Mountain Railway Research Articles

An event tree-based distance transform algorithm for simultaneously determining mountain railway alignments and station locations

The concurrent optimization of railway alignments and station locations (RA&SL) is a complex task, especially for the main railway lines in mountainous regions. The intricate coupling constraints between RA and SL are very challenging for the conventional RA&SL search methods, which consider limited solution types to generate an optimized RA&SL solution. To solve this problem, an event tree-based distance transform (ET-DT) algorithm is proposed. The study area is first divided into grid cells, followed by a preprocessing step to identify infeasible areas for station locations. Next, an event tree (ET) is constructed to represent all the possible solution types during the RA&SL design process. Afterward, in the ET-DT method, a total of eight types of RA&SL search operators are integrated to generate diverse RA&SL alternatives. Ultimately, the proposed method is applied to a realistic case with significantly-undulating terrain. Results show that ET-DT generates 2.8 times more solutions than a contemporary DT-based method (PreDT) and further improves solution quality through an 8.7% reduction in construction cost compared to the best manually-designed alignment, while PreDT only achieves a 5.7% reduction.

Early Detection and Stability Assessment of Hazardous Rock Masses in Steep Slopes

The assessment of slope stability plays a critical role in the prevention and management of slope disasters. Evaluating the condition and stability of hazardous rock masses is essential for predicting potential collapses and assessing treatment effectiveness. However, conventional measurement techniques are inadequate in high slope areas, which lack sufficient spatial data to support subsequent calculations and analyses. Therefore, this paper presents a method for the early identification and evaluation of unstable rock masses in high slopes using Unmanned Aerial Vehicle (UAV) digital photogrammetry and geographic information technology. By considering nine evaluation indices including geology, topography, and induced conditions within the study area, weights for each index are determined through an analytic hierarchy process. A semi-automatic approach is then utilized to extract and analyze rock mass stability. The reliability of this early identification method is confirmed by applying the limit equilibrium principle. The findings reveal that 17.6% of dangerous rock masses in the study area fall into the unstable category (W4, W6, W10). This method effectively assesses slope rock mass stability while providing technical support for disaster monitoring systems, warning mechanisms, and railway infrastructure safety defense capability to ensure safe mountain railway operations.

Modeling Earthquake-Induced Landslide Risk for Mountain Railway Alignment Optimization

Modeling Earthquake-Induced Landslide Risk for Mountain Railway Alignment Optimization

Suitability of Site Selection for Mountain Railway Engineering Spoil Disposal Areas from a Multi-Scenario Perspective

The current approach to selecting sites for abandoned spoil areas primarily relies on qualitative methods, often overlooking the impact of policy factors on decision-making. Traditional single-site selection strategies may not be flexible enough to accommodate evolving external policy demands. Addressing this challenge is crucial for ensuring the site selection for abandoned spoil areas is both scientifically sound and policy-compliant. This research integrates various analytical methods, including principal component analysis, complex network theory, the CRITIC method, and the ordered weighted averaging method, to thoroughly evaluate the factors influencing site selection. Utilizing geographic information system (GIS) technology, the study simulates different policy scenarios, such as construction cost, social and ecological concerns, natural security, spatial accessibility, and a comprehensive balance approach. It specifically analyzes the suitability of the spoil site of a segment of the Chongqing ZW Railway under these policy conditions. Based on the actual policy situation in the local area, six potential suitable sites were screened with the help of field investigation. This study can offer a methodological framework and theoretical guidance for optimally locating mountain railway engineering waste disposal sites. In addition, the methodology presented in this study can be adapted to the development and change in policy scenarios.

Geometry-Based Channel Modeling for Tunnel Entrance Scenarios of Mountain Railway

Geometry-Based Channel Modeling for Tunnel Entrance Scenarios of Mountain Railway

A 3D-RRT-star algorithm for optimizing constrained mountain railway alignments

Railway alignment development in mountainous regions is a complex problem, especially when there are numerous obstacles in the study area. Obtaining a feasible solution that satisfies all the obstacle constraints requires considerable computing resources and time. To solve this problem, a graph-based shortest path method, i.e., three-dimensional rapidly exploring random tree star (3D-RRT-star), is customized. Three main innovations are included in this method: (1) A heuristic sampling process is proposed to avoid getting the RRT search trapped into local ranges and overlooking possible path alternatives by combining a specially designed RRT node sampling method and a railway spatially-reachable analysis. (2) A multi-level constraint discretization approach is proposed to describe the obstacles in the study area, while procedures are developed to tackle the obstacle constraints dynamically during the search process. (3) An evolutionary search method integrating a sampling strategy and constraint handling operator is devised for generating a set of dissimilar RRT paths, which are finally refined into railway alignments satisfying curve constraints. Ultimately, the proposed method is applied to a realistic railway case. The experimental results confirm that it can yield a better alignment than the best manually obtained solution. Furthermore, its search efficiency is compared to a previous optimization method for this problem and the results reveal significant improvement.

Study on longitudinal dynamics of 5000t heavy haul train on mountain railway

In order to analyze the feasibility of running 5000t heavy-haul trains on a railway in a mountainous area, a longitudinal dynamic model of heavy-haul trains is established, taking full account of the actual horizontal profile of the railway line in the mountainous area. The results of the model are compared and analyzed with those of China Academy of Railway Sciences through a numerical example, and the results are in good agreement, which verifies the accuracy of the model. Based on this model, the longitudinal dynamic performance of planned running marshalling under the conditions of ramp traction, restricted ramp braking, emergency braking and resistance speed control braking is analyzed. The results show that the longitudinal impulse of the marshalling under each condition has a large margin compared with the safety standard. The study demonstrates the feasibility of 5000t heavy-haul train operation in the mountainous area from the perspective of simulation, and provides a theoretical basis for the safe operation of 5000t railway in the mountainous area.

Optimizing net present values of risk avoidance for mountain railway alignments with seismic performance evaluation

AbstractRailway alignment optimization in earthquake‐prone mountainous (EPM) regions should quantify and trade off construction investments and seismic risks. Unfortunately, slight attention has been previously devoted to this trade‐off. To this end, based on the FEMA‐P58 methodology, a net present value (NPV) model of risk avoidance is presented and solved. In the model, alignment alternatives are first segmented into structural groups with different probabilistic seismic fragility curves, which are then used to generate structural repair cost and repair time curves. Afterward, a probabilistic seismic hazard curve is introduced to estimate the expected annual repair cost and time for computing railway direct and indirect seismic losses. Hence, the railway total annual loss caused by seismic activity can be obtained. Next, a benefit–cost analysis is performed to combine construction cost and seismic loss as the risk‐cost NPV. To optimize this objective function, a particle swarm algorithm is used as the basic approach. For implementing the probabilistic seismic performance analysis, a Monte Carlo simulation (MCS) is employed as the risk assessment module. Furthermore, due to the computationally intensive nature of MCS, a CPU‐based parallelization is embedded into the algorithm to expedite the search. Finally, the proposed model and method are applied to a representative real‐world railway case in an EPM region. Their effectiveness is discussed and verified in five experiments, including algorithm convergence analysis, alignment solution comparison, seismic risk interpretation, computational efficiency test, and a specific sensitivity analysis.

Evaluation of Structural Stresses of Mountain-Embedded Railway Systems

Mountain railways are constructed on terrains with steep gradients and operate under unique conditions as they climb slopes at low speeds using rack rails. Recently, mountain railway systems in the form of embedded rail systems (ERSs) have been developed to minimize environmental damage caused by the construction of new roads. However, the use of ERS in mountain railway tracks is still limited, and research on their safety and behavior is lacking. Therefore, this study was conducted to evaluate the safety profile and behavioral responses of mountain-ERS under a steep gradient condition of 180‰. The effects of using high-strength concrete materials for precast concrete panels were investigated in this study, and the safety profile and behavioral response of mountain-ERS based on changes in the gradient and after adjusting the thickness of the subgrade of mountain-ERS was assessed. Under load conditions, the maximum tensile stress in the concrete elements did not exceed the tensile strength of the concrete. In the structural behavioral analysis, the patterns of stress variation were analyzed by applying stress to the concrete elements. The safety assessment and behavioral analysis results obtained in this study are considered valuable foundational research data for analytical studies on mountain-ERSs.

Mountain railway alignment optimization based on landform recognition and presetting of dominating structures

AbstractMountain railway alignment optimization has always been a challenge for designers and researchers in this field. It is extremely difficult for existing methods that optimize alignments before major structures to generate a better alignment than the best one provided by human designers when the terrain is drastically undulating between the start and endpoints. To fill this gap, a “structures before alignments” design process is proposed in this paper. Primarily, a landform recognition method is devised for recognizing dominating landforms. Then, a bi‐level alignment optimization model is proposed, with the upper level dedicated to characterizing dominating structures and the lower level focusing on optimizing the entire alignments. To solve this bi‐level model, a three‐stage optimization method is designed. At the first stage, a scanning process and screening operators are devised for generating all the possible locations of dominating structures. At the second stage, a hierarchical multi‐criteria decision‐making procedure is applied for selecting the optimized dominating structure layouts. At the third stage, alignments are optimized based on the determined structure layouts using a bi‐objective optimization method, which minimizes construction cost and geo‐hazard risk simultaneously. The proposed model and solution method are applied to two real‐world cases whose results verify their capabilities in producing alignment alternatives with better combinations of construction cost and geo‐hazard risk than manually designed alternatives.

Research on General Model of Railway Route Selection in CSM Areas Using the Sichuan–Tibet Railway and Other Typical Mountain Railways as Case Studies

In recent years, China’s rail network has been expanding to western China. Most of western China is a complicated and steep mountainous area with complex terrain and a harsh natural environment. Many engineering geological problems and unfavorable geological hazards have been encountered in railway construction in this area. Railway route selection in complex and steep mountainous (CSM) areas has become one of the fundamental issues in railway design. In view of the existing literature, this paper is aimed to summarize the characteristics and difficulties of railway route selection in CSM areas. In view of the low efficiency of railway route selection in CSM areas, a set of general models for railway route selection in CSM areas is established in the present study. A new multifactor interactive matrix dynamic weight approach is proposed in this model, and the corresponding evaluation index system is then developed. This methodology has been successfully applied in two typical CSM railway route selection cases, which proves the validity and applicability of this novel approach. This scrutiny provides a newly solid reference for the route selection method of the railway in CSM areas and gives a new direction for the evaluation and decision-making of other complex system engineering problems.

Declining trees growth and vegetation productivity resulting from decreasing soil water contents induced by tunnels excavation in karst mountain areas

Tunnel construction in karst areas greatly impacts the local hydrological conditions. The drawdown of groundwater levels and the loss of soil water storage due to tunneling limit the available water resources on the karst land surface, and this may affect the function of plants. Here, we evaluated the responses of the radial growth rates of two major tree species (Masson pine and Camphor laurel) to a tunneling induced water stress event in a typical karst trough valley. Meanwhile, to discuss the overall influence of tunnel excavation on plant growth in all vegetation cover types, the dynamics of vegetation productivity around the tunnel were evaluated using remote sensing indices, the Normalized Difference Vegetation Index (NDVI), and Net Primary Productivity (NPP). Furthermore, we estimated the spatial–temporal variations of NDVI and NPP in other tunneling regions of Southwest China. The results showed that the soil moisture contents (SMC) around the Zhongliang Mountain Railway Line 6 (ZMRL6) tunnel had dramatically declined −5.06%∼−10.53% within the areas < 1500 m. After the excavation of ZMRL6 tunnel, the basal area increment (BAI) for the tree-ring widths of Masson pine and Camphor laurel within 1500 m of the tunnel central reduced by 94.8%∼135.8% and 116.6%∼139.9%, respectively, while the trees beyond this distance range were less influenced. Meanwhile, the remote sensing indices showed that tunnel excavation can reduce 3.3%∼7.6% of the NDVI and 15.7%∼17.4% of the NPP within 1500 m of the ZMRL6 tunnel. A similar distance range of such declines in NDVI and NPP was also found in other tunneling regions throughout the karst mountain areas of Southwest China. The findings in this study suggest that tunnel excavation may cause severe ecosystem degradation within 1500 m of the tunnel center, which should be considered in ecosystem management and conservation strategies in karst mountain areas.

Optimal Hybridization with Minimum Fuel Consumption of the Hybrid Fuel Cell Train

This paper describes a numerical study of the optimal distribution of energy between fuel cells and auxiliary energy storages in the hybrid train. Internal combustion engines (ICEs) are currently under pressure from environmental agencies due to their harmful gas emissions, and pure battery vehicles have a short range; a hybrid train powered by fuel cells, batteries, and supercapacitors can provide a viable propulsion solution. In this study, special energy management on the mountain railway with optimal power distribution and minimum hydrogen consumption is proposed. Considering the characteristics of the mountain railway, the vehicle uses recuperation of regenerative braking energy and thus charges additional power devices, and hybridization optimization gives favorable power to each power source device with a minimum consumption of hydrogen in the fuel cell. In this study, a simulation model was created in a Matlab/Simulink environment for the optimization of hybridized power systems on trains, and it can be easily modified for the hybridization of any type of train. Optimization was performed by using Sequential quadratic programming (SQP). The results show that this hybrid train topology has the ability to recover battery and supercapacitor state of charge (SOC) while meeting vehicle speed and propulsion power requirements. The effect of battery and supercapacitor parameters on power distribution and fuel consumption was also simulated.

Railway Alignment Optimization Under Uncertainty With a Minimax Robust Method

Railway alignment optimization is difficult due to theoretically infinite possible alternatives, multiple conflicting and hard-to-quantify objectives, as well as large-scale and highly constrained search spaces. Besides these factors, this problem includes great uncertainties, which weaken solution robustness. However, no proactive robust approach has been developed for explicit uncertainty analysis within alignment optimization. In this article, a novel minimax approach is proposed for railway alignment optimization. First, a minimax robust optimization (RO) model is developed. In it, the comprehensive alignment cost is defined as the raw objective function, and a minimax cost evaluation is constructed as the expected objective function. Multiple design constraints are also specified and categorized into hard and soft ones for robust assessments. Afterward, a previous particle swarm optimization (PSO) algorithm is modified into an RO–PSO algorithm by improving the search process with an RO procedure whose major steps include the determination of disturbance spaces, generation of alignment counterparts and implementation of minimax analysis. Finally, the model and algorithm are applied to a complex, real-world mountain railway case. The effectiveness of the proposed approach is verified through a comparison of the resulting cost and degree of robustness (DoR) among the best alignments generated by the previous PSO and the RO–PSO. The search performance of the RO–PSO is further tested by varying an important parameter, i.e., the number of alignment counterparts. The outcomes indicate that the DoR performance of the RO–PSO can be improved as the counterparts increase, but the performance will finally converge to a certain degree.

Study on Hazard Identification for a Mountain Railway System

In Korea, a mountain railway system is being developed to solve the difficulties of residents living in the mountain areas due to the restriction of traffic by heavy snow and ice in winter. In this study, the hazard identification which is customized to the developing mountain railway system was conducted by considering the characteristics of the developing system, past accident cases of the mountain trains of the rack&amp;pinion type and trams in the world, and risk factors defined in the ordinary railway system. Predictable accidents during mountain railway operation were classified into five types of accidents: collision, derailment, fire, casualty, and crossing/competitive section accidents. Hazardous events and hazards were derived for each accident. Moreover, specific hazards were derived for each hazard. The hazards of the mountain railway system identified in this study can be used as basic data for preliminary hazard analysis and establishment of safety management measures for mountain railway systems in the future.

Assessing the Value of Railway Heritage for Sustainable Development: The Case Study of the Oraviţa–Anina Railway, Romania

The value of historical railways and their important role in social, economic, technical, political, and cultural terms has led to their inclusion as industrial heritage attractions. This study aims to evaluate the heritage value of the Oraviţa–Anina linear railway, the first mountain railway in Romania. The assessment of the value of the railway involved both quantitative and qualitative methods. The value was assessed on the basis of a rigorous quantitative evaluation of key attributes of heritage railway, using a system of criteria and indicators. On the other hand, the selected qualitative methodology facilitated the critical interpretation of the perception of the local community as a beneficiary of the railway heritage and as an active stakeholder involved in its reuse. The qualitative evaluation of the heritage railway was also highlighted based on a critical analysis of tourists’ perceptions. The results indicate the usefulness of a mixed methodology for the complex evaluation of the value of a heritage railway and its sustainable capitalization. Railway tourism is a sustainable solution meant to stimulate interest in learning about local history and culture, and can at the same time contribute to the fulfillment of knowledge of the motivations that drive tourist demand.

Vertical alignment optimization of mountain railways with terrain‐driven greedy algorithm improved by Monte Carlo tree search

AbstractVertical alignment design is an important process for railway construction which fundamentally affects the infrastructure investment cost. Determining an optimized vertical alignment is a challenging task since the objective function is non‐linear, non‐differentiable, and quite unsmooth. Great efforts have been invested in solving the vertical alignment optimization problem and many methods have been proposed. However, for vertical alignment designs in complex mountainous regions, the terrain conditions impose great difficulties and, hence, many bridges and tunnels are generally required. Thus, reasonably locating bridges and tunnels along the entire alignment (EA) is a major concern that deserves further investigations. To solve this problem, this study develops a terrain‐driven greedy algorithm improved by Monte Carlo tree search (T‐GRA‐MCTS). A terrain‐driven method is proposed to determine the number and longitudinal distribution of vertical points of intersection (VPIs). In order to trade off the local section of an alignment versus the EA when optimizing each VPI along the alignment to locate bridges and tunnels reasonably, an MCTS is employed and integrated with a GRA. The basic MCTS is modified for vertical alignment optimization with a novel equation for computing the upper confidence bounds for trees and a customized termination criterion is provided. A real‐world railway case is used to demonstrate the effectiveness of the proposed method. The results show that the T‐GRA‐MCTS performs better than a greedy search method without MCTS or a widely used nature‐inspired algorithm (i.e., a particle swarm optimization). Moreover, it can find a less expensive solution than the one designed by experienced human engineers.

Modeling of Regenerative Braking Energy for Electric Multiple Units Passing Long Downhill Section

The process of electric multiple units (EMUs) passing long downhill sections is inevitable in the construction of mountain railways. Moreover, huge regenerative braking energy (RBE) will be sent back to the traction network, threatening voltage safety. Due to the lack of accurate vehicle-grid integrated models considering slope parameters in studying the RBE, this article proposes a modeling scheme, taking China railway high-speed 3 (CRH3) EMUs as an example. First, based on the extended dual pulsewidth modulation (PWM) mathematical model, the quantitative formula for calculating the motor braking power of the CRH3 EMUs is established. Moreover, the slope parameters are introduced into the vehicle-grid model via force analysis and regenerative braking power calculation. Then, by substituting the calculated results into the extended dual PWM mathematical model, the target instruction parameters are solved. Next, the accurate electrical characteristics, including catenary voltage, electromagnetic torque, and converter voltage, are simulated to evaluate the voltage safety. Finally, by comparing the simulation and semi-physical experiment results with the experimental data from the Chengdu to Chongqing railway line, the feasibility, validity, and accuracy of the model are verified.

Mountain railway alignment optimization integrating layouts of large‐scale auxiliary construction projects

AbstractMountain railway alignment design is an important but complex civil engineering problem. To overcome the drastically undulating terrain, long tunnels and high bridges are major structures used along a mountain railway, which poses great challenges for railway design and construction. Unfortunately, despite being studied for many years, the crucial construction factors of complex structures have received slight attention in alignment optimization. In this paper, for the first time, the layout of large‐scale auxiliary construction projects (LACPs), including tunnel shafts and access roads, is incorporated into the alignment design process in order to consider construction practicability and economy. Primarily, an alignment–LACPs concurrent optimization model is built. After defining the comprehensive design variables, the alignment–LACPs total construction cost is formulated as the objective function. Besides, the separate constraints for designing the alignment and LACPs are considered. Also, a construction duration computation is proposed for constraining the alignment–LACPs integration. To solve the model, a four‐step hybrid solution method is developed. Specifically, the alignment is first generated with a particle swarm optimization (PSO). Afterward, a new divide and conquer approach is devised to search for shaft alternatives along the alignment. Then, a customized Dijkstra algorithm is developed to search for complex access roads. Finally, a novel polynomial mechanism for time‐varying acceleration coefficients (TVAC) is designed for PSO to evolve the alignment–LACPs solutions. The above model and methods have been applied to two complex actual mountain railway examples. Their effectiveness is demonstrated through detailed analysis of resulting railway solutions and control experiments with contemporary TVAC‐based methods.

GIS-Based Comparative Study of the Bayesian Network, Decision Table, Radial Basis Function Network and Stochastic Gradient Descent for the Spatial Prediction of Landslide Susceptibility

Landslides frequently occur along the eastern margin of the Tibetan Plateau, which poses a risk to the construction, maintenance, and transportation of the proposed Dujiangyan city to Siguniang Mountain (DS) railway, China. Therefore, four advanced machine learning models, namely, the Bayesian network (BN), decision table (DTable), radial basis function network (RBFN), and stochastic gradient descent (SGD), are proposed in this study to delineate landslide susceptibility zones. First, a landslide inventory map was randomly divided into 828 (75%) samples and 276 (25%) samples for training and validation, respectively. Second, the One-R technique was utilized to analyze the importance of 14 variables. Then, the prediction capability of the four models was validated and compared in terms of different statistical indices (accuracy (ACC) and Cohen’s kappa coefficient (k)) and the areas under the curve (AUC) in the receiver operating characteristic curve. The results showed that the SGD model performed best (AUC = 0.897, ACC = 80.98%, and k = 0.62), followed by the BN (AUC = 0.863, ACC = 78.80%, and k = 0.58), RBFN (AUC = 0.846, ACC = 77.36%, and k = 0.55), and DTable (AUC = 0.843, ACC = 76.45%, and k = 0.53) models. The susceptibility maps revealed that the DS railway segments from Puyang town to Dengsheng village are in high and very high-susceptibility zones.