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ML-based Real-Time Control at the Edge: An Approach Using hls4ml
This study focuses on implementing a real-time control system for a particle accelerator facility that performs high energy physics experiments. A critical operating parameter in this facility is beam loss, which is the fraction of particles deviating from the accelerated proton beam into a cascade of secondary particles. Accelerators employ a large number of sensors to monitor beam loss. The data from these sensors is monitored by human operators who predict the relative contribution of different sub-systems to the beam loss. Using this information, they engage control interventions. In this paper, we present a controller to track this phenomenon in real-time using edge-Machine Learning (ML) and support control with low latency and high accuracy. We implemented this system on an Intel Arria 10 SoC. Optimizations at the algorithm, high-level synthesis, and interface levels to improve latency and resource usage are presented. Our design implements a neural network, which can predict the main source of beam loss (between two possible causes) at speeds up to 575 frames per second (fps) (average latency of 1.74 ms). The practical deployed system is required to operate at 320 fps, with a 3ms latency requirement, which has been met by our design successfully.
Multi-Level Impacts of Extreme Climate-Related Events on Food Supply Chain: Idaho Potato's Case Study
Background: The world is experiencing frequent extreme weather events like droughts, floods, snowstorms, and shifting of seasons due to climate change. Increasing frequencies and severity of these extreme weather events threaten food security because agriculture is extremely vulnerable to climate change. Higher temperature reduces overall yields of the desirable crops but proliferates weeds and harmful pests. Current data shows that every year U.S. farmers spend more than 11 billion USD to fight weeds and this number is expected to rise in the coming years due to climate change. Due to droughts, the water required for irrigation is becoming scarcer. Since many areas are becoming climatically unusable for crop production, the amount of farmland area is shrinking rapidly. In addition, changes in precipitation patterns are causing crop failures and negatively impacting expected yields. In this study, we investigated how different extreme climate events impact different stages of a food supply chain. Approach: As a case study, we chose Idaho’s potato supply chain (SC). Idaho is the top potato producing state in the U.S. and contributes around 30% of the nation’s potato production. Using the agent-based modeling (ABM) approach, we developed a multi-echelon potato supply chain computer simulation model with six types of agents – seed producers, farmers, shippers, processors, retailers, and logistics companies. In addition to the baseline scenario, we developed two additional climate-related disruption events – drought and snowstorm. We investigated how each of these disruption events impacts different stakeholders across the supply chain in terms of revenue and some other key performance metrics such as lead time, food waste, number of delayed orders, and order fulfillment rate. Results: Extreme climate events not only impact the growers but there is also cascading ripple effects downstream of the supply chain. The methodology developed in this study could be applied to other food and agricultural SC to understand the vulnerabilities of the different links. The findings would potentially help to adopt new policies for the well-being of the overall SC.
Overall Cooling Effectiveness of Internally Cooled Additively Manufactured Blades
Power generation gas turbine blades must utilize highly effective cooling schemes to withstand moderate heat loads for long operating times. Prior work indicates that gas turbines in the 5-10 MW range primarily utilize internal cooling to prevent further increase of aerodynamic losses that result from film cooling, but few studies focus solely on internal cooling. In this study, three additively manufactured internal cooling designs were tested in the 50 percent span section of the National Experimental Turbine (NExT) blade: a baseline cooling design with pin-fin arrays and rib turbulators, a double wall design with impingement jets and serpentine channels, and an incremental impingement design. The designs were tested in a high-speed linear cascade at exit Reynolds numbers ranging from 700,000 to 1,400,000 at an exit Mach of 0.8. In addition, freestream turbulence and build angle effects on cooling performance were studied.
A Distributed Control Architecture for Cascaded H-Bridge Converter with Integrated Battery Energy Storage
Cascaded H-bridge topology has been used in grid-tied converters for battery energy storage system due to its modular structure. To fully utilize the converter’s modularity, this paper proposes a hierarchical distributed control architecture that consists of primary control, secondary control and battery state of charge (SOC) balancing control. Primary control ensures accurate current tracking while a distributed secondary control based on consensus algorithm is presented to regulate power sharing among modules and is proved to be stable theoretically. Here, a distributed SOC balancing control is further introduced to improve energy efficiency of battery energy storage system. Finally, the hierarchical distributed control strategy is implemented using hardware controllers and a software platform. Besides, a carrier phase shift control is also implemented to achieve multilevel output voltage and harmonic reduction. The experimental results demonstrate the performance of the proposed control scheme effectively.
Dual aggregation steering in bulk-heterojunction via solvent engineering toward efficient and stable binary organic solar cells
In high-performance organic solar cells (OSCs), efficient charge transport hinges on a well-optimized morphology of the photoactive layer, which depends critically on controlled aggregation and favorable interactions between donor and acceptor materials. In this work, we introduce a cascade solvent system comprising high-boiling-point ethylbenzene (EB) and low-boiling-point chloroform (CF) to finely tune the aggregation behavior of the D18 donor and L8-BO acceptor. The incorporation of EB not only promotes the H-aggregation of D18 and the J-aggregation of L8-BO but also facilitates the formation of ideal nanoscale phase separation, thereby suppressing bimolecular recombination. As a result, devices processed with the EB/CF solvent blend achieve a best power conversion efficiency (PCE) of 19.6 % and enhanced operational stability, outperforming those fabricated with pure CF (17.1 %). In conclusion, this study offers a reliable and effective strategy for optimizing donor and acceptor aggregation, providing a viable pathway toward higher-performance OSCs.
Valence Disproportionation of GeS in the PbS Matrix Forms Pb 5 Ge 5 S 12 Inclusions with Conduction Band Alignment Leading to High n-Type Thermoelectric Performance
Converting waste heat into useful electricity using solid-state thermoelectrics has a potential for enormous global energy savings. Lead chalcogenides are among the most prominent thermoelectric materials, whose performance decreases with an increase in chalcogen amounts (e.g., PbTe>PbSe>PbS). Herein, we demonstrate the simultaneous optimization of the electrical and thermal transport properties of PbS-based compounds by alloying with GeS. The addition of GeS triggers a complex cascade of beneficial events as follows: Ge 2+ substitution in Pb 2+ and discordant off-center behavior; formation of Pb 5 Ge 5 S 12 as stable second phase inclusions through valence disproportionation of Ge 2+ to Ge0 and Ge 4+ . PbS and Pb 5 Ge 5 S 12 exhibit good conduction band energy alignment that preserves the high electron mobility; the formation of Pb 5 Ge 5 S 12 increases the electron carrier concentration by introducing S vacancies. Sb doping as the electron donor produces a large power factor and low lattice thermal conductivity (κ lat ) of ~0.61 Wm -1 K -1 . The highest performance was obtained for the 14% GeS-alloyed samples, which exhibited an increased room temperature electron mobility of ~121 cm 2 V -1 s -1 for 3 × 10 19 cm -3 carrier density, and a ZT, of 1.32 at 923 K. This is ~ 55% greater that the corresponding Sb-doped PbS sample and is one of the highest reported for the n-type PbS system. Moreover, the average ZT (ZT avg ) of ~0.76 from 400 to 923 K is the highest for PbS-based systems.
Measurement of neutron production in atmospheric neutrino interactions at Super-Kamiokande
We present measurements of total neutron production from atmospheric neutrino interactions in water, analyzed as a function of electron-equivalent visible energy over a range of 30 MeV to 10 GeV. These results are based on 4,270 days of data collected by Super-Kamiokande, including 564 days with 0.011 wt% gadolinium added to enhance neutron detection. Neutron signal selection is based on a neural network trained on simulation, with its performance validated using an Am/Be neutron point source. The measurements are compared to predictions from neutrino event generators combined with various hadron-nucleus interaction models, which include an intranuclear cascade model and a nuclear deexcitation model. We observe significant variations in the predictions depending on the choice of hadron-nucleus interaction model. We discuss key factors that contribute to describing our data, such as in-medium effects in the intranuclear cascade and the accuracy of statistical evaporation modeling.
A universal metasurface transfer technique for heterogeneous integration
Metasurfaces offer a versatile platform for engineering the wavefront of light using nanostructures with subwavelength dimensions and hold great promise for dramatically miniaturizing conventional optical elements due to their small footprint and broad functionality. However, metasurfaces so far have been mainly demonstrated on bulky and planar substrates that are often orders of magnitude thicker than the metasurface itself. Conventional substrates not only nullify the reduced footprint advantage of metasurfaces, but also limit their application scenarios. The bulk substrate also determines the metasurface dielectric environment, with potentially undesired optical effects that undermine the optical performance. Here we develop a universal polymer-assisted transfer technique to tackle this challenge by decoupling the substrate employed on the fabrication of metasurfaces from that used for the target application. As an example, Huygens’ metasurfaces with 120 nm thickness in the visible range (532 nm) are demonstrated to be transferred onto a 100 nm thick freestanding SiN x membrane while maintaining excellent structural integrity and optical performance of diffraction-limited focusing. This transfer method not only enables the thinnest dielectric metalens to the best of our knowledge, but also opens up new opportunities in integrating cascaded and multilayer metasurfaces, as well as the heterogeneous integration with nonconventional substrates and various electronic/photonic devices.
Interfacial Engineering Using Covalent Organic Frameworks in Polymer Composites for High‐Temperature Electrostatic Energy Storage
Abstract The use of inorganic nanofillers has been an effective method to improve high‐temperature capacitive performance of dielectric polymers, though there are unmet challenges such as undesirable organic–inorganic compatibility, and low efficiencies and energy densities. Herein, a surface functionalization strategy using covalent organic frameworks (COFs) is employed to address such challenges in realizing high‐performing polymer composites. Specifically, core–shell structured nanoparticles, where ZrO 2 nanoparticles act as the core and a COF material forms the shell, are constructed and composited with the polyetherimide (PEI) matrix. The design leverages the high electron affinity ( E A ) of the outer COF shell to create energy traps, thereby capturing free charges and limiting electrical conduction. Concurrently, the low E A and wide bandgap of the ZrO 2 core introduce energy barriers to impede charge injection and migration. This orchestrated “energy level cascade” results in a marked reduction of leakage current and energy loss. The resulting polymer composite showcases an impressive discharged energy density of 6.21 J cm −3 at an efficiency above 90%, with a maximum discharged energy density reaching 7.43 J cm −3 at 150 °C. These performance metrics position the PEI/ZrO 2 @COF polymer composite to surpass or be on par with state‐of‐the‐art high‐temperature PEI composites and other advanced polymer dielectrics.
Nonnuclear Experimental Capabilities to Support Design, Development, and Demonstration of Microreactors
This work provides a summary of selected experimental capabilities being developed to support nonnuclear testing and demonstration of technology in support of microreactors under the U.S. Department of Energy’s (DOE’s) Microreactor Program. Major capabilities include the Single Primary Heat Extraction and Removal Emulator (SPHERE) and the Microreactor Agile Non-nuclear Experimental Test Bed (MAGNET). The SPHERE facility allows for controlled testing of the steady-state and transient heat rejection capabilities of a single heat pipe using electrical heaters that simulate nuclear heating. The facility is capable of monitoring axial temperature profiles along the heat pipe and surrounding test articles during startup, steady-state operation, and transients. Instrumentation includes noncontact infrared thermal imaging, surface thermocouples, spatially distributed fiber optic temperature and strain sensors, electrical power meters, and a water-cooled, gas-gap calorimeter for quantifying heat rejection from the heat pipe. The facility can be operated under both vacuum and inert-gas conditions. The MAGNET facility is a large-scale, 250-kW electrically heated microreactor test bed to enable nonnuclear experimental evaluation of a variety of microreactor concepts. It can be supplied to electrically heat a scaled section of a microreactor and further test the capabilities of heat rejection systems. The initial MAGNET experiments will support technology maturation and reduce uncertainty and risk associated with the design, operation, and deployment of monolithic heat pipe–based reactors. However, this test bed can broadly be applied to multiple microreactor concepts to evaluate a wide range of thermal-hydraulic and structural phenomena such as interface coupling with power conversion units and other collocated systems. MAGNET can evaluate integral thermomechanical effects during electrical heating of an array of heat pipes in a larger test article. Examples of initial testing will include thermal stresses in the monolith and the impact of debonding of a heat pipe from the core block and how that failure could impact surrounding heat pipes, i.e., understanding the potential for cascading failure. This work also discusses some modeling capabilities that can support experiment design, analysis, and interpretation, including the heat pipe code Sockeye and a comparison of thermal-structural simulations performed using ABAQUS and STAR-CCM+.
Shock tube investigation of high-temperature, extremely-rich oxidation of several co-optima biofuels for spark-ignition engines
To reduce the reliance on fossil fuels in the transportation sector and increase combustion efficiency, the Co-Optima initiative from US Department of Energy identified the top 10 biofuels for downsized, boosted, spark-ignition engines. Most of these biofuels have detailed reaction mechanisms available in literature developed based on studies at temperatures lower than 1700 K and an equivalence ratio of less than five. As such, the performance of these detailed mechanisms at high temperature and extremely rich conditions are unknown. It is important to validate kinetic mechanisms at these conditions because they are conducive to soot formation. Prediction of soot by chemical kinetic models relies on the prediction of underlying benchmark species like carbon monoxide and ethylene. In this work, we conduct high temperature (1700–2050 K) and high equivalence ratio(Φ=8.6) oxidation of these biofuels, namely 2,4,4-trimethyl-1-pentene (α-diisobutylene), ethanol, cyclopentanone, methyl acetate, and 2-methylfuran, blended in ethylene behind reflected shock waves at 4–4.7 atm pressure. Carbon monoxide and ethylene time histories are measured simultaneously using a continuous feedback quantum cascade laser near 4.9 µm and a tunable CO 2 gas laser at 10.532 nm, respectively. Results show that ethanol blend forms more carbon monoxide than other biofuels and consumes ethylene faster than the biofuel blends in the temperature range considered. Overall, the performance of different mechanisms in literature are evaluated against the experimental results. The novel reaction mechanism ‘the Co-Optima model’, which includes the sub mechanisms for all the biofuels in this study, was found to be the best mechanism for the experimental conditions studied.
A Computationally Improved Heuristic Algorithm for Transmission Switching Using Line Flow Thresholds for Load Shed Reduction
We present a computationally improved heuristic algorithm for transmission switching (TS) to recover load shed. Research from the past showed that changing power system topology may control power flows and remove line congestion. Hence, TS may reduce the required load shed. One of the main challenges is to find a potential TS candidate in a suitable time. Here, we propose a novel heuristic method that is capable of finding the potential TS candidate faster than existing algorithms in literature. The proposed method is compatible with both the AC and DC optimal power flows (OPF). Three metrics are used to compare the proposed algorithm with the state-of-the-art from literature to show the speedup and accuracy achieved. The proposed method is implemented on the IEEE 30-bus system, PEGASE 89-bus system, IEEE 118-bus system, and Polish 2383- bus system. The results on the large-scale Polish 2383-bus system shows that the proposed algorithm is scalable to large real-world systems. Parallel computing is implemented to further improve the computational performance of the proposed algorithm.
Core–Multishell-Structured Digital-Gradient Cathode Materials with Enhanced Mechanical and Electrochemical Durability
Ni-rich cathode materials provide high energy density, but their structural and surface instability limits their cyclability and thermal stability. As one of the approaches to mitigate this problem, cathode materials comprising Ni-rich high-capacity core wrapped in Mn-rich multiple shells are produced successfully. In contrast to the conventional batch-type process for concentration-gradient materials, a digital-gradient cascade coprecipitation process described here achieves the improvements in productivity and quality consistency needed to move toward large-scale manufacturing. The core-multishell cathode materials produced in this manner not only have longer cycle life and improved rate performance compared to homogeneous Ni-rich cathode materials having the same overall composition, but also show remarkably enhanced thermal stability and low impedance growth characteristics. In a novel attempt to determine the correlation between the mechanical properties of the core-multishell cathode particles and their electrochemical cyclabilities, their breaking force and elasticity were successfully measured using a statistical approach, which indicates that a cathode particle with stable surface composition as well as high breaking force has improved capacity retention and durability. These results guide the realization of long life and high thermal stability in Ni-rich cathode materials through heterogeneous particle engineering.
Observation-Based Evaluation of Flood Estimation Techniques for a Small Snow-Dominated Basin in the Washington Cascade Mountains
Here, this study examines the application of the recently developed next-generation intensity-duration-frequency (NG-IDF) curves in hydrological design, focusing on a small snow-dominated basin in Washington state. Four methods are used to assess the NG-IDF performance: (1) basin outlet flood frequency analysis, (2) use of standard precipitation-based intensity-duration-frequency (PREC-IDF) curves following surface water design manuals typically used in the basin, (3) utilization of locally constructed PREC-IDF curves, and (4) use of locally constructed NG-IDF curves. The standard PREC-IDF design method assumes precipitation as rainfall and neglecting snowmelt or rain-on-snow (ROS) events that can lead to significant flood underestimations in the test basin. In contrast, the NG-IDF method incorporates snow processes and shows promising improvements in accurately estimating design floods. The validation analysis demonstrates the superiority of NG-IDF over standard and local PREC-IDF in this test basin. The study highlights the necessity for adjustments in current design manuals to ensure sufficient flood protection, particularly in light of the planned substantial investments in US infrastructure.
Long wavelength interband cascade lasers
InAs-based interband cascade lasers (ICLs) can be more easily adapted toward long wavelength operation than their GaSb counterparts. Devices made from two recent ICL wafers with an advanced waveguide structure are reported, which demonstrate improved device performance in terms of reduced threshold current densities for ICLs near 11 μm or extended operating wavelength beyond 13 μm. Here, the ICLs near 11 μm yielded a significantly reduced continuous wave (cw) lasing threshold of 23 A/cm 2 at 80 K with substantially increased cw output power, compared with previously reported ICLs at similar wavelengths. ICLs made from the second wafer incorporated an innovative quantum well active region, comprised of InAsP layers, and lased in the pulsed-mode up to 120 K at 13.2 μm, which is the longest wavelength achieved for III–V interband lasers.
Load Shed Recovery With Transmission Switching and Intentional Islanding Methods After (N-2) Line Contingencies
Changing power system configuration may result in load shed recovery (LSR) because topology change can provide power flow control in meshed network. Some topologies may favor generation redispatch as compared to others and can eliminate line congestion which leads to LSR. One of the known methods for topology change is called transmission switching (TS) and research conducted in the past showed that TS is an effective means of mitigating load shedding. Another method of topology control is intentional islanding (IIS). In this manuscript, we explore IIS as a potential solution for LSR. IIS based on generator coherency has been presented in literature for mitigating cascading failures. However, IIS has not been explored solely as a LSR mechanism. In this paper, we compare the LSR based on IIS with well known LSR algorithm based on TS. The comparison is performed for IEEE 39-bus system and IEEE 118- bus system. The results show that IIS has a potential to perform better than TS in terms of computational efficiency and LSR.
Intermittency and Dissipative Structures Arising from Relativistic Magnetized Turbulence
Abstract Kinetic simulations of relativistic turbulence have significantly advanced our understanding of turbulent particle acceleration. Recent progress has highlighted the need for an updated acceleration theory that can account for particle acceleration within the plasma’s coherent structures. Here, we investigate how intermittency modeling connects statistical fluctuations in turbulence to regions of high-energy dissipation. This connection is established by employing a generalized She–Leveque model to characterize the exponents ζ p for the structure functions S p ∝ l ζ p . The fitting of the scaling exponents provides us with a measure of the codimension of the dissipative structures, for which we subsequently determine the filling fraction. We perform our analysis for a range of magnetizations σ and relative fluctuation amplitudes δ B 0 / B 0 . We find that increasing values of σ and δ B 0 / B 0 allow the turbulent cascade to break sheetlike structures into smaller regions of dissipation that resemble chains of flux ropes. However, as their dissipation measure increases, the dissipative regions become less volume filling. With this work, we aim to inform future turbulent acceleration theories that incorporate particle energization from interactions with coherent structures within relativistic turbulence.