Search Results (479)

Al 6061 is widely used in the automotive, aerospace, railway and shipbuilding industries due to its excellent mechanical and metallurgical properties. Friction stir welding is a solid-state method preferred in the welding of Al6061 alloy. In this study, Al 6061 plates with a thickness of 3 mm were joined at tool rotational speeds of 900 and 1120 rpm, feed rates of 50 and 80 mm.min⁻¹, and tilting angles of 0° and 2° by friction stir welding using a tapered pin tool in the Universal Milling Machine. To examine the mechanical properties of welded specimens, tensile tests and microhardness tests were applied to them. The microstructural evolution of the welded zones was studied using an optical microscope and scanning electron microscope, and energy-dispersive X-ray spectroscopy analysis. The tensile test results demonstrate that the specimen welded at 900 rpm tool rotational speed, 2° tilting angle, and 80 mm.min⁻¹ feed rate exhibited the highest welding strength of 243.77 MPa and welding performance of 82.93%, while specimen welded at 1120 rpm tool rotational speed, without tilting angle, and 50 mm.min⁻¹ feed rate exhibited the lowest welding strength of 105.76 MPa and welding performance of 36%. Full article

The design of a railway coach must meet strict certification requirements, especially in crashworthiness analysis under the European standard EN 15227. Performing this analysis with full-scale FEM models is highly demanding in terms of time, computational power and engineering resources, even with large server clusters. To improve efficiency, it is useful to simplify regions of the structure that are less influenced by external loads. In this approach, less critical parts are replaced with flexible one-dimensional elements, reducing the number of degrees of freedom while preserving the vehicle’s main dynamic behaviour. By concentrating on a specific mid-span section, the model becomes more robust and easier to manage. Calibrated elements are introduced to accurately reproduce the mass and stiffness of the removed structural components. The methodology also integrates mass and stiffness elements to capture structural response over a broader frequency range. An iterative non-gradient calibration procedure is then applied to adjust the equivalent stiffness and mass distribution so that the simplified model reproduces the response of the full-scale reference model. The results show that this strategy is effective, achieving a 77.6% reduction in simulation time while maintaining reliable accuracy. However, the process is still labour-intensive, and its performance may decline under large deformation conditions. Full article

This paper presents a new process for forming stepped shafts by upsetting with two movable deformation zones. The developed technology enables several shaft steps to be formed at the same time, thereby increasing process efficiency and reducing material consumption. A distinctive feature of the process is that it uses two forming sleeves, each with a variable cross-section of the impression, which move in an opposite direction to that of the punches during operation. This results in a simultaneous occurrence of upsetting and extrusion, thus leading to intensified plastic deformation and stabilized metal flow. The practical applicability of the process is demonstrated on the example of a forged railway axle. An analysis is carried out by the finite element method (FEM) using specimens of hot-formed C35 steel. The obtained results reveal proper material flow and the correct filling of the tool impressions. The examination of strain and stress distributions confirms favorable forming conditions. The calculated values of the Cockcroft–Latham integral indicate favorable forming conditions and a low risk of fracture initiation during the analyzed process. The results demonstrate the potential of the proposed technology and provide a basis for future experimental verification and industrial assessment. Full article

One difficult issue regarding adaptation and adaptive reuse of existing buildings is assessing the heritage significance of functional industrial-oriented heritage buildings, such as railway buildings, that have outlived their original purpose. There is a significant tension in developing strategies for the long-term viability of a sustainable, adaptive reuse of this type of heritage infrastructure. Complicating an assessment is that these buildings may be in constrained locations, or the location has changed beyond all recognition, such that the building inhabits a sterile space. Accepted practice for conserving heritage buildings is to discourage relocating these buildings, with a scholarly concern that presentation of relocated buildings for public engagement will undermine interpretive thinking. In all cases, functional heritage buildings complicate conservation decisions in comparison with mainstream heritage buildings. Existing conservation frameworks remain insufficiently equipped to evaluate industrial and utilitarian heritage buildings whose significance derives as much from operational function, social memory, and technological context as from architectural fabric or fixed location. In response, taxonomy surveying is advanced as a novel stakeholder-centred conservation methodology capable of reconciling tensions between authenticity, adaptive reuse, relocation, and public interpretation. The aim, using case study railway buildings in a museum of industrial heritage, is to test if this methodology is transferable to other functional building types. The findings suggest that taxonomy surveying, as tested on the case study buildings, offers a scalable and internationally transferable framework for evaluating complex industrial heritage assets across differing regulatory, cultural, and spatial contexts. Full article

Despite the widespread adoption of model predictive control (MPC) in railway research, the integration of intelligent learning mechanisms into train control systems operating under moving block signaling remains limited, particularly in approaches that preserve constraint satisfaction and industrial feasibility. To address this gap, this paper presents a novel learning-based model predictive control (LMPC) framework for high-speed train control under the moving block signaling principle. Moving block signaling dynamically enforces safe inter-train separation based on the absolute braking distance, imposing stringent safety, comfort, and performance constraints on train operation. The proposed LMPC exploits the repetitive nature of railway operations by progressively improving its control policy through the incorporation of historical operational data into the terminal set of the optimization problem. This learning capability enables the controller to optimize train behavior on a given line while pursuing different control objectives, namely maximum-speed operation for leading trains and minimum safe inter-train separation for following trains, in full compliance with signaling requirements, speed limits, actuator constraints, and comfort-related jerk bounds. Simulation results on a representative high-speed line show that, compared with a conventional non-learning MPC, the proposed LMPC achieves a measurable reduction in traction-related energy consumption while maintaining comparable speed profiles, travel times, and strict constraint satisfaction. These improvements are achieved through a single software-level modification of the train control algorithm, without requiring additional onboard hardware or infrastructure upgrades, positioning the proposed LMPC as a promising and practically viable solution for energy-efficient deployment in high-speed railway operations. Full article

Increasing the efficiency of the railway industry requires the creation of solutions aimed at improving the technical, economic, and operational performance of wagons. It would contribute to reducing the cost of their operation. One of the most damaged elements of wagon bodies is their paneling. Its damage not only affects the loss of cargo during transportation but also threatens the safety of the movement of goods. The article is aimed at the load analysis of the body of an open wagon, whose paneling is sandwiched with corrugated panels. This solution will improve the strength of the side walls of the body of the solved freight wagon. This hypothesis has been accepted based on the dynamic load as well as the strength calculated for the body of the solved freight wagon. The dynamic load of the open wagon body has been studied with a mathematical model of its oscillations during the lateral roll. The solution to this model has shown that the maximal values of accelerations are lower by 5% than those acting on the standard design, and they act on the body of the solved freight wagon. The values of accelerations, which act on the body of the solved freight wagon, were calculated by means of numerical simulations using the finite element method implemented in the SolidWorks Simulation software. The discrepancy between the results of mathematical modeling and computer modeling is 6.5%. The strength of the open wagon body has also been calculated. It has been found that the maximal values of stresses in the paneling were lower by 17% than those acting in a standard body structure and 12% lower than the stresses in the body with corrugated panels. The study has also included an analysis of the modal properties of the body of the solved freight wagon, which demonstrates that the safety of the open wagon in motion is observed. The studies conducted will be useful in developing proposals for the creation of the newest wagon designs, including the improved economic, operational, and technical characteristics. Full article

Railway construction and industrialization played an important role in reshaping the urban morphology of inland resource-based cities in Republican-period China. Taking Taiyuan during 1912–1937 as a case study, this paper examines the spatial association between railway corridors and industrial locations and discusses how this relationship contributed to the reorganization of urban space. Historical maps, railway maps, local gazetteers, archival materials, and existing literature were integrated into a historical GIS database. Kernel density estimation, railway buffer analysis, mean-center analysis, and standard deviational ellipse analysis were used to reconstruct the staged evolution of industrial nodes and railway corridors. The results show that Taiyuan’s industrial space evolved from a scattered point-based pattern to a railway-oriented axial-belt layout and then to a polycentric industrial corridor. Industrial nodes gradually moved closer to railway lines, while the mean center of industrial distribution shifted from the traditional city toward railway-related industrial districts. The findings suggest that Taiyuan followed one possible railway–resource–industry pathway shaped by railway construction, resource endowments, provincial industrial policies, land conditions, and the inherited urban fabric. This study provides historical spatial evidence for identifying railway–industrial heritage corridors and understanding inland industrial urban form. Full article

Operational Technology (OT) and Industrial Control Systems (ICSs) along the NATO-EU eastern flank face escalating hybrid threats, yet existing cyber-resilience metrics remain IT-centric, lacking OT-specific constraints and geopolitical exposure dimensions. This paper presents a Design Science Research contribution: the development and simulation-based feasibility demonstration of two interconnected artefacts. The first is the AI-enabled Cyber-Resilience Index (ACRI)—a composite 0–100 metric operationalized through 16 indicators across four domains (detection performance, operational continuity, governance maturity, supply-chain risk), aggregated as a three-term convex combination of capability domains with a linear subtractive supply-chain exposure penalty, weighted via AHP-based illustrative sector-reference profiles. The second is the Unified Compliance Framework (UCF), a structured R → C → E → SLO mapping linking 47 atomic regulatory requirements (NIS2, DORA, CER, AI Act, CRA) to standards (IEC 62443, ISO/IEC 27001) and auditable evidence artifacts, with a Continuous Assurance Loop operationalizing continuous control monitoring. Feasibility is demonstrated through digital twin simulation under three OT-representative threat scenarios (energy SCADA APT, railway supply-chain compromise, manufacturing ransomware). Results in simulated environments show ACRI improvement from Moderate-Risk baselines (45–61) to Adequate-Resilience thresholds (65–73); the proposed federated autoencoder–LSTM detector attains a composite $D_{perf}$ of 0.883 versus 0.510 for a static ±3$\sigma$ threshold baseline (a 73% relative improvement at the domain level). Sensitivity analysis confirms classification robustness ($\pm 7.3\%$ weight perturbation; coefficient of variation below 9.1% across 10,000 Monte Carlo iterations). Critical limitations are explicit: simulation-only evidence ($n=12$ scenario instances), illustrative (non-empirical) AHP weights, no operational field validation, and limited inferential statistical power. instances), illustrative (non-empirical) AHP weights, no operational field validation, and limited inferential statistical power. The contribution is positioned as a proof-of-concept design artifact establishing methodological foundations for OT-centric resilience assessment and compliance-to-engineering traceability, not as a field-validated operational system. Full article

The gap dimension of a railway switch machine is a critical physical quantity for determining the locking status of railway turnouts. Under operating conditions characterized by heavy oil contamination, complex illumination, and equipment vibration, existing visual measurement methods often struggle to maintain stability and achieve sub-pixel precision. To address this issue, this paper proposes a gap measurement method based on the fusion of vision and geometric features (G-VFM). The method first utilizes a confidence-aware optimized YOLOv8 model to achieve robust localization of the gap region. Subsequently, an improved multi-channel U-Net is employed to extract soft-edge probability maps, based on which a 20-dimensional structured geometric descriptor is constructed. Finally, visual semantic features and geometric priors are fused for regression through an R34-Fusion two-stream residual network, and systematic errors are corrected using a weighted Huber loss combined with a piecewise linear calibration strategy. Test results on a constructed field dataset show that the proposed method achieves a Mean Absolute Error (MAE) of 0.0076 mm and a maximum error of 0.0193 mm. It achieves a 100% pass rate under an industrial tolerance of 0.02 mm, with an end-to-end inference time of 52.23 ms (~19.15 FPS), balancing both precision and efficiency. Further tests on illumination degradation, noise interference, and cross-batch evaluations indicate that the method maintains relatively stable performance across various complex scenarios. However, performance decreases significantly under extremely low-light conditions, suggesting that actual deployment may require integration with active lighting or multi-sensor fusion to ensure system reliability across all working conditions. Overall, this method achieves high-precision gap measurement under current experimental conditions and provides a feasible solution for vision-based switch machine status monitoring. Full article

Station Signal Layout Plans (SSLPs) are pivotal engineering drawings used in the design of railway signaling systems. Accurate recognition of such drawings is essential for enabling intelligent railway operations and supporting digital management. However, the inherent complexity of engineering drawings—characterized by diverse object categories and significant scale variations—substantially increases the difficulty of detection tasks. To address these challenges, this paper proposes an improved YOLOv8-based algorithm for rapid and accurate object detection. First, to enhance the detection of small objects in engineering drawings, a cross-scale attention mechanism is introduced into the mid-scale detection head. During prediction, this mechanism leverages fine-grained details from lower-level features to improve small-object detection. In addition, to suppress noise and blurred edges in drawings, the YOLOv8 neck network is enhanced with a DWRSeg-based design. This structure enlarges the receptive field while preserving local details, thereby effectively reducing the impact of noise on localization. To evaluate the proposed method, a complex dataset was constructed from station signal layout plans provided by a railway bureau, featuring substantial variations in target scale, diverse categories, and densely distributed objects. Experimental results demonstrate that, compared with YOLOv8n, the proposed DCS-YOLO model improves precision, recall, and mAP@0.5 by 3.1%, 0.8%, and 2.1%, respectively, while maintaining a comparable mAP@0.5:0.95. Comparative experiments with representative object detection methods demonstrate that the proposed algorithm achieves competitive detection accuracy and real-time performance for SSLP symbol recognition, providing a practical technical solution for the intelligent analysis of engineering drawings in the railway industry. Full article

Urbanisation has led to dramatic alterations in pre-existing natural environments, resulting in several subsequent phenomena, such as the disappearance of habitats suitable for many plant and animal species and the concurrent arrival of generalist and non-native species, contributing to environmental homogenisation. Towns and cities serve as crossroads for transport, people, and animals, making them susceptible to colonisation by many types of plant species, dispersed either intentionally or unintentionally by these biotic vectors. Abiotic vectors, such as wind and water, also influence the composition of vegetation assemblages. Urban spontaneous vegetation occurs in (1) undisturbed areas, including brownfield sites, commons, and marginal lots, and (2) disturbed sites, such as green areas, parks, lawns (not subject to weeding), ancient monuments and walls, peripheral and industrial areas, and railways. When disturbance occurs, vegetation remains at early successional stages. Within this framework, with the aim of comparing existing contradictions and identifying knowledge gaps, we reviewed the literature on the characteristics of spontaneous plants and vegetation in urban areas, the different habitats in which they grow, the ecosystem services they provide, and management strategies, considering human perception. Our results highlight that studies on spontaneous plants are well-developed in terms of botany and ecology; however, some gaps remain, particularly regarding their integration into urban design and maintenance practices. Concerning public perception and acceptance, cultural and geographical differences emerged that deserve further investigation. In conclusion, spontaneous plants can represent a valuable heritage for cities, helping to address the challenges posed by the climate crisis. Full article

As a form of living heritage, Historic Urban Landscapes (HULs) have long been limited by the static perspectives and reductionist tendencies of conventional conservation and research approaches. Although the geological and archaeological concept of “stratification” offers a methodological basis for understanding the diachronic evolution of heritage, its unidimensional temporal lens fails to capture the inherent complexity and systemic nature of historic urban landscapes. To address this gap, this study proposes a “multidimensional stratification” theoretical framework through theoretical critique and paradigm reconstruction. The framework introduces innovations at the ontological, epistemological, and methodological levels, positing that the evolution of historic urban landscapes emerges from the nonlinear interaction and dynamic interweaving of four core dimensions: time, space, society, and value. It further systematizes five intrinsic attributes of such landscapes: authenticity, integrity, continuity, adaptability, and dynamism. Building on this foundation, the paper constructs a systematic analytical pathway—elements–processes–patterns–modes–drivers–characteristics—that enables dynamic analysis from micro-level identification to macro-level generalization, offering a scalable tool for HUL conservation and regeneration. To demonstrate the framework’s applicability, the historic urban area of Shenyang—a nationally designated historical and cultural city—is selected as a case study. Its urban landscape comprises four core districts: the Shengjing City District, the South Manchuria Railway Concession District, the Commercial Port District, and the Tiexi Industrial District, representing historical strata from the Qing dynasty capital, modern colonial planning, commercial opening, to industrial heritage. Using the multidimensional stratification approach, this study elucidates the spatial complexity, temporal nonlinearity, social dynamism, and value pluralism embedded in Shenyang’s historic urban area. Corresponding conservation strategies grounded in holism, dynamism, and differentiation are proposed. The research not only advances the theoretical understanding of HUL but also provides a novel paradigm—integrating holistic, dynamic, and operational perspectives—for the conservation, renewal, and regenerative practice of historic urban landscapes worldwide. Full article

The paradigm transition of the life cycle management of physical assets in the railway sector demands new maintenance models that imply the conventional predictive approaches to be surpassed. This paper proposes an innovative methodology that integrates Building Information Modelling (BIM) with predictive maintenance (PdM) systems to be applied to rolling stock and, in this way, be enhanced by Generative Artificial Intelligence (GenAI). The research focuses on the autonomous synchronisation of the Rolling Stock Digital Twin (DT). Unlike static BIM models, the proposed solution enables the use of GenAI algorithms to process continuous data streams from integrated sensors, allowing the digital model to evolve autonomously as physical wear occurs. In this framework, GenAI (via Generative Adversarial Networks—GANs) is essential for data augmentation, enabling the simulation of rare “long-tail” failure events that are scarce in real-world historical data. By synthesising these degradation scenarios, the model learns complex mechanical collapse patterns that otherwise would be ignored by traditional PdM approaches. GenAI is employed to synthesise degradation scenarios, perform real-time parametric updates within the IFC (Industry Foundation Classes) schema, and optimise maintenance workflows. The application of this framework demonstrates a significant reduction in diagnostic latency and optimises the rolling stock’s operational life cycle by automating updates and reducing the need for manual data entry. This study concludes that the convergence among BIM, PdM, and GenAI establishes a robust framework for railway fleet management. While the current validation focuses on bogie systems using Random Forest and LLMs, it paves the way for a future Industrial Metaverse where immersive diagnostics can be integrated into the maintenance lifecycle. Full article

The main objective of this study was to reduce the dwell time of wagons at stations and to improve the efficiency of shunting locomotive utilization. This is a combinatorial problem, since an increase in the number of loading and unloading fronts leads to a sharp growth in the number of feasible service variants. During the research, a mathematical model describing the servicing process of industrial sidings was developed. This study addressed the problem of determining the optimal sequence of wagon deliveries and the optimal distribution of workload among shunting locomotives. For conditions under which two or more shunting locomotives are used, an optimization method based on the indicator of wagon-hour reduction (σ) was proposed for allocating loading and unloading fronts. Using combinatorial properties, it was shown that many possible allocation variants are symmetric, which allowed for the development of a mathematical solution that simplifies the search for an optimal solution. Computational results demonstrated that, at the hypothetical railway station “N-1”, applying the optimal service sequence reduces wagon dwell time by 21% compared with an arbitrary sequence. At the hypothetical station “N-2”, distributing wagon groups between two shunting locomotives improves the efficiency of the servicing process by 26% compared with using a single locomotive. The results based on real data from the “B-2” railway station show that the proposed method provides an improvement of approximately 31.3% compared to the current operational practice, while Smith’s rule achieves an improvement of 14.9%. Based on the proposed model and algorithm, a software tool was developed to automatically determine servicing sequences for loading and unloading fronts, analyze alternatives, and evaluate shunting locomotive efficiency. Full article

In response to environmental degradation and social inequities exacerbated by automobile-dependent urban sprawl, this study proposes a framework for dynamic delineation and vitality assessment of 15-min walkable neighborhoods, using Baohe District, Hefei, China as a case study. Static service catchments were constructed using POI and road network data, then refined using one week’s mobile phone signaling trajectories calibrated to actual walking behavior, yielding 143 validated living circles (out of 156 initially delineated). These circles are classified into five typologies: commercial-residential, industrial-residential, educational-residential, predominantly residential, and public-service-oriented. A dual-index system—Facility Vitality Index (FVI) and Population Vitality Index (PVI)—is developed and synthesized into a Composite Vitality Index (VI) through normalization and weighting. Results show that only 27.3% of living circles achieve high vitality in both dimensions, indicating widespread service–demand misalignment. Conversely, 61.5% exhibit low or very low vitality, forming a “vitality depression” around the urban periphery—a pattern of service poverty with significant socioeconomic implications. High-vitality circles cluster along the Binhu New District corridor, while low-vitality circles concentrate in industrial parks (e.g., Feinan Industrial Park) and transport hubs (e.g., Hefei South Railway Station). The historic core lacks micro-infrastructures, whereas new districts—despite high-standard amenities—suffer from weak pedestrian activity. To address these deficiencies, we propose a differentiated zoning strategy: retrofitting micro-infrastructures in legacy neighborhoods, applying Transit-Oriented Development (TOD) principles in new urban extensions, and integrating community-serving functions within industrial peripheries. This framework provides actionable protocols for data-informed governance of 15-min living circles. Full article