Hamidreza Heydari

Climate change represents one of the most significant challenges affecting the behavior of materials and infrastructures. This phenomenon can lead to excessive increases or decreases in temperature, heightened sandstorms, increased sulfate attacks and exacerbated freeze–thaw cycles. Among the infrastructures perennially exposed to climate change are railway tracks. In ballasted railway tracks, the ballast layer is affected by various factors such as freezing and thawing, extreme temperatures and attacks by various sulfate salts which can accelerate the degradation of ballast aggregates. Considering that most of the maintenance costs of railway tracks are associated with the deterioration of the ballast layer, the impact of climate change and environmental conditions on ballast durability is examined in the current study. To achieve this goal, a comprehensive experimental investigation was conducted through a series of laboratory tests. Specifically, the durability of ballast aggregates under various states, including environmental temperature changes ranging from − 20 °C to + 100 °C, freeze–thaw cycles, and sulfate attacks, was assessed by simulating these conditions in a laboratory environment. The durability properties of ballast in these conditions were evaluated using different indices such as Los Angeles abrasion, micro-Deval wear, crushing resistance, impact performance, and breakage potential. The results indicate that the durability performance under sulfate attacks, freeze–thaw cycles, and extreme cold and warm temperatures deteriorated by an average of 50%, 20%, 40%, and 35%, respectively. Interestingly, the obtained results also led to a series of insightful empirical formulations to estimate the ballast degradation indices accounting for the impacts of thermal and environmental conditions. These findings highlight a notable impact of thermal and environmental conditions on the durability of ballast aggregates.

Utilizing the ballast layer with more durable and stable characteristics can help avoid significant expenses due to decreased maintenance efforts. Strengthening the ballast layer with different types of reinforcements or substituting the stone aggregates with the appropriate granular materials could potentially help to achieve this goal by reducing the ballast deterioration. One of the exquisite and most effective solutions to eliminate these challenges is to use waste materials such as steel slag aggregates and useless tires. Utilizing these waste materials in the ballasted railway track will contribute to sustainable development, an eco-friendly system, and green infrastructure. So in a state-of-the-art insightful, the ballast aggregates, including a mixture of steel slag and stone aggregates, are reinforced with a novel kind of geo-grid made of waste tire strips known as geo-scraps. This laboratory research tried to explain the shear strength behavior of the introduced mixing slag-stone ballast reinforced with tire geo-scrap. To achieve this goal, a series of large-scale direct shear tests were performed on the ballast which is reinforced by tire geo-scrap and included various combinations of slag and stone aggregates. The concluded results indicate that the optimal mixing ratio is attained by a combination of 75% slag and 25% stone aggregates which is reinforced by tire geo-scrap at a placing level of 120 mm. In this case, the shear strength‌, internal friction angle, vertical displacement, and dilatancy angle of stone–slag ballast reinforced with geo-scraps exhibited average changes of + 28%, + 9%, − 28%, and − 15%, respectively.

One of the primary challenges in the railway industry revolves around achieving a comprehensive and insightful understanding of track conditions. The geometric parameters and stiffness of railway tracks play a crucial role in condition monitoring as well as maintenance work. Hence, this study investigated the relationship between vertical ballast stiffness and the track longitudinal level. Initially, the ballast stiffness and track longitudinal level data were acquired through a series of experimental measurements conducted on a reference test track along the Tehran–Mashhad railway line, utilizing recording cars for geometric track and stiffness recordings. Subsequently, the correlation between the track longitudinal level and ballast stiffness was surveyed using both frequency-based techniques and machine learning (ML) algorithms. The power spectrum density (PSD) as a frequency-based technique was employed, alongside ML algorithms, including linear regression, decision trees, and random forests, for correlation mining analyses. The results showed a robust and statistically significant relationship between the vertical ballast stiffness and longitudinal levels of railway tracks. Specifically, the PSD data exhibited a considerable correlation, especially within the 1–4 rad/m wave number range. Furthermore, the data analyses conducted using ML methods indicated that the values of the root mean square error (RMSE) were about 0.05, 0.07, and 0.06 for the linear regression, decision tree, and random forest algorithms, respectively, demonstrating the adequate accuracy of ML-based approaches.

Short-span bridges are one of the most frequent infrastructures along railway tracks where railway track stiffness suddenly changes. The sudden variation in the vertical stiffness of railway tracks increases dynamic loads and causes numerous defects in ballasted railroads. Therefore, improving the dynamic performance of railway tracks can be conducted by constructing countermeasures along the transition zone. In this regard, the approach slab is a practical technique used in railway-bridge transition zones. As the dimensional shape of the approach slab plays a significant role in the dynamic response of transition zones, this study evaluated the effects of its main geometric parameters. A three-dimensional model of the railway portal bridge, including the approach slab, was built using the finite element method and analyzed by imposing moving wheel loads as a series of acting force points along rail elements. The model was validated with field-obtained results acquired through a laser/camera-based measuring technique. Then, some sensitivity analyses were performed to find optimized geometric dimensions of approach slabs to improve the dynamic behavior of railway-bridge transition zones. Obtained results of the geometrical sensitivity analysis show that when the geometrically optimized approach slab is used along the railway-bridge transition zone, the displacements of rail and ballast are decreased by 24% and 18%, respectively.