to learn and perform end-to-end crack detection. Then, a multi-dilation module embedded in an encoder-decoder architecture is proposed. The crack features of multiple context sizes can be integrated into the multi-dilation module by dilation convolution with different dilatation rates, which can obtain much more cracks information. Finally, the hierarchical feature learning module is designed to obtain a multi-scale features from the high to low-level convolutional layers, which are integrated to predict pixel-wise crack detection. Some experiments on public crack databases using 118 images were performed and the results were compared with those obtained with other methods on the same images. The results show that the proposed U-HDN method achieves high performance because it can extract and fuse different context sizes and different levels of feature maps than other algorithms

Reference trajectories of vehicles for road alignment design

The geometric design principles traditionally hypothesize that trajectories of vehicles can be assumed corre-sponding to the road longitudinal axle of the road or, more correctly, to the median line of each allowed lane. In real conditions, instead, vehicles always travel along trajectories each other different; the variability is due to dynamic actions affecting the motion and, in a great measure, because the control of vehicle trajectories, performed by users, is not perfect. In order to consider if theoretical models can be effective for safety and comfort verifications in design process, it is important to evaluate how a reference trajectory can statistically represent the whole population of road users. In fact, the difference between a real trajectory of a generic ve-hicle and the theoretical one can emphasize the safety problems related to geometric characteristics of roads. To deal with these problems, it appears interesting to analyse the dispersion of trajectories in various road sec-tions; in this way, in fact, the “reference trajectory” along a road alignment can be recognized by means of a statistical approach. Starting from surveys on real road elements, the paper presents a method aimed to obtain trajectories that have formal geometric expression and that can correctly represent the scattering of vehicles’ position, because reference lines are defined after a statistical analysis of collected data