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At least 127 records · Page 7

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Digital Transformation for the Existing Fleet: Where to Start?

To remain economically viable in today’s electricity marketplace, nuclear power plants are replacing old analog equipment with modern digital tools. Having information available in an electronic format allows most work processes to become more efficient by automating simple, time-consuming tasks. However, with thousands of routine work processes performed every day, it can be difficult for the plants to know where to begin. We partnered with a nuclear utility to develop a novel assessment tool that measures seven health indicators for each work process performed, providing a rapid digital status report of the plant. The assessment tool is inexpensive and user-friendly, administered remotely, and automatically customized to each employee. Data from 167 employees representing different perspectives were analyzed to identify optimal candidates for digital initiatives that yield the highest payback for increased process efficiencies. We ranked by a priority index to ensure that processes with a good combination of time savings and digital opportunity were at the top. The focus was on determining a maximum investment to ensure that the cost savings from these initiatives are positive over a specified period. We identified potential cost savings of $2.6m, $1.3m and $1.2m for our top priority processes. By using our novel assessment tool to determine the digital status of the plant’s work processes, they were provided with a starting point for target candidates that would most benefit from a digital initiative. Our analysis helps stakeholders understand the financial impact of digital initiatives and identify maximum investment amounts when seeking technical solutions.

assessment↗

DOE OSTI2024

Analyzing the Effects of Atmospheric Turbulent Fluctuations on the Wake Structure of Wind Turbines and Their Blade Vibrational Dynamics

In recent trends, a rising demand for renewable energy has driven wind turbines to larger proportions, where lighter blade designs are often adopted to reduce the costs associated with logistics and production. This causes modern utility-scale wind turbine blades to be inherently more flexible, and their amplified aeroelastic sensitivity results in complex multi-physics reactions to variant atmospheric conditions, including dynamic patterns of aerodynamic loading at the rotor and vortex structure evolutions within the wake. In this paper, we analyze the influence of inflow variance for wind turbines with large, flexible rotors through simulations of the National Rotor Testbed (NRT) turbine, located at Sandia National Labs’ Scaled Wind Farm Technology (SWiFT) facility in Lubbock, Texas. The Common Ordinary Differential Equation Framework (CODEF) modeling suite is used to simulate wind turbine aeroelastic oscillatory behavior and wind farm vortex wake interactions for a range of flexible NRT blade variations, operating in differing conditions of variant atmospheric flow. CODEF solutions of turbine operation in Steady-In-The-Average (SITA) wind conditions are compared to SITA wind conditions featuring a controlled gust-like pulse overimposed, to isolate the effects of typical wind fluctuations. Finally, simulations of realistic time-varying wind conditions from SWiFT meteorological tower measurements are compared to the solutions of SITA wind conditions. These increasingly complex atmospheric inflow variations are tested to show the differing effects evoked by various patterns of spatiotemporal atmospheric flow fluctuations. An analysis is presented for solutions of wind turbine aeroelastic response and vortex wake evolution, to elucidate the consequences of variant inflow, which pertain to wind turbine dynamics at an individual and farm-collective scale. The comparisons of simulated farm flow for SITA and measured fluctuating wind conditions show that certain regions of the wake contain up to a 12% difference in normalized axial velocity, due to the introduction of wind fluctuations. The findings of this study prove valuable for practical applications in wind farm control and optimization strategies, with particular significance for modern utility-scale wind power plants operating in variant atmospheric conditions.

Farrell, Alayna (ORCID:000000023555720X)↗

NASA NTRS1984

A research program in active control/aeroelasticity in the JIAFS at NASA Langley Research Center

A control law synthesis methodology for multifunctional active control system to satisfy root-mean-square load and response constraints as well as to meet stability robustness requirements at plant input and output was developed. Modern control theory, singular value analysis and optimization techniques were utilized. All stability and response derivative expressions were derived analytically for sensitivity study. The software is incorporated as an update to the AB/LAD general control design software package PADLOCS.

Whitesides, J. L.↗

NASA NTRS1996

Identification, Uncertainty Characterization and Robust Control Synthesis Applied to Large Flexible Structures Control

This paper demonstrates an approach to frequency domain identification for the explicit purpose of designing robust H(infinity) controllers. The approach transforms raw experimental data into a plant set estimate directly usable by modern robust control design software(e.g., Matlab Robust Control Toolboxes [11][2]). A key issue in control design from raw data is the question of whether the controller will work when applied to the true system. The main feature fo this approach is that the resulting controller in guaranteed to work as designed(when applied to the true system) to a prescribed statistical confidence. While the overall methodology addresses key theoretical issues, it has at the same time been specifically designed to support practical implementations. A simulation example is included to demonstrate the overall approach.

software↗

DOE OSTI2022

Application of Orthogonal Defect Classification for Software Reliability Analysis

The modernization of existing and new nuclear power plants with digital instrumentation and control systems (DI&C) is a recent and highly trending topic. However, there lacks strong consensus on best-estimate reliability methodologies by both the United States (U.S.) Nuclear Regulatory Commission (NRC) and the industry. This has resulted in hesitation for further modernization projects until a more unified methodology is realized. In this work, we develop an approach called Orthogonal-defect Classification for Assessing Software Reliability (ORCAS) to quantify probabilities of various software failure modes in a DI&C system. The method utilizes accepted industry methodologies for software quality assurance that are also verified by experimental or mathematical formulations. In essence, the approach combines a semantic failure classification model with a reliability growth model to predict (and quantify) the potential failure modes of a DI&C software system. The semantic classification model is used to address the question: How do latent defects in software contribute to different software failure root causes? The use of reliability growth models is then used to address the question: Given the connection between latent defects and software failure root causes, how can we quantify the reliability of the software? A case study was conducted on a representative I&C platform (ChibiOS) running a smart sensor acquisition software developed by Virginia Commonwealth University (VCU). The testing and evidence collection guidance in ORCAS was applied, and defects were uncovered in the software. Qualitative evidence, such as condition coverage, was used to gauge the completeness and trustworthiness of the assessment while quantitative evidence was used to determine the software failure probabilities. The reliability of the software was then estimated and compared to existing operational data of the sensor device. It is demonstrated that by using ORCAS, a semantic reasoning framework can be developed to justify if the software is reliable (or unreliable) while still leveraging the strength of the existing methods.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Application of Orthogonal Defect Classification for Software Reliability Analysis

The modernization of existing and new nuclear power plants with digital instrumentation and control systems (DI&C) is a recent and highly trending topic. However, there lacks strong consensus on best-estimate reliability methodologies by both the United States (U.S.) Nuclear Regulatory Commission (NRC) and the industry. This has resulted in hesitation for further modernization projects until a more unified methodology is realized. In this work, we develop an approach called Orthogonal-defect Classification for Assessing Software Reliability (ORCAS) to quantify probabilities of various software failure modes in a DI&C system. The method utilizes accepted industry methodologies for software quality assurance that are also verified by experimental or mathematical formulations. In essence, the approach combines a semantic failure classification model with a reliability growth model to predict (and quantify) the potential failure modes of a DI&C software system. The semantic classification model is used to address the question: How do latent defects in software contribute to different software failure root causes? The use of reliability growth models is then used to address the question: Given the connection between latent defects and software failure root causes, how can we quantify the reliability of the software? A case study was conducted on a representative I&C platform (ChibiOS) running a smart sensor acquisition software developed by Virginia Commonwealth University (VCU). The testing and evidence collection guidance in ORCAS was applied, and defects were uncovered in the software. Qualitative evidence, such as condition coverage, was used to gauge the completeness and trustworthiness of the assessment while quantitative evidence was used to determine the software failure probabilities. The reliability of the software was then estimated and compared to existing operational data of the sensor device. It is demonstrated that by using ORCAS, a semantic reasoning framework can be developed to justify software reliability (or unreliability) while still leveraging the strength of the existing methods.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1977

Thermal energy storage heat exchanger: Molten salt heat exchanger design for utility power plants

The use of thermal energy storage (TES) in the latent heat of molten salts as a means of conserving fossil fuels and lowering the cost of electric power was evaluated. Public utility systems provided electric power on demand. This demand is generally maximum during late weekday afternoons, with considerably lower overnight and weekend loads. Typically, the average demand is only 60% to 80% of peak load. As peak load increases, the present practice is to purchase power from other grid facilities or to bring older less efficient fossil-fuel plants on line which increase the cost of electric power. The widespread use of oil-fired boilers, gas turbine and diesel equipment to meet peaking loads depletes our oil-based energy resources. Heat exchangers utilizing molten salts can be used to level the energy consumption curve. The study begins with a demand analysis and the consideration of several existing modern fossil-fuel and nuclear power plants for use as models. Salts are evaluated for thermodynamic, economic, corrosive, and safety characteristics. Heat exchanger concepts are explored and heat exchanger designs are conceived. Finally, the economics of TES conversions in existing plants and new construction is analyzed. The study concluded that TES is feasible in electric power generation. Substantial data are presented for TES design, and reference material for further investigation of techniques is included.

Ferarra, A.↗

DOE OSTI2021

Using Qualified On-Site Nuclear Power Plant Simulators in Human Factors Validations of Control Room Upgrades

Existing commercial nuclear power plants (NPPs) are valuable assets in the infrastructure portfolio of the United States (U.S.) because they safely and reliably generate about 1/5th of all the electricity used. The instrumentation and control (I&C) systems in commercial NPPs are the ‘eyes and ears' of the operator, allowing operators to maintain situation awareness, thereby allowing the plant to operate safely and efficiently for all phases of operation. Because the I&C systems in NPPs are still mostly based on analog technologies, which are reliable but not especially cost-effective, upgrading the existing I&C in com-mercial NPPs to new digital I&C is very important. Furthermore, simulators and simulation are critical human factors engineering tools for this I&C modernization work. NPP control room simulators are essential test beds to simulate normal, abnormal, and emergency operations that allow human factors researchers to safely and realistically evaluate early design phase prototypes of the upgraded digital I&C, and validate final as-built digital I&C systems that have been modernized deployed in NPPs. This paper describes research performed using qualified on-site NPP simulators to perform human factors validations of digital I&C control room upgrades.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2023

Light Water Sustainability Program: Optimizing Information Automation Using a New Method Based on System-Theoretic Process Analysis

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. While there are significant opportunities to apply these technologies toward greater plant safety, efficiency, and overall cost-effectiveness, optimizing their design and avoiding potential safety and performance risks depends on ensuring that human-performance-related organizational and technical design issues are identified and addressed. This report describes modeling tools and techniques, based on sociotechnical system theory, to support these design goals and their application in the current research effort. The report is intended for senior nuclear energy stakeholders, including regulators, corporate management, and senior plant management. We have developed and employed a method to design an optimized information automation ecosystem (IAE) based on the systems-theoretic constructs underlying sociotechnical systems theory in general and the Systems-Theoretic Accident Modeling and Processes (STAMP) approach in particular. We argue that an IAE can be modeled as an interactive information control system whose behavior can be understood in terms of dynamic control and feedback relationships amongst the system’s technical and organizational components. Up to this point, we have employed a Causal Analysis based on STAMP (CAST) technique to examine a performance- and safety-related incident at an industry partner’s plant that involved the unintentional activation of an emergency diesel generator. This analysis provided insight into the behavior of the plant’s current information control structure within the context of a specific, significant event. Our ongoing analysis is focused on identifying near-term process improvements and longer-term design requirements for an optimized IAE system. The latter analyses will employ a second STAMP-derived technique, System-Theoretic Process Analysis (STPA). STPA is a useful modeling tool for generating and analyzing actual or potential information control structures. Finally, we have begun modeling plantwide organizational relationships and processes. Organizational system modeling will supplement our CAST and STPA findings and provide a basis for mapping out a plantwide information control architecture. CAST analysis findings indicate an important underlying contributor to the incident under investigation, and a significant risk to information automation system performance, was perceived schedule pressure, which exposed weaknesses in interdepartmental coordination between and within responsible plant organizations and challenged the resilience of established plant processes, until a human caused the initiating event. These findings are discussed in terms of their risk to overall system performance and their implications for information automation system resilience and brittleness. We present two preliminary information automation models. The proactive issue resolution model is a test case of an information automation concept with significant near-term potential for application and subsequent reduction in significant plant events. The IAE model is a more general representation of a broader, plantwide information automation system. From our results, we have generated a set of preliminary system-level requirements and safety constraints. These requirements will be further developed over the remainder of our project in collaboration with nuclear industry subject matter experts and specialists in the technical systems under consideration. Additionally, we will continue to pursue the system analyses initiated in the first part of our effort, with a particular emphasis on STPA as the main tool to identify weak or weakening control structures that affect the resilience of organizations and programs. Our intent is to broaden the scope of the analysis from an individual use case to a related set of use cases (e.g., maintenance tasks, compliance tasks) with similar human-system performance challenges. This will enable more generalized findings to refine the Proactive Issue Resolution and IAE models, as well as their system-level requirements and safety constraints. We will use organizational system modeling analyses to supplement STPA findings and model development. We conclude the report with a set of summary recommendations and an initial draft list of system-level requirements and safety constraints for optimized information automation systems.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Modernizing the Nuclear Industry and New Ways of Working

Nuclear energy is recognized as the most feasible energy source towards achieving nation-wide net-zero goals (COP 208, MIT). Additionally, the demand for reliable, consistent energy supply is soaring with the construction of energy hungry data centers and AI tools. This means the construction of new nuclear and the continuation of current nuclear are a high national priority. However, this leaves the nuclear industry with a workforce challenge. The rising demand for nuclear power is threatened by an underpopulated workforce. There exist a few contributors to the decreased workforce such as skewed workforce demographics resulting in large-scale workforce retirement. Also, some plants have observed difficulty hiring and retaining skill sets that typically comprise the nuclear power workforce – specifically skilled craftsman. Those who are graduating with desirable skills are seeking employment in sectors that are more modern and culturally more aligned with younger generational values. Lastly, within the nuclear sector, skilled employees will be a competitive commodity as advanced plants come online offering work environments that incorporate modern technologies, skill sets, and opportunities for career advancement. These factors emphasize the need for legacy plants to modernize with a focus on the workplace environment and culture that meets younger generations’ skills, cultural expectations, and desire for advancement opportunities. Nuclear plants are actively engaged in deploying advancements that improve the management of systems, structures, and components as well as process improvements and technologies that can reduce the costs of operation and maintenance. However, the advancements must also be analyzed, reviewed and deployed in a manner that considers the impact on how people within the organization collaborate, communicate, make decisions, and solve problems. Neglecting to consider the cultural impact of modernization risks poor adoption, unrealized opportunities, or insignificant change toward helping attract new employees. The traditional way of working is not necessarily the way new generations want to engage with their employer. For instance, in a survey performed by North American Young Generation in Nuclear the top three reasons for younger nuclear employees to seek other job opportunities was seeking better work-life balance, a lack of advancement opportunities, and work culture and leadership style differences (Smyth et al. 2022). Integrated Operations for Nuclear (ION) is an approach for the nuclear industry to create long-term strategic modernization plans and analyze each advancement for the impact on people and processes and measure how those impacts flow up to support high-level, long-term plant goals and requirements. One principle of ION is to replace the current labor-centric operation style in legacy nuclear plants with data-centric collaborative operation styles. This paper will explain how transitioning operations to leverage centralized skills and responsibility, multi-skilled teams, and collaborative decision making can flatten the hierarchical structure in plants, enable greater individual efficacy while also offering more experiences and advancement opportunities to staff. Adopting the ION way of working shifts the industry mind-set towards more networked, collaborative, and modern way of working that will attract skilled, next-generation workers to operate the legacy nuclear fleet.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2020

Impacts of directed evolution and soil management legacy on the maize rhizobiome

Domestication and agricultural intensification dramatically altered maize and its cultivation environment. Changes in maize genetics (G) and environmental (E) conditions increased productivity under high-synthetic-input conditions. However, novel selective pressures on the rhizobiome may have incurred undesirable tradeoffs in organic agroecosystems, where plants obtain nutrients via microbially mediated processes including mineralization of organic matter. Using twelve maize genotypes representing an evolutionary transect (teosintes, landraces, inbred parents of modern elite germplasm, and modern hybrids) and two agricultural soils with contrasting long-term management, here we integrated analyses of rhizobiome community structure, potential microbe-microbe interactions, and N-cycling functional genes to better understand the impacts of maize evolution and soil management legacy on rhizobiome recruitment. We show complex shifts in rhizobiome communities during directed evolution of maize (defined as the transition from teosinte to modern hybrids), with a larger effect of domestication (teosinte to landraces) than modern breeding (inbreds to hybrids) on rhizobiome structure and greater impacts of modern breeding on potential microbe-microbe interactions. Rhizobiome structure was significantly correlated with plant nutrient composition. Furthermore, plant biomass and nutrient content were affected by G x E interactions in which teosinte and landrace genotypes had better relative performance in the organic legacy soil than inbred and modern genotypes. The abundance of six N-cycling genes of relevance for plant nutrition and N loss pathways did not significantly differ between teosinte and modern rhizospheres in either soil management legacy. These results provide insight into the potential for improving maize adaptation to organic systems and contribute to interdisciplinary efforts toward developing resource-efficient, biologically based agroecosystems.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Design of a Geothermal Power Plant With Solar Thermal Topping Cycle: Preprint

Geothermal power plants are a reliable source of low-carbon power generation. However, modern electricity markets comprise relatively large proportions of variable renewable energy generation that may require power plants to dispatch energy flexibly. The power output, efficiency, and dispatch flexibility of a geothermal plant can be enhanced by integrating solar thermal energy into the system, as well as possibly compensating against ambient temperature variations. Concentrating Solar Thermal (CST) can generate temperatures much higher than conventional geothermal systems. Using a solar topping cycle is one way to efficiently convert high-temperature solar heat to electricity while also adding lower-temperature heat to the geothermal power cycle, thereby increasing its power output and possibly its efficiency. A hybrid power cycle design is proposed and is simulated using SimTech IPSEpro process modelling software. The design configuration depends upon the expected temperature of the geothermal resource and the quantity of solar heat added at the design point. These design considerations are described and expected performance is calculated. The solar heat addition varies throughout the day and year, therefore off-design models are necessary to assess the impact of solar availability (and ambient temperature) on the power plant performance. Off-design models are developed and combined with hourly weather data to facilitate an evaluation of annual system performance.

concentrating solar power↗

DOE OSTI2023

Design of a Geothermal Power Plant With Solar Thermal Topping Cycle

Geothermal power plants are a reliable source of low-carbon power generation. However, modern electricity markets comprise relatively large proportions of variable renewable energy generation that may require power plants to flexibly dispatch energy. The power output, efficiency, and dispatch flexibility of a geothermal plant can be enhanced by integrating solar thermal energy into the system, as well as possibly compensating against ambient temperature variations. Concentrating solar thermal (CST) can generate temperatures much higher than conventional geothermal systems. Using a solar topping cycle is one way to efficiently convert high-temperature solar heat to electricity while also cascading lower-temperature heat to the geothermal power cycle, thereby increasing its power output and possibly its efficiency. A hybrid power cycle design is proposed and simulated using SimTech IPSEpro process modeling software. The design configuration depends on the expected temperature of the geothermal resource and the quantity of solar heat added at the design point. These design considerations are described and expected performance is calculated. The solar heat addition varies throughout the day and year; therefore, off-design models are necessary to assess the impact of solar availability (and ambient temperature) on the power plant performance. Off-design models are developed and combined with hourly weather data to facilitate an evaluation of annual system performance.

concentrating solar power↗

DOE OSTI2020

HAZARD ANALYSIS OF DIGITAL ENGINEERED SAFETY FEATURES ACTUATION SYSTEM IN ADVANCED NUCLEAR POWER PLANTS USING A REDUNDANCY-GUIDED 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. 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 triggers of potential single points of failure in the design of digital safety systems in advanced plant designs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Plasma treating water for nitrate based nitrogen fertilizer - A review of recent device designs

Atmospheric pressure air plasma treatment of water is a promising alternative to the industrially intensive Haber-Bosch process for the production of nitrogen fertilizer. Nitrogen fertilizer is vital for plant life, and the environmental impacts of modern fertilizer application cannot be neglected. In order to maintain or increase food production in the future, more sustainable alternatives must be investigated. Plasma can be easily operated at smaller scales, onsite, utilizing green energy sources, cutting down transportation costs and impacts. This article focuses on nitrogen fixation by plasma treating water for use as nitrogen fertilizer. Here, we highlight recent advances (within the last two years) regarding water treating plasma devices, the challenges still facing the field, and recommend more thorough collaborative investigations be carried out in order to focus on the design and optimization of these devices for the future.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Manufacturing Management System Overview [Slides]

Vision: Institute a trusted manufacturing capability within the ALDWP Production Agency enabling digital product acceptance and access to digital manufacturing post-production activities. Mission: Establish a modern manufacturing infrastructure that ensures operator credentials, minimized human transcription errors, capable of managing all aspects of manufacturing including digital data acquisition, NCR resolution, and product acceptance, while providing an effective and intuitive user experience. Strategy: Constitute the modern manufacturing infrastructure to minimize risk and plant disruption while incrementally involving the capability.

42 ENGINEERING↗

NASA NTRS1995

A Globally Optimal Minimax Solution for Spectral Overbounding and Factorization

In this paper, an algorithm is introduced to find a minimum phase transfer function of specified order whose magnitude "tightly" overbounds a specified real-valued nonparametric function of frequency. This method has direct application to transforming nonparametric uncertainty bounds (available from system identification experiments and/or plant modeling) into parametric representations required for modern robust control design software (i.e., a minimum-phase transfer function multiplied by a norm-bounded perturbation).

Scheid, Robert E.↗

DOE OSTI2021

Attaining the promise of plant gene editing at scale

Crop improvement relies heavily on genetic variation that arises spontaneously through mutation. Modern breeding methods are very adept at combining this genetic variation in ways that achieve remarkable improvements in plant performance. Novel traits have also been created through mutation breeding and transgenesis. The advent of gene editing, however, marks a turning point: With gene editing, synthetic variation will increasingly supplement and, in some cases, supplant the genetic variation that occurs naturally. We are still in the very early stages of realizing the opportunity provided by plant gene editing. At present, typically only one or a few genes are targeted for mutation at a time, and most mutations result in loss of gene function. New technological developments, however, promise to make it possible to perform gene editing at scale. RNA virus vectors, for example, can deliver gene-editing reagents to the germ line through infection and create hundreds to thousands of diverse mutations in the progeny of infected plants. With developmental regulators, edited somatic cells can be induced to form meristems that yield seed-producing shoots, thereby increasing throughput and shrinking timescales for creating edited plants. As these approaches are refined and others developed, they will allow for accelerated breeding, the domestication of orphan crops and the reengineering of metabolism in a more directed manner than has ever previously been possible.

59 BASIC BIOLOGICAL SCIENCES↗