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DOE OSTI2024

Quantum routing with teleportation

We study the problem of implementing arbitrary permutations of qubits under interaction constraints in quantum systems that allow for arbitrarily fast local operations and classical communication (LOCC). In particular, we show examples of speedups over swap-based and more general unitary routing methods by distributing entanglement and using LOCC to perform quantum teleportation. We further describe an example of an interaction graph for which teleportation gives a logarithmic speedup in the worst-case routing time over swap-based routing. We also study limits on the speedup afforded by quantum teleportation—showing an O ( N log N ) upper bound on the separation in routing time for any interaction graph—and give tighter bounds for some common classes of graphs. Published by the American Physical Society 2024

Devulapalli, Dhruv (ORCID:000000022612308X)↗

DOE OSTI2021

Beacon-based precision navigation and timing (PNT) system

Beacon-based Precision Navigation and Timing (PNT) may use a constellation of space vehicles (e.g., small, low cost satellites) coupled to a network of ground stations and a network of beacons. Such a system be provided at a cost that is approximately 100 times lower than GPS both to build and to operate. The resulting system may also provide fast acquisition, improved SNR, improved anti-jam and anti-spoofing capabilities, and six-inch scale location determination, making it applicable to both existing PNT applications and enabling new applications.

Judd, Stephen↗

DOE OSTI2024

Exploring Multidimensional Spatial-Temporal Hydropower Operational Flexibilities by Modeling and Optimizing Water-Constrained Cascading Hydroelectric Systems

Because of unique characteristics such as clean and cost-competitive electricity as well as fast-ramping and storage abilities, the power industry continues to evolve its operation strategies for cascading hydroelectric (CHE) systems for providing enhanced values to the grid, especially under the deeper renewable resource integration. However, existing operation practices of CHEs predate the integration of renewables, which could prohibit the effective utilization of their inherent flexibilities in delivering maximum financial benefits and providing valuable grid services to the power system and electricity market operations. Indeed, modeling and optimizing these resource-limited while flexible CHE assets with uncertainties and imperfect information across multiple spatial-temporal dimensions present significant challenges. To facilitate CHE facility operators in effectively coordinating water usage and hydropower plant operations across multiple timescales, this project aims to fill the existing gaps by developing a suite of accurate water inflow (WI) forecast models as well as enhanced CHE modeling and optimization approaches with proper consideration of their unique characteristics, which would help explore their multidimensional spatial-temporal operational flexibility potentials. The developed approaches could better align reservoir operation strategies with variability and uncertainty of future water availability. They can also promote more effective utilization of multidimensional spatial-temporal hydropower operational flexibility potentials by designing long-term evacuation plans of reservoirs and short-term operation of CHEs, along with their coordination with other types of renewables. The project leverages various resources to facilitate the research and development activities, including actual characteristics data of CHE systems and a library of current and future cases of Portland General Electric (PGE). These realistic data enable the project team to study how to maximize the value of CHEs under current and future portfolios and evaluate opportunities to improve operation practices.

13 HYDRO ENERGY↗

DOE OSTI2020

Using Machine Learning Tools to Predict Compressor Stall

Clean energy has become an increasingly important consideration in today’s power systems. As the push for clean energy continues, many coal-fired power plants are being decommissioned in favor of renewable power sources such as wind and solar. However, the intermittent nature of renewables means that dynamic load following traditional power systems is crucial to grid stability. With high flexibility and fast response at a wide range of operating conditions, gas turbine systems are poised to become the main load following component in the power grid. Yet, rapid changes in load can lead to fluid flow instabilities in gas turbine power systems. These instabilities often lead to compressor surge and stall, which are some of the most critical problems facing the safe and efficient operation of compressors in turbomachinery today. Although the topic of compressor surge and stall has been extensively researched, no methods for early prediction have been proven effective. This study explores the utilization of machine learning tools to predict compressor stall. The long short-term memory (LSTM) model, a form of recurrent neural network (RNN), was trained using real compressor stall datasets from a 100 kW recuperated gas turbine power system designed for hybrid configuration. Two variations of the LSTM model, classification and regression, were tested to determine optimal performance. The regression scheme was determined to be the most accurate approach, and a tool for predicting compressor stall was developed using this configuration. Overall, results show that the tool is capable of predicting stalls 5–20 ms before they occur. With a high-speed controller capable of 5 ms time-steps, mitigating action could be taken to prevent compressor stall before it occurs.

42 ENGINEERING↗

DOE OSTI2018

Automated concentration of [ 18 F]fluoride into microliter volumes

Concentration of [ 18 F]fluoride has been mentioned in literature, however, reports have lacked details about system designs, operation, and performance. Here, we describe in detail a compact, fast, fully-automated concentration system based on a micro-sized strong anion exchange cartridge. The concentration of radionuclides enables scaled-up microfluidic synthesis. Our system can also be used to provide highly concentrated [ 18 F]fluoride with minimal water content. We demonstrate how the concentrator can produce varying concentrations of [ 18 F]fluoride for the macroscale synthesis of N-boc-5-[ 18 F]fluoroindole without an azeotropic drying process, while enabling high starting radioactivity. By appropriate choice of solid-phase resin, flow conditions, and eluent solution, we believe this approach can be extended beyond [ 18 F]fluoride to other radionuclides.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2017

An Evaluation of Energy Storage Options for Nuclear Power

The dynamics of energy generation, delivery, and consumption in the United States continue to change as new energy sources come online and consumers purchase more energy-intensive devices. The percentage of electricity generation from variable renewable energy sources like wind and solar power has grown year after year. Meanwhile, the evolution of electric vehicles, smart devices, and consumer appliances is changing the way that electricity is used. As a result of these trends, nuclear power plants (NPPs) are being asked to operate more flexibly. Newly constructed, advanced nuclear power plants (A-NPPs) will likely need to adapt their business models with these market shifts in mind. In the future, A-NPPs might operate in an electricity system that values flexibility (e.g. fast ramping) more than stability (e.g. baseload supply). The current fleet of NPPs is struggling to remain economically viable in competitive markets that favor low natural gas prices and renewable energy sources with low marginal costs. Rising construction costs and ambiguous national policies have only added to the challenges facing plant operators. The industry as a whole is in decline, with 19 reactors in the process of being decommissioned and 5 of these plants retiring in the past decade. However, NPPs also provide several performance and environmental benefits by maintaining a high capacity factor and generating almost zero greenhouse gas (GHG) emissions over the life cycle of the plant. As more areas of energy consumption in the United States are electrified, NPPs could potentially replace coal and natural gas as a source of heat and power to help decarbonize the U.S. energy mix. Improving the flexibility of newly constructed A-NPPs to increase revenue through market hedging and reduce costs via stable operation was explored in this analysis. The increasing penetration of variable energy resources could contribute to the uncertainty of electricity demand, which could in turn increase the need for dispatchable electricity generating units. This role is currently filled by inexpensive natural gas combined cycle (NGCC) plants, whereas coal and NPPs have traditionally been called upon to provide baseload power by maintaining a constant power output. As wholesale electricity prices continue to fall due to low natural gas prices and federally subsidized renewable energy, this business model has begun to fail, resulting in incidences of NPPs selling electricity at a loss. Since it has not been economically favorable for NPPs to operate flexibly in this situation in the past, due to their low variable costs compared to fossil fuel power plants, NPPs in the United States were not built with this purpose in mind. Therefore, legacy NPPs have had difficulty adapting to these shifting dynamics due to regulatory and technical constraints, coupled with a lack of meaningful experience. NPPs in France have operated in this manner for years, due to a much higher percentage of baseload generators and a lower percentage of fast-ramping NGCC plants. The integration of energy storage technologies (ESTs) alongside newly constructed A-NPPs will be investigated in this analysis as an alternative method for helping NPPs resolve the economic challenges they currently face. Although the deregulation of energy markets in the United States is responsible for much of the increased competition from natural gas and renewable energy that has negatively impacted NPPs, this process has also led to the creation of ancillary service markets. ESTs can provide many of these services, so an integrated energy storage system could supplement both the reliability of the electricity grid and the economic performance of a NPP by bidding into these markets. However, many technical, financial, and regulatory barriers still prevent ESTs from operating profitably in this space. The purpose of this body of work is to compile a transparent database of metrics for available ESTs and identify barriers to widespread deployment. An analytical selection methodology was also developed to identify favorable technologies for integration with specific NPPs based on information supplied by an interested developer. These tools could help reduce the perceived risk surrounding investment in energy storage systems, which could help both NPPs in need of economic assistance and ESTs in need of further research and development.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2011

10-100 Gbps Offload NIC for WAN, NLR, and Grid Computing

An extremely fast offload engine system has been developed that operates at 60 Gigabits per second (Gbps), and has scalability to 100 Gbps full-duplex (f-d). This system is based on unique coding and architecture derived from splintered UDP (User Datagram Protocol) offload technology, resulting in unique FPGA (field programmable gate array) intellectual property core and firmware. This innovation improves the networking speed of supercomputer clusters by providing an ultra-fast network protocol processing offload from a CPU (central processing unit) by inserting an offload engine into a host backplane and network connections. This runs on protocol firmware.

Awrach, James↗

DOE OSTI2017

Final Report for File System Support for Burst Buffers on HPC Systems

Distributed burst buffers are a promising storage architecture for handling I/O workloads for exascale computing. As they are being deployed on more supercomputers, a file system that efficiently manages these burst buffers for fast I/O operations carries great consequence. Over the past year, FSU team has undertaken several efforts to design, prototype and evaluate distributed file systems for burst buffers on HPC systems. These include MetaKV: a Key-Value Store for Metadata Management of Distributed Burst Buffers, a user-level file system with multiple backends, and a specialized file system for large datasets of deep neural networks. Our progress for these respective efforts are elaborated further in this report.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Physics-Informed Evolutionary Strategy Based Control for Mitigating Delayed Voltage Recovery

Here, in this work we propose a novel data-driven, real-time power system voltage stability control method based on the physics-informed guided meta evolutionary strategy (ES). The main objective is to quickly provide an adaptive control strategy to secure system voltage stability. The problem is challenging due to the high-dimensional feature of the power system model and the fast-changing and uncertain nature of power system operation scenarios. To this end, a model-free and derivative-free guided ES method is applied. The method is further combined with a meta-learning strategy to make the learnt control policy automatically adapted to unseen operation conditions and fault scenarios, which is highly desired for real-time emergency control. Last but not least, physical knowledge is embedded in the above method through a trainable action mask technique to rule out unnecessary load shedding actions for better learning and control performance. Case studies on the IEEE 300-bus system and comparisons with other state-of-the-art benchmark methods verify the superiority of the proposed physics-informed guided meta ES method in realizing fast and adaptive power system voltage stability control.

42 ENGINEERING↗

NASA NTRS2016

Evaluating Alerting and Guidance Performance of a UAS Detect-And-Avoid System

A key challenge to the routine, safe operation of unmanned aircraft systems (UAS) is the development of detect-and-avoid (DAA) systems to aid the UAS pilot in remaining "well clear" of nearby aircraft. The goal of this study is to investigate the effect of alerting criteria and pilot response delay on the safety and performance of UAS DAA systems in the context of routine civil UAS operations in the National Airspace System (NAS). A NAS-wide fast-time simulation study was conducted to assess UAS DAA system performance with a large number of encounters and a broad set of DAA alerting and guidance system parameters. Three attributes of the DAA system were controlled as independent variables in the study to conduct trade-off analyses: UAS trajectory prediction method (dead-reckoning vs. intent-based), alerting time threshold (related to predicted time to LoWC), and alerting distance threshold (related to predicted Horizontal Miss Distance, or HMD). A set of metrics, such as the percentage of true positive, false positive, and missed alerts, based on signal detection theory and analysis methods utilizing the Receiver Operating Characteristic (ROC) curves were proposed to evaluate the safety and performance of DAA alerting and guidance systems and aid development of DAA system performance standards. The effect of pilot response delay on the performance of DAA systems was evaluated using a DAA alerting and guidance model and a pilot model developed to support this study. A total of 18 fast-time simulations were conducted with nine different DAA alerting threshold settings and two different trajectory prediction methods, using recorded radar traffic from current Visual Flight Rules (VFR) operations, and supplemented with DAA-equipped UAS traffic based on mission profiles modeling future UAS operations. Results indicate DAA alerting distance threshold has a greater effect on DAA system performance than DAA alerting time threshold or ownship trajectory prediction method. Further analysis on the alert lead time (time in advance of predicted loss of well clear at which a DAA alert is first issued) indicated a strong positive correlation between alert lead time and DAA system performance (i.e. the ability of the UAS pilot to maneuver the unmanned aircraft to remain well clear). While bigger distance thresholds had beneficial effects on alert lead time and missed alert rate, it also generated a higher rate of false alerts. In the design and development of DAA alerting and guidance systems, therefore, the positive and negative effects of false alerts and missed alerts should be carefully considered to achieve acceptable alerting system performance by balancing false and missed alerts. The results and methodology presented in this study are expected to help stakeholders, policymakers and standards committees define the appropriate setting of DAA system parameter thresholds for UAS that ensure safety while minimizing operational impacts to the NAS and equipage requirements for its users before DAA operational performance standards can be finalized.

UAS Detect-and-Avoid (DAA) System↗

NASA NTRSDate not supplied

UTM Modeling and Simulation

This presentation introduces modeling and fast-time simulation research conducted under the UTM project. The background and necessity of developing such fast-time simulation capability for high-density UTM operations are first described. The system diagram, individual models, implementation, and performance of such fast-time simulation capability are then discussed. Next, studies utilizing this fast-time simulation capability are highlighted. Finally, future applications of the fast-time simulation capability are presented.

UTM↗

NASA NTRSDate not supplied

CERES Fast Longwave And SHortwave Radiative Flux (FLASHFlux): Research to Operation

The Clouds and Earth’s Radiant Energy System (CERES) project provides satellite-based observations of how Earth’s energy flows are varying in time and space and how clouds and aerosols are affecting the Earth’s radiation budget. Nominally, CERES data products require months of validation and calibration before releasing a climate quality data. The Fast Longwave and Shortwave Radiative Flux (FLASHFlux) data product was developed as to provide key radiative flux data products within a week of observations for scientific, applied science research and educational usage. FLASHFlux achieves this by using simplified calibration process and optimized CERES data fusion production system, an operation meteorology product from Global Modeling and Assimilation Office(GMAO), and surface parameterized radiative flux models. The CERES FLASHFlux provides two data products: 1) an hourly Level 2 Single Scanner Footprint (SSF) data separately for Aqua and Terra observations, and 2) a daily Level 3 Time Interpolated and Spatially Averaged (TISA) 1ox1o gridded data that combines Aqua and Terra observations.The current operational Version 3C is being transitioned to Version4A. We compare the FLASHFlux Version4A fluxes using the specialized calibration to Version3C and to the climate quality CERES Edition4A TOA and surface fluxes over time for Terra and Aqua to determine the uncertainties of the calibration process. In addition, we also compare the impact of the fluxes by using the near real-time GMAO GEOS FP-IT instead of GMAO G5-CERES meteorology data.We also compare both SSF overpass products (for Terra and Aqua) and TISA radiative flux products to a set of surface measurement sites that are globally distributed and assess agreement.Lastly, we introduce the first CERES FF SSF data products from the CERES instrument on board NOAA-20.

P Sawaengphokhai↗

NASA NTRS1978

System-state and operating condition sensitive control method and apparatus for electric power delivery systems

This invention provides a method and apparatus for determining a precise switching sequence for the power switching elements of electric power delivery systems of the on-off switching type and which enables extremely fast transient response, precise regulation and highly stable operation. The control utilizes the values of the power delivery system power handling network components, a desired output characteristic, a system timing parameter, and the externally imposed operating conditions to determine where steady state operations should be in order to yield desired output characteristics for the given system specifications. The actual state of the power delivery system is continuously monitored and compared to a state-space boundary which is derived from the desired equilibrium condition, and from the information obtained from this comparison, the system is moved to the desired equilibrium condition in one cycle of switching control. Since the controller continuously monitors the power delivery system's externally imposed operating conditions, a change in the conditions is immediately sensed and a new equilibrium condition is determined and achieved, again in a single cycle of switching control.

Burns, III, William Wesley↗

DOE OSTI2020

Pilot Plant Reliability Metrics for Grinding and Fast Pyrolysis of Woody Residues

The reliability of biomass size reduction, feeding, and conversion processes remains a critical technical hurdle and important cost driver for biomass conversion systems. While Biorefinery projects have typically focused on scaling up conversion technologies that maximize yield of desired products, e.g. fuels and chemicals, solids handling and reactor feeding systems are often considered secondarily. These are frequently scaled down or adapted from other industries, without a full appreciation of how biomass heterogeneity and variability impact process reliability. Here we present the effects of feedstock variability on relative throughput, mass loss, plant uptime, operator intervention, product yield, and product quality for grinding and fast pyrolysis operations at the pilot scale. Loblolly pine residues were sourced and collected using commercial harvesting techniques. Grinding and pyrolysis experiments were performed at INL's Biomass Feedstock National User Facility and NREL's Thermal and Catalytic Process Development Unit, respectively. Preprocessing throughput using a hammer mill varied between 31-48% of nameplate capacity (5 tons/hr), and fast pyrolysis throughput varied between 57-72% of nameplate capacity (20 kg/hr) for an overall system throughput of 18-35% of nameplate capacity across biomass preprocessing and conversion to pyrolysis oil. Pyrolysis oil yields varied between 46-53% (feedstock carbon to oil, dry basis). Grinder overloads in the size reduction step were more prevalent for lower ash and higher moisture materials. During fast pyrolysis operations, downtime was caused by bridging in the feed and char removal systems and plugging in the condensation system, and significant variation in the type and frequency of operator intervention was observed between feedstocks. Cohesion of solids (feedstock and char) leading to system plugging appeared less problematic for higher ash feedstocks, and differences in condenser plugging behavior between high and low ash feedstocks indicates the composition and physical nature of the deposited material is important for process reliability and is feedstock dependent.

09 BIOMASS FUELS↗

NASA NTRS1993

Advanced propulsion engine assessment based on a cermet reactor

A preferred Pratt & Whitney conceptual Nuclear Thermal Rocket Engine (NTRE) has been designed based on the fundamental NASA priorities of safety, reliability, cost, and performance. The basic philosophy underlying the design of the XNR2000 is the utilization of the most reliable form of ultrahigh temperature nuclear fuel and development of a core configuration which is optimized for uniform power distribution, operational flexibility, power maneuverability, weight, and robustness. The P&W NTRE system employs a fast spectrum, cermet fueled reactor configured in an expander cycle to ensure maximum operational safety. The cermet fuel form provides retention of fuel and fission products as well as high strength. A high level of confidence is provided by benchmark analysis and independent evaluations.

Parsley, Randy C.↗

DOE OSTI2015

Angular-resolution and material-characterization measurements for a dual-particle imaging system with mixed-oxide fuel

A dual-particle imaging (DPI) system, capable of simultaneously imaging fast neutrons and gamma rays, has been operated in the presence of mixed-oxide (MOX) fuel to assess the system's angular resolution and material-characterization capabilities. The detection principle is based on the scattering physics of neutrons (elastic scattering) and gamma rays (Compton scattering) in organic and inorganic scintillators. The detection system is designed as a combination of a two-plane Compton camera and a neutron-scatter camera. The front plane consists of EJ-309 liquid scintillators and the back plane consists of interleaved EJ-309 and NaI(Tl) scintillators. MCNPX-PoliMi was used to optimize the geometry of the system and the resulting prototype was built and tested using a Cf-252 source as an SNM surrogate. A software package was developed to acquire and process data in real time. The software was used for a measurement campaign to assess the angular resolution of the imaging system with MOX samples. Measurements of two MOX canisters of similar isotopics and intensity were performed for 6 different canister separations (from 5° to 30°, corresponding to distances of 21 cm and 131 cm, respectively). The measurements yielded a minimum separation of 20° at 2.5 m (86-cm separation) required to see 2 separate hot spots. Additionally, the results displayed good agreement with MCNPX-PoliMi simulations. These results indicate an angular resolution between 15° and 20°, given the 5° step. Coupled with its large field of view, and its capability to differentiate between spontaneous fission and (α,n) sources, the DPI system shows its potential for nuclear-nonproliferation applications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1992

Bit-parallel arithmetic in a massively-parallel associative processor

A simple but powerful new architecture based on a classical associative processor model is presented. Algorithms for performing the four basic arithmetic operations both for integer and floating point operands are described. For m-bit operands, the proposed architecture makes it possible to execute complex operations in O(m) cycles as opposed to O(m exp 2) for bit-serial machines. A word-parallel, bit-parallel, massively-parallel computing system can be constructed using this architecture with VLSI technology. The operation of this system is demonstrated for the fast Fourier transform and matrix multiplication.

Scherson, Isaac D.↗

NASA NTRS1994

Fuzzy logic based robotic controller

Existing Proportional-Integral-Derivative (PID) robotic controllers rely on an inverse kinematic model to convert user-specified cartesian trajectory coordinates to joint variables. These joints experience friction, stiction, and gear backlash effects. Due to lack of proper linearization of these effects, modern control theory based on state space methods cannot provide adequate control for robotic systems. In the presence of loads, the dynamic behavior of robotic systems is complex and nonlinear, especially where mathematical modeling is evaluated for real-time operators. Fuzzy Logic Control is a fast emerging alternative to conventional control systems in situations where it may not be feasible to formulate an analytical model of the complex system. Fuzzy logic techniques track a user-defined trajectory without having the host computer to explicitly solve the nonlinear inverse kinematic equations. The goal is to provide a rule-based approach, which is closer to human reasoning. The approach used expresses end-point error, location of manipulator joints, and proximity to obstacles as fuzzy variables. The resulting decisions are based upon linguistic and non-numerical information. This paper presents a solution to the conventional robot controller which is independent of computationally intensive kinematic equations. Computer simulation results of this approach as obtained from software implementation are also discussed.

Attia, F.↗