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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Fossil Power Plant Cyber Security Life-Cycle Risk Reduction, A Practical Framework for Implementation

Market conditions are forcing fossil electricity generation facility owners and operators to implement advanced digital technologies. These technologies enable efficiencies, operational flexibility, operations and maintenance efficiencies, and adapting to a transitioning workforce. These digital technologies, however, can increase the cybersecurity attack surface. The purpose of this research was to develop a holistic cybersecurity risk reduction framework for fossil generation facilities. The framework begins with assessing how cyber risk changes across facility life cycles, including plant, system, vendor, and business life cycles. The next phase performs consequence analysis to prioritize high consequence events. Focusing on high consequence events allows owners to use a graded, risk-informed approach to prioritize cybersecurity efforts. The final phase identifies the digital asset attack surface in sensors and instrumentation and control equipment. After the vulnerabilities are identified, the owner selects mitigating cybersecurity control measures (or countermeasures) based on the risk analysis from the previous phases. This report describes the current industry cybersecurity best practices in fossil generation that are based on the first principles for cybersecurity engineering. The report is divided into five sections that describe the implementation of the risk reduction framework and present identified research, methodological, and technology gaps that were identified through this course of research and development.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Fossil Power Plant Cyber Security Life-Cycle Risk Reduction: A Practical Framework for Implementation

Market conditions are forcing fossil electricity generation facility owners and operators to implement advanced digital technologies. These technologies enable efficiencies, operational flexibility, operations and maintenance efficiencies, and adapting to a transitioning workforce. These digital technologies, however, can increase the cybersecurity attack surface. The purpose of this research was to develop a holistic cybersecurity risk reduction framework for fossil generation facilities. The framework begins with assessing how cyber risk changes across facility life cycles, including plant, system, vendor, and business life cycles. The next phase performs consequence analysis to prioritize high consequence events. Focusing on high consequence events allows owners to use a graded, risk-informed approach to prioritize cybersecurity efforts. The final phase identifies the digital asset attack surface in sensors and instrumentation and control equipment. After the vulnerabilities are identified, the owner selects mitigating cybersecurity control measures (or countermeasures) based on the risk analysis from the previous phases. This report describes the current industry cybersecurity best practices in fossil generation that are based on the first principles for cybersecurity engineering. The report is divided into five sections that describe the implementation of the risk reduction framework and present identified research, methodological, and technology gaps that were identified through this course of research and development.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

Fossil Power Plant Cyber Security Life-Cycle Risk Reduction: A Practical Framework for Implementation

Market conditions are forcing fossil electricity generation facility owners and operators to implement advanced digital technologies. These technologies enable efficiencies, operational flexibility, operations and maintenance efficiencies, and adapting to a transitioning workforce. These digital technologies, however, can increase the cybersecurity attack surface. The purpose of this research was to develop a holistic cybersecurity risk reduction framework for fossil generation facilities. The framework begins with assessing how cyber risk changes across facility life cycles, including plant, system, vendor, and business life cycles. The next phase performs consequence analysis to prioritize high consequence events. Focusing on high consequence events allows owners to use a graded, risk-informed approach to prioritize cybersecurity efforts. The final phase identifies the digital asset attack surface in sensors and instrumentation and control equipment. After the vulnerabilities are identified, the owner selects mitigating cybersecurity control measures (or countermeasures) based on the risk analysis from the previous phases. This report describes the current industry cybersecurity best practices in fossil generation that are based on the first principles for cybersecurity engineering. The report is divided into five sections that describe the implementation of the risk reduction framework and present identified research, methodological, and technology gaps that were identified through this course of research and development.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

DIGITAL APPLICATIONS USING REAL-TIME VEHICLE EXHAUST INFORMATION

Vehicle emission is a major source of air pollution that causes a significant number of deaths globally. It has a profound impact on energy and the environment as well. The existing vehicle emission monitoring system is unable to help mitigating the pollution properly and therefore, requires precise real-time pollution measurement. The purpose of this paper is to discuss novel applications using the real-time measurement of pollutants from a vehicle tailpipe where exhaust gases enter the environment. Today, it is possible to measure such emission due to the emergence of affordable digital technologies such as the Internet of Things (IoT), wireless connectivity, cloud platform, and artificial intelligence. This paper discusses how digital technologies can be used for real-time monitoring of NOx gas as a measure of vehicle emission and predictive analytics applications. A description of data collection and pre-processing methodologies, actual collected data, and an approach to identify patterns between inputs such as vehicle speed and altitude and output such as NOx emission are included. Applying a simple neural network has produced promising results and is a first step towards developing predictive applications.

Digital, Vehicle Exhaust, IoT, AI, 1.4.2, Predicti↗
DOE OSTI2020

Analysis and Planning Framework for Nuclear Plant Transformation

Commercial nuclear power in the United States has been an unqualified success by any measure, providing low cost, carbon-free, and safe baseload electricity for decades. The industry today is at the peak of its historical performance in terms of generation output, reliable operations, and demonstrated nuclear safety. However, it is no longer among the lowest-cost electric generation sources with the emergence of subsidized renewables and shale gas generation. The business model that has served the operating nuclear fleet so well over its life is now a drag on cost performance due to its reliance on a large highly skilled labor force. In contrast, digital technology and innovation are enabling dramatic efficiencies in energy production, resulting in fierce competition for a commodity such as electricity. The nuclear power industry has responded to this challenge with many initiatives to improve efficiency and modernize plant equipment, especially where reliability and obsolescence issues are pressing. However, it would be a missed opportunity to merely modernize the plant components and the work processes of an outdated business model that was formulated to manage the technology of the 1960s. Rather, the greater opportunity is to transform that business model to one that fully exploits the capabilities of modern digital technology, resulting in substantially lower production costs and sustainable market viability. One successful example of such transformation is the concept of Integrated Operations, which was introduced into the North Sea oil and gas industry a couple of decades ago when the profitability of operating these fields was severely threatened by low world petroleum prices and the high overhead of operating the offshore oil and gas platforms. This effort resulted in significant changes to how these oil fields were operated and allowed the industry to continue profitable operation of these platforms. This example has some remarkable parallels to the U.S. commercial nuclear industry as described in the next section. This report provides an analysis and planning framework for such a nuclear plant operating model transformation based on the transferable learnings from the North Sea transformation. This framework is termed Integrated Operations for Nuclear or ION. This report describes the key principles and methods of Integrated Operations and how they are being applied in a collaboration between the DOE Light Water Reactor Sustainability Program and Xcel Energy in an initiative to transform its operating model for performance improvement and long-term sustainability. It describes a method to bring the operating costs of a nuclear fleet in line with market-based pricing, transforming work functions to reduce cost with technology innovations. This initiative will continue over the next several years in the detailed development of transformative concepts for nuclear plants, which will be published as follow-up to this initial report on Integrated Operations for Nuclear.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Computer-Based Procedures Among Older Adults: Findings from the Rancor Microworld Simulator

As with many industries worldwide, nuclear energy is experiencing an aging workforce; older than other energy sources and the national average. For example, while almost one in three nuclear industry professionals are 55+ years, for oil and gas that number is one in five. The challenges brought about by an aging workforce are one of the industry’s top concerns. However, the industry lacks for empirical research that examines the effects of developmental aging in older workers, as well as the interactions between aging and new digital technologies. We present the results of an experiment that tested three different computer-based procedures in a sample of 30 older adults (55+ years). While the industry has traditionally relied on paper-based procedures, these are being modernized by digital technology. Participants were randomly assigned to one of three procedure-types that varied by the level of digitalization, based on the IEEE Standard-1786. Type 1 essentially represents a digital representation of a paper-based procedure, Type 2 adds embedded indicators, and Type 3 adds soft controls. Participants performed two different operational scenarios (startup and loss of feedwater) on a simplified nuclear power plant simulator. Results revealed a weak signal that Type 2 may produce lower workload and lower completion times in some instances. However, there were no significant effects of procedure-type across any other outcomes, including simulator log data, situation awareness, and preference ratings. We discuss our findings in terms of optimal levels of digitalization/automation for an aging nuclear workforce and suggest pathways for future directions.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2022

Cyber-Informed Engineering for Nuclear Reactor Digital Instrumentation and Control

As nuclear reactors transition from analog to digital technology, the benefits of enhanced operational capabilities and improved efficiencies are potentially offset by cyber risks. Cyber-Informed Engineering (CIE) is an approach that can be used by engineers and staff to characterize and reduce new cyber risks in digital instrumentation and control systems. CIE provides guidance that can be applied throughout the entire systems engineering lifecycle, from conceptual design to decommissioning. In addition to outlining the use of CIE in nuclear reactor applications, this chapter provides a brief primer on nuclear reactor instrumentation and control and the associated cyber risks in existing light water reactors as well as the digital technology that will likely be used in future reactor designs and applications.

42 ENGINEERING↗
DOE OSTI2022

Demonstration and Evaluation of the Human-Technology Integration Function Allocation Methodology

There is an imminent need for the existing nuclear power plants to reduce their operating and maintenance (O&M) costs to remain economically viable. Digital technology, including automation, provides a significant opportunity for the existing nuclear power plant fleet to transform the way in which work is accomplished, reducing O&M costs, and allowing the fleet to remain economically competitive. One notable opportunity to significantly reduce O&M costs pertains to modifications to the plant equipment and main control room (MCR). Existing instrumentation and control (I&C) technologies in the MCR are highly analog, costly to operate and maintain, and demand a high cognitive and physical workload from plant staff (i.e., operators). Digitalizing the MCR has a range of broad economic benefits, including improved plant performance and reduced manual work. Further, digital I&C systems can fundamentally change the way in which plant staff operate the plant; this is the concept of operation. Human-technology integration is important to ensure that impacts to the concept of operation are done in a way that account for capabilities of people and technology. Human-technology integration employs human factors engineering (HFE) methods and principles to maximize the benefits of digital technology, reducing human error, improving overall decision-making and usability. The U.S. Department of Energy Light Water Reactor Sustainability Program is applying human-technology integration research to ensure digital technologies are safe, reliable, and efficient. This paper documents the demonstration of the human-technology guidance developed by the Light Water Reactor Sustainability Program from a first-of-a-kind digital I&C upgrade, specifically addressing function analysis and allocation for a new digital I&C system that included changes in automation levels. The program’s specific approach is included in this work, following lessons learned. This document serves as a resource for industry to follow in applying human-technology integration and HFE to digital modifications, specific to function analysis and allocation. The lessons learned should be considered in the planning and execution of HFE activities that support such digital modifications.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Digital Twin Technology (“Morpheus”) for Optimized Building Operations [SWR-22-74]

The electrification of buildings is an important step to reducing greenhouse gas emissions across all industries. The management of increasingly electrified buildings is a complex pursuit, and there remains a need for cost-effective software capable of handling the computational burden required of such complexity. Through a partnership with Dallas Fort Worth (DFW) Airport, researchers at NREL have developed a digital twin modeling framework to optimize building operations, called Morpheus. Pairing predictive control with automatic fault detection and diagnostics, Morpheus decreases energy expenditures, costs, and faults for large facilities. Additionally, Morpheus employs artificial intelligence to continuously improve its performance using information provided by sensor systems, human experts with deep industry domain knowledge, and even from other similar machines or fleets of machines. Coupling this novel energy-management software with other digital twins, such as NREL’s Athena software for mobility operations, enables robust decision-making for asset and space management. The implementation of Morpheus at DFW has resulted in significantly improved HVAC system operations and reduced both peak power and overall energy consumption. This enhanced functionality comes at a more affordable price than previously developed digital twins and can be customized for other facilities’ geometries to provide optimal, individualized control of a facility’s energy consumption.

Chinde, Venkatesh↗
DOE OSTI2022

An Integrated Risk Assessment Process of Safety-Related Digital I&C Systems in Nuclear Power Plants

Upgrading the existing analog instrumentation and control (I&C) systems to state-of-the-art digital I&C (DI&C) systems will greatly benefit existing light water reactors. However, the issue of software common cause failure (CCF) remains an obstacle in terms of qualification for digital technologies. Existing analyses of CCFs in I&C systems mainly focus on hardware failures. With the application and upgrading of new DI&C systems, design flaws could cause software CCFs to become a potential threat to plant safety, considering that most redundancy designs use similar digital platforms or software in their operating and application systems. With complex multilayer redundancy designs to meet the single failure criterion, these I&C safety systems are of particular concern in U.S. Nuclear Regulatory Commission licensing procedures. In Fiscal Year 2019, the Risk-Informed Systems Analysis (RISA) Pathway of the U.S. Department of Energy’s Light Water Reactor Sustainability Program initiated a project to develop a risk assessment strategy for delivering a strong technical basis to support effective, licensable, and secure DI&C technologies for digital upgrades and designs. An integrated risk assessment for the DI&C process was proposed for this strategy to identify potential key digital-induced failures, implement reliability analyses of related digital safety I&C systems, and evaluate the unanalyzed sequences introduced by these failures (particularly software CCFs) at the plant level. Here this paper summarizes these RISA efforts in the risk analysis of safety-related DI&C systems at Idaho National Laboratory.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

INTEGRATED RISK ASSESSMENT OF DIGITAL I&C SAFETY SYSTEMS FOR NUCLEAR POWER PLANTS

Upgrading the existing analog instrumentation and control (I&C) systems to state-of-the-art digital I&C (DI&C) systems provides the foremost means to improve performance and reduce costs for existing light-water reactors (LWRs). However, qualification of digital technologies remains a challenge?especially the issue of software common cause failure (CCF), which has been difficult to address. Existing analyses of CCFs in I&C systems mainly focus on hardware failures. With the application and upgrading of new DI&C systems, software CCFs due to design flaws might become a potential threat to plant safety, considering that most redundancy designs use similar digital platforms or software in their operating and application systems. With complex multi-layer redundancy designs to meet the single failure criterion, these I&C safety systems are of particular concern in U.S. Nuclear Regulatory Commission (NRC) licensing procedures. In 2019, the Risk-Informed Systems Analysis (RISA) Pathway of the U.S. Department of Energy?s (DOE?s) Light Water Reactor Sustainability (LWRS) Program initiated a project to develop a risk assessment strategy for delivering a strong technical basis to support effective, licensable, secure DI&C technologies for digital upgrades/designs. An integrated risk assessment for the DI&C (RADIC) process was proposed for this strategy to identify potential key digital-induced failures, implement reliability analyses of related digital safety I&C systems, and evaluate the unanalyzed sequences introduced by these failures (particularly software CCFs) at the plant level. This paper summarizes these RISA efforts in the risk analysis of safety-related DI& systems at Idaho National Laboratory.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Business Case Analysis for Artificial Intelligence-Large Language Model Technology Integration

AI-assisted processes are expected to enhance operational efficiency and improve decision-making, supporting the long-term economic viability of nuclear power plants. However, detailed business analyses of AI-generated cost savings are rarely performed. Given the recent industry interest in Large Language Model (LLM), the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program has conducted a comprehensive business case analysis of LLM Artificial Intelligence (AI) implementation in nuclear plant engineering workflows. The research employed three complementary business case approaches to evaluate impact of an LLM, using three representative engineering processes as use-cases: Boric Acid Corrosion (BAC) Evaluations, Maintenance Rule Evaluations, and 10 CFR 50.59 Screenings. Through detailed workload analyses and structured interviews, the study quantified significant efficiency improvements ranging from 11% to 59% across these processes. The research further considers how these efficiency gains could translate into tangible reliability improvements through enhanced engineering capacity. Analysis of historical plant trip data indicates that enabling engineers to focus on proactive reliability activities could provide substantial financial benefits through avoided outages, potentially generating greater value than the direct efficiency improvements alone. By documenting successful applications, implementation challenges, and strategic opportunities, this research provides nuclear utilities with a practical framework for evaluating the value of AI technology to support long-term operations through advanced digital technologies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Hawaii Threat Brief

The Digital Energy Transformation is redefining how power systems operate, integrating physical infrastructure with digital technologies to enhance efficiency, visibility, and resilience. For islanded and digitally modernizing systems like Hawai‘i’s, this shift presents both new opportunities and evolving challenges in cybersecurity, supply chain assurance, and environmental resilience. This brief provides an overview of critical infrastructure dependencies and systemic risks associated with increasing digital integration. It summarizes recent energy-sector threat activity and case studies that illustrate adversary tactics and supply chain vulnerabilities, and identifies pathways to strengthen resilience.

25 - ENERGY STORAGE↗
DOE OSTI2024

Digital-Twin-Enabling Technologies for Online Condition Monitoring of Nuclear Power Plant Components

Online condition monitoring is an area of active research that may enable improved scheduling, maintenance, and safety of nuclear power plant components, reducing unnecessary derates while simultaneously improving operational capacity. Digital twins are one avenue to conduct online condition monitoring and are currently being explored by national laboratories and universities alike. Digital twins for online condition monitoring are, in essence, state concurrent models that emulate a physical process which predicts a parameter and compares it against a measured value. However, digital twins may also provide additional insights by combining and interpreting various sources of information. These insights may be used for preventative maintenance scheduling optimization or early fault detection and are projected to be valuable for meeting requirements under 10 CFR 50.55a. However, digital twin technologies are still under significant development; quantifying model uncertainties, improving unique fault identification, and multimodal sensor fusion are some areas under investigation. Therefore, in this work, we discuss and review the various enabling technologies, in the form of advanced sensors, instrumentation, and modelling methods, that may be used to implement and enhance digital twins for online condition monitoring. A potential use case for pump-motors is presented to demonstrate how these various pieces of enabling digital twin technologies may integrated together for online condition monitoring. Challenges and opportunities associated with the pump-motor digital twin enabling technologies are also identified and discussed.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Digital Twin Enabling Technologies for Online Condition Monitoring of Nuclear Power Plant Components

Online condition monitoring is an area of active research that may enable improved scheduling, maintenance, and safety of nuclear power plant components, reducing unnecessary derate while simultaneously improving operational capacity. Digital twins are one avenue to conduct online condition monitoring and are currently being explored by national laboratories and universities alike. Digital twins for online condition monitoring are, in essence, state concurrent models that emulate a physical process which predicts a parameter and compares it against a measured value. However, digital twins may also provide additional insights by combining and interpreting various sources of information. These insights may be used for preventative maintenance scheduling optimization or early fault detection and are projected to be valuable for meeting requirements under 10 CFR 50.55a. However, digital twin technologies are still under significant development; quantifying model uncertainties, improving unique fault identification, and multimodal sensor fusion are some areas under investigation. Therefore, in this work, we discuss and review the various enabling technologies, in the form of advanced sensors, instrumentation, and modelling methods, that may be used to implement and enhance digital twins for online condition monitoring. A potential use case for pump-motors is presented to demonstrate how these various pieces of enabling digital twin technologies may integrated together for online condition monitoring. Challenges and opportunities associated with the pump-motor digital twin enabling technologies are also identified and discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Donald J. Trump’s Presidency in Cyberspace: A Case Study of Social Perception and Social Influence in Digital Oligarchy Era

In the past few years, with the rapid growth of digital technologies, Facebook, Twitter, and other social media platforms have become the digital oligarchies, which have the enormous capabilities to potentially control what is discussed in cyberspace. In the digital oligarchy era, social perception and social influence in different complex social systems have evolved quickly. In this article, we conducted large-scale empirical studies on social perception and social influence regarding the Trump phenomenon from personal perception, media, and public attention perspectives. We found that there exist obvious correlations between the posting behavior of Trump and the attention of news media. By constructing public attention networks using complex networks based on Google search information, we further reveal that digital platforms could affect social perception and social influence significantly. Especially, we obtained that the public attention can always be influenced by the political moments.

digital oligarchy↗
DOE OSTI2020

Hazard analysis for identifying common cause failures of digital safety systems using a redundancy-guided systems-theoretic approach

Replacing the existing aging analog instrumentation and control (I&C) systems with modern safety control and protection, digital technology offers one of the foremost means of performance improvements and cost reductions for the existing nuclear power plants (NPPs). However, the qualification of digital I&C systems remains a challenge, especially considering the issue of software common-cause failures (CCFs), which are difficult to address. With the application and upgrades of advanced digital I&C systems, software CCFs have become a potential threat to plant safety because most redundant designs use similar digital platforms or software in the operating and application systems. With complex designs of multilayer redundancy to meet the single-failure criterion, digital I&C safety systems (e.g., engineered safety-features actuation system [ESFAS]) are of a particular concern in the U.S. Nuclear Regulatory Commission (NRC) licensing procedures. Here, this paper applies a modularized approach to conduct redundancy-guided systems-theoretic hazard analysis for an advanced digital ESFAS with multilevel redundancy designs. Systematic methods and risk-informed tools are incorporated to address both hardware and software CCFs, which provide guidance to eliminate the causal factors of potential single points of failure in the design of digital safety systems in advanced plant designs.

42 ENGINEERING↗