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At least 109 records · Page 6

Decentralized oscillator-based converter control

A device includes a control unit that includes an oscillator circuit. The control unit is configured to generate, based on the oscillator circuit, at least one switching signal. The device also includes a direct current (DC)-to-DC conversion circuit comprising at least one electronic switch that is operatively coupled to the control unit. The DC-to-DC conversion circuit is configured to convert, based on the at least one switching signal, a DC input voltage to a DC output voltage, and the control unit is further configured to input, to the oscillator circuit, a current signal that is generated based on a measured output current of the DC-to-DC conversion circuit.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Hopper apparatuses for processing a bulk solid, and related systems and methods

A hopper apparatus comprises a movable wall comprising opposing walls movably connected to a support assembly and oriented at acute angles relative to a central vertical axis of the support assembly, and movement control devices configured and positioned to move the opposing walls along the support assembly to control dimensions of a discharge outlet at least partially defined by converging ends of the opposing walls; a liner assembly comprising liner structures at least partially overlying inner surfaces of the opposing walls and configured to remain at least partially stationary relative to the opposing walls during movement of the opposing walls; and pressure sensors between the inner surfaces of opposing walls and portions of the liner structures thereover. A bulk solids processing system and a method of processing a bulk solid are also described.

42 ENGINEERING↗

Open-Source Architecture for Multi-Party Update Verification for Data Acquisition Devices

Power grids are integral parts of modern daily life and are increasingly under cyberattack. Common software update processes for grid control devices rely on only one organization to provide verification. This paper roposes a multi-signature software update process to help better secure data acquisition devices from malicious actions by using standard cryptosystems such as TLS. A prototype system build on Linux and off-the-shelf hardware has shown successful update and attack prevention with our customized multi-party update software.

Newberg, Benjamin↗

Chance-constrained Service Restoration for Distribution Networks with Renewables

Power systems operation is facing great challenges from natural disasters and cyber-attacks. It is critical but also difficult to enhance the reliability and resilience against extreme events. To better response to inevitable outages or blackouts, service restoration in distribution networks is important to minimize the disastrous impacts of catastrophic events. The increasing penetration of distributed energy resources (DERs) provides new opportunities to expedite the restoration process. However, the coordination with conventional distribution system control devices and the uncertainty and variability of intermittent renewable energy resources requires new operation and control strategies for distribution service restoration (DSR). This paper develops an optimal bottom-up DSR strategy by coordinating DERs with voltage regulators and capacitor banks. The chance-constrained (CC) programming approach is used to model the probabilistic output limit of solar radiation and PV generation. The Markov's inequality and Latin hypercube sampling techniques are applied to convert and incorporate the chance constraints into the DSR optimization problem. The CC-DSR problem is formulated as a mixed integer convex programming problem, considering various operational cost functions and bidirectional three-phase unbalanced load flow. Simulation results on the modified IEEE 13-node test feeder system demonstrate the effectiveness and flexibility of the bottom-up DSR strategy.

Chance constrained optimization, Distribution serv↗

The importance of intramolecular conductivity in three dimensional molecular solids

Recent years have seen tremendous progress towards understanding the relation between the molecular structure and function of organic field effect transistors. The metrics for organic field effect transistors, which are characterized by mobility and the on/off ratio, are known to be enhanced when the intermolecular interaction is strong and the intramolecular reorganization energy is low. While these requirements are adequate when describing organic field effect transistors with simple and planar aromatic molecular components, they are insufficient for complex building blocks, which have the potential to localize a carrier on the molecule. Here, we show that intramolecular conductivity can play a role in controlling device characteristics of organic field effect transistors made with macrocycle building blocks. We use two isomeric macrocyclic semiconductors that consist of perylene diimides linked with bithiophenes and find that the trans-linked macrocycle has a higher mobility than the cis-based device. Through a combination of single molecule junction conductance measurements of the components of the macrocycles, control experiments with acyclic counterparts to the macrocycles, and analyses of each of the materials using spectroscopy, electrochemistry, and density functional theory, we attribute the difference in electron mobility of the OFETs created with the two isomers to the difference in intramolecular conductivity of the two macrocycles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Gradient-Based Multi-Area Distribution System State Estimation

The increasing distributed and renewable energy resources and controllable devices in distribution systems make fast distribution system state estimation (DSSE) crucial in system monitoring and control. We consider a large multi-phase distribution system and formulate DSSE as a weighted least squares (WLS) problem. We divide the large distribution system into smaller areas of subtree structure, and by jointly exploring the linearized power flow model and the network topology, we propose a gradient-based multi-area algorithm to exactly and efficiently solve the WLS problem. The proposed algorithm enables distributed and parallel computation of the state estimation problem without compromising any performance. Numerical results on a 4,521-node test feeder show that the designed algorithm features fast convergence and accurate estimation results. Comparison with traditional Gauss-Newton method shows that the proposed method has much better performance in distribution systems with a limited amount of reliable measurement. The real-time implementation of the algorithm tracks time-varying system states with high accuracy.

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

Enhanced π–π Interactions of Nonfullerene Acceptors by Volatilizable Solid Additives in Efficient Polymer Solar Cells

Abstract Fine‐tuning of the nanoscale morphologies of the active layers in polymer solar cells (PSCs) through various techniques plays a vital role in improving the photovoltaic performance. However, for emerging nonfullerene (NF) PSCs, the morphology optimization of the active‐layer films empirically follows the methods originally developed in fullerene‐based blends and lacks systematic studies. In this work, two solid additives with different volatilities, SA‐4 and SA‐7, are applied to investigate their influence on the morphologies and photovoltaic performances of NF‐PSCs. Although both solid additives effectively promote the molecular packing of the NF acceptors, due to the higher volatility of SA‐4, the devices processed with SA‐4 exhibit a power conversion efficiency of 13.5%, higher than that of the control devices, and the devices processed with SA‐7 exhibit poor performances. Through a series of detailed morphological analyses, it is found that the volatilization of SA‐4 after thermal annealing is beneficial for the self‐assembly packing of acceptors, while the residuals due to the incomplete volatilization of SA‐7 have a negative effect on the film morphology. The results delineate the feasibility of applying volatilizable solid additives and provide deeper insights into the working mechanism, establishing guidelines for further material design of solid additives.

Yu, Runnan↗

Learning Sequential Distribution System Restoration via Graph-Reinforcement Learning

We report a distribution service restoration algorithm as a fundamental resilient paradigm for system operators provides an optimally coordinated, resilient solution to enhance the restoration performance. The restoration problem is formulated to coordinate distribution generators and controllable switches optimally. A model-based control scheme is usually designed to solve this problem, relying on a precise model and resulting in low scalability. To tackle these limitations, this work proposes a graph-reinforcement learning framework for the restoration problem. We link the power system topology with a graph convolutional network, which captures the complex mechanism of network restoration in power networks and understands the mutual interactions among controllable devices. Latent features over graphical power networks produced by graph convolutional layers are exploited to learn the control policy for network restoration using deep reinforcement learning. The solution scalability is guaranteed by modeling distributed generators as agents in a multi-agent environment and a proper pre-training paradigm. Comparative studies on IEEE 123-node and 8500-node test systems demonstrate the performance of the proposed solution.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Employing MACS/ViBRANT as a Surrogate MARVEL Reactor for Startup Reactivity Tuning and Supervisory Control Processes

Advanced nuclear reactors are a key part of the future of nuclear energy both in the United States and globally. They offer unique benefits for various energy-demanding applications, including use in remote locations, compact size, modular manufacturing, remote monitoring, low and/or variable power rating operation, and reliance on novel technologies to enhance operational safety. To achieve economic feasibility, advanced reactors must significantly reduce their workforces in comparison with the current fleet. Achieving this reduction will occur through reducing staff workloads using technology to achieve autonomous or semi-autonomous operations, demonstrated by comprehensive testing and validation activities. These operations will require both software and hardware platforms during the design and testing phases. While simulations are useful during the design phase, their performance can significantly deviate during actual deployment on hardware. This report presents the outcomes of a collaborative technical initiative between the U.S. Department of Energy (DOE) Microreactor Program (MRP) and Advanced Sensors and Instrumentation (ASI) Program. The collaboration utilized the Microreactor Automated Control System (MACS) hardware platform to bridge the gap between theoretical reactor design and actual startup and control operations. Two key use cases were investigated: facilitating the startup testing period and demonstrating supervisory control. The first use case details the key Microreactor Applications Research Validation and Evaluation (MARVEL) reactor startup physics testing activities conducted using the MACS platform. These activities included drum worth measurements, shutdown margin assessment, temperature feedback analysis, and scram time evaluation, as well as unique testing that would apply to the MARVEL reactor to demonstrate the testing methodologies in a low-risk environment. The MACS platform, serving as a surrogate representation of the MARVEL reactor, proved instrumental in performing these tests. The exercise revealed aspects that led to optimized processes, refined hardware design, and enhanced base software capabilities. By maturing methods and technologies in this manner, the initiative promises to reduce wasted time in the actual on-site reactor deployment effort, thereby saving significant time and resources. The second use case focuses on the development and implementation of supervisory control methods aimed at managing core tilt, which can result from asymmetrical operations or manufacturing imperfections in fuel rods or reactivity control devices. A key objective was to assess and compare the use of artificial intelligence (AI) for supervisory control. The effort aimed to define the role of supervisory control to enhance performance without risking control instability. This effort explored three distinct approaches: rules-based (RB) methods, optimization techniques, and reinforcement learning (RL) algorithms. Each approach was evaluated for its ease of implementation, its usability, and its effectiveness in responding to asymmetries in neutron flux. Comparative analysis of these approaches provided valuable insights into their applicability and effectiveness, offering a robust framework for advanced reactor operations. Together, these two use cases highlight the potential of hardware test beds to help streamline the design, operation, and control of advanced nuclear reactors. This collaborative effort underscores the importance of continued innovation and experimentation in achieving the next generation of safe, reliable, and economically viable nuclear energy solutions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Automated Programmable Logic Controller Memory Forensics Using RGB Image Analysis and Deep Learning

The introduction of Industry 4.0 and Internet-based technologies has enhanced industrial control system operations but have inadvertently increased their vulnerabilities to cyber attacks. When an industrial control system is compromised, security analysts need to identify the root cause quickly to start the recovery process and develop mitigation strategies. Memory forensics is critical in the incident analysis process to ascertain what occurred. Approaches for analyzing the persistent memory in industrial control devices are limited and almost nonexistent for volatile memory. This chapter proposes an automated methodology for programmable logic controller memory dump analysis using computer vision and deep learning techniques. The methodology converts the sequences of bytes in a programmable logic controller memory dump to red-green-blue pixels and employs a deep learning model that learns the underlying patterns and features of pre-labeled forensic artifacts in images and segments them into distinct regions. The trained model is employed to automatically segment new memory images and identify forensic artifacts. Evaluation of the methodology on a Schneider Electric Modicon M221 programmable logic controller under code injection and code modification attacks demonstrates its ability to detect attack artifacts in memory dumps.

Asmar Awad, Rima [ORNL] (ORCID:0000000233407742)↗

Creating a Digital Twin for a Hydropower System through 3D Object Modeling: Alder Dam FY23

Hydropower stands as the world's leading source of renewable electricity, with hydropower plants spanning the globe. A typical hydropower plant comprises essential components including the governor, excitation system, generator, thrust bearing, hydraulic turbine, transformer, main lead, metering and control devices, tailwater depression system, and dissolved oxygen monitoring. Each of these components undergoes various measures and monitoring procedures. These measurements are collected through a diverse array of systems, encompassing standalone sensors, programmable logic controllers (PLCs), Supervisory Control and Data Acquisition (SCADA) systems, Internet of Things (IoT) devices, and data acquisition and integration platforms like OSI/PI.

13 HYDRO ENERGY↗

Tradeoff between Intermolecular Interaction and Backbone Disorder by High Molecular Dipole Block for Improving Blend Morphology of Polymer Solar Cells

Constructing terpolymer has attracted increasing attention as a strategy to improve the performance of polymer solar cell. Terpolymer usually offers an opportunity to lower the frontier molecular orbital energy level, introduces additional absorption band and sometimes optimizes the morphology of the active blend. Generally, the additional segment in terpolymer backbone inevitably introduces backbone disorder, which causes entropy rises. However, selecting a suitable dipole unit introduces extra driving forces for crystallization by enhancing intermolecular interactions. This provides a handy knob for tradeoff between intermolecular interaction and backbone disorder, thus regulating the blend morphology. In this study, a high dipole and electron-deficient group of pyrrolo[3,4-f ]benzotriazole-5,7(6H)-dione (TzBI) is incorporated into the high-performance donor polymer and a series of terpolymers with different content of TzBI are designed. As expected, the morphology is optimized gradually for improving charge generation and charge transport, also suppressing charge recombination. The champion device with 10% TzBI exhibited a power conversion efficiency (PCE) of 18.36%, which is 5% increase compared to the controlled device. This study presents a charming terpolymer strategy by highly electron-deficient and high dipole segment to realize a tradeoff between intermolecular interaction and backbone disorder, facilitating the optimization of morphology and elevation of fill factor and device efficiency.

36 MATERIALS SCIENCE↗

Continuously tunable uniaxial strain control of van der Waals heterostructure devices

Uniaxial strain has been widely used as a powerful tool for investigating and controlling the properties of quantum materials. However, existing strain techniques have so far mostly been limited to use with bulk crystals. Although recent progress has been made in extending the application of strain to two-dimensional van der Waals (vdW) heterostructures, these techniques have been limited to optical characterization and extremely simple electrical device geometries. Here, we report a piezoelectric-based in situ uniaxial strain technique enabling simultaneous electrical transport and optical spectroscopy characterization of dual-gated vdW heterostructure devices. Critically, our technique remains compatible with vdW heterostructure devices of arbitrary complexity fabricated on conventional silicon/silicon dioxide wafer substrates. We demonstrate a large and continuously tunable strain of up to –0.15% at millikelvin temperatures, with larger strain values also likely achievable. We quantify the strain transmission from the silicon wafer to the vdW heterostructure, and further demonstrate the ability of strain to modify the electronic properties of twisted bilayer graphene. Our technique provides a highly versatile new method for exploring the effect of uniaxial strain on both the electrical and optical properties of vdW heterostructures and can be easily extended to include additional characterization techniques.

Electrical properties and parameters↗

Magnon confinement in epitaxial antiferromagnetic oxide heterostructures.

Magnons, the quanta of spin waves, have been extensively studied in a range of materials for spintronics, particularly for non-volatile logic-in-memory devices. Controlling magnons in conventional antiferromagnets and harnessing them in practical applications, however, remains a challenge. Here, we demonstrate highly efficient magnon transport in a LaFeO3/ BiFeO3/ LaFeO3 all-antiferromagnetic system, which can be controlled electrically, making it highly desirable for energy-efficient computation. Leveraging spin-orbit-driven spin-charge transduction, we demonstrate that this material architecture permits magnon confinement in ultrathin antiferromagnets, enhancing the output voltage generated by magnon transport by several orders of magnitude, which provides a pathway to enable magnetoelectric memory and logic functionalities. Additionally, the non-volatility of output voltage enables ultralowpower logic-in-memory processing, where magnonic devices can be efficiently reconfigured via electrically controlled magnon spin currents within magnetoelectric channels.

Husain, Sajid↗

The Influence of Communication on the Complexity of Connected Lighting Systems

Experience in the Next Generation Lighting Systems (NGLS) ”Living Lab” at the Parsons School of Design, has clearly shown the impacts of communication on the configuration complexity of the connected lighting systems installed there. Since 2017, NGLS has invited manufacturers to submit connected lighting systems for assessment against a set of specifications. To date, 14 systems of wirelessly connected LED luminaires and controls have been installed in classrooms with existing lighting. In nine of the rooms, new LED linear pendants or recessed troffers replaced existing luminaires; in the other rooms, LED “kits” were retrofitted into the existing troffers. Eleven of the installations featured sensors integrated in the luminaires or retrofit kits; the others used ceiling mounted sensors. All systems provided wall control devices for manual operation. For half of the installations, the complete systems were furnished by single companies; for the other half, luminaires and controls were furnished by separate companies. A total of 18 different companies provided products, with four of these located outside the United States including, Korea, Poland, Germany, and the Netherlands. In addition, two different electrical contractors in New York City provided multiple installation teams totaling 10 individuals, none of whom were familiar with any of the systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Tailored Frequency Conversion in Nonlinear Subwavelength Grating Metaslabs

The use of metaslab waveguides consisting of subwavelength gratings (SWGs) is proposed as a highly flexible approach to obtain phase‐matched frequency conversion in nonlinear integrated devices. Control over the phase matching (PM) condition is achieved through modification of the linear modal propagation constants by the SWG. The method is experimentally demonstrated by fabrication of 0.4 mm‐long GaAs metaslabs designed for second harmonic generation of near‐infrared light. A controlled spectral shift of up to 100 nm in the PM condition, relative to a uniform slab is observed. Excellent agreement is found between the experimental results and finite‐difference eigenmode simulations, which predict a tunable frequency conversion bandwidth of ∼300 nm for the design parameters. The different regimes of PM control supported by the structure are discussed. This work highlights the potential of SWGs as building blocks for tailored frequency conversion in nonlinear integrated devices.

Form birefringence↗

Simultaneous measurements of turbulent Reynolds stresses and particle flux in both parallel and perpendicular directions in a linear magnetized plasma device

We report temporally resolved simultaneous measurements of the turbulent Reynolds stresses in both the parallel and perpendicular directions and the corresponding particle fluxes in the fusion relevant cylindrical magnetized plasma device Controlled Shear Decorrelation eXperiment (CSDX). CSDX simulates the plasma conditions of multiple plasma instabilities that can arise in the scrape-off layer of fusion devices. In this study, we designed and used a 6-tip Langmuir probe in a novel yet simple design to simultaneously measure all the three dimensional components (radial, azimuthal, and axial) of fluctuations in velocity from the floating potentials and plasma densities with high temporal resolution. From these, we calculated the parallel and perpendicular Reynolds stress and the particle fluxes in addition to the density and potential spectra and the cross phase between different quantities. We can obtain radial profiles of all the aforementioned plasma quantities, which are extremely useful for studying plasma turbulence due to multiple instabilities. We have also cross-checked the time averaged velocity profiles from the probe with laser induced fluorescence measurements of the mean plasma velocity for some common plasma source parameters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

BOOSTR: A Dataset for Accelerator Control Systems

The Booster Operation Optimization Sequential Time-series for Regression (BOOSTR) dataset was created to provide a cycle-by-cycle time series of readings and settings from instruments and controllable devices of the Booster, Fermilab’s Rapid-Cycling Synchrotron (RCS) operating at 15 Hz. BOOSTR provides a time series from 55 device readings and settings that pertain most directly to the high-precision regulation of the Booster’s gradient magnet power supply (GMPS). To our knowledge, this is one of the first well-documented datasets of accelerator device parameters made publicly available. We are releasing it in the hopes that it can be used to demonstrate aspects of artificial intelligence for advanced control systems, such as reinforcement learning and autonomous anomaly detection.

Kafkes, Diana (ORCID:000000021716463X)↗