Ballast Maintenance Research Articles

Augmented dataset for multidimensional ballast segmentation and evaluation

Ballast plays an important role as a railway track supporting structure against repeated loading. Ballast degradation results in poor drainage, lateral instability, excessive settlement, service interruptions, and safety concerns. Therefore, utilizing efficient methods for evaluating ballast fouling is important to ensure safe railroad operations. Emerging computer vision approaches have been effectively incorporated into the ballast inspection processes to enhance their accuracy and robustness. Owing to the inherent data-driven nature of deep learning approaches, the efficacy of the developed model heavily depends on the quality of the training dataset, revealing an urgent need for a comprehensive and high-quality annotated ballast aggregate dataset. In this study, a multidimensional ballast aggregate dataset has been established which contains realistic data collected from field and laboratory setups, augmented by data produced by a synthetic ballast particle generator. In the dataset, the 2D data comprised ballast images with 2D annotations (masks) for localizing the particles in the images. The 3D data comprises height maps, point clouds, and 3D annotations for particle localization. The collected data included various environmental lighting levels and fouling conditions to ensure adequate coverage and diversity in the training dataset. A 2D ballast particle segmentation model previously developed by the authors was trained using an augmented dataset and demonstrated reliable and accurate results in field ballast inspections. The proposed dataset will be utilized in future studies, including 3D ballast particle segmentation and shape completion, to aid in the inspection and investigative methods for effective ballast maintenance.

Micro-mechanical behavior of stone-blowing in ballast maintenance using DEM-CFD coupling method

Stone-blowing restores the track geometry by blowing small crushed stones into the bottom of the sleeper, extending the maintenance period. In this study, ballast and filling stones were modelled using discrete element method (DEM), while the air blowing was simulated using computational fluid dynamics (CFD). The DEM-CFD coupled model has been used to simulate the stone-blowing process and investigate the optimal operation parameters from a micro view.The disturbance of ballast bed during stone-blowing process was analyzed. Meanwhile, the effect of air velocity and tube layouts on the stone-blowing, as well as the sleeper settlement after stone-blowing were discussed. The results show that the maximum disturbance occurs in the inserting area between sleepers, and the disturbance increased with faster insertion speed. It was suggested that the inserting speed of the tube is 0.4 m/s. When the air velocity of stone-blowing was not less than 20 m/s, the blowing quality meets the requirement. Furthermore, the four-tubed stone-blowing approach distributed filling stones more evenly under the sleeper, and reduced the risk of tube blockage. After stone-blowing, the contact number between the bottom of the sleeper and the ballast is greatly increased, reaching 217.9 % after double cross tubes, and 245 % after four tubes stone-blowing. The crushed stone blown in greatly improves the stress distribution of the ballast bed and makes the load transfer more uniform. Overall, this study provides valuable insights into the stone-blowing process and can help optimize the stone-blowing parameters for efficient and effective track maintenance.

Predicting Ballast Fouling Conditions Through RGB-Based Statistical Quantity Analysis

Evaluating railway ballast fouling is critical to assessing track conditions and planning proper ballast maintenance. Varying material properties associated with different ballast fouling conditions can be used to evaluate the severity of fouling. Although approaches using ground penetration radar, impulse response, surface wave, and SmartRock have been developed to estimate the fouling conditions, these methods require special sensors and equipment, or well-trained technicians. Recently, convolutional neural network (CNN) based computer vision approaches have become popular in performing particle segmentation to obtain the ballast grain size distribution. The coarse aggregate fraction can be evaluated by the CNN method, but it is not easy to segment fine particles accurately with these approaches. This study proposes a novel image analysis approach to directly estimate the ballast fouling conditions. First, fouled ballast images with different fouling conditions are taken as references. The RGB (red, green, blue) color distributions of the fouled ballast images are then processed through statistical analysis. A strong linear correlation is found between Fouling Index (FI) and variance and this is used to establish the FI prediction model. The established FI prediction model is tested and validated by additional fouled ballast samples. The FI prediction model proposed in this study can be used to quantify ballast fouling conditions with promising performance.

Investigation on the drainage condition within the ballast layer based on 3D CFD simulations

Drainage capability is vital to the performance of ballasted railway tracks. Over the decades, many efforts have been made to develop practical ballast maintenance methods to improve the ballast drainage capability. Although some researchers have attempted to quantify the drainage improvement after a specific maintenance activity, the flow within the ballast lacks thorough understanding. In the study, the effect of five different maintenance activities and the presence of the crosstie on ballast drainage are studied and compared through three-dimensional computational fluid dynamics (CFD) simulations. The five maintenance activities are Cribbing All, Cribbing Interval, Scarifying, Shoulder Cleaning, and Combination. The cleaning profiles of different maintenance activities are based on field practices. The properties of the fouled ballast are derived from the field-collected fouled ballast permeability data to ensure the fidelity of the simulations. Lateral Flow Rate (LaFR) and Longitudinal Flow Rate (LoFR) are introduced to uncover the flow within the ballast layer in both lateral (along with the crosstie) and longitudinal (along with the track) directions. The results suggest that the five maintenance activities affect internal flow characteristics differently. The drainage path within the ballast layer is sensitive to the cleaned volume, and the area, especially the shoulder region is essential for drainage improvement.

Application of a modern laser technique to evaluate the performance of recycled railway ballast

The performance of railway track structure is influenced by the ballast shape properties including roundness, flatness, elongation, sphericity, angularity and surface texture. The challenge is how to accurately measure the irregular shapes of ballast materials and directly link them to performance. In this paper, a modern three-dimensional laser technique was used to determine shapes of freshly produced crushed ballast and recycled ballast sampled from the heavy-haul coal line in South Africa. The objective was to investigate the effect of ballast shapes on settlement (i.e. permanent deformation). All five ballast materials were scanned in the three-dimensional laser scanning system and the data collected was processed to reconstruct three-dimensional models of the ballast particles. The results obtained were used to develop a chart to classify ballast shapes and link these shapes physically with settlement determined from a triaxial testing programme. Based on the triaxial test results, new empirical models were developed to determine settlement on the route corridor of the heavy-haul coal line. It is anticipated that outcomes of this study would assist with quality assessments and railway ballast maintenance in the field.

Comparison of Ballast Drainage Improvement Between Track Lifting and Shoulder Cleaning Based on CFD Simulations

Railroad track performance largely depends on ballast drainage conditions. Over the years, different ballast maintenance methods have been developed and applied in the field, aiming to restore ballast drainage capability. But the benefits from different maintenance methods have not been well quantified and compared. This study investigates and compares the benefits of the two popular ballast drainage maintenance methods used in North America, shoulder cleaning and track lifting, through numerical simulations based on computational fluid dynamics (CFD). Different fouling conditions are simulated with permeabilities quantified from the field-collected fouled ballast samples to ensure that the numerical models are representative. Because the unit cost of shoulder cleaning and track lifting varies and depends on the specific application conditions, the normalized drainage health index (NDHI) and the normalized drainage restoration ratio (NDRR) are introduced to make fair comparisons and provide unbiased parameters for practitioners to use in the future. Preliminary results from this study indicate shoulder cleaning provides better ballast drainage improvement than track lifting if the unit costs per ballast volume of shoulder cleaning and track lifting are identical.

Ballast Stabilization with Polyurethane for Use in Desert Areas

Sand dune accumulation in the railways passing through desert areas leads to ballast softening and settlement, which is one of the major challenges in the ballast maintenance operation. In this regard, ballast infilling with polyurethane could be mentioned as a novel solution that has been less attentional in previous studies. In this matter, in present study using a domestic cost-effective polyurethane, the ballast stabilization has been accomplished and the relevant shear strength parameters have been investigated via a series of large-scale direct shear tests. Since the utilized polyurethane has composed of two different components, in the first stage, the best weight ratios of components have been investigated via a series of compression tests. In this matter, the ratio of 1.5 units polyol to 1 unit isocyanate has been adopted as the best composition. Then, the resulting polyurethane was injected into the ballast to perform large-scale direct shear tests. According to the measurement results, the maximum shear stress, the internal friction angle, and the cohesion coefficient increased by 109%, 9.5%, and 162.5% with respect to the non-stabilized ballast (NSB), respectively. In addition, the dilation angle decreased by 66.4% with the injection of polyurethane into the ballast. Hence, the results indicate increased shear strength and lateral track resistance in the presence of polyurethane, which can prevent lateral deflection and improve track safety. In other words, the mentioned polyurethane has improved the shear parameters of the ballast more significantly than other polyurethanes and has shown its performance in increasing the bearing capacity.

Ballast fouling inspection and quantification with ground penetrating radar (GPR)

ABSTRACT Ground penetrating radar (GPR) has been applied for ballast layer inspection for two decades, mainly for the analysis of ballast layer fouling levels. However, some issues that affect the inspection quality remain unsolved, such as issues involving the GPR equipment quality (antenna) and the correlation between the GPR indicator and fouling index. With the aim of solving these two issues, in this paper, we investigated the difference between the results of two different antennas, the GPR data processing technique, indicators for the fouling level (by GPR signal processing) and the correlation between the indicators and fouling index (obtained by sieving). The results show that the antenna quality determines the inspection quality. The indicators can reflect the ballast layer fouling level, and they correlate the best with the fouling index (obtained by the percentage of particles passing through a 5 mm sieve size). This study is helpful for the future modification of railway ballast maintenance standards.

Influences of Waste Inclusion on Impact and Crushing Force Resistance of Track Ballast

Recently, the incorporation of various waste materials into the ballast is studied in terms of physical and mechanical behavior. However, the inclusion of concrete debris (CD) and bottom ash (BA) waste, which are enlisted as the inventory materials for railway ballast have not been thoroughly examined. Hence, this paper investigates the improvement in damage resistance of waste incorporated conventional ballast (CB) under impact and crushing force using impact hammer and crushing machine. The initial and final particle size distribution (PSD) were obtained to analyze the damages through the Hardin‘s breakage index and fouling index. The results show that the resistance against crushing and impact force is better when the composition is in the ratio of 1:1 of conventional ballast (CB) and concrete debris (CD). Under crushing load, mixture with 50% of CD recorded breakage index with 4% deviation compared to using 100% of CB. However, integrating with 40% of CD and 10% of BA proved that the values are 2.14% lower than the ACV limit and 9.09% higher than the AIV limit set by British Standard. Although the impact and crushing index of 100% CB aggregates are below the allowable limit, mixing the CD and BA also records results which is only slightly different than the threshold limit. This is due to the cushioning effect caused by the waste acting as the buffering material that reduces the time of impact, which saves the angular materials from wearing off. This will reduce the ballast maintenance intervals that indirectly reduce the service cost and promotes sustainable construction. Based on the results from this study, further experiments are recommended to be carried out to relate and understand which waste material plays a major role in damage reduction or causing higher maitenance cost.

Development of Condition Assessment Index of Ballast Track Using Ground-Penetrating Radar (GPR).

The condition of the ballast is a critical factor affecting the riding quality and the performance of a track. Fouled ballast can accelerate track irregularities, which results in frequent ballast maintenance requirements. Severe fouling of the ballast can lead to track instability, an uncomfortable ride and, in the worst case, a derailment. In this regard, maintenance engineers perform routine track inspections to assess current and future ballast conditions. GPR has been used to assess the thickness and fouling levels of ballast. However, there are no potent procedures or specifications with which to determine the level of fouling. This research aims to develop a GPR analysis method capable of evaluating ballast fouling levels. Four ballast boxes were constructed with various levels of fouling. GPR testing was conducted using a GSSI (Geophysical Survey Systems, Inc.) device (400, 900, 1600 MHz), and a KRRI (Korea Railroad Research Institute) GPR device (500 MHz), which was developed for ballast tracks. The dielectric permittivity, scattering of the depth (thickness) values, signal strength at the ballast boundary, and area of the frequency spectrum were compared against the fouling level. The results show that as the fouling level increases, the former two variables increase while the latter two decrease. On the basis of these observations, a new integrated parameter, called a ballast condition scoring index (BCSI), is suggested. The BCSI was verified using field data. The results show that the BCSI has a strong correlation with the fouling level of the ballast and can be used as a fouling-level-indicating parameter.

Quantification of the Effect of Train Type on Concrete Sleeper Ballast Pressure Using a Support Condition Back-Calculator

Monitoring ballast support condition and improving current sub-structure and ballast maintenance strategies is critical to ensuring safe and efficient railroad operations. Researchers at the University of Illinois at Urbana-Champaign (Illinois) have developed a ballast support condition back-calculator, a non-destructive instrumentation method and corresponding analysis tool that quantifies ballast pressure distributions under concrete sleepers without interrupting revenue service train operations. This laboratory-validated non-intrusive method uses concrete sleeper bending moment profile and rail seat loads as inputs to back-calculate the reaction distribution using a Simulated Annealing optimization algorithm that incorporates Pareto Distribution as the random variable generator. In order to further understand in-service ballast support conditions, concrete surface strain gauges were installed on concrete sleepers at a revenue service field site to measure strains that could subsequently be converted into bending moments. This site is on a shared use rail corridor with traffic ranging from high speed passenger to heavy axle load (HAL) freight trains. Rail-mounted strain gauges were used to measure strains that were used to calculate the vertical wheel-rail loads to approximate rail seat loads. This paper quantifies the ballast pressure distributions beneath concrete sleepers under different types of rolling stock and evaluates how ballast support condition changes as a function of accumulated tonnage. A wide range of loads were observed at the field site, ranging from 4 to 35 kips (18–156 kN). Corresponding ballast pressures ranged from 14 to 175 psi (97–1,207 kPa), with sleeper-ballast contact area corresponding to 60% of the bottom of the sleeper area. The accumulation of 12.24 million gross tons (MGT) (12.44 million tons) did not generate a quantifiable change in ballast pressure values nor did it generate a change in the ballast support condition. The research results presented in this paper demonstrate the potential of the back-calculator to provide a stand-alone non-invasive method to quantify ballast support conditions, sleeper health, and sleeper bearing stress. Back calculator data will aid the rail industry in optimizing tamping cycles, enhancing safety, and developing more representative concrete sleeper flexural designs based on actual support conditions.

Effectiveness of geogrid reinforcement in improvement of mechanical behavior of sand-contaminated ballast

Vertical stiffness and shear strength of ballasts are significantly degraded when contaminated with sands. There is a lack of solutions/studies related to strengthening ballast against sand contamination. Addressing this limitation, a comprehensive laboratory investigation was made on effectiveness of geogrid reinforcement for improvement of mechanical properties of sand-contaminated ballast. To this end, large-scale direct shear tests as well as plate load tests were conducted on geogrid-reinforced ballast samples prepared with different levels of sand contamination. The obtained results indicate that geogrid reinforcement considerably improves shear strength and vertical stiffness of contaminated ballast. A bandwidth was obtained for contamination levels in which ballast reinforcement is effective. Through examining geogrid with different aperture sizes and locations in the ballast layer, the best performance conditions of geogrid reinforcement were derived. The results were used to propose an effective method of ballast reinforcement and an efficient ballast maintenance approach in sandy areas.

Prognosis of railway ballast degradation for turnouts using track-side accelerations

Maintenance of railway turnouts is a major cost driver for any infrastructure manager, which performs it based on preventive or periodic policies to guarantee minimum downtime of the infrastructure. Ballast maintenance activities, such as tamping, are scheduled by thresholding indicators derived from track geometry data in agreement with European standards. Current industrial practice adopts the same procedures for the evaluation of track geometry degradation in open track and turnouts. This lack of specificity may determine unnecessary maintenance actions with detrimental effects to the turnout dynamical performance. By employing track-side measurements of track acceleration, a probabilistic method for turnout’s ballast quality monitoring was derived by Barkhordari et al. The paper further develops such monitoring system by establishing a mapping between its output and the standard indicator of track geometry quality used by infrastructure managers to schedule ballast maintenance. This results in a predictor of track geometry quality with variable prediction horizon that is functional to the railway infrastructure manager for the predictive planning of ballast maintenance.

Geomechanical Modelling of Railroad Ballast: A Review

Traditional ballasted tracks have been used intensively around the world with ballast as the main material for tracks. Ballast has a significant contribution to the track alignment, stability and sustainability. After service, ballast deforms and degrades. Periodic ballast maintenance is needed which is a time and cost expensive activity. Understanding the mechanical behaviour of railroad ballast leads to better design and efficient maintenance. From the literature, there are two main approaches used to understand the mechanical behaviour of railroad ballast; large scale experimental and modelling. This paper aims to review the state of the art of literature on the modelling approaches used to understand ballast mechanical behaviour. It discusses the key findings from each modelling approach in understanding ballast mechanical behavior. It presents the main concerns and limitations of each modelling approach from different perspectives related to ballast modelling. It summarizes the limitations, gaps and gaps’ developments of the researches used to understand ballast behaviour via modelling approach.

The development of suitable cyclic loading and boundary conditions for ballast box tests

Laboratory tests on ballast give insight into the behaviour and performance of the ballast layer under passenger and heavy-haul traffic. It is important, however, to ensure that the simulation of train loads on the ballast layer in the laboratory represents in-situ loading conditions. Furthermore, the provision of ballast lateral confinement during laboratory tests should model the confinement along the track. With adequate, representative loading patterns and boundary conditions executed during laboratory tests on ballast, the overall response and performance of the ballast layer can be estimated and predicted more accurately. This gives an indication of an ideal response of the ballast layer in the field, as well as its impact on track structure deterioration. The objective of this study was to develop suitable cyclic loading and boundary conditions for ballast box tests in the laboratory to represent similar conditions in the field. By conducting box tests, the ballast deformation results revealed the suitable loading pattern that produced a similar rate of ballast strain accumulation as the Field Loading (FL) pattern. Furthermore, boundary condition results showed that decreasing the Level of Lateral Confinement (LoLC) increased the permanent deformation of the ballast layer and the breakage of ballast. The laboratory loading pattern developed in this research, as well as comparable laboratory and field boundary conditions, could provide accurate predictions of the long-term behaviour of ballast and support the planning for subsequent ballast maintenance interventions based on realistic and accurate laboratory test results.

Development of integrated railway ballast quality index

ABSTRACT The quality of ballast materials is an important criterion in railway track maintenance management systems. Although various studies have been made on the characteristics of ballast aggregates and ballast mechanical behaviours, making an optimal decision on the selection of appropriate ballast materials is still a serious challenge in the railway industry. It indicates a need for an integrated ballast quality index which could help to ensure improved cost-effectiveness of track maintenance. In response to this need, the mechanical, physical and environmental properties of the ballast were categorised and weighted based on their level of influences on the ballast overall conditions. Consequently, a ballast quality/condition index was developed as a function of the influencing parameters. To examine the practicability and applicability of the developed method/index, three types of ballast materials were taken from different sources and their quality was evaluated and discussed using the new index. Through illustrating the effectiveness of the new index in evaluation of ballast materials, it was shown that the new index can play a role to allocate an optimal ballast material quality and improve cost-effectiveness of the current maintenance by providing the ability to optimise ballast maintenance planning.

Development of railway ballast geometry index using automated measurement system

Ballast layer Geometry condition is an important criterion in the railway track maintenance since the track stability strictly depends on the ballast geometry. Currently, a visual inspection is a method of monitoring ballast layer geometry which is considerably costly and time-consuming. Addressing the limitations of the current ballast maintenance approach, a new ballast layer geometry index was established, using an automated measurement system. This index is a function of deficits and excess of ballast in the track. A new maintenance approach was developed based on the new index, providing the possibility of quickly measuring ballast profile for faster and more accurate ballast maintenance. To examine the practicability and applicability of the new method/index, the results of a comprehensive field measurement were used. By illustrating the effectiveness of the new index in the field, it was shown that the new approach can significantly improve the current maintenance methods. It provides the possibility of fast and easy recording ballast layer geometry and maintaining optimum ballast conditions.

Vertical Deformation and Ballast Abrasion Characteristics of Asphalt-Scrap Rubber Track Bed

Innovations in the field of railroad construction need to be improved, especially in the ballast layer which is an essential structure in conventional railways. The purpose of this study was to analyse the characteristics of vertical deformation and ballast material abrasion with 10% of scrap rubber in two types of sizes (uniform and graded) and with 3% of asphalt. This study uses a compressive test method with six types of samples modeled with ballast boxes measuring 400 x 300 x 200 mm. The test results present that the use of 10% scrap rubber can increase the vertical deformation value significantly to 84%. On the other hand, the use of 3% asphalt can minimize vertical deformation to only 14% because asphalt can increase the ballast layer stiffness. Furthermore, it can also be concluded that in general, the use of 10% scrap rubber and 3% asphalt can reduce the percentage of material abrasion up to 80%. Besides, it also can be known that the use of graded sized scrap rubber material is the most effective in increasing material durability. Scrap rubber and asphalt have the potential to be used together on ballast layers which are expected to be a solution of the problems related to the service-life and ballast maintenance work.

Large-scale direct shear tests on sand-contaminated ballast

Significant parts of railway lines in most of the Middle East and Asian countries are in sandy and desert areas. Contamination of tracks (in particular the ballast layer) caused by frequent sand storms in the desert is an important challenge for railway industries. Despite a large number of reported railway accidents caused by the loss of shear strength in the contaminated ballast layer, there is a lack of sufficient studies on the effect of sand contamination on ballast shear strength. In response to this need, extensive laboratory tests on clean and sand-contaminated ballasts were conducted, using a large-scale direct shear test machine designed and constructed in this research. Ballast samples with different dosages of sand contamination were tested. The results obtained are discussed leading to a better understanding of ballast behaviour when contaminated with various amounts of sand. The results show that sand contamination reduces the shear strength and angle of effective shearing resistance of the ballast. The critical percentage of ballast contamination, after which the ballast faces substantial reduction in its mechanical properties, was derived. The results obtained have improved the current ballast maintenance approach by providing the possibility of a more accurate planning of ballast cleaning and renewals.

Evaluation of Railway Ballast Permeability Using Machine Vision–Based Degradation Analysis

Railway ballast degrades progressively as a result of accumulated traffic primarily through abrasion and particle breakage. Degraded ballast may cause reduced lateral and longitudinal stability, ineffective drainage, and excessive settlement of track structures, all of which would adversely affect the performance of ballasted track. Traditional methods of ballast degradation assessment involve time-consuming field sampling and laboratory sieve analysis; moreover, determining the level of track performance deterioration at which ballast maintenance is best considered still remains challenging. This paper investigates the permeability of railway ballast through laboratory testing and provides insight into its field drainage capacity under degraded condition using an innovative approach of field imaging. Constant head permeability tests were conducted on clean and degraded ballast samples which indicated nonlinear power-curve trends, especially for clean ballast, of unit flow amount with its hydraulic gradient. Imaging-based degradation analysis using machine vision technology was also performed on clean and degraded in-service ballast to correlate Fouling Index (FI) from laboratory sieving with Percent Degraded Segments (PDS) obtained from the recently developed image segmentation algorithm. Accordingly, a new Permeability Index (PI) is introduced in this paper to define ballast permeability in the form of a bilinear model developed from the machine vision–based ballast degradation analysis. Based on the findings of this study, a two-stage ballast cleaning process for determining the timeframe of ballasted track maintenance considering its drainage capacity is proposed.