Railway Freight Research Articles

Accident Prevention of BOXN Wagon Train

The safety and efficiency of railway freight transportation are critical to the functioning of many national economies, and India is no exception. BOXN wagons, widely used in the Indian railway system for transporting heavy goods such as coal, minerals, and other bulk materials, are essential for supporting industries across the country. However, due to their size, weight, and the volume of cargo they carry, these wagons are prone to accidents if not properly managed. Accidents involving BOXN trains can result in severe consequences, including loss of life, damage to property, and environmental degradation. One of the biggest and most significant industries in the world is the Indian goods railway sector. It is essential for the transportation of materials and goods across the nation. Indian Railways seeks to shorten commute times by boosting the average freight train speed efficiently from 22 mph to 50 mph. The adoption of new technologies is anticipated to have positive effects on the Indian goods railway sector as well. Smart Innovations, for instance, smart goods cars and digital signaling can contribute to reducing train accidents and help to increase railroad productivity using smart mobility.

Mechanical and Metallurgical Assessment of a Submerged Arc Welded Surfaced Rail

The surfaces of rails are often damaged during constant loading, so it is essential to repair the damaged areas in a railroad network to get the best performance. However, the traditional methods of improving rails are expensive, time-consuming, and require excessive effort. Therefore, some creative ideas would be helpful in this process, one of which may be on-site overlay arc welding instead of exchanging the whole part of the rail. In this paper, the performance of such a method is assessed experimentally, and its results are interpreted.For the investigation, a worn part of the 136RE rail, used in the freight railway network in the U.S., was chosen. After milling and flattening the surface of the rail, a submerged arc welding process was applied to rebuild this rail by utilizing a 1/8-in Lincore 40-S depositing wire. This study used four destructive tests: 1) XRD residual stress measurement, 2) SEM/OM analysis, 3) hardness test, and 4) tensile test. The results showed that the required mechanical strength could be achieved. However, the repaired area seems more vulnerable to the forces encountered on a railroad network due to the more brittle structure due to high temperatures in this region. Considering this flaw is critical because forces are primarily dynamic in railway networks, especially in heavy rails, which are higher due to the extensive use of freight trains.

EXAMINING THE EFFICIENCY OF NATIONAL AND INTERNATIONAL RAILWAY FREIGHT TRANSPORTATION DURING A SPECIFIC TIME PERIOD

The aim of this study is to determine the efficiency values of the Republic of Turkey State Railways (TCDD) in national and international freight transportation between 2010 and 2019. Additionally, the study aims to identify the years in which the company operated more efficiently, process this information, and provide reference years and recommendations to relevant institutions.Since railway investment costs are very high, the efficient use of resources is of great importance. This study is significant in terms of guiding the efficient use of railway resources. Moreover, the use of different input and output variables over a specific time period distinguishes this study from other scientific research, as it incorporates both national and international data. For efficiency measurement, output (tonne-kilometres) and input variables (amount of freight transported, main line length, and number of freight wagons) were used, following the relevant literature. The data used in the research were obtained from the activity reports of TCDD and the Turkish Statistical Institute. DEAP (Data Envelopment Analysis Program) software, based on Productivity Time Analysis, was used to analyze the research data. As a result, the average efficiency in national railway freight transport decreased by 1.8%, while the average efficiency in international railway freight transport decreased by 22.4%. The reference year for both types of transport was 2010. Although efficiency in international railway freight transport showed partial improvement in certain years, it generally exhibited a continuous downward trend.

Forecasting material flows of modern logistics centres of railway freight stations exemplifi ed by Xi’an (the People’s Republic of China)

The purpose of the study is to create a more accurate material fl ow forecasting model of Xi’an freight railway station in China. The combined forecasting model is more validated for forecasting freight flows of regional logistics compared to three methods: grey forecasting, Markov chains, entropy weighting. Through the creation of the combined model, the grey forecasting method is combined with Markov chain correction, and the projected data is compared with the actual data to obtain higher accuracy of the forecasting model. A combined model using the grey forecasting method combined with Markov chain correction is created, with the forecast data compared with the actual data to obtain high accuracy of the forecasting model. The practical significance is that in the context of the present post-pandemic economic development, the logistics enterprises that do not operate in accordance with the modern logistics methods may be displaced by competitors. If the railway does not improve its logistics infrastructure, logistics equipment, railway logistics network platform, etc., it will lose out to other modes of transport. In order to meet the needs of logistics and improve the market competitiveness, the main indicator of a freight station is loading and logistics flow. Therefore, exact prediction of future changes in the logistics flow of a freight station can help to determine whether the station needs to be upgraded as a railway station or transformed into a certain type of a logistics centre.

Police Oversight of Legality in Railway Freight Transport in Russian Empire During World War I

This article analyzes the activities of the gendarmerie railway police in ensuring compliance by freight carriers with prohibitions and restrictions on the export of certain raw materials and goods during World War I. Based on documentary materials, it reveals the content of the state policy of the Russian Empire regarding measures to halt the supply of essential resources to the Central Powers’ armies. The study of the administrative documentation of the railway police indicates that particular attention was paid to monitoring freight transport at border stations. The issue of police support for the stable functioning of railways under wartime conditions is explored. Gendarmerie officers facilitated the prioritization of military cargo movement along steel corridors. A critical responsibility of the gendarmerie was uncovering collusion among railway employees and shippers to manipulate train speeds for illicit speculative profit amid commodity shortages. The study concludes that the gendarmerie railway police played a significant role in overseeing the legality of freight transport during World War I. However, amid the disorganization of state mechanisms and deepening crises in Russian society, ensuring uninterrupted and effective railway operations proved impossible.

Quantifying the impact of rail longitudinal level changes on dynamic load magnitudes through instrumented wheelset measurements

Track geometry significantly influences train-track dynamic interactions, primarily due to irregularities at the wheel-rail interface. These irregularities generate dynamic load excitations, leading to defects and damage. This study evaluates how track surface profile longitudinal level vertical changes affect vertical wheel-to-rail loads, quantified by the dynamic load factor ( ϕ ), due to the importance of ϕ in track design. A limitation of the existing studies is their focus on instrumented sections and numerical modellings without considering different track structures. This study conducted dynamic load measurements using two instrumented wheelsets (IWS) over a 340 km section operated by a North American Class 1 freight railway in the Canadian Prairies under various track structures and train speeds. Rail surface longitudinal level measurements were obtained as routine measurements through a track geometry car. The paper presents statistical distributions of rail longitudinal level across different track structures and evaluates two widely used and recently developed ϕ equations within the context of North American freight railways to quantify the impact of rail longitudinal level (i.e. profile) changes on dynamic load magnitudes. The study also evaluates regulated threshold values by considering observed trends in the measured data, which aims to quantify and compare these values with our current understanding.

A BiFPN-SECA detection network for foreign objects on top of railway freight vehicles

A BiFPN-SECA detection network for foreign objects on top of railway freight vehicles

Research on interval prediction method of railway freight based on big data and TCN‐BiLSTM‐QR

AbstractWith the rapid development of logistics, the categories of goods and the frequencies of train transportation in railway freight have increased significantly. The volatility and uncertainty of railway freight transportation have become even greater. Accurately predicting railway freight volume in the medium to long term has become increasingly challenging. On the basis of traditional prediction models, this paper introduces the concepts of interval and probability prediction, and proposes a temporal convolutional network (TCN)‐bi‐directional long short‐term memory (BiLSTM) interval prediction method for medium and long‐term railway freight volume. The method uses grey relational analysis for data dimensionality reduction and feature extraction, and TCN, BiLSTM, and quantile regression for modelling. Through a case study of freight transportation on the Shuohuang Railway, the results show that the TCN‐BiLSTM model achieves higher accuracy in point prediction and better performance in interval prediction compared to other general prediction models. The interval prediction can provide references for freight volume fluctuations in periods with significant volatility, which can assist railway transportation companies in better scheduling and planning based on such information.

Design of railway simulation training system based on WebGL

Abstract In order to solve the problems of poor interaction with students and insufficient practicality in the previous railway freight station operation training, this article developed a training system based on WebGL technology that can interact with students and truly display the operation situation of the freight yard. This system is based on the Unity3D engine and WebGL technology. It imports 3D models to build large map scenes, and introduces functions such as cargo bundling and map roaming. The complete designed system is published to the Web through WebGL technology. After experimental analysis, the parking lot training system has solved the problems of poor practicality, little interaction, low efficiency, and narrow coverage in previous teaching. It has promoted the standardization and standardization of training students’ future work, and has effectively improved the professionalism of parking lot managers.

Risk incident analyses in the transportation of anhydrous ammonia as an emerging clean energy resource.

Anhydrous ammonia has seen a rapid increase in demand due to recent developments in clean energy technologies. As it is a potential carrier of hydrogen, the transportation industry is currently facing significant logistic challenges as well as safety risks. Based on the causes and effects, this study categorizes incident patterns based on the historical incidents from 1971 to 2021 in the United States during transportation. Analysis of temporal patterns revealed that government regulations and improvement of safety infrastructures have made the biggest impact on lowering incident rates. Spatial analysis methods are also applied to understand the relationships between these incidents and spatial factors, such as land area, number of ammonia production facilities, total average production capacity, and total length of freight railway and highway in each US state. The spatial and temporal patterns and interpretations provide safety references to manage the growing hazardous transport in clean energy.

Space–time collision avoidance and train dynamics constraints-driven optimal control for heterogeneous heavy-haul trains platoon operation considering air brake delay

The potential of heavy-haul train platoon operation technology in improving railway freight capacity is increasingly recognised, with extensive trial research currently underway. This study firstly utilising longitudinal train dynamics devised a space–time collaborative collision avoidance model for trainsets, accounting for air brake delay. Secondly, an air brake application strategy was proposed, focusing on collision avoidance and managing speeds on steep ramps. Subsequently, a constraint-driven optimal control scheme tailored for heavy-haul train platooning operations within an open railway environment was developed, which simulates train platooning amidst real-world dynamic traffic flow scenarios, offering a global perspective on railway network operations. Finally, we comprehensively evaluate the impact of line conditions on key platoon control parameters based on realistic railway operation scenarios. Findings show that constraint-driven optimal control, integrating train dynamics and space–time collaborative collision avoidance, effectively replicates the dynamic traits of train platoons. The consideration of air braking delays is crucial due to heterogeneous train formations and steep ramps, which can easily cause collisions. Moreover, on real-world railway lines, the average headway of heavy-haul trains weighing 10,000 tons and below can be compressed to 99.82 s when operating in platoons, significantly enhancing transportation capacity compared to existing semi-automatic blocking systems.

Fault diagnosis of railway freight car rolling bearings based on ACMD and improved MCKD

To address the issue of accurately extracting fault characteristic information of railway freight car bearings under noisy conditions, this paper proposes a fault diagnosis method based on Adaptive Chirp Mode Decomposition (ACMD) and an optimized Maximum Correlation Kurtosis Deconvolution (MCKD) using a Sparrow Search Algorithm Combining Sine-Cosine and Cauchy Mutation (SCSSA). Firstly, ACMD is used to decompose and reconstruct the original fault signal to obtain several Intrinsic Mode Functions (IMFs). Then, the IMFs are filtered according to the Gini coefficient indicator, with the IMF having the largest Gini coefficient selected as the optimal component. Secondly, the SCSSA is employed to iteratively optimize the filter length L, fault signal period T, and displacement parameter M in the MCKD algorithm, determining the optimal parameter combination for MCKD. This avoids the limitations of manual settings and enhances the accuracy of fault diagnosis. The optimized MCKD is then applied to the optimal component, and deconvolution is performed using maximum correlation kurtosis as the criterion to extract fault characteristic information through its envelope spectrum. To verify the effectiveness and generalizability of the proposed method, simulations, experimental signals from the Case Western Reserve University Bearing Center, and actual measured signals from railway freight car bearing 353130B are used to analyze inner ring faults. The experimental results demonstrate that the method can accurately extract fault characteristic information of railway freight car bearings under noise interference and identify the fault type.

Intermittent Electrification with Battery Locomotives and the Post-Diesel Future of North American Freight Railroads

Changing attitudes, regulations, public policy, and international treaties concerning fossil fuels are likely to lead freight railroads toward carbon-neutral technologies, yet only electric traction matches the performance of diesel-electric locomotives. The tremendous power requirements of freight trains make efforts to reduce greenhouse gas (GHG) emissions challenging, but the prospect of 7.2 megawatt-hour battery-electric locomotives (BELs) offers promise, and intermittent electrification can facilitate battery charging. Train performance calculations under simulated real-world conditions show four 7.2 megawatt-hour BELs can power 8,000-ton trains up to 230 mainline miles unassisted, with average energy consumption of 12.5 watt-hours/ton-mile. This permits discontinuous electrification of major freight lines, leaving “gaps” of up to 200 mi to reduce capital costs, especially in rugged terrain or where the power grid is sparse. Massive onboard battery arrays and intermittent access to the electrical grid for traction power and recharging provide great energy savings by recycling energy now lost when traveling downhill or braking. A case study of a hypothetical Class I railroad found intermittent electrification with BELs more than 60% more cost-effective than contiguous electric districts, and dramatically reduced engine changes. To reduce railroad GHG emissions, governments must support technical development, show that electrification works in various North American settings, and develop institutional-financial frameworks to incentivize intermittent electrification with BELs, all in the context of massive environmental and capacity upgrades to electrical networks. Given proper assistance and incentives, early 21st century railroads may find discontinuous overhead-wire electrification offers great promise in operating terms.

Dual-Model Derailment Detection Algorithm Based on Variational Bayesian Kalman Filtering.

A derailment detection algorithm for railway freight cars based on micro inertial measurement units was designed to address the complex issue of the disassembly and assembly of derailment braking devices. Firstly, a horizontal attitude measurement model for freight cars was established, and attitude measurement algorithms based on gyroscopes and accelerometers were introduced. Subsequently, a high-precision attitude measurement algorithm based on variational Bayesian Kalman filtering was proposed, which used acceleration information as the observation data to correct attitude errors. In order to improve the accuracy of derailment detection, a dual-model instantaneous attitude difference measurement technique was further proposed. In order to verify the effectiveness of the algorithm, offline data from simulation experiments and in-vehicle experiments were used to validate the proposed algorithm. The results showed that the proposed algorithm can effectively improve the measurement accuracy of horizontal attitude changes, reducing the error by 89% compared to pure inertial attitude calculation, laying a technical foundation for improving the accuracy of derailment detection.

Double marginalization in the pricing of complements: The case of US freight railroads

AbstractMonopolists selling complementary products charge a higher price in a static equilibrium than a single (multiproduct) monopolist would, reducing both the industry profits and consumer surplus. Firms could instead reach a Pareto improvement by lowering prices to the single‐monopolist level. We analyze pricing data of railroad coal shipping in the United States. We compare a coal producer that needs to ship from A to C, with the route passing through B, in two cases: (1) the same railroad owning AB and BC and (2) different railroads owning AB and BC. We do not find that the price in case (2) is higher than the price in case (1), suggesting that the complementary monopolist pricing inefficiency is absent in this market. Our findings are robust to propensity score blocking, causal machine learning algorithms, and difference‐in‐differences analysis. Our results have implications for vertical mergers, tragedy of the anticommons, mergers of firms selling complements, elimination of double marginalization, and royalty stacking and patent thickets.

Comparison of train noise and vibration measurements with U.S. Department of Transportation model predictions

Wayside noise and ground-borne vibration measurements of freight and light rail train operations were carried out in Denver, CO in support of the Burnham Yard Transportation Planning Study being pursued by the Colorado Department of Transportation (CDOT). This study was intended to evaluate various track layout alternatives for the Consolidated Main Line (CML) freight railroad alignment and enhancement of Regional Transportation District (RTD) light rail operations while maintaining options for Front Range Passenger Rail (FRPR) within Burnham Yard and the surrounding areas. The objective of the measurements was to compare measured train noise and vibration levels with predictions using models sanctioned by the U.S. Department of Transportation (USDOT) in order to validate the use of these models to assess the noise and vibration impacts of the project alternatives. The models included the Federal Railroad Administration (FRA) Chicago Rail Efficiency And Transportation Efficiency (CREATE) freight noise model, the FRA Horn Noise Model, and the models included in the Federal Transit Administration (FTA) Transit Noise and Vibration Impact Assessment Manual. Based on a comparison of measured and modeled results, it was concluded that the USDOT models could be used to assess noise and vibration from train operations in the Burnham Yard Study Area.

Fatigue behavior assessment of heavy-duty freight railway axles under different heat treatments

The safety of heavy-duty freight railway axles is threatened by defects, including inclusions, corrosion pits, fretting cracks and foreign object impact damages. Accordingly, surface strengthening techniques are applied to reduce the detrimental effect of defects on the structural integrity of railway axles. This work studied the effectiveness of heat treatment, in which the specimens machined from a heavy-duty freight railway axle were induction hardened under three types of processing parameters and tempered. The fatigue strengths of specimens with electrical discharge machined (EDM) notches and impact craters on their surfaces were tested. The fatigue behavior of induction-hardened (IH) specimens was compared with that of as-received (AR) specimens and fully-quenched (FH) specimens. The fatigue limit of smooth IH specimens is close to that of FH specimens while almost twice as much as that of AR specimens. Inclusions were found on the crack initiation sites on the surface or subsurface of AR and FH specimens. For IH specimens, the crack initiation sites moved to the zone between the case and the core. Fatigue strengths of IH and FH specimens decline with increasing EDM notch size but remain higher than AR specimens’. The influence of impact damage on fatigue properties depends on damage size and heat treatment process.

Analyzing Factors Influencing the Development of Railway Freight Transportation Service through the Fuzzy Analytic Hierarchy Process Technique

The main objective of this study is to apply the Fuzzy Analytic Hierarchy Process (FAHP) technique to assess factors influencing the development of railway freight transportation services. These factors include four critical performance indicators within the supply chain: responsiveness, cost, reliability, and agility. Moreover, the study aims to develop guidelines for enhancing the effectiveness of railway freight transportation in Chiang Rai province, particularly through the Den Chai–Chiang Rai–Chiang Khong railway route. Data were collected from 9 experts, including logistics service providers, users, and academics then, pairwise comparisons of factors were conducted. The results revealed that the cost factor holds the highest significance at 33.86%, followed by reliability, responsiveness, and agility factors at 28.51%, 26.14%, and 11.49%, respectively. Consistent with satisfaction scores obtained from logistics service users, the cost factor holds the highest satisfaction score at 4.78, followed by reliability, responsiveness, and agility factors with scores of 4.41, 4.16, and 4.01, respectively. The result above will bring towards preparation in railway freight transportation of Chiang Rai province and encouraging entrepreneurs to shift to railway transportation mode in the end.

Open set transfer learning for bearing defect recognition based on selective momentum contrast and dual adversarial structure

Data-driven rotating machinery fault diagnosis methods gradually enter people’s vision due to their fast and accuracy. However, in practical engineering applications, the unpredictability of machine failure modes and the appearance of new defect types can severely disrupt the diagnostic task with closed set defect recognition data-driven methods. Addressing this concern, this paper delves into the defect transfer diagnosis of rolling bearings in an open-set context and introduces the Momentum Contrastive Dual Adversarial (MCDA) domain adaptive method. This novel approach leverages instance-based difference comparison for unsupervised clustering and implements Negative Samples Selection Optimization (NSSO) via K Nearest Neighbor across all domains. It features intra-module adversarial learning for domain adaptation between source and target domains, and inter-module adversarial learning where encoders and feature extractors across different modules share weights. The methodology prioritizes the separation of private classes during the initial phase of contrastive learning, ensuring the isolation of target private classes. Concurrently, it aligns shared classes in the subsequent phase through semi-supervised training for domain adaptation. Our experiments on the Paderborn Dataset and Railway Freight Wheel-set Bearing (RFWB) Dataset demonstrate the effectiveness of this method.

Study on rolling contact fatigue crack initiation and propagation in U75V rail treated by laminar plasma

Surface discrete hardening by laminar plasma (HLP) enhances rail wear resistance by rapidly quenching surfaces to form discrete martensitic zones. In comparative field tests on a North China freight railway, HLP-treated U75V rails supported twice the total passing weight before reaching wear limits, compared to untreated rails. However, HLP treatment increases susceptibility to rolling contact fatigue (RCF) cracks, including interface cracks from mechanical differences, impact cracks from wheel-rail contact, deformation cracks from cumulative deformation, and matrix cracks extending from interfaces. The ratchet effect and seesaw mechanism, due to plastic deformation accumulation and quenching area warping, are crucial for crack initiation and propagation. This research advances understanding of HLP-treated rails' tribological behavior, emphasizing the necessity for customized maintenance strategies.