Engineering Papers⌕ Search

Engineering topics

Lybeck, Nancy

Publications and source records attributed to Lybeck, Nancy.

15 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Nuclear Data Management and Analysis System Plan

The United States Department of Energy Advanced Reactor Technologies Program was formed in Fiscal Year 2015 and encompasses the Next Generation Nuclear Plant Project and Very High Temperature Reactor (VHTR) Program as they were known previously. The VHTR Program was created to support design and licensing of the first VHTR nuclear plant. Data created for and used by the program must be qualified for use, stored in a readily accessible electronic form, categorized to assure the correct data are used, and controlled to prevent data corruption or inadvertent changes. The Nuclear Data Management and Analysis System was designed to support the data needs of the VHTR Program, at the time and now the Advanced Reactor Technologies Program. Since its inception, use of the Nuclear Data Management and Analysis System has expanded to support additional projects and programs with similar requirements for control, analysis, and availability of large data sets.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Analytics-at-scale of Sensor Data for Digital Monitoring in Nuclear Plants (4th Annual Report)

Nuclear plant sites collect and store large volumes of data collected from various equipment and systems. These datasets typically include plant process parameters, maintenance records, technical logs, online monitoring data, and equipment failure data. The collection of such data affords an opportunity to leverage data-driven machine learning and artificial intelligence technologies to provide diagnostic and prognostic capabilities within the nuclear power industry to reduce operating and maintenance costs. In this way, nuclear energy can become more economically competitive with other energy sources, and premature closures can be avoided. From a maintenance standpoint, savings can be achieved by leveraging machine learning and artificial intelligence technologies to develop data-driven algorithms to better diagnose and predict potential faults within the system. Improved model accuracy can lead to reductions in unnecessary maintenance and more efficient planning of future maintenance, thus lowering the costs associated with parts, labor, and unnecessary planned, forced, or extended outages. From an operations perspective, cost savings can be generated by shifting from route-based monitoring to wireless technologies for online monitoring, and by transitioning from onsite- to cloud-based computing and storage services. Wireless monitoring would reduce the operator manhours required for taking routine measurements, while cloud computing services would generate cost savings by reducing the amount of hardware needing to be purchased and maintained—all while scaling to both computational and storage demands. This report summarizes this project’s effort to shift from costly, labor-intensive preventative maintenance to cheaper predictive maintenance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Cladding Profilometry Analysis of Experimental Breeder Reactor-II Metallic Fuel Pins with HT9, D9, and SS316 Cladding

BISON finite element method fuel performance simulations were conducted using an existing automated process that couples the Fuels Irradiation & Physics Database (FIPD) and the Integral Fast Reactor Materials Information System database by writing input files and comparing the BISON output to post-irradiation fuel pin profilometry measurements contained within the databases. The importance of this work is to demonstrate the ability to benchmark fuel performance metallic fuel models within BISON using Experimental Breeder Reactor-II fuel pin data for a number of similar pins, while building off previous modeling efforts. Changes to the generic BISON input file include implementing pin specific axial power and flux profiles, pin specific fluences, frictional contact, and irradiation-induced volumetric swelling models for cladding. A statistical analysis of irradiation-induced volumetric swelling models for HT9, D9, and SS316 was performed for experiments X421/X421A, X441/X441A, and X486. Between these three experiments, there were 174 post-irradiation examination (PIE) profilometries used for validating the swelling models presented using a standard error of the estimate (SEE) method. Implementation of the volumetric swelling models for D9 and SS316 claddings was found to have a significant impact on the BISON profilometry simulated, where HT9 clad pins had an insignificant change due to low fluence values. BISON profilometry simulated for HT9, D9, and SS316 fuel pins agreed with PIE profilometry measurements, with assembly SEE values being 4.4 × 10−3 for X421A, 2.0 × 10−3 for X441A, and 2.8 × 10−3 for X486. D9 clad pins in X421/X421A had the highest SEE values, which is due to the BISON simulated profilometry being shifted axially. While this work accomplished its purpose to demonstrate the modeling of multiple fuel pins from the databases to help validate models, the results suggest that the continued development of metallic fuel models is necessary for qualifying new metallic fuel systems to better capture some physical performance phenomena, such as the hot pressing of U-Pu-Zr and the fuel cladding chemical interaction.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Statistical Sampling Plan for AGR-5/6/7 Fuel Materials

Kernels, coated particles, and compacts will be manufactured to predefined specifications for irradiation in the AGR 5/6/7 experiments. Many tests will be performed for quality assurance and most of these tests correspond to criteria that have to be met with 95% confidence, based on random samples. This report describes the statistical acceptance testing methods and gives minimum sample sizes for kernels to achieve 95% confidence. Coated particles and compacts will be addressed in revisions to this report. The methods used for sample size determination are described in detail in INL/EXT 05 00349, Statistical Methods Handbook for Advanced Gas Reactor Fuel Materials (Einerson 2005). The statistical approach is to collect a representative sample, apply an acceptance test to the sample, and accept or reject the product based on this test for each criterion. The criteria or “product specifications” are contained in SPC-1352, “AGR 5/6/7 Fuel Specification,” Revision 1 and are duplicated in this plan.

+↗
DOE OSTI2015

Alloy 617 Isochronous Stress-Strain Curves

The development of isochronous stress-strain curves is an important piece of the code case for Alloy 617. A 2-parameter creep equation was used to model creep based on test results at INL. The Ramberg-Osgood and Voce equations were used to generate hot tensile curves based on INL test results at different temperatures. Both the isochronous and hot tensile curves were then shifted to represent the average heat of Alloy 617.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Prognostic and health management of active assets in nuclear power plants

This study presents the development of diagnostic and prognostic capabilities for active assets in nuclear power plants (NPPs). The research was performed under the Advanced Instrumentation, Information, and Control Technologies Pathway of the Light Water Reactor Sustainability Program. Idaho National Laboratory researched, developed, implemented, and demonstrated diagnostic and prognostic models for generator step-up transformers (GSUs). The Fleet-Wide Prognostic and Health Management (FW-PHM) Suite software developed by the Electric Power Research Institute was used to perform diagnosis and prognosis. As part of the research activity, Idaho National Laboratory implemented 22 GSU diagnostic models in the Asset Fault Signature Database and two wellestablished GSU prognostic models for the paper winding insulation in the Remaining Useful Life Database of the FW-PHM Suite. The implemented models along with a simulated fault data stream were used to evaluate the diagnostic and prognostic capabilities of the FW-PHM Suite. Knowledge of the operating condition of plant asset gained from diagnosis and prognosis is critical for the safe, productive, and economical long-term operation of the current fleet of NPPs. This research addresses some of the gaps in the current state of technology development and enables effective application of diagnostics and prognostics to nuclear plant assets.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Uncertainty Quantification of Calculated Temperatures for the U.S. Capsules in the AGR-2 Experiment

A series of Advanced Gas Reactor (AGR) irradiation experiments are being conducted within the Advanced Reactor Technology (ART) Fuel Development and Qualification Program. The main objectives of the fuel experimental campaign are to provide the necessary data on fuel performance to support fuel process development, qualify a fuel design and fabrication process for normal operation and accident conditions, and support development and validation of fuel performance and fission product transport models and codes (PLN-3636). The AGR-2 test was inserted in the B-12 position in the Advanced Test Reactor (ATR) core at Idaho National Laboratory (INL) in June 2010 and successfully completed irradiation in October 2013, resulting in irradiation of the TRISO fuel for 559.2 effective full power days (EFPDs) during approximately 3.3 calendar years. The AGR-2 data, including the irradiation data and calculated results, were qualified and stored in the Nuclear Data Management and Analysis System (NDMAS) (Pham and Einerson 2014). To support the U.S. TRISO fuel performance assessment and to provide data for validation of fuel performance and fission product transport models and codes, the daily as-run thermal analysis has been performed separately on each of four AGR-2 U.S. capsules for the entire irradiation as discussed in (Hawkes 2014). The ABAQUS code’s finite element-based thermal model predicts the daily average volume-average fuel temperature and peak fuel temperature in each capsule. This thermal model involves complex physical mechanisms (e.g., graphite holder and fuel compact shrinkage) and properties (e.g., conductivity and density). Therefore, the thermal model predictions are affected by uncertainty in input parameters and by incomplete knowledge of the underlying physics leading to modeling assumptions. Therefore, alongside with the deterministic predictions from a set of input thermal conditions, information about prediction uncertainty is instrumental for the ART program decision-making. Well defined and reduced uncertainty in model predictions helps increase the quality of and confidence in the AGR technical findings.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2013

Development of Yield and Tensile Strength Design Curves for Alloy 617

The U.S. Department of Energy Very High Temperature Reactor Program is acquiring data in preparation for developing an Alloy 617 Code Case for inclusion in the nuclear section of the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel (B&PV) Code. A draft code case was previously developed, but effort was suspended before acceptance by ASME. As part of the draft code case effort, a database was compiled of yield and tensile strength data from tests performed in air. Yield strength and tensile strength at temperature are used to set time independent allowable stress for construction materials in B&PV Code, Section III, Subsection NH. The yield and tensile strength data used for the draft code case has been augmented with additional data generated by Idaho National Laboratory and Oak Ridge National Laboratory in the U.S. and CEA in France. The standard ASME Section II procedure for generating yield and tensile strength at temperature is presented, along with alternate methods that accommodate the change in temperature trends seen at high temperatures, resulting in a more consistent design margin over the temperature range of interest.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Online Monitoring of Plant Assets in the Nuclear Industry

Today’s online monitoring technologies provide opportunities to perform predictive and proactive health management of assets within many different industries, in particular the defense and aerospace industries. The nuclear industry can leverage these technologies to enhance safety, productivity, and reliability of the aging fleet of existing nuclear power plants. The U.S. Department of Energy’s Light Water Reactor Sustainability Program is collaborating with the Electric Power Research Institute’s (EPRI’s) Long-Term Operations program to implement online monitoring in existing nuclear power plants. Proactive online monitoring in the nuclear industry is being explored using EPRI’s Fleet-Wide Prognostic and Health Management (FW-PHM) Suite software, a set of web-based diagnostic and prognostic tools and databases that serves as an integrated health monitoring architecture. This paper focuses on development of asset fault signatures used to assess the health status of generator step-up transformers and emergency diesel generators in nuclear power plants. Asset fault signatures describe the distinctive features based on technical examinations that can be used to detect a specific fault type. Fault signatures are developed based on the results of detailed technical research and on the knowledge and experience of technical experts. The Diagnostic Advisor of the FW-PHM Suite software matches developed fault signatures with operational data to provide early identification of critical faults and troubleshooting advice that could be used to distinguish between faults with similar symptoms. This research is important as it will support the automation of predictive online monitoring techniques in nuclear power plants to diagnose incipient faults, perform proactive maintenance, and estimate the remaining useful life of assets.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2012

An Assessment of Integrated Health Management Frameworks

In order to meet the ever increasing demand for energy, the United States nuclear industry is turning to life extension of existing nuclear power plants (NPPs). Economically ensuring the safe, secure, and reliable operation of aging NPPs presents many challenges. The 2009 Light Water Reactor Sustainability Workshop identified online monitoring of active and structural components as essential to better understanding and management of the challenges posed by aging NPPs. Additionally, there is increasing adoption of condition-based maintenance (CBM) for active components in NPPs. These techniques provide a foundation upon which a variety of advanced online surveillance, diagnostic, and prognostic techniques can be deployed to continuously monitor and assess the health of NPP systems and components. The next step in the development of advanced online monitoring is to move beyond CBM to estimating the remaining useful life of active components using prognostic tools. Deployment of prognostic health management (PHM) on the scale of an NPP requires the use of an integrated health management (IHM) framework - a software product (or suite of products) used to manage the necessary elements needed for a complete implementation of online monitoring and prognostics. This paper provides a thoughtful look at the desirable functions and features of IHM architectures. A full PHM system involves several modules, including data acquisition, system modeling, fault detection, fault diagnostics, system prognostics, and advisory generation (operations and maintenance planning). The standards applicable to PHM applications are indentified and summarized. A list of evaluation criteria for PHM software products, developed to ensure scalability of the toolset to an environment with the complexity of an NPP, is presented. Fourteen commercially available PHM software products are identified and classified into four groups: research tools, PHM system development tools, deployable architectures, and peripheral tools.

Lybeck, Nancy↗
DOE OSTI2011

Prognostics and Life Beyond 60 Years for Nuclear Power Plants

Safe, secure, reliable and sustainable energy supply is vital for advanced and industrialized life styles. To meet growing energy demand there is interest in longer term operation (LTO) for the existing nuclear power plant fleet and enhancing capabilities in new build. There is increasing use of condition based maintenance (CBM) for active components and growing interest in deploying on-line monitoring instead of periodic in service inspection (ISI) for passive systems. Opportunities exist to move beyond monitoring and diagnosis based on pattern recognition and anomaly detection to prognostics with the ability to provide an estimate of remaining useful life (RUL). The adoption of digital I&C systems provides a framework within which added functionality including on-line monitoring can be deployed, and used to maintain and even potentially enhance safety, while at the same time improving planning and reducing both operations and maintenance costs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2011

High Temperature Materials Interim Data Qualification Report FY 2011

Projects for the very high temperature reactor (VHTR) Technology Development Office provide data in support of Nuclear Regulatory Commission licensing of the VHTR. Fuel and materials to be used in the reactor are tested and characterized to quantify performance in high temperature and high fluence environments. The VHTR program has established the Next Generation Nuclear Plant (NGNP) Data Management and Analysis System (NDMAS) to ensure that VHTR data are qualified for use, stored in a readily accessible electronic form, and analyzed to extract useful results. This document focuses on the first NDMAS objective. It describes the High Temperature Materials characterization data stream, the processing of these data within NDMAS, and reports the interim fiscal year (FY) 2011 qualification status of the data. Data qualification activities within NDMAS for specific types of data are determined by the data qualification category assigned by the data generator. The High Temperature Materials data are being collected under the Nuclear Quality Assurance (NQA)-1 guidelines and will be qualified data. For NQA-1 qualified data, the qualification activities include: (1) capture testing to confirm that the data stored within NDMAS are identical to the raw data supplied, (2) accuracy testing to confirm that the data are an accurate representation of the system or object being measured, and (3) documenting that the data were collected under an NQA-1 or equivalent Quality Assurance program. Currently, data from seven test series within the High Temperature Materials data stream have been entered into the NDMAS vault, including tensile tests, creep tests, and cyclic tests. Of the 5,603,682 records currently in the vault, 4,480,444 have been capture passed, and capture testing is in process for the remaining 1,123,238.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2010

High Temperature Materials Interim Data Qualification Report

ABSTRACT Projects for the very high temperature reactor (VHTR) Technology Development Office provide data in support of Nuclear Regulatory Commission licensing of the VHTR. Fuel and materials to be used in the reactor are tested and characterized to quantify performance in high temperature and high fluence environments. The VHTR program has established the NGNP Data Management and Analysis System (NDMAS) to ensure that VHTR data are qualified for use, stored in a readily accessible electronic form, and analyzed to extract useful results. This document focuses on the first NDMAS objective. It describes the High Temperature Materials characterization data stream, the processing of these data within NDMAS, and reports the interim FY2010 qualification status of the data. Data qualification activities within NDMAS for specific types of data are determined by the data qualification category assigned by the data generator. The High Temperature Materials data are being collected under NQA-1 guidelines, and will be qualified data. For NQA-1 qualified data, the qualification activities include: (1) capture testing, to confirm that the data stored within NDMAS are identical to the raw data supplied, (2) accuracy testing to confirm that the data are an accurate representation of the system or object being measured, and (3) documenting that the data were collected under an NQA-1 or equivalent Quality Assurance program. Currently, data from two test series within the High Temperature Materials data stream have been entered into the NDMAS vault: 1. Tensile Tests for Sm (i.e., Allowable Stress) Confirmatory Testing – 1,403,994 records have been inserted into the NDMAS database. Capture testing is in process. 2. Creep-Fatigue Testing to Support Determination of Creep-Fatigue Interaction Diagram – 918,854 records have been processed and inserted into the NDMAS database. Capture testing is in process.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗