Development of an optimization model for biofuel facility size and location and a simulation model for design of a biofuel supply chain

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.

EVALUATING INFRASTRUCTURE PERFORMANCE TO ASSIST FACILITY MANAGEMENT TOWARD SUSTAINABLE SYSTEMS

Civil infrastructure provides essential services for the development of both society and economy. It is very important to manage systems efficiently to ensure sound performance. However, there are challenges in information extraction from available data, which also necessitates the establishment of methodologies and frameworks to assist stakeholders in the decision making process. This research proposes methodologies to evaluate systems performance by maximizing the use of available information, in an effort to build and maintain sustainable systems. Under the guidance of problem formulation from a holistic view proposed by Mukherjee and Muga, this research specifically investigates problem solving methods that measure and analyze metrics to support decision making. Failures are inevitable in system management. A methodology is developed to describe arrival pattern of failures in order to assist engineers in failure rescues and budget prioritization especially when funding is limited. It reveals that blockage arrivals are not totally random. Smaller meaningful subsets show good random behavior. Additional overtime failure rate is analyzed by applying existing reliability models and non-parametric approaches. A scheme is further proposed to depict rates over the lifetime of a given facility system. Further analysis of sub-data sets is also performed with the discussion of context reduction. Infrastructure condition is another important indicator of systems performance. The challenges in predicting facility condition are the transition probability estimates and model sensitivity analysis. Methods are proposed to estimate transition probabilities by investigating long term behavior of the model and the relationship between transition rates and probabilities. To integrate heterogeneities, model sensitivity is performed for the application of non-homogeneous Markov chains model. Scenarios are investigated by assuming transition probabilities follow a Weibull regressed function and fall within an interval estimate. For each scenario, multiple cases are simulated using a Monte Carlo simulation. Results show that variations on the outputs are sensitive to the probability regression. While for the interval estimate, outputs have similar variations to the inputs. Life cycle cost analysis and life cycle assessment of a sewer system are performed comparing three different pipe types, which are reinforced concrete pipe (RCP) and non-reinforced concrete pipe (NRCP), and vitrified clay pipe (VCP). Life cycle cost analysis is performed for material extraction, construction and rehabilitation phases. In the rehabilitation phase, Markov chains model is applied in the support of rehabilitation strategy. In the life cycle assessment, the Economic Input-Output Life Cycle Assessment (EIO-LCA) tools are used in estimating environmental emissions for all three phases. Emissions are then compared quantitatively among alternatives to support decision making.

DEVELOPMENT OF AN OPTIMIZATION MODEL FOR BIOFUEL FACILITY SIZE AND LOCATION AND A SIMULATION MODEL FOR DESIGN OF A BIOFUEL SUPPLY CHAIN

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.

SIZE OPTIMIZATION OF A BIOMASS TO LIQUID FUEL CONVERSION FACILITY WITHIN A BIOMASS SUPPLY CHAIN

Bioenergy and biobased products offer new opportunities for strengthening rural economies, enhancing environmental health, and providing a secure energy future. Realizing these benefits will require the development of many different biobased products and biobased production systems. The biomass feedstocks that will enable such development must be sustainable, widely available across many different regions, and compatible with industry requirements. The purpose of this research is to develop an economic model that will help decision makers identify the optimal size of a forest resource based biofuel production facility. The model must be applicable to decision makers anywhere, though the modeled case analysis will focus on a specific region; the Upper Peninsula (U.P.) of Michigan. This work will illustrate that several factors influence the optimal facility size. Further, this effort will reveal that the location of the facility does affect size. The results of the research show that an optimal facility size can be determined for a given location and are based on variables including forest biomass availability, transportation cost rate, and economy of scale factors. These variables acting alone and interacting together can influence the optimal size and the decision of where to locate the biofuel production facility. Further, adjustments to model variables like biomass resource and storage costs have no effect on facility size, but do affect the unit cost of the biofuel produced.

EVALUATION OF POTENTIAL TRANSLOAD FACILITY LOCATIONS IN THE UPPER PENINSULA (UP) OF MICHIGAN

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.

Quincy and Torch Lake Railroad engine house facility management and interpretive plan

The “Quincy & Torch Lake Railroad Engine House Facility Management and Interpretive Plan" was designed to serve as a guide to aid the Quincy Mine Hoist Association in their efforts to restore and interpret historic railroad resources under their stewardship. Early searches for existing management and interpretive plans demonstrated that similar plans were primarily produced by the National Park Service and were intended to guide large scale heritage sites that consist of a variety of cultural resources. This project adapts concepts found in those large scale management and interpretive site plans, to guide small scale site management, restoration, and interpretive projects. The document presents a three stage, second phase restoration process. Each stage of development is guided by a series of management and interpretive goals and objectives which were set for the engine house facility.