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Algorithms for current stabilization in the control of contact welding are considered. The proposed method for specifying and maintaining the welding current permits correction of the thyristor firing angle by means of an approximate formula taking account of the measured current-pulse parameters in phase regulation. The proposed method simplifies the equipment and increases the efficiency of regulation.
In the control of DC/AC switched power converters (SPC), one of the most important aspects to be considered is the selection of the real-time control platform. The real-time control platform must be able to meet the high performance efficiency and regulation requirements of the DC/AC SPC, as these typically operate at switching frequencies in the order of kHz to MHz. For this reason, the hardware characteristics of the ADC and PWM, and the processing capacity of the real-time control platform are of vital importance when implementing advanced digital controllers that maintain voltage and current levels within regulatory standards. In this context, we aimed to perform a comparative study of the computation times of different real-time control platforms when implementing different control strategies for DC/AC switched power converters. We also analyzed the impact of the real-time control platforms on the THD of the voltages generated by the DC/AC switched power converters. With the help of this paper, researchers and developers will have criteria to select which real-time control platform to use in real-time control for DC/AC SPC applications.
The instrumentation and control (I and C) equipment used in currently operating U.S. nuclear power plants (NPPs) is primarily based on mature analog technologies that are progressing towards obsolescence. The continued reliance on this legacy analog technology, which is also being propagated into new NPP designs, imposes performance penalties and maintenance burdens in comparison with modern digital I and C instrumentation. In many instances, currently available I and C equipment contain embedded digital devices (EDDs) such as microprocessors and programmable logic devices. Experience in other industries, such as avionics, has shown that digital I and C equipment containing EDDs can provide significant benefits over analog-based equipment in terms of performance, reliability, and maintainability. In recent years, due to the high demand for digital technologies in the industrial I and C marketplace, it is becoming increasingly difficult for NPPs to acquire instrumentation that is not equipped with an EDD. However, the nuclear power industry has been slow to adopt digital technology, especially in safety-related systems, in large part as a result of regulatory concerns about common-cause failure (CCF) vulnerabilities of equipment with EDDs. Consequently, there is a clear need to develop cost effective qualification methods to contribute to the assessment of CCF vulnerability posed by EDDs in modern instrumentation that could be used in NPPs. This paper describes the research regarding qualification methods for equipment with EDDs that is sponsored by the Nuclear Energy Enabling Technologies (NEET) Advanced Sensors and Instrumentation (ASI) program of the U.S. Department of Energy (DOE). The purpose of the current research is to develop an effective approach employing science-based methods to resolve concerns about CCF vulnerability that serve to inhibit deployment of advanced instrumentation (e.g., sensors, actuators, microcontrollers) with EDDs in nuclear power applications. (authors)
Solar fuels are proven to be promising candidates for thermochemical energy storage. However, the transient nature of solar radiation is an obstacle to maintaining a stable operational temperature inside a solar reactor. To overcome this challenge, the temperature of a solar reactor can be regulated by controlling the incoming solar radiation or the feedstock flowrate inside the reactor. In this work, a combined proportional integral derivative (PID) controller is implemented to regulate the temperature inside a high-temperature tubular solar reactor with counter-current flowing gas/particles. The control model incorporates two control systems to regulate incoming solar radiation and gas flow simultaneously. The design of the controller is based on a reduced-order numerical model of a high-temperature tubular solar reactor that is vertically oriented with an upward gas flow and downward particle flow. The reactor receives heat circumferentially through its wall over a finite segment of its length. Formulation of the heat transfer model is presented by applying the energy balance for the reactor tube and considering heat and mass transfer inside. A set of governing differential equations are solved numerically by using the finite volume method to obtain reactor wall, particles, and gas temperatures along the reactor length with various boundary conditions. Simulation results are used to tune the PID controller parameters by utilizing the Ziegler–Nichols tuning method. Both the simulation results and the controller performance are visualized on the LABVIEW platform. The controller is challenged to track different temperature setpoints with different scenarios of transient solar radiation. Here, the performance of the PID controller was compared to experimental results obtained from an industrial PID controller embedded in a 7 kW electric furnace. Results show that the combined PID controller is successful in maintaining a stable temperature inside the reactor by regulating the incoming solar radiation and the flowrate via small steady-state error and reasonable settling time and overshoot.
We propose a method to design shortcuts to adiabaticity for implementing perfect quantum state engineering by the combination of the counterdiabatic driving and the reverse engineering technique. Based on the method, we can design simple schemes to realize the intended dynamics. For the sake of clearness, we apply this method to several examples including two-level, three-level and four-level system. We show that fast quantum state engineering can be realized by utilizing simply-designed auxiliary Hamiltonian. Furthermore, a suitable choice of the control parameters can eliminate the additional couplings in the introduced auxiliary Hamiltonian. Numerical simulation reveals that the constructed scheme is reliable and robust against various dissipation effects and the fluctuations of control parameters in current technology. - Highlights: • Fast and feasible quantum state engineering can be realized by using the method. • The method allows one to control accurately the evolution of the system. • The scheme is fast and robust against dissipation effects and parameter errors. • The scheme can be generalized to realize N-dimensional quantum state engineering.
As the current fleet of nuclear power plants are maintaining outdated or obsolete equipment it is common practice to replace worn-out equipment on an as-needed basis resulting in a series of like-for-like replacements of components on the control boards addressing an immediate need to replace equipment. Such upgrades rarely represent an encompassing or systematic vision for control room modernization and do not add the additional benefit of enhanced support for operators in the control room, which tend to overlook the opportunity to reduce operations and maintenance costs through enhanced efficiency. The purpose of the research is to provide guidance on how to realize these opportunities by designing control room human-system interfaces with advanced capabilities in mind. Further, the research seeks to ensure that control room modernizations are undertaken with a sound understanding of the impacts to human operators and are designed based on state-of-the art human factors principles. This report describes the conceptual design of the liquid radiological waste system and several research activities conducted to inform the design philosophy. The report also provides recommended updates to the original design philosophy (published by the researchers in 2018) based on the findings.
Controlled partial stabilization of core m/n – 2/1 Neoclassical Tearing Modes (NTMs) by fueling deuterium pellets is reported in DIII-D and KSTAR H-mode plasmas (m=n are the poloidal/toroidal mode numbers). Analyses of DIII-D data exploring possible physics origins show that an explanation is offered by NTM-turbulence multi-scale interaction, triggered by a sudden increase of local gradients near q–2 caused by the pellet. Pellet injection from the high-field side allows deep fueling which reaches the island region. In turn, low-k turbulent density fluctuations (ñ) increase by 30% in the island region. This ñ can drive transport across the island separatrices, reducing the pressure at spot at the O-point and diminishing the NTM drive. The Mirnov probe array detects the reduction of the 2/1 magnetic amplitude by up to 20%. Causality between elevated gradients outside of the island, turbulence spreading into the island and reduced NTM drive is qualitatively supported by non-linear gyrokinetic turbulence simulations. These demonstrate increased penetration of ion-scale ñ from the background plasma to the O-point region when the background gradient is increased. This interaction has potentially far reaching consequences as it can can lead to a reduction of the required electron cyclotron current density (j ECCD ) for NTM suppression by 70%, as predicted by the modified Rutherford equation. Furthermore, this beneicial effect of fueling pellets can be important as j ECCD is the anticipated active NTM control technique for the International Thermonuclear Experimental Reactor (ITER), but its efficiency will be lowered by third harmonic absorption in Pre-Fusion Power Operation-1 (PFPO-1) at half magnetic field.
Purpose: Silicon photodetectors are of significant interest for use in positron emission tomography (PET) systems due to their compact size, insensitivity to magnetic fields, and high quantum efficiency. However, one of their main disadvantages is fluctuations in temperature cause strong shifts in gain of the devices. PET system designs with high photodetector density suffer both increased thermal density and constrained options for thermally regulating the devices. This paper proposes a method of thermally regulating densely packed silicon photodetectors in the context of a 1 mm{sup 3} resolution, high-sensitivity PET camera dedicated to breast imaging. Methods: The PET camera under construction consists of 2304 units, each containing two 8 × 8 arrays of 1 mm{sup 3} LYSO crystals coupled to two position sensitive avalanche photodiodes (PSAPD). A subsection of the proposed camera with 512 PSAPDs has been constructed. The proposed thermal regulation design uses water-cooled heat sinks, thermoelectric elements, and thermistors to measure and regulate the temperature of the PSAPDs in a novel manner. Active cooling elements, placed at the edge of the detector stack due to limited access, are controlled based on collective leakage current and temperature measurements in order to keep all the PSAPDs at a consistent temperature. This thermal regulation design is characterized for the temperature profile across the camera and for the time required for cooling changes to propagate across the camera. These properties guide the implementation of a software-based, cascaded proportional-integral-derivative control loop that controls the current through the Peltier elements by monitoring thermistor temperature and leakage current. The stability of leakage current, temperature within the system using this control loop is tested over a period of 14 h. The energy resolution is then measured over a period of 8.66 h. Finally, the consistency of PSAPD gain between independent operations of the camera over 10 days is tested. Results: The PET camera maintains a temperature of 18.00 ± 0.05 °C over the course of 12 h while the ambient temperature varied 0.61 °C, from 22.83 to 23.44 °C. The 511 keV photopeak energy resolution over a period of 8.66 h is measured to be 11.3% FWHM with a maximum photopeak fluctuation of 4 keV. Between measurements of PSAPD gain separated by at least 2 day, the maximum photopeak shift was 6 keV. Conclusions: The proposed thermal regulation scheme for tightly packed silicon photodetectors provides for stable operation of the constructed subsection of a PET camera over long durations of time. The energy resolution of the system is not degraded despite shifts in ambient temperature and photodetector heat generation. The thermal regulation scheme also provides a consistent operating environment between separate runs of the camera over different days. Inter-run consistency allows for reuse of system calibration parameters from study to study, reducing the time required to calibrate the system and hence to obtain a reconstructed image.
We propose a compact chaotic laser device, which consists of a semiconductor laser and a two-dimensional (2D) external cavity for delayed optical feedback. The overall size of the device is within 230 μm × 1 mm. A long time delay sufficient for chaos generation can be achieved with the small area by the multiple reflections at the 2D cavity boundary, and the feedback strength is controlled by the injection current to the external cavity. We experimentally demonstrate that a variety of output properties, including chaotic output, can be selectively generated by controlling the injection current to the external cavity.
This paper outlines a reduced-order aggregate dynamical model for parallel-connected single-phase grid-connected inverters. For each inverter, we place no restrictions on the converter topology and merely assume that the ac-side switch-averaged voltage can be controlled via pulsewidth modulation. The ac output of each inverter interfaces through an LCL filter to the grid. The closed-loop system contains a phase locked loop for grid synchronization, and real- and reactive-power control are realized with inner and outer PI current- and power-control loops. We derive a necessary and sufficient set of parametric relationships to ensure that a reduced-order aggregated state-space model for an arbitrary number of such paralleled inverters has the same model order and structure as any single inverter. We also present reduced-order models for the settings where the real- and reactive-power setpoints are different and where the inverters have different power ratings. We anticipate the proposed model being useful in analyzing the dynamics of large collections of parallel-connected inverters with minimal computational complexity. The aggregate model is validated against measurements obtained from a multi-inverter experimental setup consisting of three 750-VA paralleled grid-connected inverters, hence establishing robustness of the analytical result to parametric variations seen in practice.
General Electric, the National Renewable Energy Laboratory (NREL), the University of Massachusetts Amherst (UMass), and Glosten have recently completed a US Department of Energy (DOE)-funded research program to study technologies for mitigating loads on floating offshore wind turbines through the use of advanced turbine controls and tuned mass dampers (TMDs). The analysis was based upon the Glosten PelaStar tension leg platform (TLP) with GE Haliade 150 turbine, a system developed in a previous front end engineering design (FEED) study funded by the Energy Technology Institute (ETI) in the UK. The platform was designed for the WaveHub wave energy research site, with a mean water depth of 59-m. Loads were analyzed by running time-domain simulations in four 50-year return period (50-YRP) ultimate load state (ULS) conditions and 77 fatigue load state (FLS) environmental conditions. In 50-YRP conditions advanced controls are not active. The influence of TMDs on ULS loads have been reported previously (Park et al. [2]). In FLS conditions advanced controls and TMDs afford dramatic reductions in fatigue damage, offering the potential of significant savings in tower structural requirements. Simulations in turbine idling conditions were run in OrcaFlex, and simulations in operating conditions were run in FAST. Simulations were run with a baseline turbine controller, representative of the current state of the art, and an advanced controller developed by NREL to use collective and individual blade pitch control to maintain rotor speed and reduce tower loads. UMass developed a number of TMD types, with varying system configurations, including passive nonlinear dampers and semi-actively controlled dampers with an inverse velocity groundhook control algorithm. Loads and accelerations in FLS conditions were evaluated on the basis of damage equivalent loads (DELs), and fatigue damage was computed by Miner's summations of stress cycles at the tower base. To study sensitivity to water depth, loads were analyzed at both the 59-m WaveHub depth and a more commercially realistic depth of 100 m. TMDs reduce fatigue damage at the tower-column interface flange by up to 52% in 59-m water depth and up to 28% in 100 m water depth. Advanced controls reduce fatigue damage at the tower-column flange by up to 22% in 59-m water depth and up to 40% in 100 m water depth. The most effective load-mitigation strategy is combining advanced controls with TMDs. This strategy affords a 71% reduction in fatigue damage in both 59-m and 100-m water depths.
Los Alamos is currently developing novel particle accelerator controls and diagnostics algorithms to enable higher quality beams with lower beam losses than is currently possible. The purpose of this workshop was to consider tuning and optimization challenges of a wide range of particle accelerators including linear proton accelerators such as the Los Alamos Neutron Science Center (LANSCE), rings such as the Advanced Photon Source (APS) synchrotron, free electron lasers (FEL) such as the Linac Coherent Light Source (LCLS) and LCLS-II, the European X-ray Free Electron Laser (EuXFEL), the Swiss FEL, and the planned MaRIE FEL, and plasma wake- eld accelerators such as FACET, FACET-II, and AWAKE at CERN. One major challenge is an the ability to quickly create very high quality, extremely intense, custom current and energy pro le beams while working with limited real time non-invasive diagnostics and utilizing time-varying uncertain initial beam distributions and accelerator components. Currently, a few individual accelerator labs have been developing and applying their own diagnostics tools and custom control and ML algorithms for au- tomated machine tuning and optimization. The goal of this workshop was to bring together a group of accelerator physicists and accelerator related control and ML experts in order to de ne which controls and diagnostics would be most useful for existing and future accelerators and to create a plan for developing a new family of algorithms that can be shared and maintained by the community.
A novel submodule capacitor discharging control strategy is introduced and implemented for modular multilevel converters (MMCs). By sequentially controlling the arm currents of anMMC,all submodule capacitors are discharged rapidly through internal arm resistors without additional devices and circuits, resulting in improved performance and reduced cost. A closed-loop control method is explored for the effectiveness of the new control strategy.Acomparison study is evaluated between the proposed method and the traditional methods using bleeding resistors, auxiliary resistors, and load resistors. Confirmed by the simulation and experiment, the proposed method has the maximum benefits including zero hardware cost, fast discharging time, and negligible load current impact
The NO x Storage-Reduction (NSR, also known as lean-NO x trap – LNT), is based upon the concept of storing NO x as nitrates over storage components, typically barium species, during a lean-burn operation cycle and then reducing the stored nitrates to N 2 during fuel-rich conditions over a precious metal catalyst [1]. NO x Selective Catalytic Reduction (SCR), on the other hand, is accomplished by deliberately introducing reductant urea into the engine exhaust to reduce NO x with the aid of a Cu(Fe)/zeolite catalyst [2]. These two technologies have been recognized as the most promising approaches for meeting stringent NO x emission standards for diesel vehicles within the Environmental Protection Agency’s (EPA’s) 2007/2010 mandated limits. For NSR, problems arising from either or both thermal and SO 2 deactivation must be addressed to meet durability standards. For SCR, SO 2 deactivation is less of an issue, but hydrothermal deactivation of the zeolite catalysts must be addressed. With continuing R&D efforts in advanced powertrains, highly novel operating modes for internal combustion engines (ICEs) are being researched in order to meet the very stringent new demands for fuel efficiency (e.g., U.S. ‘‘CAFE’’ standards for average miles/gallon are scheduled to increase dramatically over the next 10–15 years). These new ICE engine operation modes, while highly fuel-efficient, result in much lower exhaust temperatures than current engines; temperatures so low that it is hard to imagine how the current catalytic emission control technologies will be able to function. For example, while steady-state operation of the NO x reduction technology at 150 °C may be required, current ‘‘light-off’’ temperatures for CHA-based zeolite catalysts are closer to 200 °C. Therefore, understanding low-temperature limitations in NO x reduction has become one of the most daunting challenges in R&D on new catalyst materials and processes that can effectively eliminate emissions at these quite low exhaust temperatures. This project has two clear focuses: (1) development of potassium-based high-temperature NSR materials, and studying their key causes of deactivation and methods of regeneration. By comparing results obtained on ‘Simple Model’ Pt-K/Al 2 O 3 with ‘Enhanced Model’ Pt-K/ MgAlO x and Pt-K/TiO 2 materials, we have developed an understanding of the role of various additives on the deactivation and regeneration processes. Studies have also been performed on the real commercial samples being used in a Dodge Ram truck with a Cummins diesel emission control system. However, the results about these ‘commercial samples’ will not be covered in this report. Following a brief description of our experimental approach, we will present a few highlights from some of the work performed in this CRADA with more details about these results provided in publications/reports/presentations lists presented at the end of the report. (2) for the Cu and Fe/Chabazite SCR catalysts, since these are so newly developed and references from open literature and industry are nearly absent, our work started from zeolite synthesis and catalyst synthesis methodology development, before research on their low- and high-temperature performance, deactivation, regeneration, etc. was conducted. Again, most work reported here is based on our “model” catalysts synthesized in-house. Work done on the ‘commercial samples’ will not be covered in this report.
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.
A simple kinetic model describing stationary solutions with bifurcated and single-peaked current density profiles of a plane electron beam or current sheet in plasma is presented. A connection is established between the two-dimensional constructions arising in terms of the model and the one-dimensional considerations by Bernstein−Greene−Kruskal facilitating the reconstruction of the distribution function of trapped particles when both the profile of the electric potential and the free particles distribution function are known.
Systems and methods are provided for an electrical system. The electrical system includes a load, an interface configured to receive a voltage from a voltage source, and a controller configured to receive the voltage from the voltage source through the interface and to provide a voltage and current to the load. Wherein, when the controller is in a constant voltage mode, the controller provides a constant voltage to the load, when the controller is in a constant current mode, the controller provides a constant current to the load, and when the controller is in a constant power mode, the controller provides a constant power to the load.
The low in-plane symmetry in layered 1T'-ReS 2 results in strong band anisotropy, while its manifestation in the electronic properties is challenging to resolve due to the lack of effective approaches for controlling the local current path. In this work, we reveal the giant transport anisotropy in monolayer to four-layer ReS 2 by creating directional conducting paths via nanoscale ferroelectric control. By reversing the polarization of a ferroelectric polymer top layer, we induce conductivity switching ratio of >1.5×10 8 in the ReS 2 channel at 300 K. Characterizing the domain-defined conducting nanowires in an insulating background shows that the conductivity ratio between the directions along and perpendicular to the Re-chain can exceed 5.5×10 4 in monolayer ReS 2 . Theoretical modeling points to the band origin of the transport anomaly, and further reveals the emergence of a flat band in few-layer ReS 2 . Our work paves the path for implementing the highly anisotropic 2D materials for designing novel collective phenomena and electron lensing applications.