Search Results (8)

Welding of high-carbon rail steels is widely applied in railway maintenance to restore worn rail surfaces and extend service life. However, the weldability of these steels is limited by their high carbon content and susceptibility to brittle microstructures in the heat-affected zone. This paper evaluates the quality of weld deposits applied to different grades of railway rails (UIC 1100, UIC 900A, and UIC HSH) using submerged arc welding (SAW) and flux-cored arc welding (FCAW) technologies with various filler materials. Weld quality was assessed through macrostructural examination, HV30 hardness measurements, and microstructural analysis. The results show that inappropriate combinations of filler materials and welding parameters lead to excessive hardness and martensitic structures, which are undesirable for in-service performance. In contrast, selected multi-layer welding procedures produced bainitic or tempered microstructures with favourable hardness distributions. Based on the experimental results, optimal welding procedures and filler material combinations for rail renovation are proposed. Full article

China’s urban development has entered the stage of urban renewal, transitioning from large-scale incremental construction to stock enhancement and renovation. In response to challenges such as traffic congestion and land-use constraints, urban planning has increasingly prioritized the development of urban underground space (UUS) and urban rail transit (URT). However, disparities in development levels across cities, as well as the fragmented and uncoordinated integration of UUS and URT, remain significant challenges. While existing studies have predominantly examined UUS and URT independently, the interaction between the two has been largely overlooked. In order to supplement this gap, the aim of this study is to construct an integrated measurement framework and quantitatively assess the level of integration between UUS and URT in 38 Chinese cities. We seek to explore the interrelationship between the two, identify the differences in the integration process across cities, and discuss the potential implications for urban planning and policy making. Specifically, this study assembles an integration measurement index framework from three dimensions (UUS, URT, and urban development), quantitatively evaluates the integration level of 38 Chinese cities by using the entropy weighting and VIKOR methods, and summarizes the regionalization characteristics by using K-means clustering. The results of the study show that (1) there is a positive correlation between UUS development and URT construction and the degree of correlation is affected by the level of urban development; (2) the construction of URT is dominant in the integrated system of UUS and URT; (3) the sample cities can be classified according to the characteristics of the integration into the types of developing cities (47.37%), mature cities (21.05%), and underdeveloped cities (31.58%), and there is a clustering effect on the overall spatial distribution. Full article

Numerous researchers have endeavored to amalgamate critical transit-oriented development (TOD) indicators, such as development density, walkability, and diversity, into a single TOD index to assess TOD performance. However, implementing TOD in megacities necessitates a more comprehensive selection of indicators, an objective calculation methodology, and accessible calculation data for the TOD index. This study introduces a method based on multi-indicator TOD performance assessment using multi-source urban big data; it uses Shanghai as a case study to evaluate and analyze the impact of site characteristics on performance. The method constructs the Comprehensive Socio-Economic Development Index (CSEDI) based on four indicators of TOD site operations. It establishes a multivariate regression model utilizing principal component analysis to extract 22 leading component indicators as independent variables from 71 indicators associated with TOD. Within the sample space of 77 rail transit TOD sites in Shanghai, the CSEDI exhibited a robust correlation with the independent variables. The evaluation results of the case study demonstrate consistency with the development characteristics of the city and the sites, indicating that the evaluation method can guide the renovation of existing sites and the development of new sites. Full article

Climate change is the main cause of frequent extreme weather and natural disasters. Therefore, effective climate adaptation strategies for urban rail transit (URT) should be adopted to cope with extreme precipitation events (EPEs). This study proposes a decision-making model based on climate change for drainage renovation, which consists of an optimal renovation sequence model and an optimal investment timing model. This study analyzes the inundation risk of each station and its node importance in the URT network and then uses a multi-attribute decision analysis (MADA) to determine the optimal renovation sequence. This study also uses a real options pricing approach to calculate the value of an option in order to defer the renovation project and determine the optimal investment timing. Then, the Beijing Urban Rail Transit (BURT) is taken as an example to conduct an empirical analysis of the proposed model. Considering the uncertainty of climate change and the complexity of the URT network, the model can obtain the optimal renovation sequence and the investment timing of each station, which is expected to provide a decision-making tool for urban governments to formulate an optimal plan that strengthens the prevention of flooding disasters. Full article

Having access to accurate and recent digital twins of infrastructure assets benefits the renovation, maintenance, condition monitoring, and construction planning of infrastructural projects. There are many cases where such a digital twin does not yet exist, such as for legacy structures. In order to create such a digital twin, a mobile laser scanner can be used to capture the geometric representation of the structure. With the aid of semantic segmentation, the scene can be decomposed into different object classes. This decomposition can then be used to retrieve cad models from a cad library to create an accurate digital twin. This study explores three deep-learning-based models for semantic segmentation of point clouds in a practical real-world setting: PointNet++, SuperPoint Graph, and Point Transformer. This study focuses on the use case of catenary arches of the Dutch railway system in collaboration with Strukton Rail, a major contractor for rail projects. A challenging, varied, high-resolution, and annotated dataset for evaluating point cloud segmentation models in railway settings is presented. The dataset contains 14 individually labelled classes and is the first of its kind to be made publicly available. A modified PointNet++ model achieved the best mean class Intersection over Union (IoU) of 71% for the semantic segmentation task on this new, diverse, and challenging dataset. Full article

The noise caused by rail corrugation seriously affects the operation quality of metro vehicles. In this work, the rail corrugation, interior noise and wheel–rail noise of a metro line were tested, and the test results were compared with those after two kinds of treatments. The results show that rail corrugation is the main cause of the abnormal interior noise. The interior noise in many sections exceeds the limit, where clear rail corrugations from 31.5~63 mm are found. When the train passes through the rail corrugation section, the interior noise shows a clear increase, and the maximum increase is higher than 25 dB(A). After increasing the lateral stiffness of the track and rail grinding, the interior noise is reduced by 11.4 dB(A). After a long renovation time, the interior noise is effectively equal to that when the renovation was completed. The research results of this work can provide a reference for rail corrugation treatment and noise control. Full article

Few studies assess dog ownership and walking with both self-reported or perceived and audited or objective walkability and physical activity measures. Across two years, we examined both types of walkability and activity measures for residents living within 2km of a “complete street”—one renovated with light rails, bike lanes, and sidewalks. Audited walkability (Irvine–Minnesota Inventory) was more consistently related to dog ownership and walking groups than perceived walkability (Neighborhood Environment Walkability Scale—Abbreviated). Self-reported leisure walking was much higher (289–383 min per week) among dog walkers than among other groups (100–270 min per week), despite no difference in accelerometer-measured light or moderate-to-vigorous physical activity (MVPA). Furthermore, the most powerful difference between groups involved single-family detached home residence, which was much lower among non-dog-owners (44%) than among non-dog-walkers or dog walkers (81% and 70%, respectively). Given discrepancies across walkability and activity measures, we recommend future use of walkability audits and objectively measured physical activity over the current emphasis on self-report measures. We also urge greater attention to increased densities of housing, which may negatively affect dog ownership levels unless compensating supports for dog ownership and walking are created by public health messaging, dog-friendly policies, and dog-friendly housing and community design. Full article

Few studies of walkability include both perceived and audited walkability measures. We examined perceived walkability (Neighborhood Environment Walkability Scale—Abbreviated, NEWS-A) and audited walkability (Irvine–Minnesota Inventory, IMI) measures for residents living within 2 km of a “complete street”—one renovated with light rail, bike lanes, and sidewalks. For perceived walkability, we found some differences but substantial similarity between our final scales and those in a prior published confirmatory factor analysis. Perceived walkability, in interaction with distance, was related to complete street active transportation. Residents were likely to have active transportation on the street when they lived nearby and perceived good aesthetics, crime safety, and traffic safety. Audited walkability, analyzed with decision trees, showed three general clusters of walkability areas, with 12 specific subtypes. A subset of walkability items (n = 11), including sidewalks, zebra-striped crosswalks, decorative sidewalks, pedestrian signals, and blank walls combined to cluster street segments. The 12 subtypes yielded 81% correct classification of residents’ active transportation. Both perceived and audited walkability were important predictors of active transportation. For audited walkability, we recommend more exploration of decision tree approaches, given their predictive utility and ease of translation into walkability interventions. Full article