Initiating-event frequencies for nuclear weapons dismantlement hazard analysis

A quantitative data base for initiating events encountered during nuclear weapons handling is described. This data base was assembled from incident reports at the plant where the weapons are handled. The strengths and pitfalls of constructing such a data base are elaborated using examples encountered in the data. Insights gained into accident sequences, human error probabilities, and other areas of concern are discussed

An approximate-reasoning-based method for screening flammable gas tanks

High-level waste (HLW) produces flammable gases as a result of radiolysis and thermal decomposition of organics. Under certain conditions, these gases can accumulate within the waste for extended periods and then be released quickly into the dome space of the storage tank. As part of the effort to reduce the safety concerns associated with flammable gas in HLW tanks at Hanford, a flammable gas watch list (FGWL) has been established. Inclusion on the FGWL is based on criteria intended to measure the risk associated with the presence of flammable gas. It is important that all high-risk tanks be identified with high confidence so that they may be controlled. Conversely, to minimize operational complexity, the number of tanks on the watchlist should be reduced as near to the true number of flammable risk tanks as the current state of knowledge will support. This report presents an alternative to existing approaches for FGWL screening based on the theory of approximate reasoning (AR) (Zadeh 1976). The AR-based model emulates the inference process used by an expert when asked to make an evaluation. The FGWL model described here was exercised by performing two evaluations. (1) A complete tank evaluation where the entire algorithm is used. This was done for two tanks, U-106 and AW-104. U-106 is a single shell tank with large sludge and saltcake layers. AW-104 is a double shell tank with over one million gallons of supernate. Both of these tanks had failed the screening performed by Hodgson et al. (2) Partial evaluations using a submodule for the predictor likelihood for all of the tanks on the FGWL that had been flagged previously by Whitney (1995)

Uncertainty and approximate reasoning in waste pretreatment planning

Waste pretreatment process planning within the DOE complex must consider many different outcomes in order to perform the tradeoffs necessary to accomplish this important national mission. One of the difficulties encountered by many who assess these tradeoffs is that the complexity of this problem taxes the abilities of any single person or small group of individuals. For example, uncertainties in waste composition as well as process efficiency are well known yet incompletely considered in the search for optimum solutions. This paper describes a tool, the pre-treatment Process Analysis Tool (PAT), for evaluating tank waste pretreatment options at Hanford, Oak Ridge, Idaho National Environmental and Engineering Laboratory, and Savannah River Sites. The PAT propagates uncertainty in both tank waste composition and process partitioning into a set of ten outcomes. These outcomes are, for example, total cost, Cs-137 in iLAW, iHLW MT, and so on. Tradeoffs among outcomes are evaluated or scored by means of an approximate reasoning module that uses linguistic bases to evaluate tradeoffs for each process based on user valuations of outcomes

Evaluation of high-level waste pretreatment processes with an approximate reasoning model

The development of an approximate-reasoning (AR)-based model to analyze pretreatment options for high-level waste is presented. AR methods are used to emulate the processes used by experts in arriving at a judgment. In this paper, the authors first consider two specific issues in applying AR to the analysis of pretreatment options. They examine how to combine quantitative and qualitative evidence to infer the acceptability of a process result using the example of cesium content in low-level waste. They then demonstrate the use of simple physical models to structure expert elicitation and to produce inferences consistent with a problem involving waste particle size effects

System Oriented Runway Management: A Research Update

The runway configuration used by an airport has significant implications with respect to its capacity and ability to effectively manage surface and airborne traffic. Aircraft operators rely on runway configuration information because it can significantly affect an airline's operations and planning of their resources. Current practices in runway management are limited by a relatively short time horizon for reliable weather information and little assistance from automation. Wind velocity is the primary consideration when selecting a runway configuration; however when winds are below a defined threshold, discretion may be used to determine the configuration. Other considerations relevant to runway configuration selection include airport operator constraints, weather conditions (other than winds) traffic demand, user preferences, surface congestion, and navigational system outages. The future offers an increasingly complex landscape for the runway management process. Concepts and technologies that hold the potential for capacity and efficiency increases for both operations on the airport surface and in terminal and enroute airspace are currently under investigation. Complementary advances in runway management are required if capacity and efficiency increases in those areas are to be realized. The System Oriented Runway Management (SORM) concept has been developed to address this critical part of the traffic flow process. The SORM concept was developed to address all aspects of runway management for airports of varying sizes and to accommodate a myriad of traffic mixes. SORM, to date, addresses the single airport environment; however, the longer term vision is to incorporate capabilities for multiple airport (Metroplex) operations as well as to accommodate advances in capabilities resulting from ongoing research. This paper provides an update of research supporting the SORM concept including the following: a concept of overview, results of a TRCM simulation, single airport and Metroplex modeling effort and a benefits assessment

Progress Toward Future Runway Management

The runway is universally acknowledged as a constraining factor to capacity in the National Airspace System (NAS). It follows that investigation of the effective use of runways, both in terms of selection and assignment, is paramount to the efficiency of future NAS operations. The need to address runway management is not a new idea; however, as the complexities of factors affecting runway selection and usage increase, the need for effective research in this area correspondingly increases. Under the National Aeronautics and Space Administration s Airspace Systems Program, runway management is a key research area. To address a future NAS which promises to be a complex landscape of factors and competing interests among users and operators, effective runway management strategies and capabilities are required. This effort has evolved from an assessment of current practices, an understanding of research activities addressing surface and airspace operations, traffic flow management enhancements, among others. This work has yielded significant progress. Systems analysis work indicates that the value of System Oriented Runway Management tools is significantly increased in the metroplex environment over that of the single airport case. Algorithms have been developed to provide runway configuration recommendations for a single airport with multiple runways. A benefits analysis has been conducted that indicates the SORM benefits include supporting traffic growth, cost reduction as a result of system efficiency, NAS optimization from metroplex operations, fairness in aircraft operations, and rational decision making

INTROGRESSION OF COYOTE MITOCHONDRIAL DNA INTO SYMPATRIC NORTH AMERICAN GRAY WOLF POPULATIONS

Mitochondrial DNA (mtDNA) genotypes of gray wolves and coyotes from localities throughout North America were determined using restriction fragment length polymorphisms. Of the 13 genotypes found among the wolves, 7 are clearly of coyote origin, indicating that genetic transfer of coyote mtDNA into wolf populations has occurred through hybridization. The transfer of mtDNA appears unidirectional from coyotes into wolves because no coyotes sampled have a wolf-derived mtDNA genotype. Wolves possessing coyote-derived genotypes are confined to a contiguous geographic region in Minnesota, Ontario, and Quebec, and the frequency of coyote- type mtDNA in these wolf populations is high (\u3e 500%). The ecological history of the hybrid zone suggests that hybridization is taking place in regions where coyotes have only recently become abundant following conversion of forests to farmlands. Dispersing male wolves unable to find conspecific mates may be pairing with female coyotes in deforested areas bordering wolf territories. Our results demonstrate that closely related species of mobile terrestrial vertebrates have the potential for extensive genetic exchange when ecological conditions change suddenly

Analysis of lightning-related risk in outdoor high explosive research.

The behavior of materials at high strain rates can be studied using high explosives (HE) as an energy source. Such hydrodynamic experiments may be performed on full-scale systems, requiring kilogram quantities of HE and therefore are performed at outdoor facilities. One such facility is DARHT-the Dual-Axis Radiographic Hydrodynamic Test facility located at Los Alamos National Laboratory in northern New Mexico. DARHT is a very large flash x-ray machine. The high-intensity, short-duration x-ray pulses are beamed through the hydrodynamic experiment to an x-ray camera. Density variations in the materials produce variations in the transmitted beam that are recorded by the camera. The information in these images is used to understand the basic behavior of materials subjected to very high dynamic pressures and to evaluate the accuracy of computer codes used to model the associated phenomena

Resource allocation using risk analysis

Allocating limited resources among competing priorities is an important problem in management. In this paper we describe an approach to resource allocation using risk as a metric. We call this approach the Logic-Evolved Decision (LED) approach because we use logic-models to generate an exhaustive set of competing options and to describe the often highly complex model used for evaluating the risk reduction achieved by different resource allocations among these options. The risk evaluation then proceeds using probabilistic or linguistic input data