Use of 3/sup n/ Parallel Flats Fractional Factorial Designs in Computer Code Uncertainty Analysis

Parallel flats fractions for the 3/sup n/ factorial provide near-othogonal designs for which sets of treatment combinations (flats) can be run sequentially with analysis after each flat. For the 3/sup n/ factoral the number of parameters involved including the mean, main effects, and a two-factor interactions is 1 + 2n + 4(/sup n//sub 2/) = 1 + 2n/sup 2/. In most applications a relatively small number of these will be significant, and a design which will produce a good fit in relatively few runs is desired. The concepts and the sequential analysis are illustrated using a 3/sup 4/ example and a 3/sup 6/ example. Potential areas of application of these designs are discussed. 5 tables

Estimating Loss-of-Coolant Accident Frequencies for the Standardized Plant Analysis Risk Models

The U.S. Nuclear Regulatory Commission maintains a set of risk models covering the U.S. commercial nuclear power plants. These standardized plant analysis risk (SPAR) models include several loss-of-coolant accident (LOCA) initiating events such as small (SLOCA), medium (MLOCA), and large (LLOCA). All of these events involve a loss of coolant inventory from the reactor coolant system. In order to maintain a level of consistency across these models, initiating event frequencies generally are based on plant-type average performance, where the plant types are boiling water reactors and pressurized water reactors. For certain risk analyses, these plant-type initiating event frequencies may be replaced by plant-specific estimates. Frequencies for SPAR LOCA initiating events previously were based on results presented in NUREG/CR-5750, but the newest models use results documented in NUREG/CR-6928. The estimates in NUREG/CR-6928 are based on historical data from the initiating events database for pressurized water reactor SLOCA or an interpretation of results presented in the draft version of NUREG-1829. The information in NUREG-1829 can be used several ways, resulting in different estimates for the various LOCA frequencies. Various ways NUREG-1829 information can be used to estimate LOCA frequencies were investigated and this paper presents two methods for the SPAR model standard inputs, which differ from the method used in NUREG/CR-6928. In addition, results obtained from NUREG-1829 are compared with actual operating experience as contained in the initiating events database

An Overview of the Reliability and Availability Data System (RADS)

The Reliability and Availability Data System (RADS) is a database and analysis code, developed by the Idaho National Engineering and Environmental Laboratory (INEEL) for the U.S. Nuclear Regulatory Commission (USNRC). The code is designed to estimate industry and plant-specific reliability and availability parameters for selected components in risk-important systems and initiating events for use in risk-informed applications. The RADS tool contains data and information based on actual operating experience from U.S. commercial nuclear power plants. The data contained in RADS is kept up-to-date by loading the most current quarter's Equipment Performance and Information Exchange (EPIX) data and by yearly lods of initiating event data from licensee event reports (LERS). The reliability parameters estimated by RADS are (1) probability of failure on demand, (2) failure rate during operation (used to calculate failure to run probability) and (3) time trends in reliability parameters

Westinghouse Reactor Protection System Unavailability, 1984--1995

An analysis was performed of the safety-related performance of the reactor protection system (RPS) at U. S. Westinghouse commercial reactors during the period 1984 through 1995. RPS operational data were collected from the Nuclear Plant Reliability Data System and Licensee Event Reports. A risk-based analysis was performed on the data to estimate the observed unavailability of the RPS, based on a fault tree model of the system. Results were compared with existing unavailability estimates from Individual Plant Examinations and other reports

General Electric Reactor Protection System Unavailability, 1984--1995

An analysis was performed of the safety-related performance of the reactor protection system (RPS) at U. S. General Electric commercial reactors during the period 1984 through 1995. RPS operational data were collected from the Nuclear Plant Reliability Data System and Licensee Event Reports. A risk-based analysis was performed on the data to estimate the observed unavailability of the RPS, based on a fault tree model of the system. Results were compared with existing unavailability estimates from Individual Plant Examinations and other reports

Atlantic bluefin tuna spawn at suboptimal temperatures for their offspring

Life-history traits such as spawning migrations and timing of reproduction are adaptations to specific environmental constraints and seasonal cycles in many organisms’ annual routines. In this study we analyse how offspring fitness constrains spawning phenology in a large migratory apex predator, the Atlantic bluefin tuna. The reproductive schedule of Atlantic bluefin tuna varies between spawning sites, suggesting plasticity to local environ- mental conditions. Generally, temperature is considered to be the main constraint on tuna spawning phenology. We combine evidence from long- term field data, temperature-controlled rearing experiments on eggs and larvae, and a model of egg fitness, and show that Atlantic bluefin tuna do not spawn to optimize egg and larval temperature exposure. The timing of spawning leads to temperature exposure considerably lower than optimal at all spawning grounds across the Atlantic Ocean. The early spawning is constrained by thermal inhibition of egg hatching and larval growth rates, but some other factors must prevent later spawning. Matching offspring with ocean productivity and the prey peak might be an important driver for bluefin tuna spawning phenology. This finding is important for predictions of reproductive timing in future climate warming scenarios for bluefin tuna.Versión del edito

Pelagic habitat and offspring survival in the eastern stock of Atlantic bluefin tuna

In this manuscript, we test how an understanding of geographical variation in larval fitness in relation to temperature and habitat use could be a useful method to improve our understanding of recruitment and develop better indices of annual recruitment. On the basis of the assumption that growth and survival of tuna larvae are influenced by temperature, we have developed a potential larval survival index for Atlantic bluefin tuna (Thunnus thynnus) by combining empirical data from egg and larval rearing experiments with temperature data from hydrodynamic models. The experiments were designed to test the full range of temperature variability that bluefin larvae would experience in the field and provide a mechanistic understanding of the processes driving egg and larval survival. We then developed a biological model using the temperature-related growth expressions and a size-dependent survival function for the larvae. The biological model was applied to a time-series of spatially explicit temperature data for the western Mediterranean from the Strait of Gibraltar to 6 E, which includes the major recognized bluefin tuna eastern stock spawning area, the Balearic Sea. Our results show that areas with high probabilities of larval survival coincide with those that would be considered as optimal based on other data sources (ichthyoplankton surveys, spawning female locations from commercial fisheries data, and adult tracking data). However, evidence of spawning has been found in areas with suboptimal thermal habitats, as predicted by the model, which we discuss regarding sampling effort and salinity fronts. There was a good match between the survival index and recruitment indices from standardized CPUE fisheries data. These results have implications for our understanding of the recruitment process of the eastern stock of Atlantic bluefin tuna, since they suggest that the combined effects of temporal and spatial variability of the environment drive recruitment success, which has important implications for the management of the species.Versión del editor2,27

Gene Expression Profiling Predicts Survival in Conventional Renal Cell Carcinoma

BACKGROUND: Conventional renal cell carcinoma (cRCC) accounts for most of the deaths due to kidney cancer. Tumor stage, grade, and patient performance status are used currently to predict survival after surgery. Our goal was to identify gene expression features, using comprehensive gene expression profiling, that correlate with survival. METHODS AND FINDINGS: Gene expression profiles were determined in 177 primary cRCCs using DNA microarrays. Unsupervised hierarchical clustering analysis segregated cRCC into five gene expression subgroups. Expression subgroup was correlated with survival in long-term follow-up and was independent of grade, stage, and performance status. The tumors were then divided evenly into training and test sets that were balanced for grade, stage, performance status, and length of follow-up. A semisupervised learning algorithm (supervised principal components analysis) was applied to identify transcripts whose expression was associated with survival in the training set, and the performance of this gene expression-based survival predictor was assessed using the test set. With this method, we identified 259 genes that accurately predicted disease-specific survival among patients in the independent validation group (p < 0.001). In multivariate analysis, the gene expression predictor was a strong predictor of survival independent of tumor stage, grade, and performance status (p < 0.001). CONCLUSIONS: cRCC displays molecular heterogeneity and can be separated into gene expression subgroups that correlate with survival after surgery. We have identified a set of 259 genes that predict survival after surgery independent of clinical prognostic factors

Influence of the Seasonal Thermocline on the Vertical Distribution of Larval Fish Assemblages Associated with Atlantic Bluefin Tuna Spawning Grounds

Temperature is often an important variable influencing the vertical position of fish larvae in the water column. The same species may show different vertical distributions in areas with a strong near-surface seasonal thermocline compared to isothermal near-surface regions. In areas with a strong surface thermocline, tuna larvae show a significant preference for the near-surface warmer layers. Little is known regarding larval tuna vertical distribution in isothermal waters and on the vertical distribution of the associated larval fish assemblages. We conducted vertical stratified sampling using the same methodology and fishing device (MOCNESS) in the two major spawning areas of Atlantic bluefin tuna (BFT): western Mediterranean Sea (MED), characterized by a surface thermocline, and the Gulf of Mexico (GOM) which lacks thermal stratification. Tuna larvae occupied the upper 30 m in both areas, but the average larval depth distribution was consistently deeper in the GOM. In the MED, vertical distribution of larval fish assemblages was explained by temperature, and species such as BFT, Thunnus alalunga, and Ceratoscopelus maderensis, among others, coexist above the thermocline and are separated from species such as Cyclothone braueri and Hygophum spp. (found below the thermocline). In the GOM, the environmental correlates of the vertical distribution of the larvae were salinity and fluorescence. Mesopelagic taxa such as Ceratoscopelus spp. and Cyclothone spp., among others, had a shallower average distribution than Lampanyctus spp., Hygophum spp., and Myctophum spp.Versión del edito