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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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At least 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Supercapacitor to Provide Ancillary Services: Preprint

Supercapacitor technology has reached a level of maturity as a viable energy storage option available to support a modern electric power system grid; however, its application is still limited because of its energy capacity and the cost of the commercial product. In this paper, we demonstrate transient models of supercapacitor energy storage plants operating in coordination with run-of-the-river (ROR), doubly-fed induction generator hydropower plants (HPP) using a system control concept and architecture developed. A detailed transient model of a supercapacitor energy storage device is coupled with the grid via a three-phase inverter/rectifier and bidirectional DC-DC converter. In addition, we use a version of a 14-bus IEEE test case that includes the models of the supercapacitor energy storage device, ROR HPPs, and synchronous condensers that use the rotating synchronous generators of retired coal-powered plants. The purpose of the synchronous condensers is to enhance the system stability by providing voltage and reactive power control, provide power system oscillations damping, and maintain system inertia at secure levels. The control layer provides coordinated, decentralized operation of distributed ROR HPPs and energy storage as aggregate support to power system operations.

25 ENERGY STORAGE↗
DOE OSTI2021

A systematic comparison of machine learning methods for modeling of dynamic processes applied to combustion emission rate modeling

Ten established, data-driven dynamic algorithms are surveyed and a practical guide for understanding these methods generated. Existing Python programming packages for implementing each algorithm are acknowledged, and the model equations necessary for prediction are presented. A case study on a coal-fired power plant’s NO x emission rates is performed, directly comparing each modeling method’s performance on a mutual system. Each model is evaluated by its root mean squared error (RMSE) on out-of-sample future horizon predictions. Optimal hyperparameters are identified using either an exhaustive search or genetic algorithm. The top five model structures of each method are used to recursively predict future NO x emission rates over a 60-step time horizon. The RMSE at each future timestep is determined, and the recursive output prediction trends compared against measurements in time. The GRU neural network is identified as the best candidate for representing the system, demonstrating accurate and stable predictions across the future horizon by all considered models, while satisfactory performance was observed in several of the ARX/NARX formulations. Finally, these efforts have contributed 1) a concise resource of multiple proven dynamic machine learning methods, 2) a practical guide explaining the use of these methods, effectively lowering the “barrier-to-entry” of deploying such models in control systems, 3) a comparison study evaluating each method’s performance on a mutual system, 4) demonstration of accurate multi-timestep emissions modeling suitable for systems-level control, and 5) generalizable results demonstrating the suitability of each method for prediction over a multi-step future horizon to other complex dynamic systems.

42 ENGINEERING↗
DOE OSTI2017

Light Water Reactor Sustainability Program (2016 Accomplishments Report)

This report covers selected highlights from the four research pathways in the LWRS Program: Materials Aging and Degradation; Risk-Informed Safety Margin Characterization; Advanced Instrumentation, Information, and Control Systems Technologies; and Reactor Safety Technologies, as well as a look-ahead at planned activities for 2017.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2013

Commissioning of the Varian TrueBeam linear accelerator: A multi-institutional study

Purpose: Latest generation linear accelerators (linacs), i.e., TrueBeam (Varian Medical Systems, Palo Alto, CA) and its stereotactic counterpart, TrueBeam STx, have several unique features, including high-dose-rate flattening-filter-free (FFF) photon modes, reengineered electron modes with new scattering foil geometries, updated imaging hardware/software, and a novel control system. An evaluation of five TrueBeam linacs at three different institutions has been performed and this work reports on the commissioning experience. Methods: Acceptance and commissioning data were analyzed for five TrueBeam linacs equipped with 120 leaf (5 mm width) MLCs at three different institutions. Dosimetric data and mechanical parameters were compared. These included measurements of photon beam profiles (6X, 6XFFF, 10X, 10XFFF, 15X), photon and electron percent depth dose (PDD) curves (6, 9, 12 MeV), relative photon output factors (Scp), electron cone factors, mechanical isocenter accuracy, MLC transmission, and dosimetric leaf gap (DLG). End-to-end testing and IMRT commissioning were also conducted. Results: Gantry/collimator isocentricity measurements were similar (0.27-0.28 mm), with overall couch/gantry/collimator values of 0.46-0.68 mm across the three institutions. Dosimetric data showed good agreement between machines. The average MLC DLGs for 6, 10, and 15 MV photons were 1.33 {+-} 0.23, 1.57 {+-} 0.24, and 1.61 {+-} 0.26 mm, respectively. 6XFFF and 10XFFF modes had average DLGs of 1.16 {+-} 0.22 and 1.44 {+-} 0.30 mm, respectively. MLC transmission showed minimal variation across the three institutions, with the standard deviation <0.2% for all linacs. Photon and electron PDDs were comparable for all energies. 6, 10, and 15 MV photon beam quality, %dd(10){sub x} varied less than 0.3% for all linacs. Output factors (Scp) and electron cone factors agreed within 0.27%, on average; largest variations were observed for small field sizes (1.2% coefficient of variation, 10 MV, 2 Multiplication-Sign 2 cm{sup 2}) and small cone sizes (<1% coefficient of variation, 6 Multiplication-Sign 6 cm{sup 2} cone), respectively. Conclusions: Overall, excellent agreement was observed in TrueBeam commissioning data. This set of multi-institutional data can provide comparison data to others embarking on TrueBeam commissioning, ultimately improving the safety and quality of beam commissioning.

43 PARTICLE ACCELERATORS↗
DOE OSTI2014

Nonlinear automatic landing control of unmanned aerial vehicles on moving platforms via a 3D laser radar

This paper presents a motion tracking and control system for automatically landing Unmanned Aerial Vehicles (UAVs) on an oscillating platform using Laser Radar (LADAR) observations. The system itself is assumed to be mounted on a ship deck. A full nonlinear mathematical model is first introduced for the UAV. The ship motion is characterized by a Fourier transform based method which includes a realistic characterization of the sea waves. LADAR observation models are introduced and an algorithm to process those observations for yielding the relative state between the vessel and the UAV is presented, from which the UAV's state relative to an inertial frame can be obtained and used for feedback purposes. A sliding mode control algorithm is derived for tracking a landing trajectory defined by a set of desired waypoints. An extended Kalman filter (EKF) is proposed to account for process and observation noises in the design of a state estimator. The effectiveness of the control algorithm is illustrated through a simulation example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Quantum neural networks: Current status and prospects for development

The idea of quantum artificial neural networks, first formulated in [34], unites the artificial neural network concept with the quantum computation paradigm. Quantum artificial neural networks were first systematically considered in the PhD thesis by T. Menneer (1998). Based on the works of Menneer and Narayanan [42, 43], Kouda, Matsui, and Nishimura [35, 36], Altaisky [2, 68], Zhou [67], and others, quantum-inspired learning algorithms for neural networks were developed, and are now used in various training programs and computer games [29, 30]. The first practically realizable scaled hardware-implemented model of the quantum artificial neural network is obtained by D-Wave Systems, Inc. [33]. It is a quantum Hopfield network implemented on the basis of superconducting quantum interference devices (SQUIDs). In this work we analyze possibilities and underlying principles of an alternative way to implement quantum neural networks on the basis of quantum dots. A possibility of using quantum neural network algorithms in automated control systems, associative memory devices, and in modeling biological and social networks is examined.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

MAR ASSESSMENTS OF THE HIGH LEVEL WASTE SYSTEM PLAN REVISION 16

High-level waste (HLW) throughput (i.e., the amount of waste processed per unit of time) is primarily a function of two critical parameters: waste loading (WL) and melt rate. For the Defense Waste Processing Facility (DWPF), increasing HLW throughput would significantly reduce the overall mission life cycle costs for the Department of Energy (DOE). Significant increases in waste throughput have been achieved at DWPF since initial radioactive operations began in 1996. Key technical and operational initiatives that supported increased waste throughput included improvements in facility attainment, the Chemical Processing Cell (CPC) flowsheet, process control models and frit formulations. As a result of these key initiatives, DWPF increased WLs from a nominal 28% for Sludge Batch 2 (SB2) to {approx}34 to 38% for SB3 through SB6 while maintaining or slightly improving canister fill times. Although considerable improvements in waste throughput have been obtained, future contractual waste loading targets are nominally 40%, while canister production rates are also expected to increase (to a rate of 325 to 400 canisters per year). Although implementation of bubblers have made a positive impact on increasing melt rate for recent sludge batches targeting WLs in the mid30s, higher WLs will ultimately make the feeds to DWPF more challenging to process. Savannah River Remediation (SRR) recently requested the Savannah River National Laboratory (SRNL) to perform a paper study assessment using future sludge projections to evaluate whether the current Process Composition Control System (PCCS) algorithms would provide projected operating windows to allow future contractual WL targets to be met. More specifically, the objective of this study was to evaluate future sludge batch projections (based on Revision 16 of the HLW Systems Plan) with respect to projected operating windows using current PCCS models and associated constraints. Based on the assessments, the waste loading interval over which a glass system (i.e., a projected sludge composition with a candidate frit) is predicted to be acceptable can be defined (i.e., the projected operating window) which will provide insight into the ability to meet future contractual WL obligations. In this study, future contractual WL obligations are assumed to be 40%, which is the goal after all flowsheet enhancements have been implemented to support DWPF operations. For a system to be considered acceptable, candidate frits must be identified that provide access to at least 40% WL while accounting for potential variation in the sludge resulting from differences in batch-to-batch transfers into the Sludge Receipt and Adjustment Tank (SRAT) and/or analytical uncertainties. In more general terms, this study will assess whether or not the current glass formulation strategy (based on the use of the Nominal and Variation Stage assessments) and current PCCS models will allow access to compositional regions required to targeted higher WLs for future operations. Some of the key questions to be considered in this study include: (1) If higher WLs are attainable with current process control models, are the models valid in these compositional regions? If the higher WL glass regions are outside current model development or validation ranges, is there existing data that could be used to demonstrate model applicability (or lack thereof)? If not, experimental data may be required to revise current models or serve as validation data with the existing models. (2) Are there compositional trends in frit space that are required by the PCCS models to obtain access to these higher WLs? If so, are there potential issues with the compositions of the associated frits (e.g., limitations on the B{sub 2}O{sub 3} and/or Li{sub 2}O concentrations) as they are compared to model development/validation ranges or to the term 'borosilicate' glass? If limitations on the frit compositional range are realized, what is the impact of these restrictions on other glass properties such as the ability to suppress nepheline formation or influence melt rate? The model based assessments being performed make the assumption that the process control models are applicable over the glass compositional regions being evaluated. Although the glass compositional region of interest is ultimately defined by the specific frit, sludge, and WL interval used, there is no prescreening of these compositional regions with respect to the model development or validation ranges which is consistent with current DWPF operations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Method for automatic correction of offset drift in online sensors

Abstract Successful operation and optimization of water treatment systems hinge on the availability of high-quality online sensor measurements. Ideally, the available measurements should be simultaneously accurate (i.e., unbiased and precise), representative, voluminous, and timely. This remains a pain-point in current water infrastructures, forming a barrier to a wider adoption of advanced and autonomous control systems. While short-lived symptoms, such as outliers and spikes, can be detected or corrected with state-of-the-art tools for fault detection and identification, it is much more difficult to detect, diagnose, and correct the symptoms of slow faults, such as changes in offset or sensitivity due to drift. The time scale of drift is often longer than the time scales of the system dynamics of interest. Moreover, sensor drift has been shown to occur at the same time and with similar rates when sensors are exposed to the same conditions. This challenges data quality management strategies based on redundancy. In this contribution, we develop a new method, including both a hands-off sensor calibration mechanism and an information-seeking control architecture that can handle the unique challenge of simultaneous and similar drift in online sensors.

Chowdhury, Dhrubajit↗
DOE OSTI2014

Feedback control of torsion balance in measurement of gravitational constant G with angular acceleration method

The performance of the feedback control system is of central importance in the measurement of the Newton's gravitational constant G with angular acceleration method. In this paper, a PID (Proportion-Integration-Differentiation) feedback loop is discussed in detail. Experimental results show that, with the feedback control activated, the twist angle of the torsion balance is limited to 7.3×10{sup −7} rad /√( Hz ) at the signal frequency of 2 mHz, which contributes a 0.4 ppm uncertainty to the G value.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Control of confidence domains in the problem of stochastic attractors synthesis

A nonlinear stochastic control system is considered. We discuss a problem of the synthesis of stochastic attractors and suggest a constructive approach based on the design of the stochastic sensitivity and corresponding confidence domains. Details of this approach are demonstrated for the problem of the control of confidence ellipses near the equilibrium. An example of the control for stochastic Van der Pol equation is presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

On the Limits of EM Based Detection of Control Logic Injection Attacks In Noisy Environments

The difficulty in applying traditional security mechanisms in Industrial Control System (ICS) environments makes a large portion of these mission-critical assets vulnerable to cyber attacks. Therefore, there is a dire need for the development of novel security mechanisms specifically designed to protect such critical systems. Recently a lot of attention has been given to mechanisms that exploit the EM emanations of devices for defense purposes. Such practices may lead to the development of robust external and non-intrusive anomaly detection systems. Nevertheless, the majority of current work in the area neglects to consider the implications of real-life environments, particularly environmental noise. In this work, we explore the limits of EM-based anomaly detection towards identifying injection attacks in control logic software in noisy environments. Our study conducted upon both synthetically generated and real signals identified that indeed environmental noise might significantly degrade the accuracy of the anomaly detection process. Experiments done upon synthetic data indicated that assuming that signals are captured with high sampling rates, even minor code injections can be detected with above-90% accuracy in noisy environments where SNR is up to -2dB. This is true even if naive detection methods are considered. Moreover, experiments done using a real-life testbed attest that even single-instruction injections can be detected with near-perfect accuracy in relatively clean environments. Finally, noise-elimination techniques can drastically improve the reliability of the detection mechanism even in noisy environments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Overview of simulation and control tools for extended operability of nuclear reactors - 183

The increasing penetration of Renewable Energy Sources (RES) requires the current power grid to be suitably improved. Because of the unsteady nature of RES, as long as energy storage facilities are not deployed and commercialized, an increased effort for the frequency regulation in order to ensure high reliability and performance is necessary. In such a scenario, nuclear units (traditionally deployed as baseload generating units) will be required to cooperate with intermittent RES-based power plants. Therefore, new reactors will need larger operational flexibility with respect to the capabilities of the currently operated units. Over the last few years, a comprehensive research program oriented at developing a suite of simulation tools and control system development capabilities was pursued at Argonne National Laboratory. In addition to the study of advanced reactor concepts (e.g. metal-fueled Sodium-cooled Fast Reactors) and technological innovations (such as S-CO{sub 2} Energy Conversion Cycles), new control approaches were developed to improve the operability of nuclear power plants. In particular, Model-based Predictive Control algorithm for Multiple Input Multiple Output control strategies and set-point definition algorithm based on Reference Governor were studied and applied to specific scenarios, providing with a range of novel capabilities able to meet the expected greater sets of requirements mentioned above. In this work, an overview of such tools and case studies is presented with particular focus on their impact on operability and economic competitiveness of nuclear energy. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

2D microwave imaging reflectometer electronics

A 2D microwave imaging reflectometer system has been developed to visualize electron density fluctuations on the DIII-D tokamak. Simultaneously illuminated at four probe frequencies, large aperture optics image reflections from four density-dependent cutoff surfaces in the plasma over an extended region of the DIII-D plasma. Localized density fluctuations in the vicinity of the plasma cutoff surfaces modulate the plasma reflections, yielding a 2D image of electron density fluctuations. Details are presented of the receiver down conversion electronics that generate the in-phase (I) and quadrature (Q) reflectometer signals from which 2D density fluctuation data are obtained. Also presented are details on the control system and backplane used to manage the electronics as well as an introduction to the computer based control program.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

Experiment Automation with a Robot Arm using the Liquids Reflectometer Instrument at the Spallation Neutron Source

The Liquids Reflectometer instrument installed at the Spallation Neutron Source (SNS) enables observations of chemical kinetics, solid-state reactions and phase-transitions of thin film materials at both solid and liquid surfaces. Effective measurement of these behaviors requires each sample to be calibrated dynamically using the neutron beam and the data acquisition system in a feedback loop. Since the SNS is an intense neutron source, the time needed to perform the measurement can be the same as the alignment process, leading to a labor-intensive operation that is exhausting to users. An update to the instrument control system, completed in March 2013, implemented the key features of automated sample alignment and robot-driven sample management, allowing for unattended operation over extended periods, lasting as long as 20 hours. We present a case study of the effort, detailing the mechanical, electrical and software modifications that were made as well as the lessons learned during the integration, verification and testing process.

automated alignment↗
DOE OSTI2012

Upgrade of the MIT Linear Electrostatic Ion Accelerator (LEIA) for nuclear diagnostics development for Omega, Z and the NIF

The MIT Linear Electrostatic Ion Accelerator (LEIA) generates DD and D{sup 3}He fusion products for the development of nuclear diagnostics for Omega, Z, and the National Ignition Facility (NIF). Significant improvements to the system in recent years are presented. Fusion reaction rates, as high as 10{sup 7} s{sup -1} and 10{sup 6} s{sup -1} for DD and D{sup 3}He, respectively, are now well regulated with a new ion source and electronic gas control system. Charged fusion products are more accurately characterized, which allows for better calibration of existing nuclear diagnostics. In addition, in situ measurements of the on-target beam profile, made with a CCD camera, are used to determine the metrology of the fusion-product source for particle-counting applications. Finally, neutron diagnostics development has been facilitated by detailed Monte Carlo N-Particle Transport (MCNP) modeling of neutrons in the accelerator target chamber, which is used to correct for scattering within the system. These recent improvements have resulted in a versatile platform, which continues to support the existing nuclear diagnostics while simultaneously facilitating the development of new diagnostics in aid of the National Ignition Campaign at the National Ignition Facility.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

Advanced WEC Dynamics & Controls FY16 Testing Report

A model-scale wave tank test was conducted in the interest of improving control systems design of wave energy converters (WECs). The success of most control strategies is based directly upon the availability of a reduced-order model with the ability to capture the dynamics of the system with sufficient accuracy. For this reason, the test described in this report, which is the first in a series of planned tests on WEC controls, focused on system identification (system ID) and model validation.

42 ENGINEERING↗
DOE OSTI2016

Development of autonomous multirotor platform for exploration missions

This paper outlines development process of unmanned multirotor aerial vehicle HF-4X, which consists of design and manufacturing semi-autonomous UAV dedicated for indoor flight, which would be capable of stable and controllable mission flight. A micro air vehicle was designed to participate in the International Micro Air Vehicle Conference and Flight Competition. In this paper much attention was paid to the structure of flight control system, stabilization algorithms, analysis of IMU sensors, fusion algorithms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Machine Learning-Based PV Reserve Determination Strategy for Frequency Control on the WECC System: Preprint

Frequency control from Photovoltaic (PV) plants has great potential to address the frequency response challenge of the power system with high renewable penetration. However, using model-based approaches to determine the optimal PV headroom reserve requires significant online computation and is intractable for an interconnection level system. This paper proposes a machine learning based strategy, that is suitable for real-time operation, to determine the optimal PV reserve for frequency control. The proposed machine learning algorithm is trained and tested on 1,987 offline simulations of a 60% renewable penetration Western Electricity Coordinating Council (WECC) system. Furthermore, the proposed reserve determination strategy is applied on a realistic one-day operation profile of the WECC system and demonstrates over 40% PV headroom saving compared to a conservative approach. It is evident that the proposed strategy can efficiently and effectively determine the optimal PV frequency control reserve for realistic interconnection systems.

41 EE - Solar Energy Technologies Office (EE-4S)↗