An analysis of intermodal transport carrier selection criteria for pacific-rim imports to New England

The introduction of double stack rail services opened up a variety of transportation options for shippers located in the North Eastern parts of the U.S. The availability of transcontinental double stack service from the Canadian West Coast has increased this option even further particularly because of a recent new service introduced by a small U.S. railroad company. The paper uses Analytical Hierarchy Process (AHP) methodology to provide a decision-making framework for the intermodal choices of shippers located in the region suitable for duplication elsewhere where similar options exist

Predicting the Remaining Service Life of Railroad Bearings: Leveraging Machine Learning and Onboard Sensor Data

By continuously monitoring train bearing health in terms of temperature and vibration levels of bearings tested in a laboratory setting, statistical regression models have been developed to establish relationships between the sensor-acquired bearing health data with several explanatory factors that potentially influence the bearing deterioration. Despite their merits, statistical models fall short of reliable prediction accuracy levels since they entail restrictive assumptions, such as a priori known functional relationship between the response and input variables. A data-driven machine learning algorithm is presented, which can unravel the nonlinear deterioration model purely based on the bearing health data, even when the structure is not apparent. More specifically, a Gradient Boosting Machine is trained using vast amounts of laboratory data collected over the course of over a decade. This will help predict bearing failure, thus, providing railroads and railcar owners the opportunity to schedule preventive maintenance cycles rather than costly reactive ones

Modelling Cross-Border Rail Intermodality in the Windsor-Essex Context

Shipment by truck dominates the cross-border flow of commodities in both directions between Canada and the United States (Anderson and Coates, 2010; Anderson, 2012; Anderson and Brown, 2012; and Aspila and Maoh, 2014). An individual truck typically pulling one or two trailers is an inefficient way to move goods over long distances (Eom et al., 2012) when freight trains with three or more 4400 horsepower diesel-electric locomotives pull over two-hundred intermodal containers loaded on rail cars throughout North America every day. Windsor, Ontario is an example of a border community in Canada and hosts the busiest border crossing between Canada and the United States. Crossings include two road, one rail and a sea port of entry (United States Department of Transportation – Bureau of Transportation Statistics, 2017). Presently the majority of cross-border import and export traffic is by road haulage. In addition to serving as a port of entry for goods being imported or exported between the two countries there is also a substantial local manufacturing base that consumes and produces goods on both sides of the border. There are several existing railroad border crossings including a rail tunnel between Windsor, Ontario and Detroit, Michigan. There must be a rational reason why commodities are shipped across the border using trucks and not rail. This dissertation research is proposed to answer the question of is rail viable for shipping commodities cross-border or as part of the cross-border supply chains? A network optimization model of Canada-US rail freight is developed to address this question. The model is first used to assess whether location of a conventional, large-scale intermodal facility in Windsor is viable. Results indicate that it is not. It is then applied to a scenario where innovative small-scale intermodal transfer facilities are located in Windsor and at other significant rail nodes in Ontario. Results indicate that this is a more viable strategy for increasing the rail share of cross-border freight movement

Assessing strategies for reducing carbon emissions associated with wood products transportation

Suite à la ratification par le Canada de traités de réduction des émissions de gaz à effets de serre (GES), différents paliers de gouvernement ont mis en œuvre des politiques visant la réduction des émissions industrielles et liées au transport. Depuis 2013, le Québec, conjointement avec la Californie et l’Ontario, ont mis en place un marché du carbone pour encourager les entreprises à réduire leurs émissions. L’industrie forestière, s’appuyant sur le transport de marchandises, pourrait bénéficier de ce régime en termes de prise de décision sur la planification du transport. Cette étude vise à analyser le potentiel des stratégies de réduction des émissions de carbone et à proposer des suggestions appropriées sur la prise de décision en matière de la planification du transport. Quatre stratégies sont principalement envisagées : la réduction de la vitesse, la conduite écologique, le transport intermodal et les modes de chargement. Combinant les stratégies, des modèles d'optimisation dont l'objectif est de minimiser des coûts sont développés sous les contraintes des émissions. Ces modèles impliquent la planification de la distribution de la gestion de la chaîne d'approvisionnement et des problèmes de tournées de véhicules. Microsoft Excel, OpenSolver, Gurobi et LocalSolver sont principalement utilisés pour la modélisation et l’optimisation. Un front de Pareto est par la suite utilisé pour illustrer la relation entre le coût de transport et les émissions de carbone. Pour démontrer les méthodologies, une étude de cas est présentée en utilisant des données réelles. Il est constaté que l'éco-conduite présente un potentiel de réduction des émissions intéressant dans une gamme réaliste d'augmentation des prix. Le choix des stratégies varie selon les préférences du décideur et la difficulté de mise en œuvre des stratégies.With the ratification of greenhouse gas (GHG) reduction agreements by Canada, various levels of government implemented policies to reduce transport-related and other industrial emissions. Since 2013, Québec, together with California and Ontario, has established a carbon market to encourage firms to reduce their emissions. The forest industry could benefit from this scheme in terms of improving efficiency and lessening the environmental impact of wood product transport. This study aims to assess the potential of carbon emission reduction strategies and to provide recommendations on improving the logistics of transporting wood-based materials. There are four main strategies considered in this paper; namely low-speed driving, eco-driving, intermodal transportation, and optimizing loading pattern. By combining these strategies, optimization models are developed with the objective of cost minimization under the constraints of emissions. These models involve the distribution planning of supply chain management and routing problems. Microsoft Excel, OpenSolver, Gurobi, and LocalSolver are mainly used for modeling and optimization. Pareto Front is also used to illustrate the relationship between transportation cost and carbon emission. To demonstrate the methodologies, a case study is exhibited using real world data. It is found that eco-driving has considerable potential in reducing emissions under a feasible range of price increases. The selection of strategies is based on the decision makers’ preferences and the difficulty of strategy implementation

Factors affecting commuter rail energy efficiency and its comparison with competing passenger transportation modes

As concerns about the environmental impacts and sustainability of the transportation sector continue to grow, modal energy efficiency is a factor of increasing importance when evaluating benefits and costs of transportation systems and justifying future investment. Poor assumptions on the efficiency of the system can alter the economics of investment in commuter rail. This creates a need to understand the factors affecting commuter rail energy efficiency and the comparison to competing passenger transportation modes to aid operators and decision makers in the development of new commuter rail lines and the improvement of existing services. This thesis describes analyses to further understand the factors affecting the current energy efficiency of commuter rail systems, how their efficiency may be improved through implementation of various technologies, and how their efficiency compares to competing modes of passenger transportation. After reviewing the literature, it was evident that past studies often conducted energy efficiency analyses and modal comparisons using methods that favored one energy source or competing mode by neglecting losses in the system. Therefore, four methods of energy efficiency analysis were identified and applied to 25 commuter rail systems in the United States using data from the National Transit Database (NTD). Using the same database, an analysis of trends in energy efficiency exhibited by the United States commuter rail systems was conducted. To understand the effects of congestion, traffic heterogeneity, operational parameters, and infrastructure characteristics on energy efficiency of passenger trains, single and multi-variable analyses were conducted. Simulations in Rail Traffic Controller (RTC) provided energy consumption results that were used in the statistical analyses. The results illustrated the effects of congestion due to increased freight and passenger traffic on a single-track freight-owned railroad. The effect of alternative scheduling patterns on energy intensity was analyzed through a case study of operations on one existing commuter rail line. Using the Multimodal Passenger Simulation Tool (MMPASSIM), the energy consumption of the current operations and proposed schedules of local, zonal, skip-stop and express train stopping patterns during a weekday peak period were simulated. A trade-off between improved passenger service through reduced travel times and energy consumption was evident in the results. MMPASSIM was also used to simulate the effects of technologies and strategies to increase energy efficiency and improve service levels. Changes such as electrification, driver advisory systems, equipment modifications, and slow zone reductions were evaluated for their effect on energy efficiency and service metrics. Finally, MMPASSIM was used to compare the energy intensity of the same commuter rail service to competing modes of passenger transportation for equivalent commuter trips. The rail service was evaluated under local, zonal, and skip-stop patterns and compared to automobile and bus trips under off-peak and peak highway congestion levels. Load factor sensitivity charts were developed, showing lines of equal energy intensity of rail and competing modes across a range of modal load factors

An Examination of Railroad Capacity and its Implications for Rail-Highway Intermodal Transportation

After many years of decline in market share, railroads are now experiencing an increasing demand for their services. Service intensive intermodal transportation seems to be an especially promising market area. Since the historic decline in traffic has been accompanied by a reduction in network infrastructure, however, the railroads\u27 ability to handle sizable traffic increases, at least in the short term, is in question. Since rail transportation is critical to the domestic economy of the nation, and is increasingly important in international logistics channels, shortfalls in railroad capacity are not desirable. The published literature on railroad capacity is relatively sparse, especially in comparison to the highway mode. Much of what is available pertains to individual network components such as lines or terminals. Evaluation of system capacity, considering the interactive effects of traffic flowing through a network of lines and terminals, has received less attention. A tool specifically designed for evaluating freight railroad system capacity issues could be a useful addition to the rail analyst\u27s toolbox. The research conducted in this study resulted in the formulation and application of RAILNET, a multicomrnodity, multicarrier network model for predicting equilibrium flows within a railroad network. Designed for strategic planning with a short term horizon, the model assumes fixed external demand. The predicted flows meet the conditions for Wardropian system equilibrium. At completion, the solution algorithm predicts the expected delay per train on each link, allowing the analyst to identify areas of congestion. Following completion of the model, it was applied to a case study examining the railroad network in the southeastern U.S. The public use version of the Interstate Commerce Commission\u27s Commodity Waybill Sample (CWS) provided flow data. The dissertation describes the procedure used to develop the case study and presents some results. The case points to major deficiencies in the CWS data which resulted in substantially less traffic in the network than is actually present. In general, given this limitation, the model behaved well and results appear reasonable, although not necessarily reflective of actual network conditions

Capacity optimization of a prestressed concrete railroad tie

Today the use of concrete ties is on the rise in North America as they become an economically competitive alternative to the historical industry standard wood ties, while providing performance which exceeds its competition in terms of durability and capacity. Similarly, in response to rising energy costs, there is increased demand for efficient and sustainable transportation of people and goods. One source of such transportation is the railroad. To accommodate the increased demand, railroads are constructing new track and upgrading existing track. This update to the track system will increase its capacity while making it a more reliable means of transportation compared to other alternatives. In addition to increasing the track system capacity, railroads are considering an increase in the size of the typical freight rail car to allow larger tonnage. An increase in rail car loads will in turn affect the performance requirements of the track. Due to the increased loads heavy haul railroads are considering applying to their tracks, current designs of prestressed concrete railroad ties for heavy haul applications may be undersized. In an effort to maximize tie capacity while maintaining tie geometry, fastening systems and installation equipment, a parametric study to optimize the existing designs was completed. The optimization focused on maximizing the capacity of an existing tie design through an investigation of prestressing quantity, configuration, stress levels and other material properties. The results of the parametric optimization indicate that the capacity of an existing tie can be increased most efficiently by increasing the diameter of the prestressing and concrete strength. However, researchers also found that current design specifications and procedures do not include consideration of tie behavior beyond the current tie capacity limit of cracking to the first layer of prestressing. In addition to limiting analysis to the cracking limit, failure mechanisms such as shear in deep beams at the rail seat or pullout failure of the prestressing due to lack of development length were absent from specified design procedures, but discussed in this project

Fuels and Fuel Technologies for Powering 21st Century Passenger and Freight Rail: Simulation-Based Case Studies in a U.S. Context

The last century brought a shift in rail propulsion from the (typically) coal-powered steam engine to a combination of the diesel-electric locomotive and the electrified locomotive running under electrified overhead lines. While, no doubt, an advance over the earlier technology, the two incumbent technologies are not without their shortcomings. In the current era, rapid technological developments and increased concerns about climate change have also spurred interest away from the internal combustion engine and the use of fossil fuels in various applications. These same technologies hold promise in a rail context, a mode of transportation that relies on a smaller number of more centralized operators. With the tremendous investment of time, cost, and other resources that can go into a pilot experiment of a fuel technology and, often, related regulatory processes, it makes sense to determine the key candidates for such pilots. A major goal of this work is to help industry and government narrow down the key technologies, in terms of cost, viability, and environmental impacts, and simultaneously identify the challenges that may be encountered by a given technology that otherwise appears to hold significant promise. This study focuses on a U.S. context, and on the period between 2022 and 2038. Passenger and freight rail routes and systems were examined, each with different characteristics, via simulations of a single rail trip, A general environmental analysis was also performed on freight switcher locomotive activity. The fuels examined included diesel, natural gas, Fischer-Tropsch diesel, hydrogen, and, in a passenger rail and switcher context, diesel and hydrogen powertrains paired with batteries to take in regenerative braking energy. The study finds cost reductions with both natural gas and (natural gas-derived) Fischer-Tropsch diesel, but with limited environmental benefits. Hydrogen via fuel cell has significant promise to reduce GHG and criteria pollutant emissions. That technology\u2019s costs, both fuel and equipment, are highly uncertain; however, the study finds that, with lower bound projected costs, it could be competitive with diesel-electric costs; in the case of passenger rail, hybridization with batteries is also compelling. Hybridized hydrogen also was found to demonstrate a clear environmental benefit in switcher locomotive applications