SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
A mathematical model of a gas-turbine unit with a free power turbine is presented. The model can be used to study the start-ups and emergency operation of the unit. Alternatives of the automatic start-up algorithm are considered, and the optimal one for a DYa-59L gas-turbine unit is found.
This revised AMO steam tip sheet on installing automatic blowdown controls provide how-to advice for improving industrial steam systems using low-cost, proven practices and technologies.
Navigating through the complex tapestry of technological advancements, "Response Strategy for Hyperparameter attacks of Digital Twin Machine Learning Model in Nuclear Power Plants" stands at the intersection of cybersecurity and nuclear power plant operations, embarking on a journey through the intricacies of securing digital twins against malicious cyber activities. As nuclear power plants progressively integrate digital twin technology and machine learning models to optimize operations and ensure system reliability, they inadvertently expose themselves to a new spectrum of vulnerabilities, notably in the realm of hyperparameter attacks. Hyperparameters, integral in machine learning model tuning and optimal performance of digital twins, have emerged as a target for adversaries aiming to destabilize the predictive capabilities and therefore, the operational accuracy of these digital entities within critical infrastructures like nuclear plants. This paper, therefore, meticulously threads the needle through the development of a robust response strategy, poised to shield these digital reflections against calculated hyperparameter manipulations, ensuring that the digital twin can effectively and securely function as a reliable proxy for its physical counterpart. The ensuing sections delve into the orchestrated maelstrom of multi-rate time-changing intelligent coordinated hyperparameter attacks and the implementation of event-triggered predictive control, laying down a structured, predictive, and responsive framework that safeguards the nexus where the digital and physical realms of nuclear power plants coalesce. The operational integrity of digital twins in nuclear power plants depends critically on the security of machine learning hyperparameters. This study makes two different contributions. First, a decision-based idea known as a multi-rate time changing intelligent coordinated hyperparameter attack is put forth. In this attack, many hyperparameters are repeatedly changed using both random and intelligent optimal techniques by the attacker. These assaults introduce varied rates at different attack steps, compromise various amounts of hyperparameters, and improve stealth and flexibility. Second, a technique is developed for event triggered predictive control to rapidly respond to potential hyperparameter attacks. This control integrates a sliding window framework, retaining a history of previous data points and employing linear regression to predict the next data point from the current dataset. The control gain K is determined using the Lyapunov-Krasovskii method, and subsequently, an action is developed. Finally, the outcome of the simulation demonstrates the viability of the proposed method for defending nuclear power plant digital twins from hyperparameter attacks.
The copolymer of the vinyl chloride-maleic anhydride and silver nano- and microparticle (70 wt %) composition is offered as a conductive adhesive for fixing various chips on the dielectric substrate. The wiring volume resistivity is up to 3.1×10{sup −8} Ohm×m. The adhesive strength of the silver-containing polymer composition (70% of Ag) applied under a shear on the dielectric substrate is 106 N/mm{sup 2}. Adhesive layers obtained from these substances have a high thermal conductivity up to λ = 199.93 W/m×K that depends on the amount of Ag in the polymer composition.
Campaign IV of the Floating Offshore-wind Controls Advanced Laboratory Experimental Program (FOCAL) aimed to generate a dataset enabling the validation of a floating offshore wind turbine with turbine and hull controls. The turbine considered in this campaign is the scaled IEA 15MW Reference Wind Turbine similar to the setup considered in FOCAL Campaign I. This turbine is mounted on the VolturnUS platform with integrated hull controls similar to the hull considered in FOCAL Campaign II/III. This system is deployed for a fully-coupled wind and wave testing campaign at the University of Maine's Harold Alfond Wind and Wave (W2) facility. System dynamics and turbine characteristics are measured to determine global performance and assess the effect of the control strategies employed. NREL's reference open-source controller (ROSCO) is used for active blade pitch control and hull structural control is examined through the use of tuned mass dampers (TMD's) tuned to the systems pitch and tower-bending natural frequency. The naming convention of the load cases considered are described in the data details section. Detailed properties on the modeled system are found in the following reference: Lenfest E., Floating Offshore-wind Controls Advanced Laboratory (FOCAL) Experimental Program - Campaign IV: 1:70 Model-scale Testing of the IEA-Wind 15MW Reference Turbine and the VolturnUS-S Platform. UMaine ASCC Report Number 23-57-1183.
In order to increase the reliability and improve the availability of electron cyclotron heating (ECH) and current drive during a plasma shot, an adaptive gyrotron command generator has been designed and implemented in all gyrotron systems on the DIII-D tokamak. This adaptive real-time generator is able to detect imminent faults, including gyrotron body overcurrent faults that can develop in a few microseconds, block faults, and restart RF generation within 10–30 ms, faster than the DIII-D energy confinement time. The adoption of this adaptive generator has substantially improved the performance of a depressed-collector gyrotron with recurrent body current faults, and has assisted the ECH system to achieve a record reliability of 95% during the last experimental campaign. The impact of power modulation on the collector loading of a depressed-collector gyrotron has been experimentally studied using calorimetry and collector maps taken by a diagnostic developed in-house. While lowering the modulation duty cycle kept the collector power constant as a result of low beam-wave efficiency during the modulation low state, an observed power redistribution inside the collector increased the peak collector power density, which reached levels above the manufacturer power density limit for low duty cycles.
This report provides an assessment of the performance of various instrumentation and control (I&C) and monitoring systems, with a focus on the first few days of the Fukushima Daiichi accident starting on March 11, 2011. Similar to what occurred at the Three Mile Island Unit 2 (TMI-2) accident in 1979, operator responses were challenged when information on key parameters was lost, erroneous, or misleading. While numerous improvements in instrumentation capabilities have been made since the TMI-2 event, the accident at Fukushima Daiichi suggests the potential for further improvement. The objective of this research is to review the performance of the Fukushima Daiichi Units 1–3 instrumentation systems that could have helped ensure that plant operators and emergency responders had relevant, accurate, and timely knowledge of plant conditions as they managed the accident response. As was the case with TMI-2, forensic analyses of plant instrumentation failures will be a long-term effort. As an introduction to this long-term research, this report focuses on the information available in the control room during the accident and illustrates the challenges to operators in their understanding of plant conditions during the progression of the accident. I&C systems monitor the success or failure of achievement of light water reactor safety principles in which the protection of the reactor fuel, reactor coolant system, and reactor containment is accomplished. This report (1) provides an overview of the safety principles; (2) notes parameters associated with the boiling water reactor (BWR)/3 and BWR/4 protection, actuation, and monitoring systems as they relate to the achievement of these principles; (3) presents data from past research on predicted instrumentation performance during severe accidents, and (4) assesses performance of the key I&C and monitoring systems associated with BWR/3 and BWR/4 reactors like those at Fukushima Daiichi. Lessons learned or potential improvements associated with the performance of these systems in the context of severe accidents are delineated. As background information, an overview of key BWR/3- and BWR/4-Mark I reactor designs (BWR/3 and BWR/4 with a Mark I containment) reactor protection, engineered safety features actuation, and accident monitoring systems is provided. A brief description of plant safety systems used to prevent or mitigate reactor accidents is also provided. This background information provides context for the brief discussion of previous research that has been conducted on BWR severe accidents and for the discussion of the accident sequences, which led to core damage at Fukushima Daiichi Units 1–3. The progression of the accident sequences at Fukushima Daiichi Units 1–3 occurred very much as predicted in prior severe accident research conducted in the United States and internationally, given the complete station blackout that occurred when the tsunami generated by one of the most powerful earthquakes ever recorded rolled onshore.
Licensees of commercial nuclear power plants in the US are expected to submit license renewal applications for the period of operation of 60 to 80 years which has also been referred to as long term operation (LTO). The greatest challenges to LTO are associated with degradation of passive components as active components are routinely maintained and repaired or placed through maintenance programs. Some passive component degradation concerns include stress corrosion cracking (SCC) of metal components, radiation induced embrittlement of the reactor pressure vessel (RPV), degradation of buried piping, degradation of concrete containment structures, and degradation of cables. Proactive management of passive component aging employs three important elements including online monitoring of degradation, early detection of degradation at precursor stages, and application of prognostics for the prediction of remaining useful life (RUL). This document assesses several nondestructive examination (NDE) measurement technologies for integration into proactive aging management programs. The assessment is performed by discussing the three elements of proactive aging management identified above, considering the current state of the industry with respect to adopting these key elements, and analyzing measurement technologies for monitoring large cracks in metal components, monitoring early degradation at precursor stages, monitoring the degradation of concrete containment structures, and monitoring the degradation of cables. Specific and general needs have been identified through this assessment. General needs identified include the need for environmentally rugged sensors are needed that can operate reliably in an operating reactor environment, the need to identify parameters from precursor monitoring technologies that are unambiguously correlated with the level of pre-macro defect damage, and a methodology for identifying regions where precursor damage is most likely to initiate.
While most process control industries have been able to embrace digital Instrumentation and Control (I&C) technology to improve performance, reliability, maintainability, and efficiency of production, the nuclear industry has been relatively slow to adopt digital I&C for safety critical plant functions. There are a variety of reasons for this, but in general the nuclear industry takes a conservative stance that new technologies must mature before adoption. A deeper underlying reason for not fully realizing digital I&C and automation in nuclear power is associated with the complexity that can manifest in software-based systems that is different in nature from the complexity of their analog predecessors. Accordingly, this research pursued the development of innovative architectures and methods to “constrain complexity” to enhance verifiability of digital I&C devices. These constraints can positively impact the reduction of Software Common Cause Failures (SCCF) and other systematic errors. The architectural concept developed in this research effort is called SymPLe. SymPLe is specifically aimed at safety critical functions within Nuclear Power Plants and other critical infrastructure where constraining device complexity to support verifiability and safety case arguments is important. The SymPLe architecture is designed to promote “accessible verification” between OEM/utility engineers and the regulatory agencies who review and license nuclear power plant I&C systems. The major contributions of this work to the nuclear industry are: Demonstration of SymPLe as a viable approach to “complexity aware” I&C systems and Embedded Digital Devices.Comprehensive use of model-based design and engineering to produce verifiable I&C systems for the nuclear industry with clear findings on the usability of model-based engineering. Employ comprehensive use of model-based engineering, testing, and verification in an IEC 61508 workflow in support of design assurance. Gathered evidence of “difficult to find” design flaws found using model-based design and testing methods. Detailed the nature of these SCCFs including where they were introduced, the triggers, and how they were found. Gathered evidence on the synergistic use of practical formal methods and testing and how these methods can be used to significantly increase assurance of reduction and avoidance of design flaws.
California's electricity markets are moving toward dynamic pricing models, such as real-time pricing, within the next few years, which could have a significant impact on an industrial facility's cost of energy use during the times of peak use. Adequate controls and automated systems that provide industrial facility managers real-time energy use and cost information are necessary for successful implementation of a comprehensive electricity strategy; however, little is known about the current control capacity of California industries. To address this gap, Lawrence Berkeley National Laboratory, in close collaboration with California industrial trade associations, conducted a survey to determine the current state of controls technologies in California industries. This study identifies sectors that have the technical capability to implement Demand Response (DR) and Automated Demand Response (Auto-DR). In an effort to assist policy makers and industry in meeting the challenges of real-time pricing, facility operational and organizational factors were taken into consideration to generate recommendations on which sectors Demand Response efforts should be focused.
Renewables are key enablers for the realization of a sustainable energy supply but grid operators and energy utilities have to mange their intermittent behavior and limited storage capabilities by ensuring the security of supply and power quality. Advanced control approaches, automation concepts, and communication technologies have the potential to address these challenges by providing new intelligent solutions and products. However, the validation of certain aspects of such smart grid systems, especially advanced control and automation concepts is still a challenge. The main aim of this work therefore is to introduce a hardware-in-the-loop co-simulation-based validation framework which allows the simulation of large-scale power networks and control solutions together with real-world components. The application of this concept to a selected voltage control example shows its applicability.
This work describes progress made towards the development of a real-time hardware-in-the-loop (HIL) test bed for non-nuclear testing of microreactor control schemes and failure modes. Non-nuclear testing is a crucial step in developing robust control algorithms for managing microreactor dynamics. The creation of an HIL simulation harnesses the realistic dynamics of physical analogue systems while additionally considering the challenges of variable communication delay. This collaborative effort between Oak Ridge National Laboratory and Idaho National Laboratory has resulted in a LabVIEW-based gRPC communication protocol which couples a TRANSFORM Modelica simulation of nuclear components to the ViBRANT physical hardware for realistic feedback and visual representation of control action in real time. A modular python client structure is developed to manage FMU-based Modelica simulation and real-time gRPC communication. HIL testing suggests that the modeled reactor with natural convection molten salt loop coolant configuration responds well to PID control of drum positioning for modulation of reactor core power, however, future efforts will be made to explore the added thermal inertial delay of system level control and downstream demand changes. Development of this platform with a generalized methodology provides a foundation for exploring a variety of reactor configurations and failure modes in rapid order to provide insight into the most effective avenues of study for further research and development.
The 600 A and 120 A circuits of the inner triplet magnets of the Large Hadron Collider are powered by resistive gas cooled current leads. The current solution for controlling the gas flow of these leads has shown severe operability limitations. In order to allow a more precise and more reliable control of the cooling gas flow, new flowmeters will be installed during the first long shutdown of the LHC. Because of the high level of radiation in the area next to the current leads, the flowmeters will be installed in shielded areas located up to 50 m away from the current leads. The control valves being located next to the current leads, this configuration leads to long piping between the valves and the flowmeters. In order to determine its dynamic behaviour, the proposed system was simulated with a numerical model and validated with experimental measurements performed on a dedicated test bench.
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. Nuclear plant economic survival in current and forecasted market conditions requires an efficient and technology-centric operating model that harvests the native efficiencies of advanced technology. This is analogous to transformations in nearly every other industry. In light of previous industry experience in modernizing safety Instrumentation and Controls (I&C) systems, nuclear utilities are reluctant to pursue these upgrades due to uncertainty in licensing and cost.
The upcoming environmental requirements outlined at the 2017 European Commission Integrated Pollution Prevention and Control (IPPC) are becoming more and more strict in comparison to the existing standards – IED 2010/75/EU. Questions arise about changes in boiler operating conditions after the adoption of the regulations to fulfill specified emission limits. Of initial concern is the question of which technology to pursue in order to reach the specified level of NOx emissions at 150 mg/Nm 3 @6%O 2 . By introducing an air staging technique the NOx limit can be partially achieved; however these changes affect the boiler operation in a detrimental way. In order to investigate impact of de-NOx installation on the temperature and heat flux distribution, numerical techniques can be used. In order to determine the impact of the changes in the boiler operation, here this paper presents the application of an advanced, multiphase open-source code Arches, developed at the University of Utah for modeling pulverized-coal combustion using Large-Eddy Simulation (LES). Numerical simulations showed the effect on the boiler's working parameters e.g., heat-transfer rate, temperature distribution, species concentration, and NOx emission before and after proposed modifications.
Bluesky Web is a web based interface that provides beam line controls to the end user. It allows users to issue commands to various physical devices at a beam line end station like motors and cameras. It utilizes an open source Python library (Bluesky) as the controller. It uses Bluesky to also allow for running "plans" or a sequence of device operations that can be used when running an experiment. This program is different from other controls technologies because it is intended to be open source and can be accessed from a web browser, as opposed to other paid software that is run as a stand-alone application on a computer.
SAND2025-01910O This software built in LabVIEW FPGA provides experimental control of the RF OPM prototype via a reconfigurable NI I/O card. It samples the analog input, processes it on the FPGA in real time, and generates control and feedback outputs to control and optimize the operation of the device. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
Aspects of the present disclosure include anonymous, asynchronous, and randomized control schemes for distributed energy resources (DERs). Such control schemes may include packetized energy management (PEM) control schemes for managing DERs that may provide near-optimal tracking performance under imperfect information and consumer quality of service (QoS) constraints.