scholarly journals Technical Maturity Assessment of Risk-Informed Safety Analysis Tools

2020 ◽  
Author(s):  
Yong-Joon Choi
Keyword(s):  
Best Practice ◽  
Safety Margin ◽  
Assessment Method ◽  
Nuclear Industry ◽  
Analysis Tool ◽  
Program Optimization ◽  
Analysis Tools ◽  
Maturity Assessment ◽  
Safety Margins ◽  
Requirement Traceability

Abstract Ensuring maximum safety while enhancing economic benefit is one of most important goal of In the of US Light Water Reactor Sustainability (LWRS) program. Optimization of the safety margins will provide best practice to achieve this goal which can also lead to cost reduction. Under the LWRS framework, the Risk-Informed Systems Analysis (RISA) Pathway has been focusing on the optimization of safety margin and minimization of uncertainties to ensure both safety and economics at the highest level. One of the important activities of the pathway is to deploy risk-informed analysis tools to related nuclear industry to support precise representation of safety margins and factors that contribute to cost and safety. The tools therefore need highest technical maturity so that industry can use immediately with strong credibility. The tools should have a capability to support risk-informed decision making for both probabilistic and deterministic elements of safety. The RISA Pathway, therefore, have been performing a comprehensive assessment of technical maturity and verification and validation (V&V) status of selected tools to improve adaptability to the industry. The technical maturity assessment includes three work scope: (a) define requirements based on risk-informed concept; (b) investigate and review development and V&V status for technical maturity assessment; and (c) identify technical gap and propose improvement to meet RISA toolkit requirements. The Requirement Traceability Matrix (RTM) concept was used to capture the requirements from user and developer of the project and/or software. The importance of each requirements was evaluated by Phenomena Identification and Ranking Technology (PIRT) which systematically gathers information and ranks the importance of the information. Finally, degree of the maturity was measured by Technology Readiness Level (TRL) for estimating the maturity of the technologies during the development and acquisition phase of certain technology. This paper summarizes development of assessment method and technical evaluation of multi-purpose probabilistic risk analysis tool RAVEN.

Best Estimate Plus Uncertainty Analysis of LBLOCA for a Pickering B CANDU Reactor

2010 ◽  
Author(s):  
Larry Blake ◽  
George Gavrus ◽  
Jack Vecchiarelli ◽  
J. Stoklosa
Keyword(s):  
Power Plants ◽  
Safety Margin ◽  
Reactor Power ◽  
Natural Uranium ◽  
Nuclear Industry ◽  
Initial Increase ◽  
Power Pulse ◽  
Pulse Phase ◽  
Best Estimate ◽  
Safety Margins

The Pickering B Nuclear Generating Station consists of four CANDU reactors. These reactors are horizontal pressure tube, heavy water cooled and moderated reactors fuelled with natural uranium. Under a postulated large break loss of coolant accident (LOCA), positive reactivity results from coolant void formation. The transient is terminated by the operation of the safety systems within approximately 2 seconds of the start of the transient. The initial increase in reactor power, terminated by the action of the safety system, is termed the power pulse phase of the accident. In many instances the severity of an LBLOCA can be characterized by the adiabatic energy deposited to the fuel during this phase of the accident. Historically, Limit of Operating Envelope (LOE) calculations have been used to characterize the severity of the accident. LOE analyses are conservative analyses in which the key operational and safety related parameters are set to conservative or limiting values. Limit based analyses of this type result in calculated transient responses that will differ significantly from the actual expected response of the station. As well, while the results of limit calculations are conservative, safety margins and the degree of conservatism is generally not known. As a result of these factors, the use of Best Estimate Plus Uncertainty (BEPU) analyses in safety analyses for nuclear power plants has been increasing. In Canada, the nuclear industry has been pursuing best estimate analysis through the BEAU (Best Estimate Analysis and Uncertainty) methodology in order to obtain better characterization of the safety margins. This approach is generally consistent with those used internationally. Recently, a BEAU analysis of the Pickering B NGS was completed for the power pulse phase of a postulated Large Break LOCA. The analysis comprised identification of relevant phenomena through a Phenomena Identification and Ranking (PIRT) process, assessment of the code input uncertainties, sensitivity studies to quantify the significance of the input parameters, generation of a functional response surface and its validation, and determination of the safety margin. The results of the analysis clearly demonstrate that the Limit of Operating Envelope (LOE) results are significantly conservative relative to realistic analysis even when uncertainties are considered. In addition, the extensive sensitivity analysis performed to supplement the primary result provides insight into the primary contributors to the results.

A Simplified Methodology for Extremely Low-Probability Rupture Prediction for PWR LBB Applications

2011 ◽  
Author(s):  
Heqin Xu ◽  
Ashok Nana ◽  
Samer Mahmoud ◽  
Doug Killian
Keyword(s):  
Conditional Probability ◽  
Assessment Tool ◽  
Safety Margin ◽  
Nuclear Industry ◽  
Leak Rate ◽  
Fluid System ◽  
Design Basis ◽  
Safety Margins ◽  
Low Probability ◽  
The U.S

The leak-before-break (LBB) applicability is stated in General Design Criterion 4 (GDC-4) of Title 10 of the Code of Federal Regulation Part 50 (10 CFR 50). GDC-4 requires that analyses reviewed and approved by the U.S. Nuclear Regulatory Commission (NRC) demonstrate that the probability of fluid system piping rupture is extremely low under conditions consistent with the design basis for the piping, in order that dynamic effects associated with postulated pipe ruptures in nuclear power units may be excluded from the design basis. Standard review plan 3.6.3 (SRP-3.6.3) further requires a simultaneous safety margin of two and ten on the flaw size and leak rate detectability, respectively, for deterministic analyses, believing that the very conservative and restrictive safety margins would lead to extremely low probability of fluid system piping rupture. The technology advancements of recent years make it possible to numerically quantify the probability of rupture with confidence. Planned for completion within the next six years, a long-term, large-scale assessment tool, xLPR, is currently being developed by the U.S. NRC, in cooperation with the nuclear industry, to assess the extremely low probability of rupture. The tool will include comprehensive evaluations both before and after through-wall cracks are developed in the degraded components. In this study, we are going to utilize a simplified methodology to investigate the probability of piping rupture for a postulated through-wall crack. The conditional probability, when multiplied by the probability of having a through-wall crack during the life time of plant service, produces an overall probability of piping rupture. The major quantifiable uncertainties, such as the uncertainties associated with the material tensile properties and fracture toughness, and flow-path crack morphology parameters will be modeled as correlated random variables in this paper. Efficient Dimension-Reduction methods will be applied to predict this conditional probability and the results will be compared with the Monte Carlo simulation method. As a sample application of the proposed method, the relationship between the magnitude of the conditional probabilities and the required leak rate detection capability will be established.

scholarly journals Bootstrap and Order Statistics for Quantifying Thermal-Hydraulic Code Uncertainties in the Estimation of Safety Margins

2008 ◽  
Vol 2008 ◽  
pp. 1-9 ◽  
Author(s):  
Enrico Zio ◽  
Francesco Di Maio
Keyword(s):  
Confidence Interval ◽  
Order Statistics ◽  
Nuclear Reactor ◽  
Safety Margin ◽  
Fuel Cladding ◽  
Complete Group ◽  
Bootstrap Technique ◽  
Safety Margins ◽  
Group Distribution

In the present work, the uncertainties affecting the safety margins estimated from thermal-hydraulic code calculations are captured quantitatively by resorting to the order statistics and the bootstrap technique. The proposed framework of analysis is applied to the estimation of the safety margin, with its confidence interval, of the maximum fuel cladding temperature reached during a complete group distribution blockage scenario in a RBMK-1500 nuclear reactor.

A New Analysis Tool for Continuous Glucose Monitor Data

2021 ◽  
pp. 193229682110289
Author(s):  
Evan Olawsky ◽  
Yuan Zhang ◽  
Lynn E Eberly ◽  
Erika S Helgeson ◽  
Lisa S Chow
Keyword(s):  
Glucose Monitoring ◽  
Glycemic Variability ◽  
R Package ◽  
Analysis Tool ◽  
Continuous Glucose Monitor ◽  
Analysis Tools ◽  
R Shiny ◽  
Primary Driver ◽  
Rich Information ◽  
Web App

Background: With the development of continuous glucose monitoring systems (CGMS), detailed glycemic data are now available for analysis. Yet analysis of this data-rich information can be formidable. The power of CGMS-derived data lies in its characterization of glycemic variability. In contrast, many standard glycemic measures like hemoglobin A1c (HbA1c) and self-monitored blood glucose inadequately describe glycemic variability and run the risk of bias toward overreporting hyperglycemia. Methods that adjust for this bias are often overlooked in clinical research due to difficulty of computation and lack of accessible analysis tools. Methods: In response, we have developed a new R package rGV, which calculates a suite of 16 glycemic variability metrics when provided a single individual’s CGM data. rGV is versatile and robust; it is capable of handling data of many formats from many sensor types. We also created a companion R Shiny web app that provides these glycemic variability analysis tools without prior knowledge of R coding. We analyzed the statistical reliability of all the glycemic variability metrics included in rGV and illustrate the clinical utility of rGV by analyzing CGM data from three studies. Results: In subjects without diabetes, greater glycemic variability was associated with higher HbA1c values. In patients with type 2 diabetes mellitus (T2DM), we found that high glucose is the primary driver of glycemic variability. In patients with type 1 diabetes (T1DM), we found that naltrexone use may potentially reduce glycemic variability. Conclusions: We present a new R package and accompanying web app to facilitate quick and easy computation of a suite of glycemic variability metrics.

scholarly journals Towards the Development of Language Analysis Tools for the Written Latgalian Language

2020 ◽  
Author(s):  
Daiga Deksne ◽  
Anna Vulāne
Keyword(s):  
Web Service ◽  
Morphological Analysis ◽  
Written Language ◽  
Analysis Tool ◽  
Tool Development ◽  
Joint Effort ◽  
Analysis Tools ◽  
Language Analysis ◽  
Wide Range ◽  
Development Of Language

This paper reports on the development of spell checking and morphological analysis tools for Latgalian. The Latgalian written language is a historic variant of the Latvian language. There is a wide range of language analysis tools available for Latvian, whereas the Latgalian language lacks such tools. The work is done by the joint effort of linguists who work on morphologically marked lexicon creation and IT specialists who work on language tool development. For the creation of a morphological analysis tool, we reuse the FST technology used for the Latvian morphological analyzer. We create a spelling dictionary that can be used with the Hunspell engine. All tools are accessible via Web Service. For now, the Latgalian lexicon contains 13,139 lemmas marked by 105 inflection groups. The work of lexicon replenishment still continues.

scholarly journals StrainPro – a highly accurate Metagenomic strain-level profiling tool

2019 ◽  
Author(s):  
Hsin-Nan Lin ◽  
Yaw-Ling Lin ◽  
Wen-Lian Hsu
Keyword(s):  
Microbial Community ◽  
Relative Abundance ◽  
Taxonomic Diversity ◽  
Evaluation Study ◽  
Taxonomic Composition ◽  
Strain Level ◽  
Metagenomic Analysis ◽  
Reference Database ◽  
Analysis Tool ◽  
Analysis Tools

ABSTRACTCharacterizing the taxonomic diversity of a microbial community is very important to understand the roles of microorganisms. Next generation sequencing (NGS) provides great potential for investigation of a microbial community and leads to Metagenomic studies. NGS generates DNA fragment sequences directly from microorganism samples, and it requires analysis tools to identify microbial species (or taxonomic composition) and estimate their relative abundance in the studied community. However, only a few tools could achieve strain-level identification and most tools estimate the microbial abundances simply according to the read counts. An evaluation study on metagenomic analysis tools concludes that the predicted abundance differed significantly from the true abundance. In this study, we present StrainPro, a novel metagenomic analysis tool which is highly accurate both at characterizing microorganisms at strain-level and estimating their relative abundances. A unique feature of StrainPro is it identifies representative sequence segments from reference genomes. We generate three simulated datasets using known strain sequences and another three simulated datasets using unknown strain sequences. We compare the performance of StrainPro with seven existing tools. The results show that StrainPro not only identifies metagenomes with high precision and recall, but it is also highly robust even when the metagenomes are not included in the reference database. Moreover, StrainPro estimates the relative abundance with high accuracy. We demonstrate that there is a strong positive linear relationship between observed and predicted abundances.

scholarly journals IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites

mBio ◽  
2015 ◽  
Vol 6 (4) ◽  
Author(s):  
Michalis Hadjithomas ◽  
I-Min Amy Chen ◽  
Ken Chu ◽  
Anna Ratner ◽  
Krishna Palaniappan ◽  
...  
Keyword(s):  
Secondary Metabolites ◽  
Secondary Metabolism ◽  
Genomic Data ◽  
Gene Clusters ◽  
Metagenomic Data ◽  
Integrated Analysis ◽  
Analysis Tool ◽  
Biosynthetic Gene ◽  
Biosynthetic Gene Clusters ◽  
Analysis Tools

ABSTRACTIn the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.gov/abc), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of “big” genomic data for discovering small molecules. IMG-ABC relies on IMG's comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve as the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABC's focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time inAlphaproteobacteria. IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules.IMPORTANCEIMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMG's extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG-ABC will continue to expand, with the goal of becoming an essential component of any bioinformatic exploration of the secondary metabolism world.

DESIGN OF AN ASSESSMENT METHOD BASED ON COMPETENCES BY STRATEGIC ANALYSIS TOOLS FOR SUBJECTS OF INDUSTRIAL ENGINEERING DEGREE

2016 ◽  
Author(s):  
M. Isabel Dieste-Velasco ◽  
Carmen Rodríguez-Amigo ◽  
Teófilo García-Calderón ◽  
David González Peña ◽  
Montserrat Díez-Mediavilla ◽  
...  
Keyword(s):  
Assessment Method ◽  
Industrial Engineering ◽  
Strategic Analysis ◽  
Engineering Degree ◽  
Analysis Tools
Sign in / Sign up

Export Citation Format

Share Document