12 research outputs found
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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
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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)
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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
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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
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Including uncertainty in hazard analysis through fuzzy measures
This paper presents a method for capturing the uncertainty expressed by an Hazard Analysis (HA) expert team when estimating the frequencies and consequences of accident sequences and provides a sound mathematical framework for propagating this uncertainty to the risk estimates for these accident sequences. The uncertainty is readily expressed as distributions that can visually aid the analyst in determining the extent and source of risk uncertainty in HA accident sequences. The results also can be expressed as single statistics of the distribution in a manner analogous to expressing a probabilistic distribution as a point-value statistic such as a mean or median. The study discussed here used data collected during the elicitation portion of an HA on a high-level waste transfer process to demonstrate the techniques for capturing uncertainty. These data came from observations of the uncertainty that HA team members expressed in assigning frequencies and consequences to accident sequences during an actual HA. This uncertainty was captured and manipulated using ideas from possibility theory. The result of this study is a practical method for displaying and assessing the uncertainty in the HA team estimates of the frequency and consequences for accident sequences. This uncertainty provides potentially valuable information about accident sequences that typically is lost in the HA process
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Accident reconstruction using process trees
A study conducted by Pittsburgh Energy Technology Center of sulfur emissions from about 1,300 United States coal-fired utility boilers indicated that half of the emissions were the result of burning coals having greater than 1.2 pounds of SO{sub 2} per million BTU. This was mainly attributed to the high pyritic sulfur content of the boiler fuel. A significant reduction in SO{sub 2} emissions could be accomplished by removing the pyrite from the coals by advanced physical fine coal cleaning. An engineering development project was prepared to build upon the basic research effort conducted under a solicitation for research into Fine Coal Surface Control. The engineering development project is intended to use general plant design knowledge and conceptualize a plant to utilize advanced froth flotation technology to process coal and produce a product having maximum practical pyritic sulfur reduction consistent with maximum practical BTU recovery. The overall project scope of the engineering development project is to conceptually develop a commercial flowsheet to maximize pyritic sulfur reduction at practical energy recovery values. This is being accomplished by utilizing the basic research data on the surface properties of coal, mineral matter and pyrite obtained from the Coal Surface Control for Advanced Fine Coal Flotation Project, to develop this conceptual flowsheet. This progress report provides a summary of the technical work undertaken during this period, highlighting the major results. A brief description of the work done prior to this quarter is provided in this report under the task headings
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A hazards analysis of a nuclear explosives dismantlement
This paper describes the methodology used in a quantitative hazard assessment of a nuclear weapon disassembly process. Potential accident sequences were identified using an accident-sequence fault tree based on operational history, weapon safety studies, a hazard analysis team composed of weapons experts, and walkthroughs of the process. The experts provided an initial screening of the accident sequences to reduce the number of accident sequences that would be quantified. The accident sequences that survived the screening process were developed further using event trees. Spreadsheets were constructed for each event tree, the accident sequences associated with that event tree were entered as rows on the spreadsheet, and that spreadsheet was linked to spreadsheets with initiating-event frequencies, enabling event probabilities, and weapon response probabilities. The probability and frequency distribution estimates used in these spreadsheets were gathered from weapon process operational data, surrogate industrial data, expert judgment, and probability models. Frequency distributions were calculated for the sequences whose point-value frequency represented 99% of the total point-value frequency using a Monte Carlo simulation. Partial differential importances of events and distributions of accident frequency by weapon configuration, location, process, and other parameters were calculated
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Analysis of propagating explosions
Weapons are often in close proximity to one another during transport or storage. If one weapon explodes, there is a possibility that the fragments generated will initiate a subsequent explosion in one or more neighboring weapons. Propagating explosions of this sort have the potential for severe consequences either because of the total amount of explosives that react or because the response of individual weapons may be particularly energetic. In this paper, we consider a well-defined problem in which the nature of the progression to all possible end states can be studied. We wish to determine the expected number of weapons to detonate along with other useful quantities. We examine the possible end states that the system can reach and show that we can represent the propagation process as a series of discrete time transitions. The transition probabilities from one state to the next then will depend only on the present state of the system. We present results of simulations that illustrate the effect of varying the detonation probability parameters
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Detonation probabilities of high explosives
The probability of a high explosive violent reaction (HEVR) following various events is an extremely important aspect of estimating accident-sequence frequency for nuclear weapons dismantlement. In this paper, we describe the development of response curves for insults to PBX 9404, a conventional high-performance explosive used in US weapons. The insults during dismantlement include drops of high explosive (HE), strikes of tools and components on HE, and abrasion of the explosive. In the case of drops, we combine available test data on HEVRs and the results of flooring certification tests to estimate the HEVR probability. For other insults, it was necessary to use expert opinion. We describe the expert solicitation process and the methods used to consolidate the responses. The HEVR probabilities obtained from both approaches are compared
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Probabilistic modeling of propagating explosions
Weapons containing significant quantities of high explosives (HE) are sometimes located in close proximity to one another. If an explosion occurs in a weapon, the possibility of propagation to one or more additional weapons may exist, with severe consequences possibly resulting. In the general case, a system of concern consists of multiple weapons and various other objects in a complex, three-dimensional geometry. In each weapon, HE is enclosed by (casing) materials that function as protection in the event of a neighbor detonation but become a source of fragments if the HE is initiated. The protection afforded by the casing means that only high-momentum fragments, which occur rarely, are of concern. These fragments, generated in an initial donor weapon are transported to other weapons either directly or by ricochet. Interaction of a fragment with an acceptor weapon can produce a reaction in the acceptor HE and result in a second detonation. In this paper we describe a comprehensive methodology to estimate the probability of various consequences for fragment-induced propagating detonations in arrays of weapons containing HE. Analysis of this problem requires an approach that can both define the circumstances under which rare events can occur and calculate the probability of such occurrences. Our approach is based on combining process tree methodology with Monte Carlo transport simulation. Our Monte Carlo technique very effectively captures important features of these differences. Process tree methodology is described and its use is discussed for a simplified problem and to illustrate the power of Monte Carlo simulation in estimating fragment-induced detonation of an acceptor weapon