Engineering topics

Piet, Steven J

Publications and source records attributed to Piet, Steven J.

5 records

DOE OSTI2013

Fuel Cycle System Analysis Implications of Sodium-Cooled Metal-Fueled Fast Reactor Transuranic Conversion Ratio

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 that 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.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2011

The FIT 2.0 Model - Fuel-cycle Integration and Tradeoffs

All mass streams from fuel separation and fabrication are products that must meet some set of product criteria – fuel feedstock impurity limits, waste acceptance criteria (WAC), material storage (if any), or recycle material purity requirements such as zirconium for cladding or lanthanides for industrial use. These must be considered in a systematic and comprehensive way. The FIT model and the “system losses study” team that developed it [Shropshire2009, Piet2010b] are steps by the Fuel Cycle Technology program toward an analysis that accounts for the requirements and capabilities of each fuel cycle component, as well as major material flows within an integrated fuel cycle. This will help the program identify near-term R&D needs and set longer-term goals. This report describes FIT 2, an update of the original FIT model.[Piet2010c] FIT is a method to analyze different fuel cycles; in particular, to determine how changes in one part of a fuel cycle (say, fuel burnup, cooling, or separation efficiencies) chemically affect other parts of the fuel cycle. FIT provides the following: Rough estimate of physics and mass balance feasibility of combinations of technologies. If feasibility is an issue, it provides an estimate of how performance would have to change to achieve feasibility. Estimate of impurities in fuel and impurities in waste as function of separation performance, fuel fabrication, reactor, uranium source, etc.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2011

Assessment of Tools and Data for System-Level Dynamic Analyses

The only fuel cycle for which dynamic analyses and assessments are not needed is the null fuel cycle - no nuclear power. For every other concept, dynamic analyses are needed and can influence relative desirability of options. Dynamic analyses show how a fuel cycle might work during transitions from today's partial fuel cycle to something more complete, impact of technology deployments, location of choke points, the key time lags, when benefits can manifest, and how well parts of fuel cycles work together. This report summarizes the readiness of existing Fuel Cycle Technology (FCT) tools and data for conducting dynamic analyses on the range of options. VISION is the primary dynamic analysis tool. Not only does it model mass flows, as do other dynamic system analysis models, but it allows users to explore various potential constraints. The only fuel cycle for which constraints are not important are those in concept advocates PowerPoint presentations; in contrast, comparative analyses of fuel cycles must address what constraints exist and how they could impact performance. The most immediate tool need is extending VISION to the thorium/U233 fuel cycle. Depending on further clarification of waste management strategies in general and for specific fuel cycle candidates, waste management sub-models in VISION may need enhancement, e.g., more on 'co-flows' of non-fuel materials, constraints in waste streams, or automatic classification of waste streams on the basis of user-specified rules. VISION originally had an economic sub-model. The economic calculations were deemed unnecessary in later versions so it was retired. Eventually, the program will need to restore and improve the economics sub-model of VISION to at least the cash flow stage and possibly to incorporating cost constraints and feedbacks. There are multiple sources of data that dynamic analyses can draw on. In this report, 'data' means experimental data, data from more detailed theoretical or empirical calculations on technology performance, and assumptions such as the earliest date a technology can be deployed. The only fuel cycles for which we currently have adequate data are those we are sure we will never build, e.g., a PUREX plant in the U.S. For actual candidates, even for once through LWRs, there remain missing data such as how the fuel cycle would be completed with a geologic repository. The most immediate data needs are probably basic reactor physics data for new concepts and data associated with waste management for anything other than current technology. The readiness of tools and data is fluid and depends on what purposes are envisioned to drive upcoming analyses and further definition of the waste-related characteristics of fuel cycle candidates. Tools and data sets evolve as needs evolve. Thus, much of the document explains that if the FCT program wants a certain type of analysis, then the tools and data needs are as indicated. For example, functions can be treated as either commodities or facilities. Reactors, separation, fuel fabrication, repository are treated as facility types. Other functions such as uranium mining, conversion, enrichment, and waste packaging and non-repository disposal are treated as commodities and therefore not modeled as extensively. In summary, the tools are functional and can answer many fuel cycle questions but some analyses will require that the tools be modified to support those analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2011

Dynamic Simulations of Advanced Fuel Cycles

Years of performing dynamic simulations of advanced nuclear fuel cycle options provide insights into how they could work and how one might transition from the current once-through fuel cycle. This paper summarizes those insights from the context of the 2005 objectives and goals of the U.S. Advanced Fuel Cycle Initiative (AFCI). Our intent is not to compare options, assess options versus those objectives and goals, nor recommend changes to those objectives and goals. Rather, we organize what we have learned from dynamic simulations in the context of the AFCI objectives for waste management, proliferation resistance, uranium utilization, and economics. Thus, we do not merely describe “lessons learned” from dynamic simulations but attempt to answer the “so what” question by using this context. The analyses have been performed using the Verifiable Fuel Cycle Simulation of Nuclear Fuel Cycle Dynamics (VISION). We observe that the 2005 objectives and goals do not address many of the inherently dynamic discriminators among advanced fuel cycle options and transitions thereof.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2011

Multi-Reactor Transmutation Analysis Utility (MRTAU,alpha1): Verification

Multi-Reactor Transmutation Utility (MRTAU) is a general depletion/decay algorithm under development at INL to support quick assessment of off-normal fuel cycle scenarios of similar nature to well studied reactor and fuel cycle concepts for which isotopic and cross-section data exists. MRTAU has been used in the past for scoping calculations to determine actinide composition evolution over the course of multiple recycles in Light Water Reactor Mixed Oxide and Sodium cooled Fast Reactor. In these applications, various actinide partitioning scenarios of interest were considered. The code has recently been expanded to include fission product generation, depletion and isotopic evolution over multiple recycles. The capability was added to investigate potential partial separations and/or limited recycling technologies such as Melt-Refining, AIROX, DUPIC or other fuel recycle technology where the recycled fuel stream is not completely decontaminated of fission products prior to being re-irradiated in a subsequent reactor pass. This report documents the code's solution methodology and algorithm as well as its solution accuracy compared to the SCALE6.0 software suite.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗