Variability of Site-Reactor Risk

Reactor accident consequence models have been developed (for example, the CRAC model of the Reactor Safety Study (RSS), WASH-1400) to predict the offsite health and economic consequences of severe accidents at a reactor site with generic demographic and meteorological characteristics. Application of a revised RSS accident consequence model, CRAC2, to 91 existing sites results in a band of risk curves around the earlier WASH-1400 average reactor/site predictions. This paper examines these calculations and important model assumptions such as population distribution, emergency response, and meteorological data with respect to their effects on site risk extremes—that is, the combination of high consequence/low probability events.     

Learning from Nuclear Accident Experience

Statistical procedures are developed to estimate accident occurrence rates from historical event records, to predict future rates and trends, and to estimate the accuracy of the rate estimates and predictions. Maximum likelihood estimation is applied to several learning models and results are compared to earlier graphical and analytical estimates. The models are based on (1) the cumulative number of operating years, (2) the cumulative number of plants built, and (3) accidents (explicitly), with the accident rate distinctly different before and after an accident. The statistical accuracies of the parameters estimated are obtained in analytical form using the Fisher information matrix. Using data on core damage accidents in electricity producing plants , it is estimated that the probability for a plant to have a serious flaw has decreased from 0.1 to 0.01 during the developmental phase of the nuclear industry. At the same time the equivalent frequency of accidents has decreased from 0.04 per reactor year to 0.0004 per reactor year, partly due to the increasing population of plants.     

An Expert Elicitation of the Proliferation Resistance of Using Small Modular Reactors (SMR) for the Expansion of Civilian Nuclear Systems

To facilitate the use of nuclear energy globally, small modular reactors (SMRs) may represent a viable alternative or complement to large reactor designs. One potential benefit is that SMRs could allow for more proliferation resistant designs, manufacturing arrangements, and fuel‐cycle practices at widespread deployment. However, there is limited work evaluating the proliferation resistance of SMRs, and existing proliferation assessment approaches are not well suited for these novel arrangements. Here, we conduct an expert elicitation of the relative proliferation resistance of scenarios for future nuclear energy deployment driven by Generation III+ light‐water reactors, fast reactors, or SMRs. Specifically, we construct the scenarios to investigate relevant technical and institutional features that are postulated to enhance the proliferation resistance of SMRs. The experts do not consistently judge the scenario with SMRs to have greater overall proliferation resistance than scenarios that rely on conventional nuclear energy generation options. Further, the experts disagreed on whether incorporating a long‐lifetime sealed core into an SMR design would strengthen or weaken proliferation resistance. However, regardless of the type of reactor, the experts judged that proliferation resistance would be enhanced by improving international safeguards and operating several multinational fuel‐cycle facilities rather than supporting many more national facilities.     

Analytic Bayesian Solution of the Two-Stage Poisson-Type Problem in Probabilistic Risk Analysis

The basic purpose of probabilistic risk analysis is to make inferences about the probabilities of various postulated events, with an account of all relevant information such as prior knowledge and operating experience with the specific system under study, as well as experience with other similar systems. Estimation of the failure rate of a Poisson-type system leads to an especially simple Bayesian solution in closed form if the prior probability implied by the invariance properties of the problem is properly taken into account. This basic simplicity persists if a more realistic prior, representing order of magnitude knowledge of the rate parameter, is employed instead. Moreover, the more realistic prior allows direct incorporation of experience gained from other similar systems, without need to postulate a statistical model for an underlying ensemble. The analytic formalism is applied to actual nuclear reactor data.     

The Effect of Decisions About Spent Nuclear Fuel Storage on Residential Property Values

National, regional, state, and local surveys have revealed that people have intensely negative images of "nuclear" and "radioactive" technologies, activities, and facilities, as well as associated fears of stigmatization. In light of these perceptions, the debate over where to temporarily store or permanently dispose of spent nuclear fuel (at the reactor site, an interim storage facility, or a permanent repository) provokes immense concern among possible host jurisdictions. To address these concerns, one needs to know if people's subjective opinions conform with the choices they make and are therefore reflected in their economic behavior. Argonne National Laboratory researchers used a hedonic model to complete a study of residential property value dynamics over a 5-year period within a 15-mile radius of two California nuclear power plants. They tracked the economic ramifications of decisions about the spent nuclear fuel stored at those reactors. The study revealed that no significant negative effects on residential property values resulted from a decision to move spent nuclear fuel from wet storage to a dry-cask storage facility or from a request to extend the reactor operating permit (given future changes in the type of nuclear fuel storage facility that would accompany such an extension).     

Examining Psychometrics and Polarization in a Single-Risk Case Study

This project incorporates two steps. First, the psychometric model of risk perception is evaluated for its validity under field conditions. Second, individuals are classified as risk amplifiers or attenuators and the characteristics of those groups are explored. Survey data from an ongoing case study is employed in the analysis. The case study involves a Midwestern community in which a controversy exists over the possibility of the existence of a cancer cluster caused by the operation of a small reactor. Results show that the psychometric model of risk perception, while failing to be reproduced precisely, does has utility under the field conditions in this study. Use of the psychometric model to classify individuals as risk amplifiers or risk attenuators produces a useful dichotomy that reveals differences between the two polar groups in terms of demographics, satisfaction with institutional response to the risk, concern over individual and social levels of risk, and the evaluation of various communication channels as having been useful in coming to a judgment about the risk. A final model comparing the two groups suggests that, in this case, evaluation of personal risk and satisfaction with institutional response are important determinants of individual's risk reactions. Subordinate to these forces are the demographic variables of education, gender, and years of residence in the community. The model also illustrates that aggregate-level observations may not be representative of subgroups.     

SHIFTING PRODUCTION BOTTLENECKS: CAUSES,CURES, AND CONUNDRUMS

We examine the phenomenon of shifting production bottlenecks from an analytic perspective. We quantify the propensity of a work center to be a bottleneck, defined as maximal queue length, using a simple Jackson production network model. Comparison of the analytic model against an empirical simulation-based model shows that the two are in good agreement. A scalar measure of bottleneck shiftiness is proposed and used to investigate several policies for mitigating shiftiness. Simulation experiments show that several commonly observed managerial policies for coping with shifting bottlenecks actually increase shiftiness, but that shiftiness declines when the capacity of nonbottleneck resources is increased.     

Are Individual Differences Germane to the Acceptance of New Information Technologies?

Persuading users to adopt new information technologies persists as an important problem confronting those responsible for implementing new information systems. In order to better understand and manage the process of new technology adoption, several theoretical models have been proposed, of which the technology acceptance model (TAM) has gained considerable support. Beliefs and attitudes represent significant constructs in TAM. A parallel research stream suggests that individual difference factors are important in information technology acceptance but does not explicate the process by which acceptance is influenced. The objective of this paper is to clarify this process by proposing a theoretical model wherein the relationship between individual differences and IT acceptance is hypothesized to be mediated by the constructs of the technology acceptance model. In essence then, these factors are viewed as influencing an individual's beliefs about an information technology innovation; this relationship is further supported by drawing upon extensive research in learning. The theoretical model was tested in an empirical study of 230 users of an information technology innovation. Results confirm the basic structure of the model, including the mediating role of beliefs. Results also identify several individual difference variables that have significant effects on TAM's beliefs. Theoretical contributions and practical implications that follow are discussed.     

Reexamining a Model for Evaluating Information Center Success Using a Structural Equation Modeling Approach

Structural equation modeling is a technique that has been widely used for instrument validation and model testing in research in marketing and organizational behavior. The technique has also been introduced to MIS researchers and used in several studies recently reported in the literature. This article offers an example of how the technique can be used for instrument validation and model testing. The illustration is made through a reexamination of a model for evaluating information center (IC) success. With the growth of end-user computing, the success of an IC is more important than ever. Obtaining a valid model for measuring IC success is thus crucial to organizations with ICs. The results of this study highlight the importance of a strong theoretical base in developing such a valid model, and management should be cautious when using these models to assess the performance of their ICs.     

An application of the AHP in vendor selection of a telecommunications system

Vendor selection of a telecommunications system is an important problem to a telecommunications company as the telecommunications system is a long-term investment for the company and the success of telecommunications services is directly affected by the vendor selection decision. Furthermore, the vendor selection of a telecommunications system is a complex multi-person, multi-criteria decision problem. The group decision-making process can be improved by a systematic and logical approach to assess priorities based on the inputs of several people from different functional areas within the company. The analytic hierarchy process (AHP) can be very useful in involving several decision-makers with different conflicting objectives to arrive at a consensus decision. In this paper, an AHP-based model is formulated and applied to a real case study to examine its feasibility in selecting a vendor for a telecommunications system. The use of the proposed model indicates that it can be applied to improve the group decision making in selecting a vendor that satisfies customer specifications. Also, it is found that the decision process is systematic and that using the proposed AHP model can reduce the time taken to select a vendor.     

An interactive three-stage model for mutual funds portfolio selection

The aim of this work is to be a useful instrument for helping finance practitioners on the selection of suitable mutual fund portfolios. The portfolio selection problem is characterized by imprecision and/or vagueness inherent in the required data and more generally, in the context where investors have to make decisions. In order to mitigate these problems, a three stage model has been proposed based on a multi-index model and considering several market scenarios described in an imprecise way by an expert. The proposed fuzzy model allows the Decision Maker to select, by means of an outranking method, a suitable portfolio taking into account the uncertainty related to the market scenarios and the imprecision and/or vagueness associated with the model data.     

The Dependence of the Risk of Research Reactors from Their Operating Schedule–A Case Study

The dependence of the radiological consequences of the "Demokritos" research reactor on the operating schedule of the reactor is assessed in this paper. The 5 MW reactor is located within the limits of Athens city, a large population center with over 3 million inhabitants. The consequences examined would be due to the occurrence of a postulated accident, a 20% core melt loss of coolant accident, that is also considered as the design basis accident of the reactor. Three operating schedules are taken into account: (a) a continuous operation schedule; (b) a 16 hr/day, 5 days/week schedule; and (c) the present 8 hr/day, 5 days/week operating schedule. The assessment of the source term emerges from a conservative estimation of fission product releases to the reactor operating floor, and further under the conservative assumptions of no filter mitigation, and a ground release to the environment. The results of the analysis indicate that there is a direct relation between consequences and duration of operation, the former becoming appreciable as the continuous operation limit is approached. In all cases examined, the thyroid dose and the latent thyroid health effects would be the limiting consequences.     

Sensitivity and Uncertainty Studies of the CRAC2 Computer Code

We have studied the sensitivity of health impacts from nuclear reactor accidents, as predicted by the CRAC2 computer code, to the following sources of uncertainty: (1) the model for plume rise, (2) the model for wet deposition, (3) the meteorological bin-sampling procedure for selecting weather sequences with rain, (4) the dose conversion factors for inhalation as affected by uncertainties in the particle size of the carrier aerosol and the clearance rates of radionuclides from the respiratory tract, (5) the weathering half-time for external ground-surface exposure, and (6) the transfer coefficients for terrestrial foodchain pathways. Predicted health impacts usually showed little sensitivity to use of an alternative plume-rise model or a modified rain-bin structure in bin-sampling. Health impacts often were quite sensitive to use of an alternative wet-deposition model in single-trial runs with rain during plume passage, but were less sensitive to the model in bin-sampling runs. Uncertainties in the inhalation dose conversion factors had important effects on early injuries in single-trial runs. Latent cancer fatalities were moderately sensitive to uncertainties in the weathering half-time for ground-surface exposure, but showed little sensitivity to the transfer coefficients for terrestrial foodchain pathways. Sensitivities of CRAC2 predictions to uncertainties in the models and parameters also depended on the magnitude of the source term, and some of the effects on early health effects were comparable to those that were due only to selection of different sets of weather sequences in bin-sampling.     

A Risk Assessment Model for Campylobacter in Broiler Meat

A quantitative microbiological risk assessment model describes the transmission of Campylobacter through the broiler meat production chain and at home, from entering the processing plant until consumption of a chicken breast fillet meal. The exposure model is linked to a dose-response model to allow estimation of the incidence of human campylobacteriosis. The ultimate objective of the model is to serve as a tool to assess the effects of interventions to reduce campylobacteriosis in the Netherlands. The model describes some basic mechanistics of processing, including the nonlinear effects of cross-contamination between carcasses and their leaking feces. Model input is based on the output of an accompanying farm model and Dutch count data of Campylobacters on the birds' exterior and in the feces. When processing data are lacking, expert judgment is used for model parameter estimation. The model shows that to accurately assess of the effects of interventions, numbers of Campylobacter have to be explicitly incorporated in the model in addition to the prevalence of contamination. Also, as count data usually vary by several orders of magnitude, variability in numbers within and especially between flocks has to be accounted for. Flocks with high concentrations of Campylobacter in the feces that leak from the carcasses during industrial processing seem to have a dominant impact on the human incidence. The uncertainty in the final risk estimate is large, due to a large uncertainty at several stages of the chain. Among others, more quantitative count data at several stages of the production chain are needed to decrease this uncertainty. However, this uncertainty is smaller when relative risks of interventions are calculated with the model. Hence, the model can be effectively used by risk management in deciding on strategies to reduce human campylobacteriosis.     

An Exact Analysis of the Multistage Model Explaining Dose-Response Concavity

The traditional multistage (MS) model of carcinogenesis implies several empirically testable properties for dose-response functions. These include convex (linear or upward-curving) cumulative hazards as a function of dose; symmetric effects on lifetime tumor probability of transition rates at different stages; cumulative hazard functions that increase without bound as stage-specific transition rates increase without bound; and identical tumor probabilities for individuals with identical parameters and exposures. However, for at least some chemicals, cumulative hazards are not convex functions of dose. This paper shows that none of these predicted properties is implied by the mechanistic assumptions of the MS model itself. Instead, they arise from the simplifying "rare-tumor" approximations made in the usual mathematical analysis of the model. An alternative exact probabilistic analysis of the MS model with only two stages is presented, both for the usual case where a carcinogen acts on both stages simultaneously, and also for idealized initiation-promotion experiments in which one stage at a time is affected. The exact two-stage model successfully fits bioassay data for chemicals (e.g., 1,3-butadiene) with concave cumulative hazard functions that are not well-described by the traditional MS model. Qualitative properties of the exact two-stage model are described and illustrated by least-squares fits to several real datasets. The major contribution is to show that properties of the traditional MS model family that appear to be inconsistent with empirical data for some chemicals can be explained easily if an exact, rather than an approximate model, is used. This suggests that it may be worth using the exact model in cases where tumor rates are not negligible (e.g., in which they exceed 10%). This includes the majority of bioassay experiments currently being performed.     

并联结构决策单元的DEA效率评价研究

对复杂生产系统进行效率评价,是改善其运作性能的重要工具.并联结构生产系统是一类有代表性的复杂生产系统,现有研究已经提出了若干针对并联结构生产系统的效率评价问题.然而,现有研究均未考察并联生产系统的前沿生产能力.本文分析了并联生产系统的前沿生产能力,提出了评价并联生产系统的乘数模型和包络模型,证明了这两个模型与有关文献的等价性.与传统CCR模型相比较,本文模型具有更强的鉴别能力,可更大程度挖掘系统整体性能改善的潜力.最后,一个农业评价的实证研究验证了有关结论.     

Probabilistic Risk Assessment of Wastes Buried in the Ground

The differences between probabilistic risk assessment (PRA) and safety analysis (SA) are discussed, and it is shown that PRA is more suitable than SA for determining the acceptability of a technology. Since a PRA by the fault tree-event tree analysis method used for reactor safety studies does not seem to be practical for buried waste, an alternative approach is suggested using geochemical analogs. This method is illustrated for the cases of high-level and low-level radioactive waste and for chemical carcinogens released in coal burning.     

SIMPLE MODELS FOR MONITORING NEW PRODUCT PERFORMANCE

Several studies have shown that consumers trying a new brand of frequently purchased consumer goods behave differently from repeat buyers. The “customer mix” for a new brand changes over time. Early in a new brand's life, most of the buyers are triers, while later in its life, a significant portion of the buyers are repeaters. The study presented here tests the hypothesis that an aggregate sales forecast, “averaging” the behaviors of triers and repeaters, would be outperformed by a model that treats them separately. A new product model, giving separate consideration to triers and repeaters, is developed. This model is tested on predictive ability against a widely used single-equation aggregate model. Consumer panel purchase diaries and data on advertising in measured media, covering a period of 42 months following introduction of a major brand of cold tablets, serve as the proving grounds. Data for the early part of this period serve as the data base for both models, while data for the rest of the period serve to test the predictive ability of both models. The disaggregate model is shown to perform significantly better than the aggregate model in terms of predictive accuracy. It also offers several other advantages in use as a decision aid, both for GO-NO decisions and for marketing mix decisions. Finally, several problems in the implementation of the proposed model and implications for research strategy are discussed.