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NASA NTRSDate not supplied

Merging Analytic Collaborative Frameworks with New Observing Strategies Toward a Digital Twin: Earth – Episodic Pulse Event Impacts on Ocean Carbon Cycle as an Example

Virtual representations of the Earth will allow us to address some of the most critical environmental issues of our time. Here, we show the first steps toward representation of riverine, estuarine, and coastal carbon processes to enable scenario driven “what-if” analyses of the carbon system and human footprint. Excess sediment and nutrient runoff from land-based human activities impact water quality and can pose serious threats to coastal and marine ecosystems. Episodic pulse events, such as extreme precipitation events, can increase the amount of nutrients entering estuaries and coastal regions, potentially leading to large phytoplankton blooms followed by anoxic conditions. Consequences of coastal runoff are predicted to increase with the higher intensity and frequency of extreme events. Beyond the threat to coastal ecosystems, recent findings suggest these episodic pulses might play a significant role for biological production influencing regional and global carbon fluxes and budgets. An improved understanding of these events through optimal, dynamic observing strategies will increase our knowledge of the land-ocean continuum and how regional events and nutrient fluxes affect the carbon cycle and ocean ecosystem. This conceptual framework enables focused science investigations by pairing data analytics and artificial intelligence tools (otherwise termed an Analytic Center Framework, ACF) with targeted measurement acquisition through distributed sensing and intelligent asset tasking (or New Observing Strategies, NOS). This NOS and ACF iterative approach acquires and integrates complementary and coincident satellite, in-situ and model data to build a more complete and in-depth picture of science phenomena. Specifically, Apache Science Data Analytic Platform (SDAP) is extended to incorporate relevant datasets for data access, harmonized analysis, and anomaly detection. When conditions are met for a likely pulse event, NASA’s D-SHIELD (Distributed Spacecraft with Heuristic Intelligence to Enable Logistical Decisions) tool is triggered to optimize asset overpass frequency and schedule observations for persistent monitoring. Targeted data is ingested by SDAP for enhanced investigation via iterative analysis until the trigger criteria is no longer met - steps toward a digital twin.

Laura Rogers↗

NASA NTRS2006

Star Tracker Based ATP System Conceptual Design and Pointing Accuracy Estimation

A star tracker based beaconless (a.k.a. non-cooperative beacon) acquisition, tracking and pointing concept for precisely pointing an optical communication beam is presented as an innovative approach to extend the range of high bandwidth (> 100 Mbps) deep space optical communication links throughout the solar system and to remove the need for a ground based high power laser as a beacon source. The basic approach for executing the ATP functions involves the use of stars as the reference sources from which the attitude knowledge is obtained and combined with high bandwidth gyroscopes for propagating the pointing knowledge to the beam pointing mechanism. Details of the conceptual design are presented including selection of an orthogonal telescope configuration and the introduction of an optical metering scheme to reduce misalignment error. Also, estimates are presented that demonstrate that aiming of the communications beam to the Earth based receive terminal can be achieved with a total system pointing accuracy of better than 850 nanoradians (3 sigma) from anywhere in the solar system.

star tracker↗

DOE OSTI2017

Feathermoss and epiphytic Nostoc cooperate differently: expanding the spectrum of plant–cyanobacteria symbiosis

Dinitrogen (N2)-fixation by cyanobacteria in symbiosis with feather mosses represents the main pathway of biological N input into boreal forests. Despite its significance, little is known about the gene repertoire needed for the establishment and maintenance of the symbiosis. To determine gene acquisitions or regulatory rewiring allowing cyanobacteria to form this symbiosis, we compared closely related Nostoc strains that were either symbiosis-competent or non-competent, using a proteogenomics approach and a unique experimental setup allowing for controlled chemical and physical contact between partners. Thirty-two protein families were only in the genomes of competent strains, including some never before associated with symbiosis. We identified conserved orthologs that were differentially expressed in competent strains, including gene families involved in chemotaxis and motility, NO regulation, sulfate/phosphate transport, sugar metabolism, and glycosyl-modifying and oxidative stress-mediating exoenzymes. In contrast to other cyanobacteria-plant symbioses, the moss-cyanobacteria epiphytic symbiosis is distinct, with the symbiont retaining motility and chemotaxis, and not modulating N-fixation, photosynthesis, GS-GOGAT cycle, and heterocyst formation. Our work expands our knowledge of plant cyanobacterial symbioses, provides an interaction model of this ecologically significant symbiosis, and suggests new currencies, namely nitric oxide and aliphatic sulfonates, may be involved in establishing and maintaining this symbiosis.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2015

Nuclear Energy Infrastructure Database Description and User’s Manual

In 2014, the Deputy Assistant Secretary for Science and Technology Innovation initiated the Nuclear Energy (NE)–Infrastructure Management Project by tasking the Nuclear Science User Facilities, formerly the Advanced Test Reactor National Scientific User Facility, to create a searchable and interactive database of all pertinent NE-supported and -related infrastructure. This database, known as the Nuclear Energy Infrastructure Database (NEID), is used for analyses to establish needs, redundancies, efficiencies, distributions, etc., to best understand the utility of NE’s infrastructure and inform the content of infrastructure calls. The Nuclear Science User Facilities developed the database by utilizing data and policy direction from a variety of reports from the U.S. Department of Energy, the National Research Council, the International Atomic Energy Agency, and various other federal and civilian resources. The NEID currently contains data on 802 research and development instruments housed in 377 facilities at 84 institutions in the United States and abroad. The effort to maintain and expand the database is ongoing. Detailed information on many facilities must be gathered from associated institutions and added to complete the database. The data must be validated and kept current to capture facility and instrumentation status as well as to cover new acquisitions and retirements. This document provides a short tutorial on the navigation of the NEID web portal at NSUF-Infrastructure.INL.gov.

42 ENGINEERING↗

DOE OSTI2014

AMS/NRCan Joint Survey Report: Aerial Campaign

In January 2014 the U.S. Department of Energy (DOE), National Nuclear Security Administration (NNSA) Aerial Measuring System (AMS) and the Natural Resources Canada (NRCan) Nuclear Emergency Response project conducted a series of joint surveys at a number of locations in Nevada including the Nevada National Security Site (NNSS). The goal of this project was to compare the responses of the two agencies’ aerial radiation detection systems and data analysis techniques. This test included varied radioactive surface contamination levels and isotopic composition experienced at the NNSS and the differing data processing techniques utilized by the respective teams. Because both teams used the commercial aerial radiation detection systems from Radiation Solutions, Inc., the main focus of the campaign was to investigate the data acquisition techniques, data analysis, and ground-truth verification. The NRCan system consisted of four 4" × 4" × 16" NaI(Tl) scintillator crystals of which two were externally mounted in a modified commercial cargo basket certified for the Eurocopter AS350; the NNSA AMS system consisted of twelve 2" × 4" × 16" NaI(Tl) crystals in externally mounted dedicated pods. For NRCan, the joint survey provided an opportunity to characterize their system’s response to extended sources of various fission products at the NNSS. Since both systems play an important role in their respective countries’ national framework of radiological emergency response and are subject to multiple mutual cooperation agreements, it was important for each country to obtain more thorough knowledge of how they would employ these important assets and define the roles that they would each play in an actual response.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Bayesian D‐Optimal Designs for Gaussian Process Surrogate Models

Computer experiments often employ space-filling strategies to create surrogate models with strong predictive performance. The impact of model parameter estimation for Gaussian process surrogates, however, is often overlooked. Obtaining a better initial estimate of the covariance lengthscale parameter, θ, can greatly improve the resulting Gaussian process fit through more effective sequential acquisitions during active learning. In this work, we propose a novel initial design maximizing the Bayesian D-optimality criterion of the Gaussian process lengthscale parameter. Previously published results have shown the emphasis on lengthscale estimation to be promising, but relied on an empirically driven design creation process. Our Bayesian D-optimal designs are rooted in information theory and lead to more informative sequential acquisitions by improving lengthscale estimation. In many cases, these gains eventually result in better surrogates than those seeded with space-filling initial designs. Furthermore, Bayesian D-optimal designs can be tailored to either isotropic or anisotropic covariance structures, and the Bayesian framework enables the inclusion of prior knowledge in the design process, offering greater flexibility and adaptability. Through several simulation studies, we demonstrate the advantages of Bayesian D-optimal designs in terms of both lengthscale estimation accuracy and predictive performance during active learning.

Bayesian experimental design↗

DOE OSTI2013

Seismic Technology Adapted to Analyzing and Developing Geothermal Systems Below Surface-Exposed High-Velocity Rocks Final Report

The objective of our research was to develop and demonstrate seismic data-acquisition and data-processing technologies that allow geothermal prospects below high-velocity rock outcrops to be evaluated. To do this, we acquired a 3-component seismic test line across an area of exposed high-velocity rocks in Brewster County, Texas, where there is high heat flow and surface conditions mimic those found at numerous geothermal prospects. Seismic contractors have not succeeded in creating good-quality seismic data in this area for companies who have acquired data for oil and gas exploitation purposes. Our test profile traversed an area where high-velocity rocks and low-velocity sediment were exposed on the surface in alternating patterns that repeated along the test line. We verified that these surface conditions cause non-ending reverberations of Love waves, Rayleigh waves, and shallow critical refractions to travel across the earth surface between the boundaries of the fast-velocity and slow-velocity material exposed on the surface. These reverberating surface waves form the high level of noise in this area that does not allow reflections from deep interfaces to be seen and utilized. Our data-acquisition method of deploying a box array of closely spaced geophones allowed us to recognize and evaluate these surface-wave noise modes regardless of the azimuth direction to the surface anomaly that backscattered the waves and caused them to return to the test-line profile. With this knowledge of the surface-wave noise, we were able to process these test-line data to create P-P and SH-SH images that were superior to those produced by a skilled seismic data-processing contractor. Compared to the P-P data acquired along the test line, the SH-SH data provided a better detection of faults and could be used to trace these faults upward to the boundaries of exposed surface rocks. We expanded our comparison of the relative value of S-wave and P-wave seismic data for geothermal applications by inserting into this report a small part of the interpretation we have done with 3C3D data across Wister geothermal field in the Imperial Valley of California. This interpretation shows that P-SV data reveal faults (and by inference, also fractures) that cannot be easily, or confidently, seen with P-P data, and that the combination of P-P and P-SV data allows VP/VS velocity ratios to be estimated across a targeted reservoir interval to show where an interval has more sandstone (the preferred reservoir facies). The conclusion reached from this investigation is that S-wave seismic technology can be invaluable to geothermal operators. Thus we developed a strong interest in understanding the direct-S modes produced by vertical-force sources, particularly vertical vibrators, because if it can be demonstrated that direct-S modes produced by vertical-force sources can be used as effectively as the direct-S modes produced by horizontal-force sources, geothermal operators can acquire direct-S data across many more prospect areas than can be done with horizontal-force sources, which presently are limited to horizontal vibrators. We include some of our preliminary work in evaluating direct-S modes produced by vertical-force sources.

15 GEOTHERMAL ENERGY↗

NASA NTRS1985

Thermionic noise measurements for on-line dispenser cathode diagnostics for linear beam microwave tubes

A test stand has been set up to measure the current fluctuation noise properties of B- and M-type dispenser cathodes in a typical TWT gun structure. Noise techniques were used to determine the work function distribution on the cathode surfaces. Significant differences between the B and M types and significant changes in the work function distribution during activation and life are found. In turn, knowledge of the expected work function can be used to accurately determine the cathode-operating temperatures in a TWT structure. Noise measurements also demonstrate more sensitivity to space charge effects than the Miram method. Full automation of the measurements and computations is now required to speed up data acquisition and reduction. The complete set of equations for the space charge limited diode were programmed so that given four of the five measurable variables (J, J sub O, T, D, and V) the fifth could be computed. Using this program, we estimated that an rms fluctuation in the diode spacing d in the frequency range of 145 Hz about 20 kHz of only about 10 to the -5 power A would account for the observed noise in a space charge limited diode with 1 mm spacing.

Holland, C.↗

DOE OSTI2019

In Situ X-ray Absorption Spectroscopy of a Synergistic Co–Mn Oxide Catalyst for the Oxygen Reduction Reaction

Identifying the catalytically active site(s) in the oxygen reduction reaction (ORR), under real-time electrochemical conditions, is critical to the development of fuel cells and other technologies. We have employed in situ synchrotron-based X-ray absorption spectroscopy (XAS) to explore the synergistic interaction of a Co–Mn oxide catalyst which exhibits impressive ORR activity in alkaline fuel cells. X-ray absorption near edge structure (XANES) was used to track the dynamic structural changes of Co and Mn under both steady state (constant applied potential) and nonsteady state (potentiodynamic cyclic voltammetry, CV). Under steady state conditions, both Mn and Co valences decreased at lower potentials, suggesting the conversion from Mn-(III,IV) and Co(III) to Mn(II,III) and Co(II), respec-tively. Rapid X-ray data acquisition, combined with a slow sweep rate in CV, enabled a 3 mV resolution in the applied potential, approaching a nonsteady (potentiody-namic) state. Changes in the Co and Mn valence states were simultaneous and exhibited periodic patterns that tracked the cyclic potential sweeps. To the best of our knowledge, this represents the first study, using in situ XAS, to resolve the synergistic catalytic mechanism of a bimetallic oxide. Strategies developed/described herein can offer an enticing approach to unveil the reaction mechanism for other multimetallic electrocatalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1993

High-performance mass storage system for workstations

Reduced Instruction Set Computer (RISC) workstations and Personnel Computers (PC) are very popular tools for office automation, command and control, scientific analysis, database management, and many other applications. However, when using Input/Output (I/O) intensive applications, the RISC workstations and PC's are often overburdened with the tasks of collecting, staging, storing, and distributing data. Also, by using standard high-performance peripherals and storage devices, the I/O function can still be a common bottleneck process. Therefore, the high-performance mass storage system, developed by Loral AeroSys' Independent Research and Development (IR&D) engineers, can offload a RISC workstation of I/O related functions and provide high-performance I/O functions and external interfaces. The high-performance mass storage system has the capabilities to ingest high-speed real-time data, perform signal or image processing, and stage, archive, and distribute the data. This mass storage system uses a hierarchical storage structure, thus reducing the total data storage cost, while maintaining high-I/O performance. The high-performance mass storage system is a network of low-cost parallel processors and storage devices. The nodes in the network have special I/O functions such as: SCSI controller, Ethernet controller, gateway controller, RS232 controller, IEEE488 controller, and digital/analog converter. The nodes are interconnected through high-speed direct memory access links to form a network. The topology of the network is easily reconfigurable to maximize system throughput for various applications. This high-performance mass storage system takes advantage of a 'busless' architecture for maximum expandability. The mass storage system consists of magnetic disks, a WORM optical disk jukebox, and an 8mm helical scan tape to form a hierarchical storage structure. Commonly used files are kept in the magnetic disk for fast retrieval. The optical disks are used as archive media, and the tapes are used as backup media. The storage system is managed by the IEEE mass storage reference model-based UniTree software package. UniTree software will keep track of all files in the system, will automatically migrate the lesser used files to archive media, and will stage the files when needed by the system. The user can access the files without knowledge of their physical location. The high-performance mass storage system developed by Loral AeroSys will significantly boost the system I/O performance and reduce the overall data storage cost. This storage system provides a highly flexible and cost-effective architecture for a variety of applications (e.g., realtime data acquisition with a signal and image processing requirement, long-term data archiving and distribution, and image analysis and enhancement).

Chiang, T.↗

DOE OSTI2018

X-Ray Phase Contrast Imaging (XPCI) System

Sandia National Laboratories (Sandia) and Carestream Health, Inc. (CHI) collaborated on the development of a grating-based X-ray Phase Contrast Imaging (XPCI) system at Sandia. The purpose of the agreement was to share research and development knowledge, resources, and capabilities in the advancement of XPCI that would be mutually beneficial to CHI and Sandia. In the course of this agreement Sandia designed and built an XPCI apparatus including opto-mechanical design, source and x-ray detector selection, software interface, hardware assembly, and system alignment. Data acquisition and image reconstruction were demonstrated at both CHI and Sandia. XPCI is a new imaging modality that enables non-destructive inspection of low density materials not previously possible with conventional x-ray. The technique fills a capability gap valuable to both the industry partner in their technical portfolio and in national security applications important to Sandia and the DOE mission space.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

An updated estimate of the Mu2e experiment sensitivity

The Mu2e experiment at Fermilab will search for the conversion of a negative muon into an electron inside the field of a nucleus. This process does not conserve charged-lepton flavour and is heavily suppressed in the Standard Model (SM), with a branching ratio < 10-50. Any evidence of it would be an undeniable evidence of new physics beyond the SM. The project sets out to achieve a single event sensitivity of $\sim 3 × 10^{-17}$ on the ratio between the probability for a conversion of a negative muon into an electron and the one for a muon capture by the nucleus. Such a sensitivity would represent a 4 orders of magnitude improvement on the previous upper limit for the process, making possible to test predictions of different extensions of the SM. Mu2e uses three superconducting solenoids to produce and measure the muon conversions. In the first solenoid, the Production Solenoid, pions and kaons are produced, together with other secondary products, by 8 GeV kinetic energy proton interactions in a tungsten target. A gradient magnetic field is specifically designed to direct low momentum particles into the Transport Solenoid, an S-shaped magnet that filters out particles with unwanted charge and momentum. Muons, produced by pion and kaon decays, finally reach the aluminum Stopping Target in the Detector Solenoid, where they eventually stop and convert. The result of the conversion process is a monochromatic electron of ~105 MeV/c momentum. The Detector Solenoid also hosts the two main detectors: a straw tube tracker and two CsI calorimeter disks, both providing measurement of event kinematics. A germanium detector and a LaBr crystal are located downstream of the Detector Solenoid to measure the X and gamma rays produced by the muon captures in the Stopping Target. A veto system of scintillators covering the Detector Solenoid and half of the Transport Solenoid is used to identify and reject cosmic rays interactions. With respect to the initial project, the Mu2e running plan has evolved to a staged configuration with 2 years at reduced intensity before the 2025 accelerator shutdown for the neutrino beam upgrade and 2 or 3 years at full intensity after that. This, together with geometry changes and a better knowledge of detector performances obtained by the first slice tests, has required a full revision of the signal over background selection that is the subject of this thesis. In order to achieve a new estimate of Mu2e sensitivity, the simulation of the data corresponding to the first 2 years of data acquisition has been performed. This includes both conversion electrons (CE) and the main sources of background: cosmics, decay-in orbits (DIO), radiative pion captures (RPC) and antiprotons. The characteristics of the signal and of the main backgrounds have been studied to define the best selection variables for CE. A special effort has been devoted to the evaluation of the antiproton background. The lack of experimental data for antiproton production cross section makes the systematic uncertainty on this background significant. A new parameterization of the cross section has been developed to fit the existing data and to provide a more reliable estimate of the systematic uncertainty by comparing the results of the old and the new model. A special effort has been devoted to the optimization of the antiprotons Monte Carlo generator. This study has also revealed that the dominant component within this background is represented by antiprotons produced in the opposite direction with respect to the Transport Solenoid entrance and then redirected to it by back-scattering processes in the Production Target. This ultimately highlights the sensitivity of the background estimate to the G4 handling of antiproton interactions in the 1 to 3 GeV/c momentum range. Finally, the final experimental sensitivity has been studied. The momentum and time selection have been optimized to obtain the 5-sigma discovery reach or, in case of no signal, the upper limit on conversion probability. The results confirm that, in the firs t two years of data taking, Mu2e will be able to improve the current experimental sensitivity for muon-to-electron conversion in an atomic field by more than 3 order of magnitudes.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRSDate not supplied

NASA R&M Efficiency through Findable, Accessible, Interoperable, and Reusable (FAIR) Digital Assets

At the intersection of mission, technology, and place is NASA’s need to modernize for a digital-forward future. Digitalization, the process of moving toward digital business, is occurring everywhere and remains an ongoing process across the federal government.”[1] Whereas, Digital Transformation is “employing digitization/digital technologies (e.g., Artificial Intelligence (AI), mobile, cloud, data) to change a process, product, or capability so dramatically (e.g., real-time, intelligent, personalized, anywhere, anytime) that it is unrecognizable compared to its traditional form.” [2] In order to facilitate a digital transformation it is essential for NASA to understand and identify where data exists today and which data are value-needed in the future, understand where there are unfulfilled data needs that limit the advancement of NASA work, and ensure NASA efficiency through Findable, Accessible, Interoperable, and Reusable (FAIR) digital assets in the future. Therefore, NASA’s Reliability & Maintainability (R&M) Enterprise Data Sharing team is working to leverage both Digitization and Digital Transformation to achieve their vision of developing an R&M data discovery framework that enables our community, our partners, and our stakeholders with the ability to efficiently, robustly, and seamlessly access information that enables real-time knowledge and model-based, analytics driven, decision-making impacting R&M. As a result the R&M Enterprise Data Sharing team has conducted a survey of its Reliability, Maintainability, and Availability (RMA) community members to identify data existence (created or used) and where there are corresponding barriers to data acquisition and/or R&M or other issues as shown within this presentation.

Digital Transformation↗

NASA NTRSDate not supplied

Trilateral Task Force – Reliability Analysis Supporting Mission Extension/Post Mission Disposal

Digital Transformation, Reliability Engineering↗

DOE OSTI2026

Gearbox bearing crack growth prognostics and uncertainty quantification with physics-informed machine learning

This paper introduces the extreme theory of functional connections (X-TFC), a physics-informed machine learning algorithm, and tailors it to estimate the remaining useful life (RUL) of wind turbine gearbox bearings experiencing fatigue crack growth. Unlike purely data-driven methods, X-TFC embeds a physics model, based on Head's theory in this work, into its training objective. The core of X-TFC is a random-projection single-layer neural network trained via an extreme learning machine, which requires only limited damage progression data and solves for output weights with a least-squares optimization algorithm. A composite loss function balances the network's fit to observed degradation data against the residuals of the governing crack growth differential equation, ensuring the learned damage trajectory remains physically plausible. When applied to a vibration-based health-index (HI) dataset measured during the growth of a crack on the inner ring of a high-speed bearing in a wind turbine gearbox (Bechhoefer and Dubé, 2020), X-TFC achieves near-zero prediction bias. Even when trained on only the first 10 %–20 % of the damage progression data, with sufficient physics weighting its predictions remain monotonic and smooth, delivering high prognosability and trendability. To quantify the epistemic uncertainty, we employ a Monte Carlo ensemble of independently initialized X-TFC models trained on noise-perturbed data, which yields confidence intervals around each RUL estimate and captures both model-parameter and epistemic uncertainty. In addition to a vibration-based HI, we demonstrate that the proposed framework can be directly applied to a supervisory control and data acquisition (SCADA) data-based HI (Eftekhari Milani et al., 2026) measured during similar wind turbine gearbox bearing crack faults, preserving its accuracy and interpretability. This extension shows the versatility of our approach, which is applicable to bearings of multiple gearbox manufacturers, models, and ratings using only SCADA data. By integrating domain knowledge with machine learning, X-TFC offers a rapid, reliable tool for crack prognostics. Its adaptability to other bearing failure modes, such as pitch bearing ring cracks, positions X-TFC as a powerful enabler of data-driven, physics-informed asset management in the wind energy sector and beyond.

17 WIND ENERGY↗

NASA NTRS1993

Failure monitoring in dynamic systems: Model construction without fault training data

Advances in the use of autoregressive models, pattern recognition methods, and hidden Markov models for on-line health monitoring of dynamic systems (such as DSN antennas) have recently been reported. However, the algorithms described in previous work have the significant drawback that data acquired under fault conditions are assumed to be available in order to train the model used for monitoring the system under observation. This article reports that this assumption can be relaxed and that hidden Markov monitoring models can be constructed using only data acquired under normal conditions and prior knowledge of the system characteristics being measured. The method is described and evaluated on data from the DSS 13 34-m beam wave guide antenna. The primary conclusion from the experimental results is that the method is indeed practical and holds considerable promise for application at the 70-m antenna sites where acquisition of fault data under controlled conditions is not realistic.

Smyth, P.↗

DOE OSTI2018

Evaluating Wind Direction Consensus Methods: A Case Study

Wind turbines in a wind farm typically operate individually to maximize their own performance and do not take into account information from nearby turbines. To enable cooperation to achieve farm-level objectives, turbines will need to use information from nearby turbines to optimize performance, ensure resiliency when other sensors fail, and adapt to changing local conditions. A key element of achieving these cooperative wind farms is to develop algorithms that provide necessary information to ensure reliable and efficient operation of turbines in a wind plant using local sensor information that is already being collected, such as supervisory control and data acquisition (SCADA) data, local meteorological stations, and nearby radars/sodars/lidars. This presentation demonstrates a framework for implementing a cooperative wind. Farm that incorporates information from local sensors in real time to better align turbines in a wind farm. Oftentimes, measurements made at an individual turbine are noisy and unreliable. By incorporating measurements from multiple nearby turbines, a more reliable estimate of the wind direction can be obtained at an individual turbine. Results indicate that this estimate of the wind direction can be used to improve the turbine's knowledge of the wind direction and could decrease dynamic yaw misalignment, decrease the amount of time a turbines spends yawing due to a more reliable input to the yaw controller, and increase resiliency to faulty wind-vane measurements. The concept was evaluated on data provided by WindESCo and was evaluated across several other averaging techniques to demonstrate the resiliency of the proposed consensus method.

17 WIND ENERGY↗

DOE OSTI2020

Electrochemistry of PUREX: R is for Reduction and Ion Transfer

The PUREX (Plutonium, Uranium, Reduction, EXtraction) process is the foundation of all industrial activities that involve the recycling of plutonium and uranium from used nuclear fuel. With over 70 years of research, engineering, and operations, it can be argued that little opportunity is left for further discovery and new fundamental understandings regarding PUREX, in general, and tri-n-butyl phosphate (TBP), in particular. Through use of an advanced electroanalytical approach, molecular-level insights regarding the back-extraction of Pu(IV) by reductive separation is reported. Studies of model PUREX systems, with lanthanide ions extracted into 20 % TBP in n-dodecane, are used to demonstrate the approach. These studies reveal knowledge pertinent to mass transfer aspects of the biphasic reductive stripping reaction central to the separation of U and Pu in PUREX. Two lanthanide ions—Ce(IV) and Yb(III)—were extracted from their concentrated solutions in aqueous 3 M HNO 3 to expressly provide electrically conducting third phases to facilitate electrochemical data acquisition. To simplify the diabolically-complicated reductive separation aspects of PUREX, the controlled polarization of electrode surfaces was used to reduce Ce(IV) and Yb(III) in place of chemical reductants. Electroanalyses of the biphasic systems with Ce(IV) and Yb(III) using three-phase electrode differential pulse voltammetry demonstrate the effects of mass transfer across water-oil interfaces on the electrode potentials for the reduction to Ce(III) and Yb(II). These reductions trigger nitrate transfer out of the oil phase for Ce and proton transfer into the organic phase for Yb. This is in correlation with the transfer of the charge-neutral ion pairs Ce·3NO 3 and Yb·2NO 3 out of the oil phases. Here, the differences in ion transfer steps reflect significant variations in the equilibrium speciation of multinuclear Ce(IV) and mononuclear Yb(III) solvates of TBP in the oil phases and the loading of the organic phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗