test-page

LWRS researchers in collaboration with ORNL and Blue Wave AI Labs examined the capabilities, feasibility, and regulatory concerns of cloud computing in relation to meeting nuclear industry needs, specifically for achieving risk-informed predictive maintenance strategy. The technical viability of cloud computing was analyzed using data from a boiling-water reactor’s safety relief valve.

Assessment Cloud based Applications

The LWRS Digitalization Project at INL seeks to leverage digital technologies to synthesize and transform work processes. We provide a state-of-the-art analysis of digitalized work processes in nuclear power and investigate ways in which researchers at INL and the nuclear industry can work together to identify what data to access, how to access it, what to do with the data, and most importantly, how to use the insights for decision-making across all levels within the business.

Digitalization Guiding Principles

The purpose and mission of the Integrated Operations for Nuclear Business Model and research effort at Light Water Reactors Sustainability (LWRS) Program is to identify and integrate technological and programmatic changes and modernizations to nuclear plant operations. These changes, called “work reduction opportunities,” are first advanced and integrated into the integrated operations for nuclear model then verified and explored further in applied ways with partnering utilities and plant sites. As the integrated operations for nuclear model gains structure, researchers actively seek to incorporate new work reduction opportunities as components to the existing work reduction opportunities suite from ongoing research within the LWRS Program. To achieve this, each pathway in the LWRS Program was assessed, and interviews conducted with each pathway lead to gather insights into current and future research and development efforts that could contribute to the creation of new work reduction activities.

ION Cross Pathway

The report concludes by summarizing the overall effort and implications for utility modernization. The performance of the screening and TERA are discussed as well as the impact on the nuclear industry. The TERA process enables utilities to evaluate and inform investment decisions for WROs and mitigate any potential risks. Through this research, we provide utilities with a valuable framework to optimize operations, reduce costs, and drive continuous process improvement.

Development Technical Economic Risk Assessment

The purpose of this report is to communicate the next phase of research associated with the Integrated Operations for Nuclear (ION) business model advanced and detailed by the researchers who are part of the Light Water Reactor Sustainability (LWRS) Program. Previous reports detailed work-reduction opportunities and their potential impact on savings, operations and maintenance (O&M) cost reductions to domestic nuclear plants. Advancing the concept once again, researchers have developed and now tested a methodology for assessing a nuclear plant and developing a roadmap for implementation of ION. This report describes that process, which was completed with a domestic nuclear site partner.

ION Business Model

In this report we show in detail how the integration and reasoning from numeric and textual ER data elements is performed. First, we present the developed library of MBSE modelsthat focus on common NPP systems and assets. Then we show the development of computational methods designed to process and analyze numeric and textual ER data elements simultaneously. Here, we apply the developed computational methods on the circulating water system of an existing NPP. Our final considerations provide additional insights on further potential applications of these methods to support additional NPP decisions.

Analysis Methods Integrate Numeric

This document leverages these select ION WROs as a starting point to initiate a specific WRO demonstration strategy. The strategy addresses the select ION WROs categories described above with the intent of applying this outline to other WROs in the future.

ION Demonstration Strategy

While the existing U.S. light-water reactors are highly reliable and safe and provide a significant proportion of carbon-free electricity, the cost of operating and maintaining them has become less competitive compared to other electricity generating sources. The reason for the gap in operating and maintenance costs can be attributed at least in part to the advent of new digital technologies that other electricity generating industries are currently using. Advanced capabilities, including digital instrumentation and control (I&C) systems, advanced automation and analytics, and a greater span of data integration (i.e., connectedness), across these nonnuclear plants have transformed the way work is performed and ultimately given them a competitive advantage in terms of the cost required for operating, maintaining, and supporting them.

Human Technology Integration Evaluation

While the existing U.S. light-water reactors are highly reliable and safe and provide a significant proportion of carbon-free electricity, the cost of operating and maintaining them has become less competitive compared to other electricity generating sources. The reason for the gap in operating and maintenance costs can be attributed at least in part to the advent of new digital technologies that other electricity generating industries are currently using. Advanced capabilities, including digital I&C systems, advanced automation and analytics, and a greater span of data integration, across these nonnuclear plants have transformed the way work is performed and ultimately given them a competitive advantage in terms of the cost required for operating, maintaining, and supporting them.

M3LW-23IN0603089 FINAL

This report describes progress and findings for a program of research supporting the design and optimization of information automation systems for nuclear power plants (NPPs). Information automation is the customization and delivery of information for a work process, thereby providing users with intuitive, actionable information based on continuous measurements of plant performance.

Optimizing Information Automation

A review of published reports and knowledge gained by working in the nuclear energy sector will form the basis for this scoping study. This study will not seek to draw any conclusions regarding the underlying causes of these personnel issues but will attempt to ask questions and help outline future research. The Integrated Operations for Nuclear business model provides opportunities to partially mitigate some of the current issues facing staffing the nuclear fleet.

ION_Based_Approaches

Historically, nuclear power plants have operated predominantly at or near full power, meaning that most of the data collected are in this operating regime. Therefore, data-driven anomaly detection methods that are developed using this data can perform well at full power operations. This presents a challenge when the power drops (referred to as a transient) and may result in false alarms due to the lack of historical data at those new power levels. The current approach to handling this challenge is to turn the anomaly detection algorithms off during transients, causing missed detections. This effort developed and tested multiple data-driven anomaly detection methods that can extend to transient conditions.

Extending Data-Driven Anomaly Detection

Light Water Reactor Sustainability researchers at Idaho National Laboratory in collaboration with Public Service Enterprise Group (PSEG), Nuclear, LLC, completed development and demonstration of three aspects of artificial intelligence (AI) technologies: performance, explainability, and trustworthiness. The work focused on leveraging specific metrics, developing a user-centric visualization interface, and performing human-in-the-loop evaluations to build user confidence in adoption of AI and machine learning technologies for risk-informed predictive maintenance strategy. This effort, documented in INL/RPT-23-74159, concluded that the development, implementation, and sustainment of advanced AI-guided technologies will require many different types of expertise for maintenance and regulation. Deployment of AI demands bringing together a truly multidisciplinary team of experts to clearly understand broader societal implications.

Explainable Artificial Intelligence Technology

This report focuses on developing methods for applying the U.S. Nuclear Regulatory Commission (NRC)–approved guidance to implement a licensee-controlled, risk-informed surveillance frequency change program in digital instrumentation and control (I&C) systems that include self-diagnostics and online monitoring (OLM) capabilities. This report presents an evaluation of different information and data made available by the utility partner for a digital I&C system since its implementation and describes an application of the proposed methodology. The methodology seeks to take advantage of the self-diagnostics and OLM capabilities to reduce risk or reduce the level of qualitative monitoring assessment needed to perform a risk-informed surveillance test interval extension using existing NRC approved guidance or both.

Technical Specification Surveillance

This report describes the interim progress for research supporting the design and optimization of information automation systems for nuclear power plants. Much of the domestic nuclear fleet is currently focused on modernizing technologies and processes, including transitioning toward digitalization in the control room and elsewhere throughout the plant, along with a greater use of automation, artificial intelligence, robotics, and other emerging technologies.

Optimizing Information Automation Using New Method

With the advancements made to date in the field of artificial intelligence (AI), significant potential exists to utilize AI capabilities for nuclear power plant (NPP) applications. AI can replicate human decision making and it is usually faster and more accurate than humans. For implementations that impact critical NPP applications (e.g., safety-related or non-safety systems that potentially affect overall plant risk), a deeper safety analysis of the AI methods is necessary.

Use-of Computer Vision ML Safety-Related

Researchers selected nine work reduction opportunities from the full Integrated Operations for Nuclear (ION) suite of initiatives. A selected group of utilities verified details of the work reduction opportunities and inputs to the ION model first published in the original report. Verification categories included capital cost, technology requirements, and operational and maintenance savings, among others. Researchers then modeled the data points and data ranges using probabilistic analysis to predict the likelihood of positive or negative net present value outcomes.

Process Significant Nuclear Work Function Innovation

This report provides an analysis and planning framework for transforming the current NPP operating model via transferable learnings from the North Sea O&G industry. This framework is termed “Integrated Operations for Nuclear” (ION). This report describes the key principles and methods of IO and how they are being applied via collaboration between the DOE LWRSProgram and Xcel Energy in an initiative to transform the NPP operating model in order to foster performance improvement and long-term sustainability.

Analysis and Planning Framework for Nuclear Plant Transformation

Digital Infrastructure Pilot Business Case Objective One: Addressing Concerns with Implementation Costs by Demonstrating Long-Term Value of Digital I&C Modernization. The first major objective of this report and the wider LWRS research is to relieve the concern associated with prohibitively high implementation costs of plant I&C upgrades. This is addressed through demonstrating the long-term net economic value of digital upgrades with an in-depth exposition of the business case for, and detailed process associated with digital I&C modernizations.

Pilot Digital Infrastructure BCA

Researchers selected nine work reduction opportunities from the full ION. A selected group of utilities verified details of the work reduction opportunities and inputs to the ION model first published in the original report. Verification categories included capital cost, technology requirements, and operational and maintenance savings, among others. Researchers then modeled the data points and data ranges using probabilistic analysis to predict the likelihood of positive or negative net present value outcomes.

ION Operation Model Analysis

This report conducts a techno-economic assessment of a provisional cloud deployment architecture for a nuclear power plant predictive monitoring system. The cloud-based monitoring system would enable maintenance and diagnostics analysts and other authorized plant users to remotely monitor equipment functionality so as to enable predictive monitoring practices and early detection of faults. This report covers certain regulatory and security aspects that may concern licensees looking to implement cloud computing. The report also focuses on the integration of sensor database storage, the application of cloud resources to predictive maintenance, and the identification of technological and economic hurdles associated with moving to a cloud-computing-based architecture.

Development Cloud-based Application

This report identifies some of the important requirements that need to be considered as part of the data evolution for the condition-based maintenance application on a circulating water system in an nuclear power plant. The concept of data evolution converts data into information, which in turn is converted into insight, decision, and action. An overview of AI design, development, deployment, and operation principles is introduced to support the lifecycle of AI technologies.

Data Architecture Analytics Requirements AI

The nuclear power industry is data-rich and these data introduce a tremendous potential for automation and cost savings. On the other hand, research organizations, among other stakeholders, have very capable methods and solutions often developed using simulated or synthetic data due to the lack of real data. One cause of this disconnect is data privacy. Data privacy is of paramount importance in all industries, but especially the nuclear industry. This challenge motivated the data obfuscation method called deceptive infusion of data (DIOD).

Novel Data Obfuscation Method Share

Technical Basis for Advanced Artificial Intelligence and Machine Learning Adoption in Nuclear Power Plants, INL/RPT-22-68942, September 2022.

Technical Basis Advanced AIand ML

Integrated Operations for Nuclear Business Operation Model Analysis and Industry Validation, INL/RPT-22-68671, August 2022.

ION Business Operation Model Analysis

Using Information Automation and Human Technology Integration to Implement Integrated Operations for Nuclear, INL/RPT-22-68076, July 2022

Information Automation Human Technology

Nuclear Work Function Innovation Tool Set Development for Performance Improvement and Human Systems Integration, INL/EXT-21-64428, C. Kovesdi, J. Mohon, K. Thomas, J. Remer, J. Joe, L. Hanes, M. Dainoff, L. Hettinger, September 2021.

Innovation Tool Set

Report on the Use and Function of the Work Function Analysis Tool and Nuclear Innovation Portal, INL/EXT-20-59827, C. Kovesdi, K. Thomas, S. Remer, J. Boyce, September 2020.

Use Function Work Function Analysis Tool

Development of Improved Graphical Displays for an Advanced Outage Control Center, Employing Human Factors Principles for Outage Schedule Management, INL/EXT-15-36489, S. St. Germain, R. Farris, K. Thomas, September 2015.

Development Improved Graphical Displays

Benchmark Report on Key Outage Attributes: An Analysis of Outage Improvement Opportunities and Priorities, INL/EXT-14-32848, St. Germain. R. Farris, September 2014.

Benchmark Report Key Outage Attributes

Resolving Emergent Issues During Nuclear Plant Outages, INL/EXT-12-26807, G. Weatherby, K. LeBlanc, R. Farris, July 2012.

Emergent Issues

Advanced Outage and Control Center: Strategies for Nuclear Plant Outage Work Status Capabilities, INL/EXT 12 26197, G. Weatherby, May 2012.

Advanced Outage Control Center

Concrete Structure Health Monitoring Using Vibroacoustic Testing and Machine Learning, INL/EXT-20-59941, M. Miele, P. Karve, S. Mahadevan, V. Agarwal, September 2020.

Concrete Structure Health Monitoring Using Vibroacoustic

Vibration-based Techniques for Concrete Structural-health Monitoring, INL/EXT-19-53248, S. Miele, Y. Bao, P. Karve, S. Mahadevan, V. Agarwal, E. Giannini, J. Zhu, March 2019.

Vibration-based Techniques for Concrete Structural-health

Automated Work Packages: Radio Frequency Identification, Bluetooth Beacons, and Video Applications in the Nuclear Power Industry, INL/EXT-17-43264, A. Rashdan, S. St Germain, R. Boring, T. Ulrich, B. Rice, September 2017.

Automated Work Packages Radio Frequency Identification, Bluetooth Beacons, and Video Applications in the Nuclear Power Ind

Data Analysis of Different Nondestructive Testing Techniques to Monitor Concrete Structure Degradation due to Alkali-Silica Reaction, INL/EXT-16-39915, V. Agarwal, K. Neal, S. Mahadevan, B. Pham, D. Adams, September 2016.

Data Analysis of Different Nondestructive Testing Techniques to Monitor Concrete Structure Degradation due to Alkali-Silica

A Demonstration of Concrete Structural Health Monitoring Framework for Degradation due to Alkali-Silica Reaction, INL-EXT-16-38602, S. Mahadevan, V. Agarwal, K. Neal, P. Nath, Y. Bao, G. Cai, P. Orme, D. Adams, D. Kosson, April 2016.

A Demonstration of Concrete Structural Health Monitoring Framework for Degradation due to Alkali-Silica Reaction

Computer-Based Procedures for Field Workers—Result and Insights from Three Usability and Interface Design Evaluations, J. Oxstrand, K. Le Blanc, A. Bly, H. Medema, W. Hill, INL/EXT-15-36658, September 2015.

Computer-Based Procedures for Field Workers Result and Insights from Three Usability and Interface Design Evaluations

Concept for Integrated Multi-Modal Online Piping Monitoring System along with Data Fusion and Advanced Data Analytical Algorithms Using High- Resolution Fiber Optics Sensors, INL/EXT-20-59810, A. Gribok, M. Wang, J. Wu, Q. Wang, A. Venketeswaran, K. Zhao, K. Chen, September 2020.

Concept Integrated Multi-Modal Online Piping Monitoring

Automated Work Package: Conceptual Design and Data Architecture, INL-EXT-16-38809, A. Al Rashdan, J. Oxstrand, V. Agarwal, May 2016.

Automated Work Package Conceptual Design and Data Architecture

Automated Work Packages Architecture: An Initial Set of Human Factors and Instrumentation and Controls Requirements, INL/EXT-14-33172, V. Agarwal, J. Oxstrand, and K. Le Blanc, Idaho National Laboratory, September 2014.

Automated Work Packages Architecture

Computer-Based Procedures for Field Workers – FY16 Research Activities, INL/EXT-39984, J. Oxstrand, A. Bly, September 2016.

Computer-Based Procedures FY16 Research Activities

Design Guidance for Computer-Based Procedures for Field Workers, INL-EXT-16-39808, J. Oxstrand, K. Le Blanc, A. Bly, September 2016.

Design Guidance CBP for Field Workers

Computer-Based Procedures for Field Worker – Identified Benefits, INL/EXT-14-33011, J. Oxstrand, K. Le Blanc, September 2014.

Computer based Procedures for Field Workers

Computer-Based Procedures for Field Workers: Results from Three Evaluation Studies, J. Oxstrand, K. Le Blanc, and A. Bly, INL/EXT-13-30183, September 2013.

Computer Based Procedures M2LW-13IN0603098

Evaluation of Computer-Based Procedure System Prototype, J. Oxstrand, K. Le Blanc, S. Hays, INL/EXT-12-27155, September 2012.

M3LW-12IN0603092 Computer Based Procedures Report

Computer Based- Procedures for Field Workers in Nuclear Power Plants: Development of a Model of Procedure Usage and Identification of Requirements, INL/-12-25671, J. Oxstrand, K. Le Blanc, April 2012.

Computer Based-Procedures for Field Workers in Nuclear Power Plants

Development of an Advanced Integrated Operations Concept for Hybrid Control Rooms, INL/EXT-20-57862, C. Kovesdi, J. Mohon, R. Li, T. Miyake, J. Lehmer, R. Hill, Z. Spielman, T. Mortenson, K. Le Blanc, March 2020.

Development of an Advanced Integrated Operations Concept for Hybrid CR

Development and Evaluation of the Conceptual Design for a Liquid Radiological Waste System in an Advanced Hybrid Control Room, INL/EXT-18-51107, C. Kovesdi, Z. Spielman, R. Hill, K.Le Blanc, J. Oxstrand, August 2018.

Development and evaluation of the conceptual design for a liquid radiological waste system in an advanced hybrid control

Migration of Older to New Digital Control Systems in Nuclear Power Plant Main Control Rooms, INL/EXT-16-38576, C. Kovesdi, J. Joe, R. Boring, April 2016.

Migration of Older to New Digital Control Systems in Nuclear Power Plant Main Control Rooms

Verification and Validation of Digitally Upgraded Control Rooms, INL/EXT-15-36704, R. Boring, N. Lau, September 2015.

Verification and Validation of Digitally Upgraded Control Rooms

HSI Prototypes for the Human Systems Simulation Laboratory, INL/EXT-15-36839, H., Jokstad, R. McDonald, September 2015.

HSI Prototypes for the Human Systems Simulation Laboratory

Operator Performance Metrics for Control Room Modernization: A Practical Guide for Early Design Evaluation, R. Boring, J. Joe, T. Ulrich, and R. Lew, INL/EXT-14-31511 Revision 0, Idaho National Laboratory, March 2015.

LWRS 2015 M3 Report Human Performance Measures

Human Factors Engineering Design Phase Report for Control Room Modernization, T. Ulrich, R. Boring, and R. Lew, Idaho National Laboratory, INL/EXT-14-33221, September 2014.

LWRS 2014 M2 Report Design Phase Control Room Modernization Final Release

Baseline Human Factors and Ergonomics in Support of Control Room Modernization at Nuclear Power Plants, R. Boring and J. Joe, Idaho National Laboratory, INL/EXT-14-33223, September 2014.

LWRS Sept 2014 M3 Report Baseline HFE

Strategy for Migration of Traditional to Hybrid Control Boards in a Nuclear Power Plant, INL/EXT-14-32534, R. Boring, J. Joe, T. Ulrich, July 2014.

Strategy for Migration of Traditional to Hybrid Control Boards in a Nuclear Power Plant

A Reference Plan for Control Room Modernization: Planning and Analysis Phase, J. Hugo, R. Boring, L. Hanes, and K. Thomas INL/EXT-13-30109, September 2013.

Control Room Modernization M2LW-13IN0603073

Digital Full-Scope Simulation of a Conventional Nuclear Power Plant Control Room, Phase 2: Installation of a Reconfigurable Simulator to Support Nuclear Plant Sustainability, R. Boring, V. Agarwal, K. Fitzgerald, J. Hugo, B. Hallbert, INL/EXT-13-28432, March 2013.

LWRS 2013 M1 Report CR Modernization-Final

Cyber Security Evaluation of II&C Technologies, K. Thomas, Idaho National Laboratory; M. Thow, T. Kenny, L Watkins, AREVA Inc., INL/EXT-14-33609, Revision 0, November 2014.

Cyber Security Evaluation of IIandC Technologies Final

Automation Technologies Impact on the Work Process of Nuclear Power Plants, INL/EXT-18-51457, A. Rashdan, T. Mortenson, September 2018.

Automation Technologies Impact on the Work Process of Nuclear Power Plants

Automation of Data Collection Methods for Online Monitoring of Nuclear Power Plants, INL/EXT-18-51456, A. Rashdan, S. St. Germain, September 2018.

Automation of Data Collection Methods for Online Monitoring of Nuclear Power Plants

The nuclear power industry is data-rich and these data introduce a tremendous potential for automation and cost savings. On the other hand, research organizations, among other stakeholders, have very capable methods and solutions often developed using simulated or synthetic data due to the lack of real data. One cause of this disconnect is data privacy. Data privacy is of paramount importance in all industries, but especially the nuclear industry. This challenge motivated the data obfuscation method called deceptive infusion of data (DIOD).

Novel Data Obfuscation Method Share Nuclear Data

Process Anomaly Detection for Sparsely Labeled Events in Nuclear Power Plants, INL/EXT-21-64303, J. Farber, A. Al Rashdan, H. Abdel-Khalik, Y. Li, M. Abdo, D. Mandelli, D. Huang, September 2021.

Process Anomaly Detection Sparsely Labeled

The outcomes presented in this report lay the foundation and provide a much-needed technical basis for focusing on the explainability and trustworthiness of machine language and artificial intelligence-based technologies as part of future research.

Scalable Technologies Achieving Risk-Informed Condition-Based

The R&D activities reported lay the foundation to develop and demonstrate a digital automated platform to centralize the implementation of condition monitoring. Development of fault signatures and ML diagnostic models will be extended to other CWP, CWP motor, and system-level faults in the future.

Machine Learning Economic Models

An Applied Strategy for Using Empirical and Hybrid Models in Online Monitoring, INL/EXT-20-59688, A. Rashdan, H. Abdel-Khalik, K. Giraud, L. Griffel, D. Guillen, A. Varuttamaseni, September 2020.

Applied Strategy Using Empirical Hybrid Models

Automating Fire Watch in Industrial Environments through Machine Learning-Enabled Visual Monitoring, INL-EXT-19-55703, A. Rashdan, M. Griffel, L. Powell, September 2019.

Automating Fire Watch in Industrial Environments through Machine

Data Integration Aggregated Model and Ontology for Nuclear Deployment (DIAMOND): Preliminary Model and Ontology, INL/EXT-19-55610, A. Rashdan, J. Browning, C. Ritter, September 2019.

DIAMOND Preliminary Model and Ontology

Automating Surveillance Activities in a Nuclear Power Plant, INL/EXT-19-55620

Automating Surveillance Activities in Nuclear Power Plant

Subtle Process-Anomalies Detection Using Machine-Learning Methods, INL/EXT-19-55629, A. Rashdan, M. Griffel, R. Boza, D. Guillen, September 2019.

Subtle Process-Anomalies Detection Using Machine-Learning Methods

Creating a data warehouse in a plant or a data broker for a fleet of plants requires overcoming multiple challenges, including the lack of a standard form of storing and using data and the lack of integration methods to compare and map the different data sources. This effort develops and demonstrates a data integration method and application through data fusion and data warehousing pilots.

Method Application Data Integration

Developing a Roadmap for Total Nuclear Plant Transformation, INL/EXT-19-54766

Developing Roadmap Total NP Transformation

The primary objective of this proposed research project is to integrate advancements in online monitoring and data analytic techniques with advanced risk assessment methodologies to reduce operating costs and enhance the reliability of commercial nuclear power plants (NPPs).

PKMJ FOA FY18

Development of a Technology Roadmap for Online Monitoring of Nuclear Power Plants, INL/EXT-18-52206, A. Rashdan, J. Smith. S. St. Germain, C. Ritter, V. Agarwal, R. Boring, T. Ulrich, J. Hansen, December 2018.

Development of a Technology Roadmap for Online Monitoring of NPP

Requirements for Control Room Computer-Based Procedures for use in Hybrid Control Rooms, K. Le Blanc, J. Oxstrand, and J. Joe, INL/EXT-15-35284 Revision 0, Idaho National Laboratory, May 2015.

LWRS Requirements for Control Room

Report for 2.2.1 Task 3: Develop and Document an Advanced Human System Interface for the Generic Pressurized Water Reactor Simulator, INL/EXT-19-55788, R. McDonald, A. Ove Braseth, J. Joe, September 2019.

Develop Document Advanced Human Systems interface

Seamless Digital Environment – Data Analytics Use Case Study, INL/EXT-17- 42918, J. Oxstrand, A. Bly, August 2017.

Seamless Digital Environment Data Analytics Use Case Study

Digital Architecture Planning Model, INL/EXT-16-38220, J. Oxstrand, A. Al Rashdan, A. Bly, B. Rice, K. Fitzgerald, K. Wilson, March 2016.

Digital Architecture Planning Model

A Business Case for Advanced Outage Management, INL/EXT-16-38265, K. Thomas, S. Lawrie, J. Niedermuller, March 2016.

A Business Case for Advanced Outage Management

Digital Architecture – Results from a Gap Analysis, J. Oxstrand, K. Thomas, K. Fitzgerald, INL/EXT-15-36662 September 2015.

Digital Architecture

Digital Architecture Project Plan, INL/EXT-14-33177, K. Thomas, September 2014.

Digital Architecture Plan

Guidelines for Implementation of an Advanced Outage Control Center to Improve Outage Coordination, Problem Resolution, and Outage Risk Management, S. St. Germain, R. Farris. A. Whaley, H. Medema, and D. Gertman, Idaho National Laboratory, INL/EXT-14-33182, September 2014.

LWRS AOCC 2014 Milestone Report

Status Report on the Development of Micro-Scheduling Software for the Advanced Outage Control Center Project, S. St. Germain, K. Thomas, J. Joe, and R. Farris, Idaho National Laboratory, INL/EXT-14-33036, September 2014.

Status Report Development of Micro-Scheduling Software Advanced Outage Control Center Project

Development of Methodologies for Technology Deployment for Advanced Outage Control Centers That Improve Outage Coordination, Problem Resolution and Outage Risk Management, S. St. Germain, R. Farris, and H. Medema, INL/EXT-13-29934, September 2013.

Advanced Outage Control Centers M3LW-13IN0603103

Installation of Halden Reactor Project Digital Interface Prototypes in the Human Systems Simulation Laboratory, H. Jokstad, J. O. Hol, T. J. Bjorlo, A. O. Braseth, C. Nihlwing, H. Svengren, and L. Hurlen, with additional contributions by Idaho National Laboratory staff, including J. Joe, R. Boring, D. Gertman, J. Persensky, INL/EXT-13-29039, May 2013.

INL-EXT-13-29039 Halden M3LW-13IN0603023

Digital Full-Scope Mockup of a Conventional Nuclear Power Plant Control Room, Phase I: Installation of a Utility Simulator at the Idaho National Laboratory, R. Boring, V. Agarwal, J. Joe, and J. Persensky, June 2012.

LWRS Simulator Buildout Milestone Report 

This report summarizes outreach efforts to both industry wide organizations and specific utilities. Industry organizations that were engaged including the Pressurized Water Reactor Owner’s Group, the Nuclear Information Technology Strategic Leadership group, and Light Water Reactor Sustainability Plant Modernization Pathway Stakeholders.

Digital Infrastructure Industry Engagement

Digital Infrastructure Migration Framework, INL/EXT-21-64580, P. Hunton, R. England, September 2021.

Digital Infrastructure Migration Framework

​​​I&C Infrastructure Modernization Safety-Related I&C Pilot Upgrade Project at Limerick Generating Station (LGS)

I&C Infrastructure Modernization Safety-Related

This LWRS Program research seeks to assist in breaking this impasse through the support of a SR I&C Pilot Upgrade Project. Exelon’s Limerick Generating Station, a BWR, has been selected as the target for this Project. This research report (1) describes the process followed and products developed during the SR I&C Pilot Project Initial Scoping Phase and (2) captures lessons learned.

SR I-C Pilot Upgrade Phase Implementation

While regulatory advances have improved the environment for modernizing safety systems, the industry has remained reluctant to perform such I&C upgrades because of perceived regulatory risks associated with being the first adopter of the DI&C-ISG-06, Revision 2 process for a major critical safety system.

Business Case Analysis Digital Safety-Related

The commercial nuclear sector faces unprecedented financial challenges driven by low natural gas prices and subsidized renewables in a marketplace that does not reward carbon-free baseload capacity. These circumstances, along with increasingly antiquated labor-centric operating models and analog technology, have forced the premature closure of multiple nuclear facilities and placed a much larger population of nuclear power stations at-risk.

Vendor-Independent Design Requirements

This research focuses on presenting advancements that have been made by non-nuclear I&C vendors and potential savings that could be realized by their optimized nuclear industry application. To promote understanding and to bound the initial scope for this effort, a pilot vendor and an associated pilot implementation were chosen as an integrated presentation example for illustration.

Addressing Nuclear I C Modernization Through Application Techniques Employed

This report presents an assessment of digital I&C qualification issues and addresses gaps in qualification methods and processes that would potentially benefit from DOE sponsored research and development. Two new qualification methods are described that are recommended for further investigation. They are 1) Testability, and 2) Elimination of CCF triggers.

Strategy for Implementation of Safety-Related Digital IC Systems

Reliable instrumentation, information, and control (II&C) systems technologies are essential to ensuring safe and efficient operation of the U.S. light water reactor (LWR) fleet. These technologies affect every aspect of nuclear power plant (NPP) and balance-of-plant operations. They are varied and dispersed, encompassing systems from the main control room to primary systems and throughout the balance of the plant. They interact with every active component in the plant and serve as a kind of central nervous system.

Long-Term II and C Modernization Future Vision Strategy Final

Advanced Instrumentation, Information and Control System Technologies: Nondestructive Examination Technologies FY11 Report, R. M. Meyer, P. Ramuhalli, J. B. Coble, L. J. Bond, Pacific Northwest National Laboratory, PNNL-20671, August 2011.

Advanced Instrumentation Information Control System Technologies

Preliminary Results of a Bounded Exhaustive Testing Study for Software in Embedded Digital Devices in Nuclear Power Applications, INL/EXT-19-55606, C. Elks, A. Jayakumar, A. Collins, R. Hite, T. Karles, C. Deloglos, B. Simmons, A. Tantawy, S. Gautham, September 2019.

Preliminary Results Bounded Exhaustive Testing Study Software Embedded Digital Devices NP Applications

Specification of a Bounded Exhaustive Testing Study for a Software-based Embedded Digital Device, INL/EXT-18-52032, C. Elks, C. Deloglos, A. Jayakumar, November 2018.

Specification of a Bounded Exhaustive Testing Study for a Software-based Embedded Digital Device

A Business Case for Nuclear Plant Control Room Modernization, INL/EXT-16-39098, K. Thomas, S. Lawrie, J. Niedermuller, June 2016.

Business Case Cntrl Rm Modern

Digital Technology Business Case Methodology Guide, INL/EXT-14-33129, K. Thomas, S. Lawrie, A. Hart, C. Viahoplus, S. Madden, September 2014.

Digital Technology Business Case

Developing a Strategy for Full Nuclear Plant Modernization, INL/EXT-18-51366, J. Joe, C. Kovesdi, September 2018.

Developing a Strategy for Full Nuclear Plant Modernization

The Strategic Value of Human Factors Engineering in Control Room Modernization, EXT-18-51365, J. Hugo, C. Kovesdi, J. Joe, September 2018.

The Strategic Value of Human Factors Engineering in Control Room Modernization

Planning and Analyses Performed to Install Halden’s Advanced Control Room Concept in the Human Systems Simulation Laboratory, INL/EXT-18-45966, J. Joe, R. McDonald, July 2018.

Planning and Analyses Performed to Install Halden’s Advanced Control Room Concept in the Human Systems Simulation Laborator

Connecting LWRS Human Factors Engineering R&D to NUREG-0711 Elements and Modification Activities in Nuclear Power Plants, INL/EXT-18-45149, G. Clefton, J. Joe, C. Kovesdi, May 2018.

Connecting LWRS Human Factors Engineering RD to NUREG-0711 Elements and Modification Activities in Nuclear Generating Plan

Usability Evaluation of the Innovation Portal and Integrated Capability Analysis Platform, INL/EXT-21-63101, J. Mohon, C. Pederson, C. Kovesdi, J. Joe, June 2021.

Usability Evaluation Innovation Portal Integrated

Report for 2.2.1 Task 5: Develop and Document a State-Based Alarm System for a Nuclear Power Plant Control Room Using Machine Learning, INL/EXT-20-60549, J. Langstrand, R. McDonald H. Nguyen, November 2020.

Report for 2.2.1 Task 5 Develop Document

Modeling and Simulation Introducing hardware-in-the-loop capabilities to the Human Systems Simulation Laboratory, INL/MIS-19-55969, B. Rice, J. Lehmer, R. England, September 2019.

Modeling and Simulation Introducing hardware-in-the-loop capabilities HSSL

Report for 2.2.1 Task 4: Software-Based Tools to Support Human-System Evaluation Studies, INL/EXT-19-55789, M. Hildebrandt, J. Langstrand, H. Nguyen, J. Joe, September 2019.

Report for 2.2.1 Task 4 Software-Based Tools to Support Human-System Evaluation

Developing a Human Factors Engineering Program Plan and End State Vision to Support Full Nuclear Power Plant Modernization, INL/EXT-18-51212, J. Joe, L. Hanes, C. Kovesdi, August 2018.

Developing a Human Factors Engineering Program Plan and End State Vision to Support Full Nuclear Power Plant Modernization

Control Room Modernization End-State Design Philosophy, INL/EXT-18-44798 K. Le Blanc, Jacques Hugo, Z. Spielman, C. Kovesdi, R. Hill, J. Oxstrand, T. Hansen, B. Rice, March 2018.

Control Room Modernization End-State Design Philosophy

Lessons Learned from Performing a Human Factors Engineering Validation of an Upgraded Digital Control System in a Nuclear Power Plant Control Room, INL/EXT-18-44618, P. Braarud, H. Svengren, T. Ulrich, R. Boring, J. Joe, L. Hanes, February 2018.

Lessons Learned from Performing a Human Factors Engineering Validation of an Upgraded Digital Control System

Evaluation of Control Room Interface Designs to Support Modernization in Nuclear Power Plants, INL/EXT-17-43250, K. Le Blanc, C. Kovesdi, R. Hill, Z. Spielman,

Evaluation of Control Room Interface Designs to Support Modernization in Nuclear Power Plants

Prototype Design, Analysis, and Results for a Liquid Radiological Waste Control Room, INL/EXT-17-43226, C. Kovesdi, R. Hill, J. Oxstrand, Z. Spielman, K, Le Blanc, T. Hansen, September 2017.

Prototype Design, Analysis, and Results for a Liquid Radiological Waste Control Room

Development of an Initial Business Case Framework for Fleet-Based Control Room Modernization, INL/EXT-17-42604, C. Adolfson, K. Thomas, J. Joe, July 2017.

Development of an Initial Business Case Framework for Fleet-Based Control Room Modernization

Human Factors Engineering Aspects of Modifications in Control Room Modernization, INL/EXT-17-42190, J. Hugo, G. Clefton, J. Joe, June 2017.

Human Factors Engineering Aspects of Modifications in Control Room Modernization

Development of an Overview Display to Allow Advanced Outage Control Center Management to Quickly Evaluate Outage Status, INL/EXT-16-39622, S. St. Germain, J. Hugo, September 2016.

Development of an Overview Display to Allow Advanced Outage Control Center Management

Report for Task 8.4: Development of Control Room Layout Recommendations, INL/EXT-16-39800, R. McDonald, September 2016.

IFE Control Room Recommendations

Baseline Study Methodology for Future Phases of Research on Nuclear Power Plant Control Room Technologies, INL/EXT-16-39497, K. Le Blanc, G. Bower, R. Hill, Z. Spielman, B. Rice, July 2016.

Baseline Study Methodology for Future Phases of Research on Nuclear Power Plant Control Room Technologies

Benefits of Advanced Control Room Technologies: Phase One Upgrades to the HSSL and Performance Measures, K. Le Blanc, J. Joe, B. Rice, T. Ulrich, R. Boring, INL/EXT-15-3538, May 2015.

LWRS Benefits Final May2015

Implementation of Software Tools for Hybrid Control Rooms in the Human Systems Simulation Laboratory, H. Jokstad, O. Berntsson, R, McDonald, Halden Reactor Project; R. Boring, B., K. Fitzgerald, Idaho National Laboratory, INL/EXT-14-33710, November 2014.

LWRS 2014 M3 Halden Displays

Towards a Deeper Understanding of Automation Transparency in the Operation of Nuclear Plants, INL/EXT-20-59469, G. Skraaning, G. Jamieson, J. Joe, August 2020.

Towards Deeper Understanding Automation Transparency

Report for 2.2.1 Task 5: Develop and Document a State-Based Alarm System for a Nuclear Power Plant Control Room Using Machine Learning, INL/EXT-19-55368, J. Langstrand, H. Nguyen, R. McDonald, August 2019.

Alarm System NPP CR Using Machine Learning

Report for 2.2.1 Task 1: Support of Operator in the Loop Studies to be Conducted in the HSSL, INL/EXT-18-51360, R. Mcdonald, September 2018.

Report for 2-2-1 Task 1 Support of Operator in the Loop Studies to be Conducted in the HSSL

Report for 2.2.1 Task 2: Provide Support for the Human Factors Studies Conducted for the LWRS Control Room Modernization Project for PVNGS, INL/EXT-18-51358, M. Hildebrandt, J. Langstrand, H. Nguyen, September 2018.

Report for 2.2.1 Task 2 Provide Support for the Human Factors Studies Conducted for the LWRS Control Room Modernization

This report presents interim findings of two key collaborations with United States utilities currently planning and executing large-scale digital instrumentation and control modifications to their main control rooms. While these collaborations are ongoing, this report presents lessons learned in the demonstration of the human and technology integration methodology.

Demonstration Human Technology Integration

The scope of this work documents the demonstration of the recently developed human and technology integration methodology, as applied to developing a new vision and concept of operations for a major U.S. nuclear power plant fleet. This report focuses on the methodological aspects of developing a vision and concept of operations. This report shares the tools, activities, and lessons learned during a modernization currently underway for industry as a whole to consider when planning any significant digital modification and developing a new vision and concept of operations.

Demonstration Evaluation Human Technology Integration

Demonstration and Evaluation of the Human-Technology Integration Function Allocation Methodology, INL/RPT-22-68472, August 2022.

Demonstration Evaluation Human-Technology

Development of an Assessment Methodology That Enables the Nuclear Industry to Evaluate Adoption of Advanced Automation, INL/EXT-21-64320, C. Kovesdi, Z. Spielman, R. Hill. J. Mohon, T. Miyake, C. Pederson, September 2021.

Assessment Methodology that Enables Nuclear Industry Evaluate

Nuclear Power Plant Modernization Strategy and Action Plan, INL/EXT-19-55852, K. Thomas, P. Hunton, September 2019.

NPP Modernization Strategy Action Plan

FY 2018 Summary Report on Industrial and Regulatory Engagement Activities, INL/EXT-18-51462, K. Thomoas, September 2018.

FY18 Summary Report on Industrial and Regulatory Engagement Activities

FY 2017 Summary Report on Industrial and Regulatory Engagement Activities, INL/EXT-17-43352, K. Thomas, September 2017.

FY 2017 Summary Report on Industrial and Regulatory Engagement Activities

2015 Summary Report on Industrial and Regulatory Engagement Activities, K. Thomas, INL/EXT-15-36705, September 2015.

2015 Summary Report on Industrial and Regulatory Engagement Activities

Guidance for Deployment of Mobile Technologies for Nuclear Power Plant Field Workers, R. K. Farris, H. Medema, INL/EXT-12-27094, September 2012.

M3 LW12IN0603082 Guidance for Deployment of Mobile Technologies

Online Monitoring of Induction Motors, T. McJunkin, V. Agarwal, N. Lybeck, INL/EXT-15-36681, January 2016.

Online_Monitoring_of_Induction_Motors

Diagnostic and Prognostic Models for Generator Step-Up Transformers, INL/EXT-14-33124, V. Agarwal, N. Lybeck, and B. Pham, Idaho National Laboratory, September 2014.

Diagnostic_and_Prognostic_Models_for_Generator_Step-Up_Transformers

Online Monitoring Technical Basis and Analysis Framework for Emergency Diesel Generators—Interim Report for FY 2013, B. T. Pham, N. J. Lybeck, V. Agarwal, INL/EXT-12-27754, December 2012.

M4-12-27754_OnlineMonitoringRpt_EDGs_FINAL

Online Monitoring Technical Basis and Analysis Framework for Large Power Transformers; Interim Report for FY 2012, N. J. Lybeck, V. Agarwal, B. T. Pham, H. D. Medema, K. Fitzgerald, INL/EXT-12-27181, September 2012.

M3LW-12IN0602062_Report_INL-EXT-12-27181

Casting of Reinforced Concrete Beam: Casting of Reinforced, INL/EXT-18-51461, S. Mahadevan, J. Zhu, V. Agarwal, September 2018.

Casting of Reinforced Concrete Beam Casting of Reinforced

Interrogation of Alkali-Silica Reaction Degraded Concrete Samples using Acoustic and Thermal Techniques to Support Development of a Structural Health Monitoring Framework, INL/EXT-17-41852, S. Mahadevan, S. Miele, K. Neal, Y. Bao, V. Agarwal, B. Pham, D. Adams, April 2017.

Interrogation of Alkali-Silica Reaction Degraded Concrete Samples using Acoustic and Thermal Techniques to Support

Monitoring, Modeling, and Diagnosis of Alkali-Silica- Reaction in Small Concrete Samples, INL/EXT-15-36683, V. Agarwal, G. Cai, A. Gribok, P. Nath, R. Hansley, K. Neal, Y. Bao, S. Mahadevan, September 2015.

Monitoring Modeling and Diagnosis of Alkali-Silica-Reaction in Small Concrete Samples

A Simple Demonstration of Concrete Structural Health Monitoring Framework, S. Mahadevan, V. Agarwal, G. Cai, P. Nath, Y. Bao, J. Maria Bru Brea, N. Myrent, D. Koester, D. Adams, and D. Kosson, INL/EXT-15-34729 Revision 0, March 2015.

Simple Demonstration of Concrete

Interim Report on Concrete Degradation Mechanisms and Online Monitoring Techniques, S. Mahadevan, V. Agarwal, K. Neal, D. Kosson, and D. Adams, Idaho National Laboratory, INL/EXT-14-33134, September 2014.

M3 OLM Passive

Potential to Extend the Range of Established Online Monitoring Technologies, Such as Guided Waves in Nuclear Power Plant Systems, INL/EXT-17-43242, A. Gribok, September 2017.

Potential to Extend the Range of Established Online Monitoring Technologies Such as Guided Waves in Nuclear Power Plant Sys

Framework for Structural Online Health Monitoring of Aging and Degradation of Secondary Systems due to some Aspects of Erosion, INL/EXT-16-39903, A. Gribok, S. Patnaik, C. Williams, M. Pattanaik, R. Kanakala, September 2016.

Framework Structural Online Health Monitoring of Aging Degradation

Methods to Automate Assessing Outage Risk and Technical Specification Compliance for Planned Work and Current Plant Conditions, INL-EXT-19-55308, S. St Germain, J. Masterlark, R. Priddy, S. Beck, August 2019.

Methods to Automate Assessing Outage Risk and Technical Specification Compliance

Prototype System for Detecting Interactions between Current Plant Configuration States and Component Manipulations Directed by In-Use Procedures, INL/EXT-18-51474, S. St. Germain, J. Hugo, G. Gobbel, R. Reeves, September 2018

Prototype System for Detecting Interactions between Current Plant Configuration States and Component

Technologies for Detecting Interactions between Current Plant Configuration States and Component Manipulations Directed by In-Use Procedures, INL/EXT-17-43234 S. St. Germain, J. Hugo, M. Manic. K. Amarasinghe, September 2017.

Technologies for Detecting Interactions between Current Plant Configuration States and Component Manipulations Directed

Plant Modernization Pathway: FY 2019 External Review Summary Report, INL/EXT-18-52030, K. Thomas, November 2018.

FY19 External Review Summary Report

Hybrid Modeling of a Circulating Water Pump Motor, INL/EXT-20-59600 V. Agarwal, S. Kovacevic, P. Harry, August 2020.

Hybrid Modeling of a Circulating Water Pump Motor

Markov Process to Evaluate the Value Proposition of a Risk-Informed Predictive Maintenance Strategy, INL/EXT-20-59146, V. Agarwal, A. Gribok, P. Harry, July 2020.

Markov Process Evaluate Value Proposition

Determination of Sensor Quality of Calibration Using Advanced Data Analytics and Machine Learning Methods, INL/EXT-19-55407, S. Cetiner, N. Rao, P. Ramuhalli, C. Greulich, P. Devineni, F. Zhang, A. Gurgen, V. Agarwal, September 2019.

Determination of Sensor Quality of Calibration Using Advanced Data Analytics and Machine Learning Methods

Utilizing FLEX Equipment for Operations and Maintenance Cost Reduction in Nuclear Power Plants, INL/EXT-19- 55445, V. Yadav, J. Biersdorf, August 2009.

Utilizing FLEX Equipment for Operations and Maintenance Cost Reduction in NPP

The technology-centric approach is designed to reduce preventive maintenance frequency, drive down costs, enhance safety and reliability, and improve the economics of operation in NPPs. This will ensure the nuclear industry as a whole will remain economically competitive and viable in the energy market.

TERMS Costs

Technical Specification Surveillance Interval Extension of Digital Equipment in Nuclear Power Plants: Review, Research, and Recommendations, INL-EXT-19-54251, T. Quinn, J. Mauck, M. Bailey, V. Agarwal, S. St. Germain, P. Ramuhalli, G. Coles, June 2019.

Technical Specification Surveillance Interval Extension of Digital Equipment NPP Review Research

Lifecycle Prognostics Architecture for Selected High-Cost Active Components, N. Lybeck, B. Pham, and M. Tawfik, INL, and J. B. Coble, R. M. Meyer, P. Ramuhalli, and L. J. Bond, Pacific Northwest National Laboratory, INL/ EXT-11-22915, August 2011.

M2L11IN06020302-Final