7 resultados para Intermodal Container Terminal, Rail Transportation, Delays, Simulation, Australia

em Digital Commons - Michigan Tech


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Recent changes in the cost and availability of natural gas (NG) as compared to diesel have sparked interest at all levels of the commercial shipping sector. In particular, Class 1 heavy-duty rail has been researching NG as a supplement to diesel combustion. This study investigates the relative economic and emissions advantage of making use of the energy efficiencies if combustion is circumvented altogether by use of fuel cell (FC) technologies applied to NG. FC technology for the transport sector has primarily been developed for the private automobile. However, FC use in the automobile sector faces considerable economic and logistical barriers such as cost, range, durability, and refueling infrastructure. The heavy-duty freight sector may be a more reasonable setting to introduce FC technology to the transportation market. The industry has shown interest in adopting NG as a potential fuel by already investing in NG infrastructure and locomotives. The two most promising FC technologies are proton exchange membrane fuel cells (PEMFCs) and solid oxide fuel cells (SOFCs). SOFCs are more efficient and capable of accepting any kind of fuel, which makes them particularly attractive. The rail industry can benefit from the adoption of FC technology through reduced costs and emissions, as well as limiting dependence on diesel, which accounts for a large portion of operation expenses for Class 1 railroads. This report provides an economic feasibility analysis comparing the use of PEMFCs and SOFCs in heavy freight rail transport applications. The scope is to provide insight into which technologies could be pursued by the industry and to prioritize technologies that need further development. Initial results do not show economic potential for NG and fuel cells in locomotion, but some minimal potential for reduced emissions is seen. Various technology configurations and market scenarios analyzed could provide savings if the price of LNG is decreased and the price of diesel increases. The most beneficial areas of needed research include technology development for the variable output of SOFCs, and hot start-up optimization.

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Demand for bio-fuels is expected to increase, due to rising prices of fossil fuels and concerns over greenhouse gas emissions and energy security. The overall cost of biomass energy generation is primarily related to biomass harvesting activity, transportation, and storage. With a commercial-scale cellulosic ethanol processing facility in Kinross Township of Chippewa County, Michigan about to be built, models including a simulation model and an optimization model have been developed to provide decision support for the facility. Both models track cost, emissions and energy consumption. While the optimization model provides guidance for a long-term strategic plan, the simulation model aims to present detailed output for specified operational scenarios over an annual period. Most importantly, the simulation model considers the uncertainty of spring break-up timing, i.e., seasonal road restrictions. Spring break-up timing is important because it will impact the feasibility of harvesting activity and the time duration of transportation restrictions, which significantly changes the availability of feedstock for the processing facility. This thesis focuses on the statistical model of spring break-up used in the simulation model. Spring break-up timing depends on various factors, including temperature, road conditions and soil type, as well as individual decision making processes at the county level. The spring break-up model, based on the historical spring break-up data from 27 counties over the period of 2002-2010, starts by specifying the probability distribution of a particular county’s spring break-up start day and end day, and then relates the spring break-up timing of the other counties in the harvesting zone to the first county. In order to estimate the dependence relationship between counties, regression analyses, including standard linear regression and reduced major axis regression, are conducted. Using realizations (scenarios) of spring break-up generated by the statistical spring breakup model, the simulation model is able to probabilistically evaluate different harvesting and transportation plans to help the bio-fuel facility select the most effective strategy. For early spring break-up, which usually indicates a longer than average break-up period, more log storage is required, total cost increases, and the probability of plant closure increases. The risk of plant closure may be partially offset through increased use of rail transportation, which is not subject to spring break-up restrictions. However, rail availability and rail yard storage may then become limiting factors in the supply chain. Rail use will impact total cost, energy consumption, system-wide CO2 emissions, and the reliability of providing feedstock to the bio-fuel processing facility.

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Shippers want to improve their transportation efficiency and rail transportation has the potential to provide an economical alternative to trucking, but it also has potential drawbacks. The pressure to optimize transportation supply chain logistics has resulted in growing interest in multimodal alternatives, such as a combination of truck and rail transportation, but the comparison of multimodal and modal alternatives can be complicated. Shippers in Michigan’s Upper Peninsula (UP) face similar challenges. Adding to the challenge is the distance from major markets and the absence of available facilities for transloading activities. This study reviewed three potential locations for a transload facility (Nestoria, Ishpeming, and Amasa) where truck shipments could be transferred to rail and vice versa. These locations were evaluated on the basis of transportation costs for shippers when compared to the use of single mode transportation by truck to Wisconsin, Chicago, Minneapolis, and Sault Ste. Marie. In addition to shipping costs, the study also evaluated the potential impact of future carbon emission penalties on the shipping cost and the effects of changing fuel prices on shipping cost. The study used data obtained from TRANSEARCH database (2009) and found that although there were slight differences between percent savings for the three locations, any of them could provide potential benefits for movements to Chicago and Minneapolis, as long as final destination could be accessed by rail for delivery. Short haul movements of less than 200 miles (Wisconsin and Sault Ste. Marie) were not cost effective for multimodal transport. The study also found that for every dollar increase in fuel price, cost savings from multimodal option increased by three to five percent, but the inclusion of emission costs would only add one to two percent additional savings. Under a specific case study that addressed shipments by Northern Hardwoods, the most distant locations in Wisconsin would also provide cost savings, partially due to the possibility of using Michigan trucks with higher carrying capacity for the initial movement from the facility to transload location. In addition, Minneapolis movements were found to provide savings for Northern Hardwoods, even without final rail access.

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The challenges posed by global climate change are motivating the investigation of strategies that can reduce the life cycle greenhouse gas (GHG) emissions of products and processes. While new construction materials and technologies have received significant attention, there has been limited emphasis on understanding how construction processes can be best managed to reduce GHG emissions. Unexpected disruptive events tend to adversely impact construction costs and delay project completion. They also tend to increase project GHG emissions. The objective of this paper is to investigate ways in which project GHG emissions can be reduced by appropriate management of disruptive events. First, an empirical analysis of construction data from a specific highway construction project is used to illustrate the impact of unexpected schedule delays in increasing project GHG emissions. Next, a simulation based methodology is described to assess the effectiveness of alternative project management strategies in reducing GHG emissions. The contribution of this paper is that it explicitly considers projects emissions, in addition to cost and project duration, in developing project management strategies. Practical application of the method discussed in this paper will help construction firms reduce their project emissions through strategic project management, and without significant investment in new technology. In effect, this paper lays the foundation for best practices in construction management that will optimize project cost and duration, while minimizing GHG emissions.

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To mitigate greenhouse gas (GHG) emissions and reduce U.S. dependence on imported oil, the United States (U.S.) is pursuing several options to create biofuels from renewable woody biomass (hereafter referred to as “biomass”). Because of the distributed nature of biomass feedstock, the cost and complexity of biomass recovery operations has significant challenges that hinder increased biomass utilization for energy production. To facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization and tapping unused forest residues, it is proposed to develop biofuel supply chain models based on optimization and simulation approaches. The biofuel supply chain is structured around four components: biofuel facility locations and sizes, biomass harvesting/forwarding, transportation, and storage. A Geographic Information System (GIS) based approach is proposed as a first step for selecting potential facility locations for biofuel production from forest biomass based on a set of evaluation criteria, such as accessibility to biomass, railway/road transportation network, water body and workforce. The development of optimization and simulation models is also proposed. The results of the models will be used to determine (1) the number, location, and size of the biofuel facilities, and (2) the amounts of biomass to be transported between the harvesting areas and the biofuel facilities over a 20-year timeframe. The multi-criteria objective is to minimize the weighted sum of the delivered feedstock cost, energy consumption, and GHG emissions simultaneously. Finally, a series of sensitivity analyses will be conducted to identify the sensitivity of the decisions, such as the optimal site selected for the biofuel facility, to changes in influential parameters, such as biomass availability and transportation fuel price. Intellectual Merit The proposed research will facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization in the renewable biofuel industry. The GIS-based facility location analysis considers a series of factors which have not been considered simultaneously in previous research. Location analysis is critical to the financial success of producing biofuel. The modeling of woody biomass supply chains using both optimization and simulation, combing with the GIS-based approach as a precursor, have not been done to date. The optimization and simulation models can help to ensure the economic and environmental viability and sustainability of the entire biofuel supply chain at both the strategic design level and the operational planning level. Broader Impacts The proposed models for biorefineries can be applied to other types of manufacturing or processing operations using biomass. This is because the biomass feedstock supply chain is similar, if not the same, for biorefineries, biomass fired or co-fired power plants, or torrefaction/pelletization operations. Additionally, the research results of this research will continue to be disseminated internationally through publications in journals, such as Biomass and Bioenergy, and Renewable Energy, and presentations at conferences, such as the 2011 Industrial Engineering Research Conference. For example, part of the research work related to biofuel facility identification has been published: Zhang, Johnson and Sutherland [2011] (see Appendix A). There will also be opportunities for the Michigan Tech campus community to learn about the research through the Sustainable Future Institute.

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The Michigan Department of Transportation is evaluating upgrading their portion of the Wolverine Line between Chicago and Detroit to accommodate high speed rail. This will entail upgrading the track to allow trains to run at speeds in excess of 110 miles per hour (mph). An important component of this upgrade will be to assess the requirement for ballast material for high speed rail. In the event that the existing ballast materials do not meet specifications for higher speed train, additional ballast will be required. The purpose of this study, therefore, is to investigate the current MDOT railroad ballast quality specifications and compare them to both the national and international specifications for use on high speed rail lines. The study found that while MDOT has quality specifications for railroad ballast it does not have any for high speed rail. In addition, the American Railway Engineering and Maintenance-of-Way Association (AREMA), while also having specifications for railroad ballast, does not have specific specifications for high speed rail lines. The AREMA aggregate specifications for ballast include the following tests: (1) LA Abrasion, (2) Percent Moisture Absorption, (3) Flat and Elongated Particles, (4) Sulfate Soundness test. Internationally, some countries do require a highly standard for high speed rail such as the Los Angeles (LA) Abrasion test, which is uses a higher standard performance and the Micro Duval test, which is used to determine the maximum speed that a high speed can operate at. Since there are no existing MDOT ballast specification for high speed rail, it is assumed that aggregate ballast specifications for the Wolverine Line will use the higher international specifications. The Wolverine line, however, is located in southern Michigan is a region of sedimentary rocks which generally do not meet the existing MDOT ballast specifications. The investigation found that there were only 12 quarries in the Michigan that meet the MDOT specification. Of these 12 quarries, six were igneous or metamorphic rock quarries, while six were carbonate quarries. Of the six carbonate quarries four were locate in the Lower Peninsula and two in the Upper Peninsula. Two of the carbonate quarries were located in near proximity to the Wolverine Line, while the remaining quarries were at a significant haulage distance. In either case, the cost of haulage becomes an important consideration. In this regard, four of the quarries were located with lake terminals allowing water transportation to down state ports. The Upper Peninsula also has a significant amount of metal based mining in both igneous and metamorphic rock that generate significant amount of waste rock that could be used as a ballast material. The main drawback, however, is the distance to the Wolverine rail line. One potential source is the Cliffs Natural Resources that operates two large surface mines in the Marquette area with rail and water transportation to both Lake Superior and Lake Michigan. Both mines mine rock with a very high compressive strength far in excess of most ballast materials used in the United States and would make an excellent ballast materials. Discussions with Cliffs, however, indicated that due to environmental concerns that they would most likely not be interested in producing a ballast material. In the United States carbonate aggregates, while used for ballast, many times don't meet the ballast specifications in addition to the problem of particle degradation that can lead to fouling and cementation issues. Thus, many carbonate aggregate quarries in close proximity to railroads are not used. Since Michigan has a significant amount of carbonate quarries, the research also investigated using the dynamic properties of aggregate as a possible additional test for aggregate ballast quality. The dynamic strength of a material can be assessed using a split Hopkinson Pressure Bar (SHPB). The SHPB has been traditionally used to assess the dynamic properties of metal but over the past 20 years it is now being used to assess the dynamic properties of brittle materials such as ceramics and rock. In addition, the wear properties of metals have been related to their dynamic properties. Wear or breakdown of railroad ballast materials is one of the main problems with ballast material due to the dynamic loading generated by trains and which will be significantly higher for high speed rails. Previous research has indicated that the Port Inland quarry along Lake Michigan in the Southern Upper Peninsula has significant dynamic properties that might make it potentially useable as an aggregate for high speed rail. The dynamic strength testing conducted in this research indicate that the Port Inland limestone in fact has a dynamic strength close to igneous rocks and much higher than other carbonate rocks in the Great Lakes region. It is recommended that further research be conducted to investigate the Port Inland limestone as a high speed ballast material.

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A range of societal issues have been caused by fossil fuel consumption in the transportation sector in the United States (U.S.), including health related air pollution, climate change, the dependence on imported oil, and other oil related national security concerns. Biofuels production from various lignocellulosic biomass types such as wood, forest residues, and agriculture residues have the potential to replace a substantial portion of the total fossil fuel consumption. This research focuses on locating biofuel facilities and designing the biofuel supply chain to minimize the overall cost. For this purpose an integrated methodology was proposed by combining the GIS technology with simulation and optimization modeling methods. The GIS based methodology was used as a precursor for selecting biofuel facility locations by employing a series of decision factors. The resulted candidate sites for biofuel production served as inputs for simulation and optimization modeling. As a precursor to simulation or optimization modeling, the GIS-based methodology was used to preselect potential biofuel facility locations for biofuel production from forest biomass. Candidate locations were selected based on a set of evaluation criteria, including: county boundaries, a railroad transportation network, a state/federal road transportation network, water body (rivers, lakes, etc.) dispersion, city and village dispersion, a population census, biomass production, and no co-location with co-fired power plants. The simulation and optimization models were built around key supply activities including biomass harvesting/forwarding, transportation and storage. The built onsite storage served for spring breakup period where road restrictions were in place and truck transportation on certain roads was limited. Both models were evaluated using multiple performance indicators, including cost (consisting of the delivered feedstock cost, and inventory holding cost), energy consumption, and GHG emissions. The impact of energy consumption and GHG emissions were expressed in monetary terms to keep consistent with cost. Compared with the optimization model, the simulation model represents a more dynamic look at a 20-year operation by considering the impacts associated with building inventory at the biorefinery to address the limited availability of biomass feedstock during the spring breakup period. The number of trucks required per day was estimated and the inventory level all year around was tracked. Through the exchange of information across different procedures (harvesting, transportation, and biomass feedstock processing procedures), a smooth flow of biomass from harvesting areas to a biofuel facility was implemented. The optimization model was developed to address issues related to locating multiple biofuel facilities simultaneously. The size of the potential biofuel facility is set up with an upper bound of 50 MGY and a lower bound of 30 MGY. The optimization model is a static, Mathematical Programming Language (MPL)-based application which allows for sensitivity analysis by changing inputs to evaluate different scenarios. It was found that annual biofuel demand and biomass availability impacts the optimal results of biofuel facility locations and sizes.