Robert F. Jeffers

VERIFIABLE FUEL CYCLE SIMULATION MODEL (VISION): A TOOL FOR ANALYZING NUCLEAR FUEL CYCLE FUTURES

Abstract 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 timing of events in any part of the fuel cycle system such as how the system would respond to each technological change, a series of which moves the fuel cycle from where it is to a postulated future state. The system analysis working group of the United States research program on advanced fuel cycles (formerly called the Advanced Fuel Cycle Initiative) is developing a dynamic simulation model, VISION, to capture the relationships, timing, and changes in and among the fuel cycle components to help develop an understanding of how the overall fuel cycle works. This paper is an overview of the philosophy and development strategy behind VISION. The paper includes some descriptions of the model components and some examples of how to use VISION. For example, VISION users can now change yearly the selection of separation or reactor technologies, the performance characteristics of those technologies, and/or the routing of material among separation and reactor types—with the model still operating on a PC in <5 min.

VISION User Guide - VISION (Verifiable Fuel Cycle Simulation) Model

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.

Modeling and simulating blast effects on electric substations

A software simulation tool was developed at Idaho National Laboratory to estimate the fragility of electric substation components subject to an explosive blast. Damage caused by explosively driven fragments on a generic electric substation was estimated by using a ray-tracing technique to track and tabulate fragment impacts and penetrations of substation components. This technique is based on methods used for assessing vulnerability of military aircraft and ground vehicles to explosive blasts. An open-source rendering and ray-trace engine was used for geometric modeling and interactions between fragments and substation components. Semi-empirical material interactions models were used to calculate blast parameters and simulate high-velocity material interactions between explosively driven fragments and substation components. Finally, a Monte Carlo simulation was added to model the random nature of fragment generation allowing a skilled analyst to predict failure probabilities of substation components.