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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Efficient Reformulation of Linear and Nonlinear Solid-Phase Diffusion in Lithium-ion Battery Models using Symmetric Polynomials: Mass Conservation and Computational Efficiency

Lithium-ion batteries are typically modeled using porous electrode theory coupled with various transport and reaction mechanisms, along with suitable discretization or approximations for the solid-phase diffusion equation. The solid-phase diffusion equation represents the main computational burden for typical pseudo-2-dimensional (p2D) models since these equations in the pseudo r -dimension must be solved at each point in the computational grid. This substantially increases the complexity of the model as well as the computational time. Traditional approaches towards simplifying solid-phase diffusion possess certain significant limitations, especially in modeling emerging electrode materials which involve phase changes and variable diffusivities. A computationally efficient representation for solid-phase diffusion is discussed in this paper based on symmetric polynomials using Orthogonal Collocation and Galerkin formulation (weak form). A systematic approach is provided to increase the accuracy of the approximation (p form in finite element methods) to enable efficient simulation with a minimal number of semi-discretized equations, ensuring mass conservation even for non-linear diffusion problems involving variable diffusivities. These methods are then demonstrated by incorporation into the full p2D model, illustrating their advantages in simulating high C-rates and short-time dynamic operation of Lithium-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2021

A Spatiotemporal Prediction Model for Regional Scheduling of Shared Bicycles Based on the INLA Method

Dock-less bicycle-sharing programs have been widely accepted as an efficient mode to benefit health and reduce congestions. And modeling and prediction has always been a core proposition in the field of transportation. Most of the existing demand prediction models for shared bikes take regions as research objects; therefore, a POI-based method can be a beneficial complement to existing research, including zone-level, OD-level, and station-level techniques. Point of interest (POI) is the location description of spatial entities, which can reflect the cycling route characteristics for both commuting and noncommuting trips to a certain extent, and is also the main generating point and attraction point of shared-bike travel flow. In this study, we make an effort to model a POI-level cycling demand with a Bayesian hierarchical method. The proposed model combines the integrated nested Laplace approximation (INLA) and random partial differential equation (SPDE) to cope with the huge computation in the modeling process. In particular, we have adopted the dock-less bicycle-sharing rental records of Mobike as a case study to validate our method; the study area was one of the fastest growing urban districts in Shanghai in August 2016. The operation results show that the method can help better understand, measure, and characterize spatiotemporal patterns of bike-share ridership at the POI level and quantify the impact of the spatiotemporal effect on bicycle-sharing use.

Yu, Zhuoran↗
DOE OSTI2025

Tunturi virus isolates and metagenome-assembled viral genomes provide insights into the virome of Acidobacteriota in Arctic tundra soils

Arctic soils are climate-critical areas, where microorganisms play crucial roles in nutrient cycling processes. Acidobacteriota are phylogenetically and physiologically diverse bacteria that are abundant and active in Arctic tundra soils. Still, surprisingly little is known about acidobacterial viruses in general and those residing in the Arctic in particular. Here, we applied both culture-dependent and -independent methods to study the virome of Acidobacteriota in Arctic soils. Five virus isolates, Tunturi 1–5, were obtained from Arctic tundra soils, Kilpisjärvi, Finland (69°N), using Tunturiibacter spp. strains originating from the same area as hosts. The new virus isolates have tailed particles with podo- (Tunturi 1, 2, 3), sipho- (Tunturi 4), or myovirus-like (Tunturi 5) morphologies. The dsDNA genomes of the viral isolates are 63–98 kbp long, except Tunturi 5, which is a jumbo phage with a 309-kbp genome. Tunturi 1 and Tunturi 2 share 88% overall nucleotide identity, while the other three are not related to one another. For over half of the open reading frames in Tunturi genomes, no functions could be predicted. To further assess the Acidobacteriota-associated viral diversity in Kilpisjärvi soils, bulk metagenomes from the same soils were explored and a total of 1881 viral operational taxonomic units (vOTUs) were bioinformatically predicted. Almost all vOTUs (98%) were assigned to the class Caudoviricetes. For 125 vOTUs, including five (near-)complete ones, Acidobacteriota hosts were predicted. Acidobacteriota-linked vOTUs were abundant across sites, especially in fens. Terriglobia-associated proviruses were observed in Kilpisjärvi soils, being related to proviruses from distant soils and other biomes. Approximately genus- or higher-level similarities were found between the Tunturi viruses, Kilpisjärvi vOTUs, and other soil vOTUs, suggesting some shared groups of Acidobacteriota viruses across soils. This study provides acidobacterial virus isolates as laboratory models for future research and adds insights into the diversity of viral communities associated with Acidobacteriota in tundra soils. Predicted virus-host links and viral gene functions suggest various interactions between viruses and their host microorganisms. Largely unknown sequences in the isolates and metagenome-assembled viral genomes highlight a need for more extensive sampling of Arctic soils to better understand viral functions and contributions to ecosystem-wide cycling processes in the Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Idaho National Laboratory CY 2021 National Emission Standards for Hazardous Air Pollutants Analysis, Methodology and Results for Radionuclides

This report details calculations of potential dose at public receptor locations surrounding the Idaho National Laboratory (INL) Site boundary, and INL in-town facilities, from radionuclides reported to be in use and potentially emitted from INL facilities during calendar year (CY) 2021. All calculations were performed in accordance with the requirements in Code of Federal Regulations (CFR), Title 40, “Protection of the Environment,” Part 61, “National Emission Standards for Hazardous Air Pollutants (NESHAPs),” Subpart H, “National Emission Standards for Emissions of Radionuclides Other than Radon from Department of Energy Facilities” (40 CFR 61, Subpart H). Modeling methodology, model input parameters, and contribution to dose by facility, source, and radionuclide at the maximally exposed individual (MEI) location are also discussed. The information in this report supports the “National Emission Standards for Hazardous Air Pollutants - Calendar Year 2021 INL Report for Radionuclides” (INL 2022). In CY 2021, the estimated annual potential dose at the INL Site MEI location was 6.67E-02 mrem/yr, up slightly from the previous year, but far less than the regulatory standard of 10 mrem/yr (CFR 40 Part 61, Subpart H). Approximately 97% of the total dose to the INL Site MEI originated from MFC sources. Emissions from INL in-town facilities resulted in an estimated annual potential dose of 6.21E-03 mrem/yr to the MEI, down 40% from the CY 2020 estimated dose. Year-to-year variations in estimated annual dose can be attributed to adjustments in laboratory operations, changes to facility infrastructure, and variation in meteorological conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Differences In High Burnup Fuel Management Strategies to Minimize FFRD and Increase Economic Viability

The nuclear industry is pursuing approval of an increase in the length of the pressurized water reactor (PWR) cycle from 18 months to 24 months to reduce reactor downtime and enhance the economic competitiveness of nuclear energy. Such an increase in reactor cycle length will require that the maximum rod average burnup exceeds the current regulatory limit of 62 GWd/MTU, and it could peak at approximately 75 GWd/MTU, posing potential reactor safety and performance concerns. One such concern is that fuel fragmentation, relocation, and dispersal (FFRD) could occur during a severe loss-of coolant accident (LOCA) in which a fuel rod balloons and bursts, and pulverized fuel fragments are dispersed throughout the reactor’s primary coolant system. Previous analyses have identified which reactor operating conditions leave the core more susceptible to FFRD and have shown that FFRD susceptibility is strongly linked to fuel rod burnup and linear heat rate (LHR) history. The work described in this report uses an optimization strategy known as parallel simulated annealing (PSA) and a coarse mesh Purdue Advanced Reactor Core Simulator (PARCS) reactor physics model to develop two core fuel loading patterns, each with a different optimization objective. One core optimization maximized the core’s cycle length while still respecting regulatory limits on the radial peaking factor and soluble boron concentration with a peak rod average burnup of 75 GWd/MTU. The second optimization was aimed at minimizing FFRD susceptibility while still targeting a 24-month cycle length and respecting regulatory limits. PARCS model predictions were verified using the high-fidelity Virtual Environment for Reactor Applications (VERA). The two core designs were compared to highlight core design strategies to minimize FFRD susceptibility and to maximize economic viability.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Slow Strain Rate Testing of A537 Tank Wall Material

At Savannah River Site (SRS), High-Level Waste is stored in below-grade carbon steel tanks. This waste in part consists of sludge, salt cake, and/or supernate. Preparation of this waste for future processing involves dissolution of the salt cake layer. The salt dissolution process can create conditions that leave the carbon steel tanks susceptible to localized corrosion. The salt to be dissolved contains high concentrations of nitrate, that once released, create an environment that may be conducive to pitting corrosion and/or stress corrosion cracking (SCC) of carbon steel. The salt dissolution process also liberates interstitial liquid trapped between the salt crystals. This liquid is initially high in nitrite and hydroxide concentration. High pH and greater ratios of nitrite to nitrate act as inhibitors to minimize corrosion of carbon steel in high nitrate environments. However, as dissolution proceeds, the concentration of nitrate will increase, while the hydroxide and nitrite concentration of the interstitial liquid will deplete and become insufficient to prevent the onset of corrosion attack. Tank blending and the addition of inhibitors are used to ensure adequate concentrations of hydroxide and nitrite. However, this is not desirable during salt dissolution as it can reduce process efficiency and increase the amount of waste that needs processing. This testing program was designed to examine the risk of SCC associated with utilizing the pitting factor (PF) and nitrite/nitrate (NO 2 - /NO 3 - ) ratio limits for handling dissolved salt solutions at an elevated temperature in the carbon steel waste tanks. The previously identified limits are a PF of 1.2 and an NO 2 - /NO 3 - ratio of 0.15. The results indicate that as long as the NO 2 - /NO 3 - ratio exceeds 0.1 and the PF is above approximately 0.8, there is a discernible safety margin between the open circuit potential (OCP) and the critical cracking potential (CCP) observed during applied potential testing. However, this margin, defined by the difference between the OCP and CCP, is relatively narrow, ranging from 0.1 to 0.25 volts. This small margin raises concerns about potential shifts in OCP during waste retrieval operations, which could inadvertently increase the risk of SCC if the OCP approaches or exceeds the CCP. These results confirm that dissolved salt solutions provide a potent chemistry that, under certain conditions, makes carbon steel susceptible to SCC. The next question to consider is the influence these results have on decisions for storage and retrieval of waste from the tanks. For Type III/IIIA waste tanks, the risk of SCC remains very low. First, and most importantly, the post-weld stress relief of the tanks has reduced the residual stress near the welds. Thus, without the stress component, SCC risk is minimized. The material of construction (A537 Carbon steel) for the Type III/IIIA tanks is superior to the steel in its resistance to SCC than the steel that was utilized for the Type I, II, and IV tanks (A285 carbon steel). From a chemistry control standpoint for a Type III/IIIA tank directly involved with handling dissolved salt solutions, the PF and NO 2 - /NO 3 - ratio limits may be utilized wherein chemistry control provides an extra layer of defense against SCC. Chemistry control for a Type III/IIIA tank minimizes the risk for a tank that may receive the dissolved salt solution, particularly if that tank is a Type I, II, or IV waste tank. On the other hand, if the dissolved salt solution is handled by a Type I, II, or IV waste tank the risk of SCC is real. The potent chemistry, absence of stress relief, and inferior material result in a condition that is conducive to cracking. Efforts should be made to either avoid transferring waste that may not meet the PF and NO 2 - /NO 3 - ratio criteria to one of these tanks or if it is unavoidable, take measures to minimize the consequences of a leak. As shown by these tests, even if the PF and NO 2 - /NO 3 - ratio criteria are met, there is a risk that the tank potential may be disturbed in the positive direction and the risk of SCC increase.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

AIACHNE's contribution for Nuclear Energy Agency Working Party on International Nuclear Data Evaluation Co-operation Subgroup 50

The AIACHNE (AI/ML Informed cAlifornium CHi Nuclear data Experiment) project aims at designing an experiment for the 252 Cf Prompt Fission Neutron Spectrum (PFNS) that explores systematic biases in an experimental database retrieved from the EXFOR databases. To that end, machine learning (ML) methods were applied to pint-point measurement features likely related to bia. From that information, we selected a feature that should be explored by the AIACHNE experiment. Measurement features are metadata encapsulating all pertinent information about the physical measurement and analysis techniques. Examples are, for instance, what neutron and fission detectors were used for the physical metadata, and what background reduction techniques were employed for analysis techniques. Such metadata were retrieved both from EXFOR entries as well as the literature of data sets described in detail in Ref. [2]. The prerequisite for applying machine learning techniques is casting the metadata into a format that can be parsed by the algorithm. This step might seem trivial but requires to find a unique language where metadata that carry the same physics meaning across several experiments must have the same identifier. One example is, for instance, the neutron detector. As seen in Figure 1, the machine learning code identified the use of 6 Li detectors as being related to bias in some datasets of the AIACHNE 252 Cf PFNS experimental database. In fact, here are several experiments that used neutron detectors containing 6Li in the database, for instance for the example below. EXFOR format has a unique keywords describing detectors such as “SCIN” or “GLASD”. One may think that these keywords are already sufficient descriptors for ML to uniquely find an issue. However, “SCIN” (used for [3, 4]) and “GLASD” (used for [5]) fail to inform the algorithm what is the active material in the detector. And, the key common issue leading to bias in 252 Cf related to neutron detectors is not whether it is a glass detector or a scintillator. No, the issue is that 6 Li was within both detector types and that even small mistakes in the detector response functions around approximately 200 keV are amplified by the 6 Li(n,α) resonance there leading to bias in data as highlighted in Fig. 1 and Ref. [1]. Hence, the features describing the neutron detector must call out the active material in the detector, rather than the existing EXFOR detector keyword, that the ML algorithm can find physically meaningful features related to bias. The AIACHNE team used a precursor of the WPEC (Working Party on International Nuclear Data Evaluation Co-operation) SG(Subgroup)-50 format to store the metadata for the ML analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Bound-preserving finite element approximations of the Keller–Segel equations

We report this paper aims to develop numerical approximations of the Keller–Segel equations that mimic at the discrete level the lower bounds and the energy law of the continuous problem. We solve these equations for two unknowns: the organism (or cell) density, which is a positive variable, and the chemoattractant density, which is a non-negative variable. We propose two algorithms, which combine a stabilized finite element method and a semi-implicit time integration. The stabilization consists of a nonlinear artificial diffusion that employs a graph-Laplacian operator and a shock detector that localizes local extrema. As a result, both algorithms turn out to be nonlinear and can generate cell and chemoattractant numerical densities fulfilling lower bounds. However, the first algorithm requires a suitable constraint between the space and time discrete parameters, whereas the second one does not. We design the latter to attain a discrete energy law on acute meshes. We report some numerical experiments to validate the theoretical results on blowup and nonblowup phenomena. In the blowup setting, we identify a locking phenomenon that relates the L ∞ (Ω)-norm to the L 1 (Ω)-norm limiting the growth of the singularity when supported on a macroelement.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Investigation of main bearing operating conditions in a three-Point mount wind turbine drivetrain

Wear-related failures of spherical roller bearings in the main bearing position of three-point mount wind turbines have been higher than expected and can contribute to higher than anticipated operation-and-maintenance costs. In this paper, the operational conditions of such a main bearing—including measured axial displacement and velocity subject to the estimated axial loads—are described for an instrumented, commercial wind turbine. The field measurements suggest a maximum axial speed between the bearing rings that is less than 2 millimeters per second. It is estimated that the axial speed between the ring and rollers is approximately 25% of this value. When compared to a speed of rolling from approximately 200–352 millimeters per second, the measured axial sliding is therefore significantly less than 1% of the speed of rolling. Previous numerical studies of lubricant film formation in rolling contacts have shown that the effect of axial sliding starts to be noticeable only when this ratio exceeds 10%; therefore, the axial velocity represents only a small disturbance to the nominal pure rolling case, and the influence on oil film building can be neglected. A simple analytic model of the main bearing motion was also developed and demonstrated similar displacement and velocity characteristics.

17 WIND ENERGY↗
DOE OSTI2021

How much information on precipitation is contained in satellite infrared imagery?

Satellite infrared (IR) brightness temperature providing information on the characteristics of cloud tops is one of the primary input data used for estimating precipitation from satellites. Thus, the natural questions to ask are: Does IR imagery contain more information about precipitation in some regions more than others? What are the factors that lead to such differences? Should we expect the amount of information provided by IR imagery to change with respect to temporal or spatial aggregation? Comprehensive analysis of the accuracy of satellite-based precipitation estimates obtained from any given algorithm may provide qualitative answers to the above questions. However, such an approach only offers conclusions within the limited context of the algorithm used to obtain precipitation estimates; that is, patterns caused by the inherent information content of IR imagery are inextricable from those induced by assumptions embedded in the precipitation estimation algorithm. Here, we address the abovementioned questions from a different perspective using an information-theoretic measure, free of structural assumptions and general to a wide range of relationships, to characterize the average and seasonal dependence between IR imagery provided by satellite sensors in the spectral range (10.7–11.5 μm) and precipitation rates in the contiguous United States (CONUS) across distinct temporal and spatial scales. We analyze a total of more than 1.3 billion pairs of IR and precipitation observations over CONUS, and we observe interesting patterns. First, we show that there is a strong inverse relationship (ρ = - 0.73) between the information content of IR data and the number of no-rain observations; however, its robustness varies regionally and seasonally with less significant correlation during the warm season. Second, we demonstrate that the intuitive relationship of increasing dependence between IR and precipitation as a result of temporal or spatial aggregation exhibits a diminishing returns behavior. For instance, temporal aggregation from 1 to 3 h increases the dependence approximately 7 times as much as temporal aggregation from 12 to 24 h. Furthermore, we quantitatively examine and re-confirm several statements previously reported in the literature such as the strong association between IR and precipitation in convective storms and the low association in orographic rainfall. Finally, we conclude by illustrating the potential of the analysis in diagnosis of operational algorithms for estimating precipitation from IR brightness temperature. The findings of this study pinpoint spatial domains and time scales at which IR is not an adequate proxy for estimating precipitation. Thus, they can potentially guide the development of operational algorithms that utilize satellite Infrared imagery for estimating, downscaling and data fusion of precipitation. Finally, the analysis presented here opens up the possibility of developing new methodologies for diagnosis of satellite-based precipitation estimation algorithms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Revised monthly energy generation estimates for 1,500 hydroelectric power plants in the United States

Abstract The U.S. Energy Information Administration (EIA) conducts a regular survey (form EIA-923) to collect annual and monthly net generation for more than ten thousand U.S. power plants. Approximately 90% of the ~1,500 hydroelectric plants included in this data release are surveyed at annual resolution only and thus lack actual observations of monthly generation. For each of these plants, EIA imputes monthly generation values using the combined monthly generating pattern of other hydropower plants within the corresponding census division. The imputation method neglects local hydrology and reservoir operations, rendering the monthly data unsuitable for various research applications. Here we present an alternative approach to disaggregate each unobserved plant’s reported annual generation using proxies of monthly generation—namely historical monthly reservoir releases and average river discharge rates recorded downstream of each dam. Evaluation of the new dataset demonstrates substantial and robust improvement over the current imputation method, particularly if reservoir release data are available. The new dataset—named RectifHyd—provides an alternative to EIA-923 for U.S. scale, plant-level, monthly hydropower net generation (2001–2020). RectifHyd may be used to support power system studies or analyze within-year hydropower generation behavior at various spatial scales.

13 HYDRO ENERGY↗
DOE OSTI2023

Glueballs at physical pion mass

Glueballs are investigated through gluonic operators on two $ N_f=2+1 $ RBC/UKQCD gauge ensembles at the physical pion mass. The statistical errors of glueball correlation functions are considerably reduced through the cluster decomposition error reduction (CDER) method. The Bethe-Salpeter wave functions are obtained for the scalar, tensor, and pseudoscalar glueballs by using spatially extended glueball operators defined through the gauge potential $ A_\mu(x) $ in the Coulomb gauge. These wave functions exhibit similar features of non-relativistic two-gluon systems and are used to optimize the signals of the related correlation functions at the early time regions, where the ground state masses are extracted. These masses are close to those from the quenched approximation and indicate the possible existence of glueballs at the physical point. The resonance feature of glueballs and the mixing with conventional mesons and multi-hadron systems should be considered in a more systematic lattice study.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Quantum mereology: Factorizing Hilbert space into subsystems with quasiclassical dynamics

We study the question of how to decompose Hilbert space into a preferred tensor-product factorization without any preexisting structure other than a Hamiltonian operator, in particular the case of a bipartite decomposition into “system” and “environment.” Such a decomposition can be defined by looking for subsystems that exhibit quasiclassical behavior. The correct decomposition is one in which pointer states of the system are relatively robust against environmental monitoring (their entanglement with the environment does not continually and dramatically increase) and remain localized around approximately classical trajectories. We present an in-principle algorithm for finding such a decomposition by minimizing a combination of entanglement growth and internal spreading of the system. Both of these properties are related to locality in different ways. Furthermore, this formalism is relevant to questions in the foundations of quantum mechanics and the emergence of spacetime from quantum entanglement.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Dispersive optical systems for scalable Raman driving of hyperfine qubits

Hyperfine atomic states are among the most promising candidates for qubit encoding in quantum information processing. In atomic systems, hyperfine transitions are typically driven through a two-photon Raman process by a laser field which is amplitude modulated at the hyperfine qubit frequency. Here we introduce a method for generating amplitude modulation by phase modulating a laser and reflecting it from a highly dispersive optical element known as a chirped Bragg grating. This approach is passively stable, offers high efficiency, and is compatible with high-power laser sources, enabling large Rabi frequencies and improved quantum coherence. We benchmark this approach by globally driving an array of approximately 300 neutral 87 Rb atomic qubits trapped in optical tweezers and obtain Rabi frequencies of 2 MHz with photon-scattering error rates of less than 2×10 -4 per π pulse. This robust approach can be directly integrated with local addressing optics in both neutral atom and trapped ion systems to facilitate high-fidelity single-qubit operations for quantum information processing.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Lifetime of Almost Strong Edge-Mode Operators in One-Dimensional, Interacting, Symmetry Protected Topological Phases

Almost strong edge-mode operators arising at the boundaries of certain interacting one-dimensional symmetry protected topological phases with Z 2 symmetry have infinite temperature lifetimes that are nonperturbatively long in the integrability breaking terms, making them promising as bits for quantum information processing. We extract the lifetime of these edge-mode operators for small system sizes as well as in the thermodynamic limit. For the latter, a Lanczos scheme is employed to map the operator dynamics to a one-dimensional tight-binding model of a single particle in Krylov space. We suggest this model to be that of a spatially inhomogeneous Su-Schrieffer-Heeger model with a hopping amplitude that increases away from the boundary, and a dimerization that decreases away from the boundary. We associate this dimerized or staggered structure with the existence of the almost strong mode. Thus, the short time dynamics of the almost strong mode is that of the edge mode of the Su-Schrieffer-Heeger model, while the long time dynamics involves decay due to tunneling out of that mode, followed by chaotic operator spreading. Furthermore, we show that competing scattering processes can lead to interference effects that can significantly enhance the lifetime.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Sphynx

Sphynx is a software library for parallel graph partitioning and load balancing. It partitions a set of vertices in a graph such that the vertex parts are balanced, and the edge cut is approximately minimized. The primary use case is to partition a computational graph into smaller tasks that can be assigned to processors (cores) for efficient parallel computing. Sphynx is based on the Trilinos scientific computing toolkit so can run on both multi-CPU and multi-GPU systems. SAND2020-12183 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Boman, Erik↗
DOE OSTI2026

Beam Performance of the Positron Transport Line for CEBAF Positron Upgrade

The Low Energy Recirculator Facility (LERF) at Jefferson Lab, formerly operated for the Free-Electron Laser program, has been proposed as the injector complex for the planned 12 GeV CEBAF positron upgrade (Ce+BAF), with an additional pathway to support a potential 22 GeV CEBAF electron upgrade. In this configuration, LERF would generate and pre-accelerate positrons to 123 MeV, matching the present injection energy into the North Linac. Due to the relatively large emittance expected from the positron source, a comprehensive acceptance study has been performed from LERF through the CEBAF recirculating linacs and beam transport lines to the experimental halls. The objective is to establish the positron phase-space acceptance and provide design feedback to the positron production and capture systems. Furthermore, given CEBAF’s capability to deliver highly polarized beams, spin-tracking simulations have been carried out including magnet imperfections, alignment errors, and synchrotron-radiation–induced energy spread. Particular attention is given to the evolution of the spin tune and the corresponding depolarization mechanisms along the beam delivery path, especially for providing longitudinal polarization at the experimental halls. These results inform injector design choices and assess the overall feasibility of delivering high-polarization positron beams in CEBAF.

Ogur, S. [Thomas Jefferson National Accelerator Fa↗
DOE OSTI2021

Flue Gas Desulfurization (FGD) Wastewater Treatment Using Polybenzimidazole (PBI) Hollow Fiber (HF) Membranes

Polybenzimidazole (PBI) hollow fiber membranes were used to treat flue gas desulfurization (FGD) wastewater (WW) from a coal fired power plant. Membranes were tested using both single salt solutions and real FGD WW. The PBI membranes showed >99% rejection for single salt solutions of NaCl, MgCl2, CaSO4, and CaCl2 at approximately 2000 PPM (parts per million). The membranes also showed >97% rejection for FGD WW concentrations ranging from 6900 to 14,400 PPM total dissolved solids (TDS). The pH of the FGD WW was adjusted between 3.97–8.20, and there was an optimal pH between 5.31 and 7.80 where %rejection reached a maximum of >99%. The membranes were able to operate stably up to 50 °C, nearly doubling the water flux as compared to room temperature, and while maintaining >98% salt rejection.

activation energy↗