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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Hazard and risk analysis framework for nuclear power plant–based integrated energy systems

Employing integrated energy systems (IESs) with nuclear power plants (NPPs) can improve NPP utilization by leveraging dedicated thermal and electric power delivery, but it may also increase operational safety risks. This paper presents a framework to identify and quantify hazards and risks for such IESs. The framework combines accidentology to review past industrial accidents with failure modes and effects analysis (FMEA) to identify potential future incidents. Hydrogen explosion and toxic chemical release hazards are of particular concern. Explosion consequences are quantified using the Bauwens-Dorofeev (Bauwens) and trinitrotoluene equivalent mass (TNT-EM) methods, while chemical release consequences are computed using the Gaussian atmospheric dispersion method. Operational disturbances from direct electrical and thermal integration that may affect NPP safety are modeled using probabilistic risk analysis (PRA). Hazards and risks are then evaluated for regulatory compliance. The framework is applied to IESs comprising pressurized or boiling water reactors supplying three levels of thermal and electrical power to industrial customers. Case studies include high-temperature steam electrolysis hydrogen plants of varying capacities and a synthetic fuel production plant. Sensitivity analysis examines piping component failures in the PRA model as a precursor to cost estimation for thermal extraction line design. Additionally, Fussel-Vessely (FV) and risk increase importance (RII) measures identify risk-informed design improvements for the thermal extraction system. FMEA highlights hazards such as loss of offsite power, prompt loss of electrical load, loss of thermal output, and immediate steam diversion, in addition to hydrogen explosions and toxic chemical releases. Both Bauwens and TNT-EM methods suggest maintaining several hundred meters of separation between the NPP and hydrogen facility to mitigate explosion risks. PRA results show a maximum initiating event frequency increase of 1.15% and an overall risk increase of 0.28%. Importance measure analysis identifies upstream pipe leak isolation components as critical. Evaluating the results against safety regulations, it is concluded that hazards and risks can be managed to comply with regulations through risk-informed thermal and electrical connection designs, component selection, maintenance programs, and safe separation distances between NPPs and integrated industrial facilities.

08 - HYDROGEN↗
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 optimized scheduling, maintenance, and safety of nuclear power plant components, reducing unnecessary derates while simultaneously improving operational capacity. Digital twins (DTs) are one avenue to conduct online condition monitoring and are currently being explored by national laboratories and universities alike. DTs 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. A DT’s goal is to provide additional insights by combining and interpreting various sources of information for preventative maintenance scheduling optimization or early fault detection. DTs for condition monitoring are projected to be valuable for meeting requirements under 10 CFR 50.55a, “Codes and Standards,” and 10 CFR 50.65, “Requirements for Monitoring the Effectiveness of Maintenance at Nuclear Power Plants”. However, DT technologies are still under significant development, and the process for developing a DT for condition monitoring has not been formalized. Therefore, in this work, we present an initial framework for developing a DT, discuss and review the various challenges and considerations for DT deployment, and identify the opportunities that a DT can improve. The presented framework is intended to help developers formulate a strategy when approaching DT development for condition monitoring. In conclusion, a DT use case for a reactor coolant pump is presented to demonstrate the proposed framework.

advanced sensor instrumentation↗
DOE OSTI2023

Development of a Scalable Risk-informed Predictive Maintenance Cloud-based Strategy at Nuclear Power Plants

The fact that light-water reactor operation and maintenance costs are prohibitively expensive and contribute to the premature decommissioning of nuclear power plants is partly due to how the equipment is monitored. In recent years, cloud computing has emerged as a dominant technology, as its low cost, computing and storage adaptability, and ability to host applications across numerous virtual infrastructures potentially make it a cost-effective alternative to onsite storage and diagnostics. In this paper, a technological assessment is carried out on a provisional cloud deployment architecture for a nuclear power plant predictive monitoring system. This cloud-based monitoring system would enable maintenance and diagnostic analysts and other authorized plant users to remotely monitor equipment functionality, thus enabling early fault detection and effective predictive maintenance practices. To provide data processing and storage, sensor device networking, and database management, the Microsoft Azure cloud platform is utilized as part of the proposed cloud architecture; however, this analysis could be extended to other cloud computing service providers as well. The focus of this paper is on application of cloud resources for enabling predictive maintenance, identification of technological hurdles associated with moving to a cloud-computing-based architecture, and potential benefits from moving to a centralized cloud system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

NiCrMoNb age hardenable alloy for creep-resistant high temperature applications, and methods of making

Nickel alloys, methods of making nickel alloys, articles including the nickel alloys, uses of the alloys, and methods of treating nickel alloys are described. The inventive heat resistant structural materials are suitable for applications requiring high yield stress at room temperature and good creep strength at high temperatures, such as in gas turbines, steam turbines, fossil energy boilers, aero engines, power generation systems using fluids such as supercritical carbon dioxide (e.g., advanced ultra-supercritical power plants), concentrated solar power plants, nuclear power plants, molten salt reactors: turbine blades, casings, valves, heat exchangers and recuperators.

Detrois, Martin↗
DOE OSTI2025

NiCrMoNb age hardenable alloy for creep-resistant high temperature applications, and methods of making

Nickel alloys, methods of making nickel alloys, articles including the nickel alloys, uses of the alloys, and methods of treating nickel alloys are described. The inventive heat resistant structural materials are suitable for applications requiring high yield stress at room temperature and good creep strength at high temperatures, such as in gas turbines, steam turbines, fossil energy boilers, aero engines, power generation systems using fluids such as supercritical carbon dioxide (e.g., advanced ultra-supercritical power plants), concentrated solar power plants, nuclear power plants, molten salt reactors: turbine blades, casings, valves, heat exchangers and recuperators.

Detrois, Martin↗
DOE OSTI2022

Automatic recognition system for document digitization in nuclear power plants

With the increasing number of data-driven models in nuclear applications, large volumes of numerical data are required to accurately model and predict the health status of a plant component. However, many historical operation logs that contain useful information are not fully utilized due to the lack of a systematic approach of digitization. To overcome this issue, this study proposes an automatic pipeline for extracting information from handwritten tabular documents collected from nuclear power plants. In our pipeline, we first denoise scanned documents with morphological operations, and then extract relevant parts from individual pages using both traditional computer vision and neural network methods. Handwriting recognition is applied to obtain text and numbers. As the most challenging step is how to crop only relevant information, the main focus of our paper is to detect tables and cells from scanned handwritten documents. Here we evaluate the efficiency and accuracy of our proposed method on handwritten operational reports obtained from a real-world case study. The results demonstrate the high accuracy and practicality of our proposed method.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Radiation-Induced Changes in Single Crystal Calcite and Dolomite: Mineral Analogues of Light Water Reactor, Nuclear Power Plant Concrete Aggregates

Two analogues of aggregates (calcite and dolomite) found in nuclear power plant (NPP) concrete have been neutron irradiated to fluences up to 2 × 10 20 n/cm 2 at 52 °C and 4 × 10 19 n/cm 2 at 95 °C (E > 0.1 MeV). X-ray diffraction studies showed that these aging conditions affected crystallography of both calcite and dolomite, with both showing a growth in their unit cells compared to that of the unirradiated samples. Only dolomite samples showed a continuous increase of its lattice parameters with the increase in irradiation. In calcites, the lattice growth with irradiation dissipated after a fluence of 5 × 10 18 n/cm 2 . Radiation-induced disordering of the crystal structure was observed in both materials, while a healing effect of irradiation temperature was mainly observed in calcites. Dislocation densities calculated by using XRD data also supported these observations. Insights made into the unit cells of both minerals by using Fourier synthesis showed that the Mg sites are more prone to the neutron irradiation than the Ca sites, resulting in larger radiation effects and higher disruption in the crystal structure of dolomite than that of calcite. Furthermore, other than the polycrystalline characteristics observed by using TEM, these minerals did not show complete amorphization or significant structural decomposition at the studied irradiation fluences.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1972

Nuclear power plants for mobile applications

Mobile nuclear powerplants for applications other than large ships and submarines will require compact, lightweight reactors with especially stringent impact-safety design. The technical and economic feasibility that the broadening role of civilian nuclear power, in general, (land-based nuclear electric generating plants and nuclear ships) can extend to lightweight, safe mobile nuclear powerplants are examined. The paper discusses technical experience, identifies potential sources of technology for advanced concepts, cites the results of economic studies of mobile nuclear powerplants, and surveys future technical capabilities needed by examining the current use and projected needs for vehicles, machines, and habitats that could effectively use mobile nuclear reactor powerplants.

Anderson, J. L.↗
DOE OSTI2024

Common Cause Failure Analysis for Nuclear Power Plant Instrumentation and Control Systems

This presentation is prepared for the IAEA Virtual Consultancy Meeting on Preparation of a Coordinated Research Project on Common Cause Failures in Nuclear Power Plant Instrumentation and Control Systems from February 5 ? 8, 2024. It provides an overview of the INL activities on the common cause failure analysis for instrumentation and control system in nuclear power plants.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Uncertainty-Aware and Explainable Human Error Detection in the Operation of Nuclear Power Plants

The timely and accurate identification of incidents, such as human factor error, is important to restore nuclear power plants (NPPs) to a stable state. However, the identification of abnormal operating conditions is difficult because of the existence of multiple scenarios. In addition, to implement mitigation actions rapidly after an incident occurs, operators must accurately identify an incident by monitoring the trends of many variables. The mental burden posed by this can increase human error and cause failure in identifying incidents. Failure to identify incidents directly results in erroneous mitigation measures, which are detrimental to NPPs. In this study, we leverage uncertainty-aware models to identify such errors and thereby increase the chances of mitigating them. We use the data collected from a physical test bed. The goal is to identify both certain and accurate models. For this, the two main aspects of focus in this study are explainable artificial intelligence (XAI) and uncertainty quantification (UQ). While XAI elucidates the decision pathway, UQ evaluates decision reliability. Their integration paints a comprehensive picture, signifying that understanding decisions and their confidence should be interlinked. Thus, in this study we leverage UQ measures (e.g. entropy and mutual information) along with Shapley additive explanations to gain insights into the features contributing to both accuracy and uncertainty in error identification. Furthermore, our results show that uncertainty-aware models combined with XAI tools can explain the artificial intelligence–prescribed decisions, with the potential of better explaining errors for the operators.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Neural-based time series forecasting of loss of coolant accidents in nuclear power plants

During the last few years, deep learning in neural networks has demonstrated impressive successes in the areas of computer vision, speech and image recognition, text generation, and many others. However, sensitive engineering areas such as nuclear engineering benefited less from these efficient techniques. In this work, deep learning expert systems are utilized to model and predict time series progression of a design-basis nuclear accident, featuring a loss of coolant accident. Two major findings are accomplished in this work. First, the ability to train expert systems with high accuracy, which could help nuclear power plant operators to figure out plant responses during the accident. Second, building fast, efficient, and accurate deep models to simulate nuclear phenomena, which could be valuable to nuclear computational science. In this work, large amount of time series data is obtained from simulation tools by simulating different conditions of the base-case/nominal accident scenario. Four critical outputs/responses are monitored during the accident (e.g. temperature, pressure, break flow rate, water level). Two approaches are adopted in this work. The first approach is to use feedforward deep neural networks (DNN) to fit all time steps and outputs in a single model. The second approach is to use long short-term memory (LSTM) to fit all time steps together for each reactor response separately. Both DNN and LSTM demonstrate very good performance in predicting the test and base-case scenarios, with accuracy as low as 92% and as high as 99%, where these test scenarios are unknown to the expert systems and are not included in the model training. In addition, both approaches demonstrate a significant reduction in computational costs, as the deep expert system is able to accurately predict the accident 100,000 times faster than the original simulation tool. Given sufficient data, the methodology adopted in this study demonstrates that DNN/LSTM expert systems can be used as a decision support system to model advanced time series phenomena within nuclear power plants with high accuracy and negligible computational costs.

42 ENGINEERING↗
DOE OSTI2024

Quantifying Investment Risk: Analysis of the Purchase Decision of a Nuclear Power Plant

Cost overruns are an ill-fated part of the deployment history of nuclear power plants (NPPs) in the United States, and yet studies increasingly show the important role nuclear technologies must play in decarbonizing the U.S. economy. Paradoxically, then, a key piece of a coherent decarbonization strategy depends on attracting investor action to a purchase where historical cost overruns have been sizeable. To address this challenge, this study aims to develop a financial model that quantifies risk of cost overruns in the decision-making process for purchasing advanced reactor concepts. Using the concept of Value at Risk (VaR), the model is built to evaluate financial risk nuclear construction with the aim to identify risk mitigation strategies. The objective is to identify strategies to mitigate cost-risk challenges and to assess the potential reduction in investor risk exposure. The paper presents the initial development and preliminary verification of the financial risk analysis model. The development of this model involved a comprehensive approach to estimating financial risk over the operating life of NPP that stems from construction uncertainties. By utilizing net present value (NPV) with discounted cash flows, the model captures the complex interconnections of project costs, construction timelines, revenue, and uncertainties. Verification of the model involved testing historical data from previous reactor construction projects against the construction project of Vogtle 3 and 4. The results of this paper present the comparison of the preconstruction cost overrun prediction with the current cost estimates from a nearly complete Vogtle 3 and 4.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Application of Artificial Intelligence in Detection and Mitigation of Human Factor Errors in Nuclear Power Plants: A Review

Human factors and ergonomics have played an essential role in increasing the safety and performance of operators in the nuclear energy industry. In this critical review, we examine how artificial intelligence (AI) technologies can be leveraged to mitigate human errors, thereby improving the safety and performance of operators in nuclear power plants (NPPs). First, we discuss the various causes of human errors in NPPs. Next, we examine the ways in which AI has been introduced to and incorporated into different types of operator support systems to mitigate these human errors. We specifically examine (1) operator support systems, including decision support systems, (2) sensor fault detection systems, (3) operation validation systems, (4) operator monitoring systems, (5) autonomous control systems, (6) predictive maintenance systems, (7) automated text analysis systems, and (8) safety assessment systems. Finally, we provide some of the shortcomings of the existing AI technologies and discuss the challenges still ahead for their further adoption and implementation to provide future research directions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1973

Some studies on the use of NASTRAN for nuclear power plant structural analysis and design

Studies made on the use of NASTRAN for nuclear power plant analysis and design are presented. These studies indicate that NASTRAN could be effectively used for static, dynamic and special purpose problems encountered in the design of such plants. Normal mode capability of NASTRAN is extended through a post-processor program to handle seismic analysis. Static and dynamic substructuring is discussed. Extension of NASTRAN to include the needs in the civil engineering industry is discussed.

Setlur, A. V.↗
DOE OSTI2022

Draft Methodology for Cybersecurity Analysis for Adoption of Wireless Technology in Nuclear Power Plants

The report is delivered as DOE-NE Cybersecurity Program Milestone M2CT-22IN1104014-Industry cybersecurity guidance adoption status. The milestone is specifically to document the process and the status of the efforts towards developing guidance in support of industry’s adoption of wireless communication technologies. To transform the operation of nuclear power plants, including domestic light-water reactors, advanced reactors, microreactors, and fission battery, for grid and non-grid applications, secure and resilient wireless capabilities are required. In addition, to realize new operational concepts such as autonomous operation and remote monitoring, advanced sensor, and instrumentation, wireless technology is essential. However, industry implementation is low, and there is no technical basis for how to understand and address potential risks for wireless communications for critical plant functions. A methodology with a technical basis for implementing secure wireless communication is crucial. This wireless adoption methodology is intended to assist a licensee in identifying an appropriate technological approach for securing wireless communications in nuclear power plant. However, this methodology does not provide guidance for addressing wireless design criteria or for addressing all the cybersecurity commitments in licensees’ cybersecurity plans (CSPs) including addressing security impact analysis that a licensee must perform before an update to a Critical Digital Asset (CDA). This methodology guides a licensee through a process of evaluating a proposed wireless implementation and drafting a plant change notification for an example use case. The example is a generic/nonproprietary version of the first test case of the methodology, which, if successfully implemented, is part of the consideration for protecting other functions’ use of wireless in a cybersecure manner.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

1. Physical Security Engineering by Design for Nuclear Facilities; 2. Nuclear Power Plant Site Security Management – A Security Strategy; 3. The UAE Women in Nuclear Energy Security

1. Security by design, or SeBD, is a comprehensive approach that integrates the physical protection system of a nuclear plant into every stage of its existence. This includes planning, designing, constructing, commissioning, and operating the facility, using a combination of analytical, physical, technological, and procedural measures. Essentially, SeBD involves intentionally applying and incorporating security into all aspects of design and operation throughout the entire lifecycle of a facility. By implementing this methodology throughout various phases such as program development, process implementation, staff training and procedures management in conjunction with plant equipment, facilities can be optimized to minimize security risks without compromising functional design requirements. This ultimately improves the overall security posture of the site and reduces the need for costly modifications or additional security resources post-design. 2. A site security strategy is a living document that is revised on a periodic or event-driven basis, ensuring that site security operations and corresponding procedures provide long-term, effective protection for the entire nuclear power plant (NPP) site. A site security strategy aims to mitigate threats across the entire NPP site via in-depth defense approaches and mutual support; therefore, if a layer is omitted or altered, then the effect across all layers must be re-evaluated. Therefore, the aim of the site security strategy is to provide an appropriate, scalable security regime that deters, denies, delays, and detects incidents and, equally importantly, reassures legitimate users and the regulator that due diligence and regulatory compliance have been achieved, ensuring that the site is safe and secure. Robust access control for vehicles and pedestrians is at the heart of the strategy. Vehicle and pedestrian searching and screening are seen as the strongest mitigation methods against vehicle- and pedestrian-borne attacks. The security strategy must also be supported through comprehensive staff training and the development of robust processes, procedures, and planning. If all these measures are to be effective, then training must be implemented during each phase of construction, partial operation/commissioning, and full operation. No single element of site security is completely isolated from the influence of other elements. Ideally, consideration of all key elements will result in a security strategy that is integrated and proportional to the threat and that does not over specify individual security solutions through the application of isolated measures but rather applies a holistic, all-encompassing approach. 3. When women enter the labor force, numerous positive outcomes emerge, including increased GDP, educational gains, and decreased maternal mortality. Despite these benefits, women's employment rates and equality vary significantly worldwide as does support for women in the workforce. This paper will explore the multifaceted benefits of women's employment, the factors influencing labor force participation rates, and the urgency to achieve gender equality as outlined in the 2015 United Nations Sustainable Development Goals (SDGs). It will then examine the emerging presence of women in the traditionally male-dominated nuclear field, specifically within the United Arab Emirates (UAE) as a testament to their resilience and determination to break social norms and advance gender equality.

Zineddin, Dr. Z.↗
DOE OSTI2024

Human Factors Challenges in Modernizing Nuclear Power Plant Control Rooms

Jeffrey Joe has been invited to give a presentation entitled, “Human Factors Challenges in Modernizing Nuclear Power Plant Control Rooms,” at the 2024 Human Systems Symposium. Experts conducting human factors and human systems research will gather and share research at this conference. This conference is a good opportunity to develop new business for INL via research collaborations, as attendees exchange knowledge and explore the latest trends, advancements, and challenges in the field of human systems research across the DOE national laboratories.

99 GENERAL AND MISCELLANEOUS↗