The Melan method, pioneered by Austrian engineer Josef Melan in the late 19th century, revolutionized concrete arch bridge construction by embedding steel I-beams as both reinforcement and formwork. The historical evolution of the Melan method and the global development of Melan arch bridges are systematically reviewed. Early Melan arch bridges encountered challenges such as excessive deflections, concrete cracking, and reinforcement corrosion, primarily attributed to inadequate understanding of material durability and the use of high water-cement ratios. The method experienced a revival in China in the late 20th century, with over 67 Melan arch bridges constructed. Modern adaptations, such as the application of Concrete-filled Steel Tube (CFST) frameworks in China, demonstrate the systemu2019s continued relevance, improving economic efficiency and structural performance while reducing steel consumption. Key lessons highlight the importance of prioritizing durability, protecting steel-concrete interfaces, and adopting construction techniques to control deformation. Future research should focus on corrosion mitigation, shrinkage control, and long-term maintenance strategies to conserve both historic and modern Melan arch bridges.
Ancient bridges in China are significant testimonies to Chinese civilization, reflecting remarkable engineering ingenuity as well as rich historical and cultural values. They can be divided into various structural types including beam bridges, arch bridges, suspension bridges, and pontoon bridges. These bridges not only serve as physical evidence of the evolution of bridge structural forms and building technologies, but also act as important medias for cultural transmission. In recent years, with the increasing emphasis on the conservation of cultural heritage, researches on ancient bridges in China has gradually developed into an interdisciplinary issue encompassing archaeology, architecture, surveying and mapping, and cultural studies. In disciplines such as architectural history, hydraulic engineering history, and transportation history, ancient bridges have been recognized as a special type of immovable cultural relics, which attracted particular interest of study. This paper presents a systematic review of researches in these fields, summarize the major advances of studies in both China and other countries, analyzing existing key challenges and technical bottlenecks, and outline current research approaches and future trends. On this basis, together with recent technological innovations in the conservation of ancient bridges in China, the study further discusses the future directions for studying and protecting ancient bridges, providing theoretical basis and technical references for their scientific conservation and appropriate utilization.
The supply of high-quality talent plays a decisive role in the sustainable development of the highway industry. To accurately capture trends in AIu2013highway engineering interdisciplinary talent and to inform talent cultivation and policy formulation in higher education, this study analyzes data from Fujian Province spanning 2019u20132024, including the total number of highway engineering professionals, total industry investment, talent attrition, and the supply of college graduates. A Bayesian regression model is employed for predictive analysis. The results indicate that parameter estimates are consistent with prior assumptions, the sampling process is stable, inter-chain convergence is satisfactory, and parameter estimates are reliable. The posterior distributions are approximately normal, and the Markov chain Monte Carlo (MCMC) trajectories exhibit random behavior without discernible trends, indicating good chain mixing and robust posterior estimation. Overall, demand for AI interdisciplinary talent in the highway engineering sector of Fujian Province shows a significant upward trend. Under the baseline scenario, the total industry workforce is projected to reach 5,351 by 2029, including 1,605 AI interdisciplinary professionals, representing a cumulative increase of 687 over five years. In the optimistic scenario, driven by increased investment, reduced drain, and growth in graduate supply, the workforce is expected to expand to 6,508 by 2029, with 1,952 AI interdisciplinary professionals, a cumulative increase of 999 over five years. Even in the pessimistic scenario, despite adverse conditions such as reduced investment and higher turnover leading to a workforce decline to 4,743 by 2029, the number of AI interdisciplinary professionals is projected to continue growing, reaching 1,423, with a cumulative increase of 522 over five years. These results demonstrate that the Bayesian regression model effectively quantifies the dynamic effects of total highway industry investment, brain drain, and graduate supply on workforce scale, and that the forecasts are consistent with practical industry constraints.
The Zhaozhou Bridge, built during the Sui dynasty (581u2013600) by Li Chun, is a masterpiece of world bridge engineering for its 37.02 m span, remarkably low rise-to-span ratio of 0.195, and two spandrel arches on each side. Although the bridge was included in the list of u201Cpotential World Heritage Bridgesu201D in the ICOMOS 1997 document, its heritage values have not yet been systematically examined within the World Heritage framework. Against this background, this paper aims to improve the conservation of the Zhaozhou Bridge based on a value-based approach, which is widely used for the nomination, protection and management of World Heritage Sites. The paper analyses the heritage values of the Zhaozhou Bridge, identifying the value attributes and their expressed elements based on an understanding of the principal concepts in the World Heritage framework, and examines the bridgeu2019s current conservation practices. Then, the paper proposes value-based conservation strategies, including establishing a long-term protection and management mechanism, digitally interpreting the bridgeu2019s original structure, recovering its historical settings, and recognizing and protecting the Chinese open-spandrel stone arch bridges. These strategies could enhance the authenticity and integrity of the Zhaozhou Bridgeu2019s value expression and promote a more comprehensive and sustainable approach to its conservation.
Nepalu2019s historic bridges, including timber, stone masonry, and early suspension typologies, are vital components of both the national mobility network and the cultural heritage landscape. However, progressive material deterioration, environmental exposure, increasing service demands, and the lack of standardized conservation frameworks have increased their vulnerability. This study develops an integrated multi-criteria decision framework that jointly evaluates structural condition and cultural significance to support systematic conservation planning. Seven structural and four cultural indicators were identified and weighted using the analytic hierarchy process (AHP) based on responses from 191 experts. Material degradation (0.193) and structural deformation (0.153) emerged as the most influential structural indicators, while local cultural importance (0.295) and historic age (0.276) dominated the cultural dimension. The weighted indicators are combined into a composite scoring model with defined decision thresholds on a ten-point scale: scores below 2.883 indicate replacement, values between 2.883 and 6.289 require retrofitting, and scores above 6.289 support continued use with minor intervention. The framework links each decision range with heritage-sensitive strengthening strategies, providing a transparent and reproducible methodology for balancing structural safety and cultural preservation. The proposed model offers a scalable reference for sustainable management of historic bridge infrastructure in Nepal and similar heritage contexts.
Masonry arch bridges represent a unique synthesis of engineering efficiency and cultural heritage that has evolved over more than two millennia across different civilizations. Despite their historical relevance and continued widespread use, research on these structures often remains fragmented between historical evolution and structural engineering perspectives. This paper aims to address this gap by providing an integrated overview of the evolution, structural behavior, and conservation of historic masonry arch bridges, encompassing both Chinese and European heritage. The study reviews the evolution of arch bridges from early origins to the scientific era, then examines their typological and morphological features, highlighting the interplay between geometry, materials, and construction techniques. It analyses structural behavior and reviews current assessment and modelling approaches. Finally, it discusses conservation strategies and future perspectives, with emphasis on advanced materials, digital tools, and the renewed role of masonry arch bridges in contemporary infrastructure.
The ruin of the Chuiyu Bridge is located in Wuyishan, Fujian Province, China. Originally built as a woven wooden arch bridge in 1887, the bridge was destroyed by Japanese bombs in 1942, and today only parts of its abutments and pier foundations remain. According to historical records, the Chuiyu Bridge was built around the same time as the nearby Yuqing Bridge, a well-known woven wooden arch bridge. Both bridges are important nodes in the ancient Great Tea Route. Currently, the Yuqing Bridge is well preserved as a National Cultural Relics Protection Unit (CRPU) and as part of the Wuyi Mountains World Heritage property. By contrast, the ruin of the Chuiyu Bridge is listed only as an ungraded immovable cultural relic and has not received any formal protection. Such a condition is largely due to the fact that its value as a cultural heritage site has not yet been fully recognized. This paper aims to promote the identification and recognition of the Chuiyu Bridge Ruins as an important cultural heritage site, raise professional and public awareness of its value, and encourage corresponding conservation practices. To do so, it examines the bridgeu2019s history and surveys its current condition through literature review and field investigation. On this basis, the paper systematically evaluates the ruin's historical, scientific, cultural and social values. It proposes several conservation measures, including administrative and legal protections, the development of protection plans, and the establishment of dedicated research funds. These suggestions will help the comprehensive conservation of the ruin and support the future inscription of the Great Tea Route in the World Heritage List.
Overloaded traffic loads can increase the risk of bridge damage and reduce the service life of bridges. To further refine the research on the fragility analysis of different small and medium span bridges to traffic loads by considering the regional characteristics of traffic loads. This article systematically conducts a traffic load fragility analysis of bridges, taking into account the structural characteristics of small- and medium-span bridges and vehicle load characteristics within the region. First, statistical analysis is conducted on the collected measured traffic load data within a certain area, and the Metropolis-Hasting sampling algorithm and Copula function are used to consider the correlation of traffic load parameters to simulate random traffic flow. Then, the calculation method for the resistance level corresponding to the three states of bridge cracking, yielding, and failure is given. Finally, eight types bridges with a high proportion within a certain route is selected, and their fragility to traffic loads has been analyzed. The analysis indicates that the failure probability corresponding to cracking conditions exceeds the serviceability limit state target for all hollow slab bridges, even when the vehicle load limit is set at 15 t. Similarly, T-beam bridges are also relatively easy to enter a state of working with cracks. Furthermore, hollow slab bridges exhibit a higher failure probability than T-beam bridges under identical traffic loading conditions. This indicates that T-beam bridges are more suitable for the current traffic load conditions. In hollow slab bridges, the failure probability of 13m span and 16m is relatively high. In T-beam bridges, the probability of failure is relatively high for 30m span. These bridges should receive more attention in operation and maintenance work. The proposed fragility analysis method for traffic loads can facilitate bridge operation and maintenance, while also guiding the formulation of vehicle load limit policies.
This article discusses the need for digitalization, as well as the concept and features of a next-generation intelligent operation and control management system uFF08IOCMSuFF09 based on digitalization. It highlights the differences between this new system and the existing standard architecture of rail transit stations, and summarizes the advantages of the new intelligent operation and control management system. The feasibility of digitally upgrading rail transit station operations is analyzed, and a system architecture plan for the intelligent management platform is proposed. Several key technologies of the intelligent operation and control management system are explored, and major innovative business aspects are listed. By conducting a comparative analysis before and after the digitalization upgrade of rail transit operations, a brief evaluation of the digitalization upgrade is presented. Finally, other aspects to consider in the construction of the new generation digitized intelligent operation and control management system are summarized.
To further improve the regulatory efficiency of the driver training industry and promote the development of u201CInternet + supervisionu201D in the driver training industry, an off-site supervision method for the driver training industry based on geofence technology and geospatial analysis methods is studied. This method aims to automatically identify and comprehensively supervise whether training vehicles operate in accordance with specified routes and times. Through spatiotemporal matching and spatial mapping of multi-source heterogeneous data such as trajectory data of training vehicles from driving training institutions and geofence data, a multi-source dataset for industry supervision is established. Using the Shapely geospatial analysis library, based on the DE-9IM model, and combined with the multi-source data infrastructure, real-time supervision of training vehicles and automatic identification of violations are realized. The results show that the off-site supervision method proposed in this study can achieve precise supervision of the driving training industry, with a supervision accuracy rate as high as 99.87%. The identification results can serve as an important basis for relevant industry regulatory and law enforcement departments to carry out off-site supervision and early warning in the industry, and promote the intelligent transformation of off-site supervision in the driving training industry.
Smart highway refers to a system that comprehensively applies new-generation information technologies to achieve digital, networked, and intelligent upgrades of highway infrastructure, thereby significantly enhancing efficiency, safety, and sustainability. Although the importance is increasingly prominent, current studies focus on specific technologies or regional development analyses, lacking a systematic review and comparison of the global evolutionary trajectory of smart highways. By synthesizing the trajectories of representative countries and regions, the evolution of smart highways can be understood as proceeding through several stages, ranging from the early emergence and exploration, to the rise of ITS, and further to stages characterized by cooperative vehicle-infrastructure systems and digital development. The conceptual characteristics and technological connotations of various stages are investigated. The evolutionary process of system architectures across countries is analyzed, through which a development trend is revealed toward a physical hierarchy structured around the cloud-edge-end paradigm and a logical hierarchy centered on sensing-communication-computing-application. On this basis, key enabling technologies are summarized in the domains of sensing, control, safety, and vehicle-infrastructure cooperation. The findings are expected to contribute to a more comprehensive understanding of the concepts, architectures, and technological evolution of smart highways, while providing the references for technical road mapping, standard publishing, and large-scale deployment.
The mechanical performance of concrete structures under corrosive environments largely depends on the bond behavior between rebar and concrete. Existing studies primarily focus on predicting the peak bond stress, paying limited attention to the complete degradation process of bond strength. To address the deterioration of bond strength caused by internal rebar corrosion in concrete structures, a comprehensive bondu2013slip dataset was constructed based on extensive pull-out test data from existing literature. Nine input features were selected: corrosion rate, bond length, rebar diameter, concrete compressive strength (both cube and cylinder), concrete cover thickness, rebar yield strength, rebar type, and slip. This dataset captures the full evolution of bond strength at the corroded rebaru2013concrete interface as a function of slip. A bondu2013slip prediction model for corroded rebar was developed using a stacking GBDTu2013SVR (Gradient Boosting Decision Treeu2013Support Vector Regression) machine learning approach. Feature importance analysis was conducted using the SHAP method. The results showed a strong agreement between predicted and actual values. Performance metrics such as R2, u03C3, u03B7, and u03B3 confirmed the high accuracy of the model, with prediction outside 0.8u20131.2 confidence band only at low bond stress values. Compared to traditional empirical formulas, the proposed model demonstrates superior precision.
Trajectory imputation aims to reconstruct complete movement sequences from noisy or incomplete GPS data, crucial for intelligent transportation systems (ITS). This study proposes GNTI (Gaussian Noise-based Trajectory Imputation), a self-supervised learning framework that introduces Gaussian noise during model training to simulate real-world GPS errors. By perturbing the input trajectories with probabilistic Gaussian noise, GNTI enables the model to learn robust trajectory representations without relying on labeled datasets. A transformer-based BERT encoder is employed to capture complex spatial-temporal dependencies, while a simple multilayer perceptron (MLP) decoder predicts corrected trajectory points based on contextualized embeddings. Extensive experiments were conducted on two large-scale real-world datasets, Chengdu and Porto. Comparative results show that GNTI outperforms traditional Seq2Seq-based models (gated recurrent unit (GRU), long short-term memory (LSTM)) and recent transformer-based models (Transformer, ST-BerImp), achieving the highest Micro-F1 scores across all settings. Specifically, GNTI improves Micro-F1 scores by 3%u20135% over ST-BerImp. Ablation studies demonstrate that Gaussian noise augmentation improves model robustness by approximately 5% compared to models trained without augmentation. GNTI offers a practical and scalable solution for trajectory imputation tasks, enhancing robustness to GPS inaccuracies and reducing the need for complex multi-task objectives. Future work may explore extending the method to denser urban environments and optimizing it for real-time deployment.
As the penetration rate of connected and autonomous vehicles (CAVs) increases on highways, their role as network nodes for communication tasks raises significant challenges. Spatial heterogeneity in node distribution creates density discrepancies that substantially impact network lifetime and stability, thereby constraining optimal deployment strategies for road side units (RSUs). This study introduces an enhanced low-energy adaptive clustering hierarchy (LEACH) clustering algorithm tailored for vehicular networks. By identifying dense and sparse regions through dynamic clustering, the algorithm categorizes node functions according to regional characteristics to balance energy consumption and improve network connectivity. MATLAB simulations validate the algorithmu2019s performance under non-uniform vehicle distributions.The research further analyzes how vehicle node distribution patterns and CAV penetration rates affect optimal RSU deployment intervals. Key findings reveal that with consistent RSU-vehicle communication ranges: At a CAV traffic density of 0.01 and relative spatial density of 0.5 (uniform distribution), RSUs should be deployed at 641 m intervals. At a relative density of 0.9 (concentrated distribution), deployment intervals can expand to 1,887 m while maintaining high network connectivity. This adaptive strategy reduces communication blind spots by 32%, lowers deployment costs by 18%, and enhances vehicle-road coordination efficiency and traffic safety. The results provide critical technical support for intelligent vehicle-road collaboration systems.
Humanity is entering a digital society, and transportation systems are undergoing a phase of transformation. This paper summarizes the developmental trajectory of transportation, analyzes the necessity of researching the basic theories of digital transportation, and proposes a preliminary definition of digital transportation from perspectives including productivity, production relations, transportation scope, traffic scope, management approach, system composition. It describes core characteristics and identifies key research directions for future focus, aiming to stimulate academic discourse and advance basic theoretical research in this field.
This study conducted indoor consolidation tests on the aging road and natural ground foundational soils from the G214 permafrost section in the Yellow River source area to compare their consolidation characteristics. The results revealed that the consolidation deformation of the aging road foundation soil was significantly lower than that of the natural foundation soil, with a flatter consolidation curve. In the aging road foundation, the 2.5-4.3 m soil layer affected by annual temperature fluctuations exhibited void ratio variations 2.05 times greater than other layers. However, the variation in void ratio in multiple layers of the natural foundation was greater than that in the aging road foundation. The maximum settlement of the aging road foundation originated from the 2.5-4.3 m layer with smaller shallow settlement, while the natural foundation showed dominant shallow settlement followed by the 2.5-7.5 m layer, reaching a total settlement 1.37 times that of the aging road foundation. A layered treatment strategy is recommended: applying techniques adapted from soft foundation treatment to shallow layers while implementing thermal stability protection for permafrost in deeper layers, achieving a coordinated approach between deformation control and permafrost environmental protection.
Microscopic traffic simulation can provide scientific support for traffic design, traffic planning, traffic monitoring, and traffic demand management, and how to construct accurate and efficient microscopic traffic simulation is an important research direction. Current research on microscopic traffic simulation mainly focuses on the basic theory, such as the car following model and lane changing model. However, there is a lack of research on the practice and application of microscopic traffic simulation, especially for large-scale microscopic traffic simulation. In this study, we proposed a simple and efficient method for large-scale microscopic traffic simulation, and built a city-level microscopic traffic simulation system of Xiaoshan District, Hangzhou, China as an example. OpenStreetMap (OSM) data and license plate recognition (LPR) data were firstly fused, and then the road network, traffic infrastructure and travel information of vehicles were obtained based on the fused data. Next, the travel demand was obtained using the dynamic traffic assignment method and route choice algorithm. On this basis, the Simulation of Urban MObility (SUMO) platform was used for city-level microscopic traffic simulation. Finally, a calibration method was proposed to calibrate the microscopic traffic simulation system. The results show that the proposed method can simulate the traffic operation dynamics well.
