Search

A nuclear fuel cycle systems modeling and code-to-code comparison effort was coordinated across multiple national laboratories to verify the tools needed to perform fuel cycle analyses of the transition from a once-through nuclear fuel cycle to a sustainable potential future fuel cycle. For this verification study, a simplified example transition scenario was developed to serve as a test case for the four systems codes involved (DYMOND, VISION, ORION, and MARKAL), each used by a different laboratory participant. In addition, all participants produced spreadsheet solutions for the test case to check all the mass flows and reactor/facility profiles on a year-by-year basis throughout the simulation period. The test case specifications describe a transition from the current US fleet of light water reactors to a future fleet of sodium-cooled fast reactors that continuously recycle transuranic elements as fuel. After several initial coordinated modeling and calculation attempts, it was revealed that most of the differences in code results were not due to different code algorithms or calculation approaches, but due to different interpretations of the input specifications among the analysts. Therefore, the specifications for the test case itself were iteratively updated to remove ambiguity and to help calibrate interpretations. In addition, a fewmore » corrections and modifications were made to the codes as well, which led to excellent agreement between all codes and spreadsheets for this test case. Although no fuel cycle transition analysis codes matched the spreadsheet results exactly, all remaining differences in the results were due to fundamental differences in code structure and/or were thoroughly explained. As a result, the specifications and example results are provided so that they can be used to verify additional codes in the future for such fuel cycle transition scenarios.« less

In this paper we propose a multi-objective, mixed integer linear programming model to design and manage the supply chain for biofuels. This model captures the trade-offs that exist between costs, environmental and social impacts of delivering biofuels. The in-bound supply chain for biofuel plants relies on a hub-and-spoke structure which optimizes transportation costs of biomass. The model proposed optimizes the $$\hbox {CO}_{2}$$ emissions due to transportation-related activities in the supply chain. The model also optimizes the social impact of biofuels. The social impacts are evaluated by the number of jobs created. The multi-objective optimization model is solved using an augmented $$\epsilon $$ -constraint method. The method provides a set of Pareto optimal solutions. We develop a case study using data from the Midwest region of the USA. The numerical analyses estimates the quantity and cost of cellulosic ethanol delivered under different scenarios generated. The insights we provide will help policy makers design policies which encourage and support renewable energy production.

Decentralized biomass processing facilities, known as biomass depots, may be necessary to achieve feedstock cost, quantity, and quality required to grow the future U.S. bioeconomy. In this paper, we assess three distinct depot configurations for technical difference and economic performance. The depot designs were chosen to compare and contrast a suite of capabilities that a depot could perform ranging from conventional pelleting to sophisticated pretreatment technologies. Our economic analyses indicate that depot processing costs are likely to range from ∼US$30 to US$63 per dry metric tonne (Mg), depending upon the specific technology implemented and the energy consumption for processing equipment such as grinders and dryers. We conclude that the benefits of integrating depots into the overall biomass feedstock supply chain will outweigh depot processing costs and that incorporation of this technology should be aggressively pursued.

Pioneer cellulosic biorefineries across the United States rely on a conventional feedstock supply system based on one-year contracts with local growers, who harvest, locally store, and deliver feedstock in low-density format to the conversion facility. While the conventional system is designed for high biomass yield areas, pilot scale operations have experienced feedstock supply shortages and price volatilities due to reduced harvests and competition from other industries. Regional supply dependency and the inability to actively manage feedstock stability and quality, provide operational risks to the biorefinery, which translate into higher investment risk. The advanced feedstock supply system based on a network of depots can mitigate many of these risks and enable wider supply system benefits. This paper compares the two concepts from a system-level perspective beyond mere logistic costs. It shows that while processing operations at the depot increase feedstock supply costs initially, they enable wider system benefits including supply risk reduction (leading to lower interest rates on loans), industry scale-up, conversion yield improvements, and reduced handling equipment and storage costs at the biorefinery. When translating these benefits into cost reductions per liter of gasoline equivalent (LGE), we find that total cost reductions between –$0.46 to –$0.21 per LGE for biochemical and –$0.32 to –$0.12 per LGE for thermochemical conversion pathways are possible. Naturally, these system level benefits will differ between individual actors along the feedstock supply chain. Further research is required with respect to depot sizing, location, and ownership structures. Published 2015. This article is a U.S. Government work and is in the public domain in the USA. Biofuels, Bioproducts and Biorefining published by Society of Industrial Chemistry and John Wiley & Sons Ltd.

This article analyzes rail transportation costs of products that have similar physical properties as densified biomass and biofuel. The results of this cost analysis are useful to understand the relationship and quantify the impact of a number of factors on rail transportation costs of denisfied biomass and biofuel. These results will be beneficial and help evaluate the economic feasibility of high-volume and long-haul transportation of biomass and biofuel. High-volume and long-haul rail transportation of biomass is a viable transportation option for biofuel plants, and for coal plants which consider biomass co-firing. Using rail optimizes costs, and optimizes greenhouse gas (GHG) emissions due to transportation. Increasing bioenergy production would consequently result in lower GHG emissions due to displacing fossil fuels. To estimate rail transportation costs we use the carload waybill data, provided by Department of Transportation’s Surface Transportation Board for products such as grain and liquid type commodities for 2009 and 2011. We used regression analysis to quantify the relationship between variable transportation unit cost ($/ton) and car type, shipment size, rail movement type, commodity type, etc. The results indicate that: (a) transportation costs for liquid is $2.26/ton–$5.45/ton higher than grain type commodity; (b) transportation costs in 2011 were $1.68/ton–$5.59/ton higher than 2009; (c) transportation costs for single car shipments are $3.6/ton–$6.68/ton higher than transportation costs for multiple car shipments of grains; (d) transportation costs for multiple car shipments are $8.9/ton and $17.15/ton higher than transportation costs for unit train shipments of grains.

The 2011 US Billion-Ton Update estimates that by 2030 there will be enough agricultural and forest resources to sustainably provide at least one billion dry tons of biomass annually, enough to displace approximately 30% of the country's current petroleum consumption. A portion of these resources are inaccessible at current cost targets with conventional feedstock supply systems because of their remoteness or low yields. Reliable analyses and projections of US biofuels production depend on assumptions about the supply system and biorefinery capacity, which, in turn, depend upon economic value, feedstock logistics, and sustainability. A cross-functional team has examined combinations of advances in feedstock supply systems and biorefinery capacities with rigorous design information, improved crop yield and agronomic practices, and improved estimates of sustainable biomass availability. A previous report on biochemical refinery capacity noted that under advanced feedstock logistic supply systems that include depots and pre-processing operations there are cost advantages that support larger biorefineries up to 10 000 DMT/day facilities compared to the smaller 2000 DMT/day facilities. This report focuses on analyzing conventional versus advanced depot biomass supply systems for a thermochemical conversion and refinery sizing based on woody biomass. The results of this analysis demonstrate that the economies of scalemore » enabled by advanced logistics offsets much of the added logistics costs from additional depot processing and transportation, resulting in a small overall increase to the minimum ethanol selling price compared to the conventional logistic supply system. While the overall costs do increase slightly for the advanced logistic supply systems, the ability to mitigate moisture and ash in the system will improve the storage and conversion processes. In addition, being able to draw on feedstocks from further distances will decrease the risk of biomass supply to the conversion facility.« less

The 2011 US Billion-Ton Update1 estimates that there are enough agricultural and forest resources to sustainably provide enough biomass to displace approximately 30% of the country's current petroleum consumption. A portion of these resources are inaccessible at current cost targets with conventional feedstock supply systems because of their remoteness or low yields. Reliable analyses and projections of US biofuels production depend on assumptions about the supply system and biorefinery capacity, which, in turn, depend on economics, feedstock logistics, and sustainability. A cross-functional team has examined optimal combinations of advances in feedstock supply systems and biorefinery capacities with rigorous design information, improved crop yield and agronomic practices, and improved estimates of sustainable biomass availability. Biochemical-conversion-to-ethanol is analyzed for conventional bale-based system and advanced uniform-format feedstock supply system designs. The latter involves ‘pre-processing’ biomass into a higher-density, aerobically stable, easily transportable format that can supply large-scale biorefineries. Feedstock supply costs, logistics and processing costs are analyzed and compared, taking into account environmental sustainability metrics. © 2013 Society of Chemical Industry and John Wiley & Sons Ltd

If advanced fuel cycles are to include a large number of fast reactors (FRs), what should be the transuranic (TRU) conversion ratio (CR)? The nuclear energy era started with the assumption that they should be breeder reactors (CR > 1), but the full range of possible CRs eventually received attention. For example, during the recent U.S. Global Nuclear Energy Partnership program, the proposal was burner reactors (CR < 1). Yet, more recently, Massachusetts Institute of Technology's "Future of the Nuclear Fuel Cycle" proposed CR [approximately] 1. Meanwhile, the French company EDF remains focused on breeders. At least one of the reasons for the differences of approach is different fuel cycle objectives. To clarify matters, this paper analyzes the impact of TRU CR on many parameters relevant to fuel cycle systems and therefore spans a broad range of topic areas. The analyses are based on a FR physics parameter scan of TRU CR from 0 to [approximately]1.8 in a sodium-cooled metal-fueled FR (SMFR), in which the fuel from uranium-oxide-fueled light water reactors (LWRs) is recycled directly to FRs and FRs displace LWRs in the fleet. In this instance, the FRs are sodium cooled and metal fueled. Generally, it is assumed thatmore » all TRU elements are recycled, which maximizes uranium ore utilization for a given TRU CR and waste radiotoxicity reduction and is consistent with the assumption of used metal fuel separated by electrochemical means. In these analyses, the fuel burnup was constrained by imposing a neutron fluence limit to fuel cladding to the same constant value. This paper first presents static, time-independent measures of performance for the LWR [right arrow] FR fuel cycle, including mass, heat, gamma emission, radiotoxicity, and the two figures of merit for materials for weapon attractiveness developed by C. Bathke et al. No new fuel cycle will achieve a static equilibrium in the foreseeable future. Therefore, additional analyses are shown with dynamic, time-dependent measures of performance including uranium usage, TRU inventory, and radiotoxicity to evaluate the complex impacts of transition from the current uranium-fueled LWR system, and other more realistic impacts that may not be intuited from the time-independent steady-state conditions of the end-state fuel cycle. These analyses were performed using the Verifiable Fuel Cycle Simulation Model VISION. Compared with static calculations, dynamic results paint a different picture of option space and the urgency of starting a FR fleet. For example, in a static analysis, there is a sharp increase in uranium utilization as CR exceeds 1.0 (burner versus breeder). However, in dynamic analyses that examine uranium use over the next 1 to 2 centuries, behavior as CR crosses the 1.0 threshold is smooth, and other parameters such as the time required outside of reactors to recycle fuel become important. Overall, we find that there is no unambiguously superior value of TRU CR; preferences depend on the relative importance of different fuel cycle system objectives.« less

This perspective provides an overview of wood pellet markets in a number of countries of high significance, together with an inventory of market factors and relevant past or existing policies. In 2010, the estimated global wood pellet production and consumption were close to 14.3 Mt (million metric tonnes) and 13.5 Mt, respectively, while the global installed production capacity had reached over 28 Mt. Two types of pellets are mainly traded (i) for residential heating and (ii) for large-scale district heating or co-firing installations. The EU was the primary market, responsible for nearly 61% and 85% of global production and consumption, respectively in 2010. EU markets were divided according to end use: (i) residential and district heating, (ii) power plants driven market, (iii) mixed market, and (iv) export-driven countries. North America basically serves as an exporter, but also with significant domestic consumption in USA. East Asia is predicted to become the second-largest consumer after the EU in the near future. The development perspective in Latin America remains unclear. Five factors that determine the market characteristics are: (i) the existence of coal-based power plants, (ii) the development of heating systems, (iii) feedstock availability, (iv) interactions with wood industry, and (v) logistics factor. Furthermore, intervention policies play a pivotal role in market development. The perspective of wood pellets industry was also analyzed from four major aspects: (i) supply potential, (ii) logistics issues, (iii) sustainability considerations, and (iv) technology development. © 2013 Society of Chemical Industry and John Wiley & Sons, Ltd

Biomass is increasingly being considered as a feedstock to provide a clean and renewable source of energy in the form of both liquid fuels and electric power. In the United States, the biofuels and biopower industries are regulated by different policies and have different drivers, which impact the maximum price the industries are willing to pay for biomass. This article describes a dynamic computer simulation model that analyzes future behavior of bioenergy feedstock markets given policy and technical options. The model simulates the long-term dynamics of these markets by treating advanced biomass feedstocks as a commodity and projecting the total demand of each industry, as well as the market price over time. The model is used for an analysis of the United States bioenergy feedstock market that projects supply, demand, and market price given three independent buyers: domestic biopower, domestic biofuels, and foreign exports. With base-case assumptions, the biofuels industry is able to dominate the market and meet the federal Renewable Fuel Standard (RFS) targets for advanced biofuels. Further analyses suggest that United States bioenergy studies should include estimates of export demand in their projections, and that GHG-limiting policy would partially shield both industries from export dominance.

The nuclear fuel cycle consists of a set of complex components that are intended to work together. To support the nuclear renaissance, it is necessary to understand the impacts of changes and timin...

Abating the dependence of the United States on foreign oil by reducing oil consumption and increasing biofuels usage will have far-reaching global effects. These include reduced greenhouse gas emissions and an increased demand for biofuel feedstocks. To support this increased demand, cellulosic feedstock production and conversion to biofuels (e.g. ethanol, butanol) is being aggressively researched. Thus far, research has primarily focused on optimizing feedstock production and ethanol conversion, with less attention given to the feedstock supply chain required to meet cost, quality, and quantity goals. This supply chain comprises a series of unit operations from feedstock harvest to feeding the conversion process. Our objectives in this review are (i) to summarize the peer-reviewed literature on harvest-to-reactor throat variables affecting feedstock composition and conversion to ethanol; (ii) to identify knowledge gaps; and (iii) to recommend future steps.

A review of existing nuclear fuel cycle systems analysis codes was performed to determine if any existing codes meet technical and functional requirements defined for a U.S. national program supporting the global and domestic assessment, development and deployment of nuclear energy systems. The program would be implemented using an interconnected architecture of different codes ranging from the fuel cycle analysis code, which is the subject of the review, to fundamental physical and mechanistic codes. Four main functions are defined for the code: (1) the ability to characterize and deploy individual fuel cycle facilities and reactors in a simulation, while discretely tracking material movements, (2) the capability to perform an uncertainty analysis for each element of the fuel cycle and an aggregate uncertainty analysis, (3) the inclusion of an optimization engine able to optimize simultaneously across multiple objective functions, and (4) open and accessible code software and documentation to aid in collaboration between multiple entities and facilitate software updates. Existing codes, categorized as annualized or discrete fuel tracking codes, were assessed according to the four functions and associated requirements. These codes were developed by various government, education and industrial entities to fulfill particular needs. In some cases, decisions were made duringmore » code development to limit the level of detail included in a code to ease its use or to focus on certain aspects of a fuel cycle to address specific questions. The review revealed that while no two of the codes are identical, they all perform many of the same basic functions. No code was able to perform defined function 2 or several requirements of functions 1 and 3. Based on this review, it was concluded that the functions and requirements will be met only with development of a new code, referred to as GENIUS.« less

This paper analyzes the rural Chinese biomass supply system and models supply chain operations according to U.S. concepts of logistical unit operations: harvest and collection, storage, transportation, preprocessing, and handling and queuing. In this paper, we quantify the logistics cost of corn stover and sweet sorghum in China under different scenarios. We analyze three scenarios of corn stover logistics from northeast China and three scenarios of sweet sorghum stalks logistics from Inner Mongolia in China. The case study estimates that the logistics cost of corn stover and sweet sorghum stalk to be $52.95/dry metric ton and $52.64/dry metric ton, respectively, for the current labor-based biomass logistics system. However, if the feedstock logistics operation is mechanized, the cost of corn stover and sweet sorghum stalk decreases to $36.01/dry metric ton and $35.76/dry metric ton, respectively. The study also includes a sensitivity analysis to identify the cost factors that cause logistics cost variation. Results of the sensitivity analysis show that labor price has the most influence on the logistics cost of corn stover and sweet sorghum stalk, with a variation of $6 to $12/dry metric ton.

Logistical barrier are tied to feedstock harvesting, collection, storage and distribution. Current crop harvesting machinery is unable to selectively harvest preferred components of cellulosic biomass while maintaining acceptable levels of soil carbon and minimizing erosion. Actively managing biomass variability imposes additional functional requirements on biomass harvesting equipment. A physiological variation in biomass arises from differences in genetics, degree of crop maturity, geographical location, climatic events, and harvest methods. This variability presents significant cost and performance risks for bioenergy systems. Currently, processing standards and specifications for cellulosic feedstocks are not as well-developed as for mature commodities. Biomass that is stored with high moisture content or exposed to moisture during storage is susceptible to spoilage, rotting, spontaneous combustion, and odor problems. Appropriate storage methods and strategies are needed to better define storage requirements to preserve the volume and quality of harvested biomass over time and maintain its conversion yield. Raw herbaceous biomass is costly to collect, handle, and transport because of its low density and fibrous nature. Existing conventional, bale-based handling equipment and facilities cannot cost-effectively deliver and store high volumes of biomass, even with improved handling techniques. Current handling and transportation systems designed for moving woodchips can be inefficient for bioenergy more » processes due to the costs and challenges of transporting, storing, and drying high-moisture biomass. The infrastructure for feedstock logistics has not been defined for the potential variety of locations, climates, feedstocks, storage methods, processing alternatives, etc., which will occur at a national scale. When setting up biomass fuel supply chains, for large-scale biomass systems, logistics are a pivotal part in the system. Various studies have shown that long-distance international transport by ship is feasible in terms of energy use and transportation costs, but availability of suitable vessels and meteorological conditions (e.g., winter time in Scandinavia and Russia) need to be considered. However, local transportation by truck (both in biomass exporting and importing countries) may be a high-cost factor, which can influence the overall energy balance and total biomass costs. « less

The U.S. Department of Energy is scheduled to design and install hundreds of landfill caps/barriers over the next several decades and these caps will have a design life expectancy of up to 1,000 years. Other landfill caps with 30 year design lifetimes are reaching the end of their original design life; the changes to these caps need to be understood to provide a basis for lifetime extension. Defining the attributes that make a successful cap (one that isolates the waste from the environment) is crucial to these efforts. Because cap systems such as landfill caps are dynamic in nature, it is impossible to understand, monitor, and update lifetime predictions without understanding the dynamics of cap degradation, which is most often due to multiple interdependent factors rather than isolated independent events. In an attempt to understand the dynamics of cap degradation, a computer model using system dynamics is being developed to capture the complex behavior of an evapotranspiration cap. The specific objectives of this project are to capture the dynamic, nonlinear feedback loop structures underlying an evapotranspiration cap and, through computer simulation, gain a better understanding of long-term behavior, influencing factors, and, ultimately, long-term cap performance.

The siting of new waste containment systems is becoming increasing difficult as the public and stakeholders want more confidence that contaminant barrier systems will perform effectively for very long durations and owners want to store more wastes in the least area while knowing and limiting their long-term liabilities. These developments motivate reexamination of long-term performance issues and their implications for barrier designs. Accordingly, design principles are herein considered from the standpoint of long-term performance and management, including the ability to monitor and repair barriers. Then, some design concepts that may be implemented on the basis of these principles, especially evapotranspiration (ET) caps are discussed. Five design principles are recommended on the basis of considerations of infrastructure implementation experience and facility management experiences in other fields. The principles are: establishment of a clear and defendable design basis; design for ease of monitoring a...

System dynamics is a computer-aided approach to evaluating the interrelationships of different components and activities within complex systems. Recently, system dynamics models have been developed in areas such as policy design, biological and medical modeling, energy and the environmental analysis, and in various other areas in the natural and social sciences. The Idaho National Engineering and Environmental Laboratory, a multipurpose national laboratory managed by the Department of Energy, has developed a system dynamics model in order to evaluate its utility for modeling large complex hydrological systems. We modeled the Bear River basin, a transboundary basin that includes portions of Idaho, Utah, and Wyoming. We found that system dynamics modeling is very useful for integrating surface water and ground water data and for simulating the interactions between these sources within a given basin. In addition, we also found that system dynamics modeling is useful for integrating complex hydrologic data with other information (e.g., policy, regulatory, and management criteria) to produce a decision support system. Such decision support systems can allow managers and stakeholders to better visualize the key hydrologic elements and management constraints in the basin, which enables them to better understand the system via the simulation of multiple "what-if" scenarios. Although system dynamics models can be developed to conduct traditional hydraulic/hydrologic surface water or ground water modeling, we believe that their strength lies in their ability to quickly evaluate trends and cause-effect relationships in large-scale hydrological systems, for integrating disparate data, for incorporating output from traditional hydraulic/hydrologic models, and for integration of interdisciplinary data, information, and criteria to support better management decisions.

Idaho National Laboratory (INL) supports the U.S. Department of Energy’s bioenergy research program. As part of the research program INL investigates the feedstock logistics economics and sustainability of these fuels. A series of reports were published between 2000 and 2013 to demonstrate the feedstock logistics cost. Those reports were tailored to specific feedstock and conversion process. Although those reports are different in terms of conversion, some of the process in the feedstock logistic are same for each conversion process. As a result, each report has similar information. A single report can be designed that could bring all commonality occurred in the feedstock logistics process while discussing the feedstock logistics cost for different conversion process. Therefore, this report is designed in such a way that it can capture different feedstock logistics cost while eliminating the need of writing a conversion specific design report. Previous work established the current costs based on conventional equipment and processes. The 2012 programmatic target was to demonstrate a delivered biomass logistics cost of $55/dry ton for woody biomass delivered to fast pyrolysis conversion facility. The goal was achieved by applying field and process demonstration unit-scale data from harvest, collection, storage, preprocessing, handling, and transportation operations into more » INL’s biomass logistics model. The goal of the 2017 Design Case is to enable expansion of biofuels production beyond highly productive resource areas by breaking the reliance of cost-competitive biofuel production on a single, low-cost feedstock. The 2017 programmatic target is to supply feedstock to the conversion facility that meets the in-feed conversion process quality specifications at a total logistics cost of $80/dry T. The $80/dry T. target encompasses total delivered feedstock cost, including both grower payment and logistics costs, while meeting all conversion in-feed quality targets. The 2012 $55/dry T. programmatic target included only logistics costs with a limited focus on biomass quantity, quality and did not include a grower payment. The 2017 Design Case explores two approaches to addressing the logistics challenge: one is an agronomic solution based on blending and integrated landscape management and the second is a logistics solution based on distributed biomass preprocessing depots. The concept behind blended feedstocks and integrated landscape management is to gain access to more regional feedstock at lower access fees (i.e., grower payment) and to reduce preprocessing costs by blending high quality feedstocks with marginal quality feedstocks. Blending has been used in the grain industry for a long time; however, the concept of blended feedstocks in the biofuel industry is a relatively new concept. The blended feedstock strategy relies on the availability of multiple feedstock sources that are blended using a least-cost formulation within an economical supply radius, which, in turn, decreases the grower payment by reducing the amount of any single biomass. This report will introduce the concepts of blending and integrated landscape management and justify their importance in meeting the 2017 programmatic goals. « less

Biomass is a desirable source of energy because it is renewable, sustainable, widely available throughout the world, and amenable to conversion. Biomass is composed of cellulose, hemicellulose, and lignin components. Cellulose is generally the dominant fraction, representing about 40 to 50% of the material by weight, with hemicellulose representing 20 to 50% of the material, and lignin making up the remaining portion [4,5,6]. Although the outward appearance of the various forms of cellulosic biomass, such as wood, grass, municipal solid waste (MSW), or agricultural residues, is different, all of these materials have a similar cellulosic composition. Elementally, however, biomass varies considerably, thereby presenting technical challenges at virtually every phase of its conversion to useful energy forms and products. Despite the variances among cellulosic sources, there are a variety of technologies for converting biomass into energy. These technologies are generally divided into two groups: biochemical (biological-based) and thermochemical (heat-based) conversion processes. This chapter reviews the specific technologies that can be used to convert biomass to energy. Each technology review includes the description of the process, and the positive and negative aspects.

The U.S. Department of Energy promotes the production of liquid fuels from lignocellulosic biomass feedstocks by funding fundamental and applied research that advances the state of technology in biomass sustainable supply, logistics, conversion, and overall system sustainability. As part of its involvement in this program, Idaho National Laboratory (INL) investigates the feedstock logistics economics and sustainability of these fuels. Between 2000 and 2012, INL quantified and the economics and sustainability of moving biomass from the field or stand to the throat of the conversion process using conventional equipment and processes. All previous work to 2012 was designed to improve the efficiency and decrease costs under conventional supply systems. The 2012 programmatic target was to demonstrate a biomass logistics cost of $55/dry Ton for woody biomass delivered to fast pyrolysis conversion facility. The goal was achieved by applying field and process demonstration unit-scale data from harvest, collection, storage, preprocessing, handling, and transportation operations into INL’s biomass logistics model.

This report describes a proposed thermochemical process for converting biomass into liquid transportation fuels via fast pyrolysis followed by hydroprocessing of the condensed pyrolysis oil. As such, the analysis does not reflect the current state of commercially-available technology but includes advancements that are likely, and targeted to be achieved by 2017. The purpose of this study is to quantify the economic impact of individual conversion targets to allow a focused effort towards achieving cost reductions.

Engineering feedstock supply systems that deliver affordable, high-quality biomass remains a challenge for the emerging bioenergy industry. Cellulosic biomass is geographically distributed and has diverse physical and chemical properties. Because of this feedstock supply systems that deliver cellulosic biomass resources to biorefineries require integration of a broad set of engineered unit operations. These unit operations include harvest and collection, storage, preprocessing, and transportation processes. Design decisions for each feedstock supply system unit operation impact the engineering design and performance of the other system elements. These interdependencies are further complicated by spatial and temporal variances such as climate conditions and biomass characteristics. This paper develops an integrated model that couples a SQL-based data management engine and systems dynamics models to design and evaluate biomass feedstock supply systems. The integrated model, called the Biomass Logistics Model (BLM), includes a suite of databases that provide 1) engineering performance data for hundreds of equipment systems, 2) spatially explicit labor cost datasets, and 3) local tax and regulation data. The BLM analytic engine is built in the systems dynamics software package Powersim™. The BLM is designed to work with thermochemical and biochemical based biofuel conversion platforms and accommodates a range of cellulosic biomass types (i.e., herbaceous residues, short-rotation woody and herbaceous energy crops, woody residues, algae, etc.). The BLM simulates the flow of biomass through the entire supply chain, tracking changes in feedstock characteristics (i.e., moisture content, dry matter, ash content, and dry bulk density) as influenced by the various operations in the supply chain. By accounting for all of the equipment that comes into contact with biomass from the point of harvest to the throat of the conversion facility and the change in characteristics, the BLM evaluates economic performance of the engineered system, as well as determining energy consumption and green house gas performance of the design. This paper presents a BLM case study delivering corn stover to produce cellulosic ethanol. The case study utilizes the BLM to model the performance of several feedstock supply system designs. The case study also explores the impact of temporal variations in climate conditions to test the sensitivity of the engineering designs. Results from the case study show that under certain conditions corn stover can be delivered to the cellulosic ethanol biorefinery for $35/dry ton.

The nuclear fuel cycle is a very complex system that includes considerable dynamic complexity as well as detail complexity. In the nuclear power realm, there are experts and considerable research and development in nuclear fuel development, separations technology, reactor physics and waste management. What is lacking is an overall understanding of the entire nuclear fuel cycle and how the deployment of new fuel cycle technologies affects the overall performance of the fuel cycle. The Advanced Fuel Cycle Initiative’s systems analysis group is developing a dynamic simulation model, VISION, to capture the relationships, timing and delays in and among the fuel cycle components to help develop an understanding of how the overall fuel cycle works and can transition as technologies are changed. This paper is an overview of the philosophy and development strategy behind VISION. The paper includes some descriptions of the model and some examples of how to use VISION.

This report updates the status of U.S. biomass resources currently and future potentials for domestic and export markets of residues, energy crops, and woody resources. Includes energy and fuel production and consumption statistics, driving policies, targets, and government investment in bioenergy industry development.

The purpose of this document is to provide a guide for using the current version of the Verifiable Fuel Cycle Simulation (VISION) model. This is a complex model with many parameters and options; the user is strongly encouraged to read this user guide before attempting to run the model. This model is an RD this model represents a dynamic rather than steady-state approximation of the nuclear fuel system. VISION models the nuclear cycle at the system level, not individual facilities, e.g., 'reactor types' not individual reactors and 'separation types' not individual separation plants. Natural uranium can be enriched, which produces enriched uranium, which goes into fuel fabrication, andmore » depleted uranium (DU), which goes into storage. Fuel is transformed (transmuted) in reactors and then goes into a storage buffer. Used fuel can be pulled from storage into either separation or disposal. If sent to separations, fuel is transformed (partitioned) into fuel products, recovered uranium, and various categories of waste. Recycled material is stored until used by its assigned reactor type. VISION is comprised of several Microsoft Excel input files, a Powersim Studio core, and several Microsoft Excel output files. All must be co-located in the same folder on a PC to function. You must use Powersim Studio 8 or better. We have tested VISION with the Studio 8 Expert, Executive, and Education versions. The Expert and Education versions work with the number of reactor types of 3 or less. For more reactor types, the Executive version is currently required. The input files are Excel2003 format (xls). The output files are macro-enabled Excel2007 format (xlsm). VISION 3.4 was designed with more flexibility than previous versions, which were structured for only three reactor types - LWRs that can use only uranium oxide (UOX) fuel, LWRs that can use multiple fuel types (LWR MF), and fast reactors. One could not have, for example, two types of fast reactors concurrently. The new version allows 10 reactor types and any user-defined uranium-plutonium fuel is allowed. (Thorium-based fuels can be input but several features of the model would not work.) The user identifies (by year) the primary fuel to be used for each reactor type. The user can identify for each primary fuel a contingent fuel to use if the primary fuel is not available, e.g., a reactor designated as using mixed oxide fuel (MOX) would have UOX as the contingent fuel. Another example is that a fast reactor using recycled transuranic (TRU) material can be designated as either having or not having appropriately enriched uranium oxide as a contingent fuel. Because of the need to study evolution in recycling and separation strategies, the user can now select the recycling strategy and separation technology, by year.« less

The purpose of this document is to provide a guide for using the current version of the Verifiable Fuel Cycle Simulation (VISION) model. This is a complex model with many parameters; the user is strongly encouraged to read this user guide before attempting to run the model. This model is an RD this model represents a dynamic rather than steady-state approximation of the nuclear fuel system. VISION models the nuclear cycle at the system level, not individual facilities, e.g., “reactor types” not individual reactors and “separation types” not individual separation plants. Natural uranium can be enriched, which produces enriched uranium, which goes into fuel fabrication, and depleted uranium (DU), which goes into storage. Fuel is transformed (transmuted) in reactors and then goes into a storage buffer. Used fuel can be pulled from storage into either separation of disposal. If sent to separations, fuel is transformed (partitioned) into fuel products, recovered uranium, and various categories of waste. Recycled material is stored until used by its assigned reactor type. Note that recovered uranium is itself often partitioned: some RU flows with recycled transuranic elements, some flows with wastes, and the rest is designated RU. RU comes out of storage if needed to correct the U/TRU ratio in new recycled fuel. Neither RU nor DU are designated as wastes. VISION is comprised of several Microsoft Excel input files, a Powersim Studio core, and several Microsoft Excel output files. All must be co-located in the same folder on a PC to function. We use Microsoft Excel 2003 and have not tested VISION with Microsoft Excel 2007. The VISION team uses both Powersim Studio 2005 and 2009 and it should work with either.

This report outlines the status of U.S. biomass resources currently and future potentials for domestic and export markets of residues, energy crops, and woody resources. Includes energy and fuel production and consumption statistics, driving policies, targets, and government investment in bioenergy industry development.

VISION (VerifIable fuel cycle SImulatiON) is the Advanced Fuel Cycle Initiative’s and Global Nuclear Energy Partnership Program’s nuclear fuel cycle systems code designed to simulate the US commercial reactor fleet. The code is a dynamic stock and flow model that tracks the mass of materials at the isotopic level through the entire nuclear fuel cycle. As VISION is run, it calculates the decay of 70 isotopes including uranium, plutonium, minor actinides, and fission products. VISION.ECON is a sub-model of VISION that was developed to estimate fuel cycle and reactor costs. The sub-model uses the mass flows generated by VISION for each of the fuel cycle functions (referred to as modules) and calculates the annual cost based on cost distributions provided by the Advanced Fuel Cycle Cost Basis Report1. Costs are aggregated for each fuel cycle module, and the modules are aggregated into front end, back end, recycling, reactor, and total fuel cycle costs. The software also has the capability to perform system sensitivity analysis. This capability may be used to analyze the impacts on costs due to system uncertainty effects. This paper will provide a preliminary evaluation of the cost uncertainty affects attributable to 1) key reactor and fuel cyclemore » system parameters and 2) scheduling variations. The evaluation will focus on the uncertainty on the total cost of electricity and fuel cycle costs. First, a single light water reactor (LWR) using mixed oxide fuel is examined to ascertain the effects of simple parameter changes. Three system parameters; burnup, capacity factor and reactor power are varied from nominal cost values and the affect on the total cost of electricity is measured. These simple parameter changes are measured in more complex scenarios 2-tier systems including LWRs with mixed fuel and fast recycling reactors using transuranic fuel. Other system parameters are evaluated and results will be presented in the paper. Secondly, the uncertainty due to variation in scheduling effects is evaluated. For example, economic impacts due to increased nuclear energy growth rates and speed-ups in deployment of fuel cycle facilities and fast reactors. Preliminary results show that significant variations in the costs of the scenarios can result from variations in burnup, capacity factor and reactor power. The paper will include new results from analysis of additional system variables and due to scheduling dynamics. Reference 1. Shropshire, D.E. et al, 2007, Advanced Fuel Cycle Cost Basis, INL/EXT-07-12107, April 2007.« less

The DOE Biomass Program recently implemented the Biofuels Initiative, or 30x30 program, with the dual goal of reducing U.S. dependence on foreign oil by making cellulosic ethanol cost competitive with gasoline by 2012 and by replacing 30 percent of gasoline consumption with biofuels by 2030. Experience to date with increasing ethanol production suggests that it distorts agricultural markets and therefore raises concerns about the sustainability of the DOE 30 X 30 effort: Can the U.S. agricultural system produce sufficient feedstocks for biofuel production and meet the food price and availability expectations of American consumers without causing environmental degradation that would curtail the production of both food and fuel? Efforts are underway to develop computer-based modeling tools that address this concern and support the DOE 30 X 30 goals. Beyond technical agronomic and economic concerns, however, such models must account for the publics’ growing interest in sustainable agriculture and in the mitigation of predicted global climate change. This paper discusses ongoing work at the Center for Advanced Energy Studies that investigates the potential consequences and long-term sustainability of projected biomass harvests by identifying and incorporating “sustainable harvest indicators” in a computer modeling strategy.

This report aims to clarify many of the issues being discussed within the AFCI program, including Inert Matrix Fuel (IMF) versus Mixed Oxide (MOX) fuel, single-pass versus multi-pass recycling, thermal versus fast reactors, potential need for transmutation of technetium and iodine, and the value of separating cesium and strontium. It documents most of the work produced by INL, ANL, and SNL personnel under their Simulation, Evaluation, and Trade Study (SETS) work packages during FY2005 and the first half of FY2006. This report represents the first attempt to calculate a full range of metrics, covering all four AFCI program objectives - waste management, proliferation resistance, energy recovery, and systematic management/economics/safety - using a combination of "static" calculations and a system dynamic model, DYMOND. In many cases, we examine the same issue both dynamically and statically to determine the robustness of the observations. All analyses are for the U.S. reactor fleet. This is a technical report, not aimed at a policy-level audience. A wide range of options are studied to provide the technical basis for identifying the most attractive options and potential improvements. Option improvement could be vital to accomplish before the AFCI program publishes definitive cost estimates. Information from this report will be extracted and summarized in future policy-level reports. Many dynamic simulations of deploying those options are included. There are few "control knobs" for flying or piloting the fuel cycle system into the future, even though it is dark (uncertain) and controls are sluggish with slow time response: what types of reactors are built, what types of fuels are used, and the capacity of separation and fabrication plants. Piloting responsibilities are distributed among utilities, government, and regulators, compounding the challenge of making the entire system work and respond to changing circumstances. We identify four approaches that would increase our ability to pilot the fuel cycle system: (1) have a recycle strategy that could be implemented before the 2030-2050 approximate period when current reactors retire so that replacement reactors fit into the strategy, (2) establish an option such as multi-pass blended-core IMF as a downward plutonium control knob and accumulate waste management benefits early, (3) establish fast reactors with flexible conversion ratio as a future control knob that slowly becomes available if/when fast reactors are added to the fleet, and (4) expand exploration of blended assemblies and cores, which appear to have advantages and agility. Initial results suggest multi-pass full-core MOX appears to be a less effective way than multi-pass blended core IMF to manage the fuel cycle system because it requires higher TRU throughput while more slowly accruing waste management benefits. Single-pass recycle approaches for LWRs (we did not study the VHTR) do not meet AFCI program objectives and could be considered a "dead end". Fast reactors appear to be effective options but a significant number of fast reactors must be deployed before the benefit of such strategies can be observed.

The Demonstration of Decision Support Tools for Sustainable Development project integrated the Bechtel/Nexant Industrial Materials Exchange Planner and the Idaho National Engineering and Environmental Laboratory System Dynamic models, demonstrating their capabilities on alternative fuel applications in the Greater Yellowstone-Teton Park system. The combined model, called the Dynamic Industrial Material Exchange, was used on selected test cases in the Greater Yellow Teton Parks region to evaluate economic, environmental, and social implications of alternative fuel applications, and identifying primary and secondary industries. The test cases included looking at compressed natural gas applications in Teton National Park and Jackson, Wyoming, and studying ethanol use in Yellowstone National Park and gateway cities in Montana. With further development, the system could be used to assist decision-makers (local government, planners, vehicle purchasers, and fuel suppliers) in selecting alternative fuels, vehicles, and developing AF infrastructures. The system could become a regional AF market assessment tool that could help decision-makers understand the behavior of the AF market and conditions in which the market would grow. Based on this high level market assessment, investors and decision-makers would become more knowledgeable of the AF market opportunity before developing detailed plans and preparing financial analysis.

The Demonstration of Decision Support Tools for Sustainable Development project integrated the Bechtel/Nexant Industrial Materials Exchange Planner and the Idaho National Engineering and Environmental Laboratory System Dynamic models, demonstrating their capabilities on alternative fuel applications in the Greater Yellowstone-Teton Park system. The combined model, called the Dynamic Industrial Material Exchange, was used on selected test cases in the Greater Yellow Teton Parks region to evaluate economic, environmental, and social implications of alternative fuel applications, and identifying primary and secondary industries. The test cases included looking at compressed natural gas applications in Teton National Park and Jackson, Wyoming, and studying ethanol use in Yellowstone National Park and gateway cities in Montana. With further development, the system could be used to assist decision-makers (local government, planners, vehicle purchasers, and fuel suppliers) in selecting alternative fuels, vehicles, and developing AF infrastructures. The system could become a regional AF market assessment tool that could help decision-makers understand the behavior of the AF market and conditions in which the market would grow. Based on this high level market assessment, investors and decision-makers would become more knowledgeable of the AF market opportunity before developing detailed plans and preparing financial analysis.