Jabbar Ali Zakeri

Increasing the train speed in railway networks is the most important factors in improving the fields of attracting more passengers and cargo than other transportation modes. The construction of new railway structures with the aim of increasing the speed of trains requires a lot of money. Therefore, the purpose of this study is to investigate the possibility of increasing the speed train using a low-cost method compared to the construction of new structures, such as changing the conditions of bridge bearings in existing concrete slab deck bridges. First, a 3D finite element model of the bridge and the train was created by considering the interaction of the track and the train, and it was validated based on the results of a valid field test. Then, the effect of increasing the speed of the train on the results of the vertical displacement and vertical acceleration of the bridge deck and the vertical acceleration of the train car body under different bridge bearing conditions is investigated. The obtained results show that by reducing the stiffness of the bridge bearing, the maximum values of vertical displacement and vertical acceleration of the bridge deck increase, but the vertical acceleration of the train carbody decreases.

Due to increasing train speed and passage tonnage, the repair and maintenance of ballasted railway tracks is essential. As a result of cyclic train loads on ballasted tracks, the ballast layer can deteriorate. When the ballast bed deteriorates, it can change the track geometry, which leads to uncomfortable ride and an increase in wheel-rail interaction. Tamping is one of the most widely used methods for filling the ballast layer gaps around sleepers and homogenizing ballast beds in order to align the track geometry. After passing the tamping machine, the dynamic stabilizing machine is utilized to improve the quality of the ballast bed. The rail support modulus is an essential parameter for analyzing ballasted railway tracks, and it can change after maintenance operations. This paper extensively discusses the effects of maintenance operations on rail support modulus as an essential safety factor in ballasted tracks. In this study, a series of field tests are planned and conducted at Karaj station in Iran to investigate the effects of passing tamping and stabilizing machines on the rail support modulus in ballasted tracks. In this regard, the rail support modulus of the ballasted track according to deflection basins was measured in three stages (before tamping, after tamping, and after stabilizing), and the results were analyzed to determine the effects of passing maintenance machines on ballast beds. Based on the results, the tamping operation results in a 75.5% reduction in the rail support modulus, and after stabilizing the railway track, the rail support modulus is increased by 35.8%.

Railway bridges are built to allow trains to cross over highways, valleys, or other transportation infrastructure. In recent years, the number of railway bridges subjected to over-height collision forces has increased. These collisions damage the bridge and affect the safety of the running train. In this investigation, first, a 3D GT26 train-track-bridge interaction model was created to study the effects of collision forces applied to the bridge superstructure and not to the bridge piers as a novelty of this research using the finite element analysis. Then, the dynamic responses of the railway bridge due to the GT26 train load and subjected to over-height collision forces were obtained. Finally, the different sensitivity analyses describe that changing the length of the collision area, the bridge span, and the value of collision forces affect the dynamic responses of the bridge in the contact area. The results show that maximum lateral displacement of the concrete girder in case of assuming the GT26 train 3D model plus over-height collision force is 8.88% less than the case in which considering only freight train axle-load and same over-height collision force apply to the bridge superstructure, and its value reduces from 45 mm to 41 mm. The maximum lateral displacement of the bridge deck is reduced by about 71% by increasing the collision area length from 0.2 m to 1.2 m and at the impact area rises about 43.5% by changing collision speed from 48 km/hr to 144 km/hr as collision force from 7753 kN to 13370 kN.

Nowadays, attention to railways has been increased as one of the important transportation methods. Various factors can cause longitudinal forces on the railway tracks, so the most important factors are the temperature changes due to the rail contraction and expansion (thermal forces), train braking system forces and acceleration, etc. Increasing longitudinal force can lead to buckling phenomena in railway tracks. In this paper, the effects of tensile and compressive longitudinal forces on the parameters of rail, sleeper, and ballast layers under vertical moving loads are investigated by using the finite element method. In this regard, by performing sensitivity analyses for different values of longitudinal forces and train speeds dynamic responses (displacement, velocity, and acceleration) of railway track components like rail, sleeper, and ballast have been studied. The results show that increasing the values of longitudinal axial force from –2000 [kN] up to 2000 [kN] as well as increasing the train speed from 10 [m/s] (36 [km/h]) up to 100 [m/s] (360 [km/h]) increases the rail displacement and velocity in the range of 25% up to 37% also the rail acceleration in the range of 9% up to 14%. The velocity and acceleration of the sleeper also the ballast velocity increase in the range of 24% up to 30% and 7% up to 9%, respectively, by increasing the speed of the train from 10 [m/s] (36 [km/h]) to 100 [m/s] (360 [km/h]) in all three modes without applying axial force, considering compressive and tensile one in the train-track interaction system.

One of the constant concerns in public and private organizations is choosing a project from among the multitude of potential projects to be implemented. Due to the limited resources in different sectors, projects should be prioritized in order to obtain the maximum benefit. In national and government projects, it is not necessarily important to pay attention to financial components, and more dimensions should be considered. Sustainability is a component that considers various economic, environmental, and social aspects in the evaluation of projects. In this regard, in this study, the main goal is to evaluate and select rail transportation projects according to sustainability criteria. In general, 15 indicators were identified in three economic, environmental, and social sectors, which were weighted using the best–worst fuzzy method (FBWM). The most important indicators in the evaluation of projects are the investment cost, the rate of internal return from a national perspective, and the lesser impact of the plan on environmental destruction. According to the weighted indicators, the stochastic VIKOR approach is developed for the first time in this article, which was evaluated according to two scenarios of demand changes and cost changes of candidate projects. In the stochastic VIKOR approach, to deal with uncertainty, different scenarios are defined, through which it is possible to respond to different conditions and evaluate projects more realistically. Validation of this method is compared to other multi-criteria decision-making methods. The main contribution of this study is presenting the stochastic VIKOR approach for the first time and considering the uncertainty in project evaluation. The findings show that the projects that have the most economic gains from the national and environmental aspects are selected as the best projects.

The railway network design problem is one of the critical issues in the transportation sector due to its significance and variety of necessary applications. The major issue of this field relates to the decision of whether to increase the railways’ capacity or construct a new route to meet demand. Although the budget is a great concern of the managers for making such a decision, environmental factors should be necessarily included in the decision-making process. Therefore, this research proposes a novel robust bi-objective mixed-integer linear programming (MILP) model to simultaneously minimize the total cost and environmental impact under uncertain conditions and within a given time horizon. The proposed problem addresses strategic and operational decisions through railway project selection and product flow determination. To deal with the bi-objectiveness of the model and tackle the complexity of the problem, a nondominated sorting genetic algorithm (NSGA-II) is employed. The proposed NSGA-II could reach near-optimal Pareto solutions in a reasonable solution time and showed a reliable performance for being employed in large-sized instances. It also indicates that the proposed NSGA-II can be utilized for solving large-sized samples in a very short time.