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DOE OSTI2020

Distributed Algorithm for Volt-VAr Optimization in Unbalanced Distribution System

Conservation voltage reduction (CVR) is implemented in the distribution system to reduce the voltage along the feeder with the objective to reduce the power consumption. Due to the increased penetration of distributed generators in the distribution system the centralized control is cumbersome. Hence, in this paper, a distributed algorithm is proposed for volt-var optimization (VVO) with CVR objective in a three-phase unbalanced distribution network. The proposed method is based on alternating direction method of multipliers (ADMM) algorithm. Mathematically the problem is formulated as a convex optimization problem with reactive power support from smart inverters. The convexity guarantees the solution obtained using the proposed method is a converged solution. The proposed method is validated on IEEE 4-bus and 13-bus three-phase unbalanced systems.

ADMM↗

NASA NTRS1996

An Analysis of MSFC Public Affairs Television and Target Audiences with Suggestions for Future Growth and Directions

Because of profound changes in government and the space program, this may be an ideal time to evaluate MSFC's Public Affairs television efforts. The changes are continued downsizing of government programs; reduction in research and development; changes in the space program from periodic manned launches to a full-time presence in space with Space Station; and greater emphasis on science and communicating science information. At the same time that NASA is undergoing change, the media and society are also undergoing substantial upheaval. Twenty-five years ago, the three main over-the-air television networks (ABC, CBS and NBC) had a 93 share of the television audience. We now have four popular over-the-air networks (ABC, CBS, NBC and Fox) who maintain a 52 percent share of the television audience. Technological development, competition, and changing consumer tastes have created specialized media and audiences. This media fragmentation is part of a normal maturation cycle of use or adoption. While phases in the cycle vary in length due to many factors, the cycle has been consistent and reflects patterns of adoption. The cycle is: (1) Elite Media usage, (2) Popular or Mass Media usage, and (3) Specialized Media usage. Another factor that affects the media development and adoption cycle is the creation of new and competing mass and personal mediums. While television remains the dominant and most popular mass medium, it is declining and we see (via cable television) specialized networks catering to small audience segments. Because of changing technology and consumer behavior, we may not see a dominant mass media like television again.

Smeyak, Gerald P.↗

NASA NTRS2000

Upgrade of the Thermal Vacuum Data System at NASA/GSFC

The Goddard Space Flight Center's new thermal vacuum data acquisition system is a networked client-sever application that enables lab operations crews to monitor all tests from a central location. The GSFC thermal vacuum lab consists of eleven chambers in Building 7 and one chamber in Building 10. The new data system was implemented for several reasons. These included the need for centralized data collection, more flexible and easier to use operator interface, greater data accessibility, a reduction in testing time and cost, and increased payload and personnel safety. Additionally, a new data system was needed for year-2000 compliance. This paper discusses the incorporation of the Thermal Vacuum Data System (TVDS) within the thermal vacuum lab at GSFC, its features and capabilities and lessons learned in its implementation. Additional topics include off-center (Internet) capability for remote monitoring and the role of TVDS in the efforts to automate thermal vacuum chamber operations.

Palmer, John↗

NASA NTRS2000

Upgrade of The Thermal Vacuum Data System at NASA/GSFC

Palmer, John↗

DOE OSTI2023

Physics-informed neural network with transfer learning (TL-PINN) based on domain similarity measure for prediction of nuclear reactor transients

Nuclear reactor safety and efficiency can be enhanced through the development of accurate and fast methods for prediction of reactor transient (RT) states. Physics informed neural networks (PINNs) leverage deep learning methods to provide an alternative approach to RT modeling. Applications of PINNs in monitoring of RTs for operator support requires near real-time model performance. However, as with all machine learning models, development of a PINN involves time-consuming model training. Here, we show that a transfer learning (TL-PINN) approach achieves significant performance gain, as measured by reduction of the number of iterations for model training. Using point kinetic equations (PKEs) model with six neutron precursor groups, constructed with experimental parameters of the Purdue University Reactor One (PUR-1) research reactor, we generated different RTs with experimentally relevant range of variables. The RTs were characterized using Hausdorff and Fréchet distance. We have demonstrated that pre-training TL-PINN on one RT results in up to two orders of magnitude acceleration in prediction of a different RT. The mean error for conventional PINN and TL-PINN models prediction of neutron densities is smaller than 1%. We have developed a correlation between TL-PINN performance acceleration and similarity measure of RTs, which can be used as a guide for application of TL-PINNs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Tunable thermoplastic elastomer gels derived from controlled-distribution triblock copolymers with crystallizable endblocks

Thermoplastic elastomers (TPEs), a commercially important category of triblock copolymers, are employed alone or upon physical modification with a midblock-selective oil (to form TPE gels, TPEGs) in a broad range of contemporary technologies. While most copolymers in this class of self-networking macromolecules possess glassy polystyrene endblocks and a rubbery polydiene or polyolefin midblock, we investigate TPEGs fabricated from a novel controlled-distribution copolymer with crystallizable polyolefin endblocks and a random-copolymer midblock. According to both electron microscopy and small-angle scattering, the morphologies of these TPEGs remain largely invariant up to 40 wt% oil and then transform considerably at higher oil levels. Although reductions in endblock melting point and crystallinity measured by thermal calorimetry accompany increasing oil content, mechanical properties such as the uniaxial strain at break and fracture toughness improve in some cases by over 50% between 5 and 40 wt% oil. In fact, the strain at break can reach 2500% within this range, thereby confirming that (i) the structure–property relationships of these unique TPEGs are highly composition-tunable and (ii) these TPEGs, stabilized by crystallizable endblocks, provide an attractive alternative for ultrasoft and stretchy recyclable materials.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Estimating PV power from aggregate power measurements within the distribution grid

The increased integration of photovoltaic (PV) systems in distribution grids reduces visibility and situational awareness for utilities because the PV systems' power production is usually not monitored by them. To address this problem, a method called Contextually Supervised Source Separation (CSSS) has been recently adapted for real-time estimation of aggregate PV active power generation from aggregate net active and reactive power measurements at a point in a radially configured distribution grid (e.g., substation). In its original version, PV disaggregation is formulated as an optimization problem that fits linear regression models for the aggregate PV active power generation and true substation active power load. This paper extends the previous work by adding regularization terms in the objective function to capture additional contextual information such as smoothness, by adding new constraints, by introducing new regressors such as ambient temperature, and by investigating the use of time-varying regressors. Furthermore, we perform extensive parametric analysis to study tuning of the objective function weighting factors in a way that maximizes performance and robustness. The proposed PV disaggregation method can be applied to networks with either a single PV system (e.g., megawatt scale) or many distributed ones (e.g., residential scale) connected downstream of the substation. Simulation studies with real field recorded data show that the enhancements of the proposed method reduce disaggregation error by 58% in winter and 35% in summer compared to previous CSSS-based work. When compared against a commonly used transposition model based approach, the reduction in disaggregation error is more pronounced (78% reduction in winter and 45% in summer). Additional simulations indicate that the proposed algorithm is also applicable for PV systems with time-varying power factors. In conclusion, overall, our results show that—with appropriate modeling and tuning—it is possible to accurately estimate the aggregated PV active power generation of a distribution feeder with minimal or no additional sensor deployment.

14 SOLAR ENERGY↗

DOE OSTI2024

Smart pixel sensors: towards on-sensor filtering of pixel clusters with deep learning

Highly granular pixel detectors allow for increasingly precise measurements of charged particle tracks. Next-generation detectors require that pixel sizes will be further reduced, leading to unprecedented data rates exceeding those foreseen at the High- Luminosity Large Hadron Collider. Signal processing that handles data incoming at a rate of $\mathcal{O}$(40 MHz) and intelligently reduces the data within the pixelated region of the detector at rate will enhance physics performance at high luminosity and enable physics analyses that are not currently possible. Using the shape of charge clusters deposited in an array of small pixels, the physical properties of the traversing particle can be extracted with locally customized neural networks. In this first demonstration, we present a neural network that can be embedded into the on-sensor readout and filter out hits from low momentum tracks, reducing the detector's data volume by 57.1%–75.7%. The network is designed and simulated as a custom readout integrated circuit with 28 nm CMOS technology and is expected to operate at less than 300 μW with an area of less than 0.2 mm 2 . The temporal development of charge clusters is investigated to demonstrate possible future performance gains, and there is also a discussion of future algorithmic and technological improvements that could enhance efficiency, data reduction, and power per area.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Models and Strategies for Optimal Demand Side Management in the Chemical Industries

Deregulation and the increase of renewable electricity generation from wind and solar photovoltaics have transformed the U.S. electricity market. Economic and environmental benefits notwithstanding, the presence of renewables has increased variability and uncertainty on the supply side of the grid. Managing demand, rather than generation – a strategy referred to as “demand response (DR)” – is an attractive approach for mitigating this imbalance. DR efforts aim to reduce electricity usage during peak demand times, lessening stress on the grid. Industrial users are particularly attractive entities for DR participation since they present large, localized loads that can provide significant relief on grid demand and –unlike other large loads, such as buildings – are minimally dependent on human needs and preferences. In this project, we accomplished three main objectives. (1) We developed data-driven low-order DR scheduling-relevant dynamic models of chemical processes. Concurrently, we studied the formulation and solution of the associated optimal DR production scheduling problems. (a) A prototype air separation unit (ASU) model was used to generate simulated operating data for initial modeling efforts, which enabled the later use of industrial data for data-driven modeling. (b) We utilized Hammerstein-Wiener (HW) and Finite Step Response (FSR) models to represent nonlinear plant dynamics. (c) The HW models were linearized using exact linearization so they could potentially be embedded in power system models, which are formulated as mixed integer linear programs (MILPs). (d) We solved DR optimization problems under uncertainty and found that even naïve predictions of electricity price and product demand led to significant cost savings benefits. (2) Our DR scheduling optimization problem formulations are amenable to real-time solution. (a) We utilized Lagrangian Relaxation (LR) to efficiently solve the optimization problem by decoupling subproblems linked by complicating constraints. (b) We have achieved computation times for the 3-day DR scheduling problem of an ASU as low as 1.88 minutes. (3) Our representations of the DR behavior of chemical process as grid-level batteries were embedded in power system models. (a) For a small-scale grid, we found that incorporating the dynamics of the chemical plant in the optimal power flow calculations resulted in better resource management leading to up to 15% and 46% cost reduction for the grid and chemical plant operations, respectively, during periods of power line congestion. We have published several works dedicated to modeling and solving DR optimization problems from the user side. These were published in top peer-reviewed journals and are summarized in this report. The most recent work (and papers in preparation) considers DR scheduling from the grid side. Future efforts will consider networked plants (e.g., air separation units operating on a common pipeline) for DR participation, which is expected to amplify the capabilities of industrial DR participants to perform load-shifting. Our consideration of uncertainty in DR has inspired future directions in this area as well: we plan to develop multistage methods to fully account for the effects of uncertainty in DR scheduling.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Effect of Biomass Water Dynamics in Cosmic-Ray Neutron Sensor Observations: A Long-Term Analysis of Maize–Soybean Rotation in Nebraska

Precise soil water content (SWC) measurement is crucial for effective water resource management. This study utilizes the Cosmic-Ray Neutron Sensor (CRNS) for area-averaged SWC measurements, emphasizing the need to consider all hydrogen sources, including time-variable plant biomass and water content. Near Mead, Nebraska, three field sites (CSP1, CSP2, and CSP3) growing a maize–soybean rotation were monitored for 5 (CSP1 and CSP2) and 13 (CSP3) years. Data collection included destructive biomass water equivalent (BWE) biweekly sampling, epithermal neutron counts, atmospheric meteorological variables, and point-scale SWC from a sparse time domain reflectometry (TDR) network (four locations and five depths). In 2023, dense gravimetric SWC surveys were collected eight (CSP1 and CSP2) and nine (CSP3) times over the growing season (April to October). The N0 parameter exhibited a linear relationship with BWE, suggesting that a straightforward vegetation correction factor may be suitable (fb). Results from the 2023 gravimetric surveys and long-term TDR data indicated a neutron count rate reduction of about 1% for every 1 kg m−2 (or mm of water) increase in BWE. This reduction factor aligns with existing shorter-term row crop studies but nearly doubles the value previously reported for forests. This long-term study contributes insights into the vegetation correction factor for CRNS, helping resolve a long-standing issue within the CRNS community.

Chemistry↗

NASA NTRS1973

Supply support of NASA tracking networks

The extent which supply support for Jet Propulsion Laboratory's Deep Space Network and Goddard Space Flight Center's Space Flight Tracking and Data Network should be consolidated is considered along with the Identification of opportunities for improvements in each of the supply systems without regard to consolidation. There is a considerable amount of commonality between the items in the stock catalogs at the two network depots, 58% for federal stock number items and 30% overall. The workload at the DSIF Supply Depot (DSD) is small (less than 20%) compared to the Network Logistics Depot (NLD). A number of important benefits in supply support would result from a consolidation of DSD into NLD. LMI found that a consolidation as is, without any changes in inventory management techniques, would reduce annual operating costs by from $208,000 to $358,000. However, if the consolidation were coupled with a change to use of economic order quantities, the annual operating cost reduction would range from $930,000 to $1,078,000.

Source record↗

NASA NTRSDate not supplied

NASA's Efforts to Pursue Commercial Communications Services for Missions in Near Space

The National Aeronautics and Space Administration (NASA) Space Communications and Navigation (SCaN) Program enables high speed, robust, secure and cost-effective space communications and navigation services to current and future science and exploration missions. Consistent with National Space Policy, NASA is seeking commercial services for all its future near Earth requirements by incorporating additional direct to Earth (DTE) providers and introducing commercial satellite communications (SATCOM) vendors as NASA’s Tracking and Data Relay Satellites (TDRS) begin to decline. Through the progression of these efforts, SCaN is also integrating commercial services in the cislunar domain. The overarching objective is to satisfy the demands from the mission community – both in terms of capacity and capability – in a robust and cost-effective way, leveraging the strong and growing commercial space sector. For near earth space relay, six SATCOM vendors were awarded Funded Space Act Agreements in June of 2022 to demonstrate the ability to serve near-Earth missions, and are working through their committed milestones. The failure of TDRS Flight-9 (F9) in late 2022 prompted an increased tempo of mission engagement to identify driving user needs that commercial SATCOM can meet in the near-term. NASA has set a course to accelerate a decision to terminate commitments for TDRS services to new missions and has developed a plan to execute validation and risk reduction efforts with early adopter “pathfinder” missions to pave the way to earlier operational services. As the Artemis Program matures and builds on the successful Artemis I flight in November/December of 2022, the definition of the supporting communications and navigation architecture has further been refined. Although NASA government assets will continue to play a key role in provision of services, such as through the Deep Space Network, SCaN is pursuing commercial services offerings to expand ground network capability and implement lunar relay services. In February of 2023, SCaN released solicitation for services that include DTE services to missions near-Earth and in cislunar space, as well as lunar relay services. Further, SCaN is seeking opportunities to integrate commercial capability into lunar surface communications infrastructure. NASA is also advocating for standards that promote interoperability and strategic technology investments in the commercial sector. This paper addresses the recent progress and future plans in the near-Earth space and lunar regimes, discusses the unified approach for industry engagement, and highlights both the common and unique challenges of commercialization efforts in the two regimes.

commercialization↗

NASA NTRSDate not supplied

NASA’s Efforts to Pursue Commercial Communications Services for Missions in Near Space

The National Aeronautics and Space Administration (NASA) Space Communications and Navigation (SCaN) Program enables high speed, robust, secure, and cost-effective space communications and navigation services to current and future science and exploration missions. Consistent with National Space Policy, NASA is seeking commercial services for all its future near-Earth requirements by incorporating additional direct to Earth (DTE) providers and introducing commercial satellite relay communications (SATCOM) vendors as NASA’s Tracking and Data Relay Satellites (TDRS) begin to decline. Through the progression of these efforts, SCaN is also integrating commercial services in the cislunar domain. The overarching objective is to satisfy the demands from the mission community – both in terms of capacity and capability – in a robust, reliable, and cost-effective way, leveraging the strong and growing commercial space sector. For near earth space relay, six SATCOM vendors were awarded Funded Space Act Agreements in June of 2022 to demonstrate the ability to serve near-Earth missions with space-based communication relay services. All six vendors are working through their committed milestones with end-to-end service demonstrations tacking place throughout the mid-2020’s. The failure of TDRS Flight-9 (F9) in late 2022 prompted an increased tempo of mission engagement to identify driving user needs that commercial SATCOM can meet in the near-term. NASA has set a course to accelerate a decision to terminate offering TDRS services to new missions and is developing a plan to execute validation and risk reduction efforts with early adopter “pathfinder” missions, paving the way to operational services. As the Artemis Program matures and builds on the successful Artemis I flight in November-December of 2022, the definition of the supporting communications and navigation architecture has further been refined. Although NASA government assets will continue to play a key role in provision of services, such as through the Deep Space Network, SCaN is pursuing commercial services offerings to expand ground network capability and implement lunar relay services. In February of 2023, SCaN released solicitation for services that include DTE services to missions near-Earth and in cislunar space, as well as lunar relay services. Further, SCaN is seeking opportunities to integrate commercial capability into lunar surface communications infrastructure. NASA is also advocating for standards that promote interoperability and strategic technology investments in the commercial sector. This paper addresses the recent progress and future plans in the near-Earth space and lunar regimes, discusses the unified approach for industry engagement, and highlights both the common and unique challenges of commercialization efforts in the two regimes.

commercial services↗

DOE OSTI2024

CO 2 storage site characterization using ensemble-based approaches with deep generative models

Estimating spatially distributed properties such as permeability from available sparse measurements is a great challenge in efficient subsurface CO 2 storage operations. In this paper, a deep generative model that can accurately capture complex subsurface structure is tested with an ensemble-based inversion method for accurate and accelerated characterization of CO 2 storage sites. We chose Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP) for its realistic reservoir property representation and Ensemble Smoother with Multiple Data Assimilation (ES-MDA) for its robust data fitting and uncertainty quantification capability. WGAN-GP are trained to generate high-dimensional permeability fields from a low-dimensional latent space and ES-MDA then updates the latent variables by assimilating available measurements. Several subsurface site characterization examples including Gaussian, channelized, and fractured reservoirs are used to evaluate the accuracy and computational efficiency of the proposed method and the main features of the unknown permeability fields are characterized accurately with reliable uncertainty quantification. Furthermore, the estimation performance is compared with a widely-used variational, i.e., optimization-based, inversion approach, and the proposed approach outperforms the variational inversion method in several benchmark cases. We explain such superior performance by visualizing the objective function in the latent space: because of nonlinear and aggressive dimension reduction via generative modeling, the objective function surface becomes extremely complex while the ensemble approximation can smooth out the multi-modal surface during the minimization. This suggests that the ensemble-based approach works well over the variational approach when combined with deep generative models at the cost of forward model runs unless convergence-ensuring modifications are implemented in the variational inversion.

42 ENGINEERING↗

DOE OSTI2016

Iron loading effects in Fe/SSZ-13 NH3-SCR catalysts: nature of the Fe-ions and structure-function relationships

Using a traditional aqueous solution ion-exchange method under a protecting atmosphere of N2, a series of Fe/SSZ-13 catalysts with various Fe loadings were synthesized. UV-Vis, EPR and Mössbauer spectroscopies, coupled with temperature programmed reduction and desorption techniques, were used to probe the nature of the Fe sites. The major monomeric and dimeric Fe species are extra-framework [Fe(OH)2]+ and [HO-Fe-O-Fe-OH]2+. Larger oligomers with unknown nuclearity, poorly crystallized Fe2O3 particles, together with isolated Fe2+ ions, are minor Fe-containing moieties. Reaction rate and Fe loading correlations suggest that isolated Fe3+ ions are the active sites for standard SCR while the dimeric sites are the active centers for NO oxidation. NH3 oxidation, on the other hand, is catalyzed by sites with higher nuclearity. A low-temperature standard SCR reaction network is proposed that includes redox cycling of both monomeric and dimeric Fe species, for SCR and NO2 generation, respectively. The authors gratefully acknowledge the US Department of Energy (DOE), Energy Efficiency and Renewable Energy, Vehicle Technologies Program for the support of this work. The research described in this paper was performed at the Environmental Molecular Sciences Laboratory (EMSL), a national scientific user facility sponsored by the DOE’s Office of Biological and Environmental Research and located at Pacific Northwest National Laboratory (PNNL). PNNL is operated for the US DOE by Battelle.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2013

Structural and Spectroscopic Characterization of 17- and 18-Electron Piano-Stool Complexes of Chromium. Thermochemical Analyses of Weak Cr–H Bonds

The 17-electron radical CpCr(CO)2(IMe)• (IMe = 1,3-dimethylimidazol-2-ylidene) was synthesized by the reaction of IMe with [CpCr(CO)3]2, and characterized by single crystal X-ray diffraction and by EPR, IR and variable temperature 1H NMR spectroscopy. The metal-centered radical is monomeric under all conditions and exhibits Curie paramagnetic behavior in solution. An electrochemically reversible reduction to 18-electron CpCr(CO)2(IMe)- takes place at E½ = -1.89(1) V vs Cp2Fe+•/0 in MeCN, and was accomplished chemically with KC8 in THF. The salts K+(18-crown-6)[CpCr(CO)2(IMe)]- • ½THF and K+[CpCr(CO)2(IMe)]- • ¾THF were crystallographically characterized. Monomeric ion pairs are found in the former, whereas the latter has a polymeric structure due to a network of K∙∙∙O(CO) interactions. Protonation of K+(18-crown-6)[CpCr(CO)2(IMe)]- • ½THF gives the hydride CpCr(CO)2(IMe)H, which could not be isolated, but was characterized in solution; a pKa of 27.2(4) was determined in MeCN. A thermochemical analysis provides the Cr-H bond dissociation free energy (BDFE) for CpCr(CO)2(IMe)H in MeCN solution as 47.3(6) kcal mol-1. This value is exceptionally low for a transition metal hydride, and implies that the reaction 2 [Cr-H] → 2 [Cr•] + H2 is exergonic (ΔG = -9.0(8) kcal mol-1). This analysis explains the experimental observation that generated solutions of the hydride produce CpCr(CO)2(IMe)• (typically on the timescale of days). By contrast, CpCr(CO)2(PCy3)H has a higher Cr-H BDFE (52.9(4) kcal mol-1), is more stable with respect to H2 loss, and is isolable. We thank the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences and Biosciences for support. M.L.H. carried out the crystallographic studies and was supported as part of the Center for Molecular Electrocatalysis, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences. The EPR studies were performed at the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL), a national scientific user facility sponsored by the Department of Energy’s Office of Biological and Environmental Research located at PNNL. Pacific Northwest National Laboratory is a multiprogram national laboratory operated by Battelle for the U.S. Department of Energy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Deep Reinforcement Learning Based Volt-VAR Optimization in Smart Distribution Systems

This paper develops a model-free volt-VAR optimization (VVO) algorithm via multi-agent deep reinforcement learning (DRL) in unbalanced distribution systems. This method is novel since we cast the VVO problem in distribution networks to an intelligent deep Q-network (DQN) framework, which avoids solving a specific optimization model directly when facing time-varying operating conditions in the systems. We consider statuses/ratios of switchable capacitors, voltage regulators, and smart inverters installed at distributed generators as the action variables of the agents. A delicately designed reward function guides these agents to interact with the distribution system, in the direction of reinforcing voltage regulation and power loss reduction simultaneously. The forward-backward sweep method for radial three-phase distribution systems provides accurate power flow results within a few iterations to the DRL environment. The proposed method realizes the dual goals for VVO. We test this algorithm on the unbalanced IEEE 13-bus and 123-bus systems. Numerical simulations validate the excellent performance of this method in voltage regulation and power loss reduction.

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

DOE OSTI2020

In-Situ Uranium Source Treatment Performance Assessment Elements - 20247

Field-scale in situ injection of an aqueous polyphosphate amendment was conducted to decrease uranium leaching from a vadose zone source to groundwater near the Columbia River at the U.S. Department of Energy's Hanford Site. After an initial phase of application in November 2015, this treatment was applied as an enhanced attenuation approach in September 2018, targeting uranium in a subsurface zone where water table periodically rises in response to the seasonal high river stage. Uranium within this zone is aqueous, adsorbed, and in low- and high-solubility precipitates and is mobilized into the groundwater at high river stage, resulting in a persistent groundwater plume. The polyphosphate amendment creates phosphate coatings on uranium (potentially including low solubility uranium-phosphate precipitates) that decrease the uranium leached into groundwater when the zone is periodically rewetted to improve the ability of natural attenuation to meet groundwater concentration objectives. For treatment, the amendment was injected into a network of wells within the periodically rewetted source area. Multiple lines of evidence are being applied to evaluate the performance of the phosphate treatment. Three elements of this performance assessment include 1) identifying the distribution of injected phosphate amendment to the targeted treatment zone using cross-borehole electrical resistivity tomography and comparisons of phosphate precipitates between pre- and post-treatment samples, 2) demonstrating the functional reduction in uranium mobility and leachability using laboratory tests with pre- and post- treatment sediments from the source zone, and 3) evaluating the presence of low-solubility uranium phosphate minerals and/or coatings associated with reduced uranium mobility. (authors)

07 ISOTOPE AND RADIATION SOURCES↗