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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2022

Real-time Multi-granular Analytics Framework for HIT Systems

Streaming analytics is the process of ingesting and digesting live data from multiple data sources. In the healthcare domain, as the importance of extracting immediate insights while data are streaming into the system grows, the focus is shifting from batch processing to streaming analytics. With data increasing dramatically at high speeds, many informatics designs have been proposed to adapt healthcare domain into this new environment. In our previous work, we introduced a prototype of health informatics technology (HIT) framework that aims to address challenges in adopting state-of-the-art technologies to enable advanced healthcare analytic tasks in new streaming environments. We recently made major updates to the framework so that anomaly from multiple streaming data sources at different granularity levels can be detected in near real-time. In this paper, we detail the implementation and deployment of the framework in Kubernetes clusters and report its performances when tested on electronic health record (EHR) data of Veterans Affairs.

Park, Byung↗
DOE OSTI2024

Designing and prototyping extensions to the Message Passing Interface in MPICH

As HPC system architectures and the applications running on them continue to evolve, the MPI standard itself must evolve. The trend in current and future HPC systems toward powerful nodes with multiple CPU cores and multiple GPU accelerators makes efficient support for hybrid programming critical for applications to achieve high performance. However, the support for hybrid programming in the MPI standard has not kept up with recent trends. The MPICH implementation of MPI provides a platform for implementing and experimenting with new proposals and extensions to fill this gap and to gain valuable experience and feedback before the MPI Forum can consider them for standardization. Here, in this work, we detail six extensions implemented in MPICH to increase MPI interoperability with other runtimes, with a specific focus on heterogeneous architectures. First, the extension to MPI generalized requests lets applications integrate asynchronous tasks into MPI’s progress engine. Second, the iovec extension to datatypes lets applications use MPI datatypes as a general-purpose data layout API beyond just MPI communications. Third, a new MPI object, MPIX_Stream, can be used by applications to identify execution contexts beyond MPI processes, including threads and GPU streams. MPIX stream communicators can be created to make existing MPI functions thread-aware and GPU-aware, thus providing applications with explicit ways to achieve higher performance. Fourth, MPIX Streams are extended to support the enqueue semantics for offloading MPI communications onto a GPU stream context. Fifth, thread communicators allow MPI communicators to be constructed with individual threads, thus providing a new level of interoperability between MPI and on-node runtimes such as OpenMP. Lastly, we present an extension to invoke MPI progress, which lets users spawn progress threads with fine-grained control to adapt the communication performance to their application designs. We describe the design and implementation of these extensions, provide usage examples, and highlight their expected benefits with performance results.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

CONUS-wide Projected Flood Frequency and Uncertainty Estimates, Version 1.0

This dataset presents a large-ensemble of CONUS-wide projected flood frequency and uncertainty estimates across ~2.7 million NHDPlusV2 river reaches over the CONUS. The framework producing this dataset leverages a multi-model, uncertainty-aware modeling framework that allows evaluating shifts in flood frequences at the stream reach level across the CONUS. CONUS-wide ensemble streamflow projections generated from hydrologic simulations driven by downscaled and bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6) outputs are used to derive these flood frequency and uncertainty estimates over the period 1980 - 2099. A spatially consistent regional L-moment algorithm is applied across clusters defined by the US Hydrologic Unit Code Subregions (HUC4s and HUC8s) and NHDPlusV2 stream orders to estimate flood frequencies. The dataset also includes at-site based flood estimates that allow for the comparison between local and regional approach-based estimates, assess projected changes, and characterize their uncertainties. For more reliable estimation of rare flood frequencies such as 500 and 1000-year return periods, super-ensemble based estimates are also included in the dataset. This dataset is derived to support the "Impact-Informed Dam Safety Risk Assessment for Securing Hydropower Assests" project for the US Department of Energy (DOE) Hydropower and Hydrokinetic Office (H2O). For further details, refer to Kao et al. (2022), Ghimire et al. (2023), Ghimire et al. (2025), and Hosking and Wallis (1997).

Ghimire, Ganesh [ORNL] (ORCID:0000000242843941)↗
DOE OSTI2022

Riparian vegetation composition and diversity shows resilience following cessation of livestock grazing in northeastern Oregon, USA

Riparian ecosystem restoration has been accomplished through exclusion of livestock using corridor fencing along hundreds of kilometers of streams in the western United States, for the benefit of riparian-obligate wildlife and endangered fishes. Yet, there are limited scientific studies that have evaluated more than short-term shifts in vegetation composition and diversity at a single location or handful of locations following grazing. We sampled riparian vegetation composition along 11-paired grazed and ungrazed (exclosed) stream reaches in northeastern Oregon. Exclosure ages ranged from 2 to >30 years and grazing treatments varied from light grazing every one out of three years to heavy season-long grazing. Species richness and diversity was higher in the ungrazed reaches (p = 0.002). The abundance of native sedges ( Carex spp.) and broad-leaved forbs were also significantly (p ≤ 0.05) greater in ungrazed areas. In contrast, exotic species adapted to grazing such as Poa pratensis and Trifolium repens were more abundant in grazed stream reaches. The prevalence of hydrophytic species significantly increased (p ≤ 0.01) in ungrazed reaches, (based on wetland species indicator scores), indicating that wetland-dominated communities within the ungrazed stream reaches were replacing ones adapted to drier environments. The increased abundance of facultative and wetland-obligate species in ungrazed reaches compared to grazed reaches suggests that livestock grazing exacerbates those climate change effects also leading to warmer and drier conditions. Further, riparian-obligate shrub cover along the streambank was higher in 7 of 8 exclosures that were older than 5 years (p = 0.05). As a restoration approach, the inherent resilience of riparian ecosystems exhibited in ungrazed riparian zones suggest positive feedbacks to other beneficial ecosystem processes such as increased species and habitat diversity, increased carbon sequestration, enhanced allochthonous inputs and greater sediment retention, that would affect the aquatic and terrestrial biota, water quality, and stream morphology.

Kauffman, J. Boone (ORCID:0000000290202815)↗
DOE OSTI2021

Cryogenic Carbon Capture™ (CCC) Status Report

The Cryogenic Carbon Capture™ (CCC) process separates CO2 from light gases in essentially any continuous process. CCC cools the gases to the frost or desublimation point of CO2 (-100 to -135 °C), separates and pressurizes the solids, and warms all streams to produce a CO2-depleted stream at ambient pressure and a pure (99+%) pressurized liquid CO2 stream typically to about 150 bar, both at ambient temperature. The process also recovers all gas moisture and most gas impurities less volatile than CO2 (NOx, SOx, Hg, PM, UHC, CCC, etc.) in separable streams. CCC nearly eliminates refrigeration energy for sensible temperature changes through heat integration. CCC does require energy to change the CO2 phase from a mixed vapor to a pressurized fluid, which represents the minimum energy required of any process for this separation. CCC uses additional energy for turbomachinery inefficiencies, heat losses, moisture removal and overall process pressure drop. Aside from these real-world energy demands, CCC operates near the minimum energy required to perform this gas separation by minimizing stream recycling. CCC compresses CO2 as a liquid, which is one of several reasons it costs about about half as much and consumes about half as much energy as an amine process when using flue gases with about 15% CO2. The process also has several major additional advantages, including (a) it is a bolt-on retrofit technology that does not need steam or any modification of existing equipment, (b) it recovers water and nearly all pollutants in addition to CO2 from the flue gas, (c) it enables highly efficient and cost effective energy storage at grid scale and on time scales of minutes, (d) it enables NG storage if the energy storage option is used, and (d) it has a small footprint and is minimally disruptive to existing plants, requiring only electrical power and a gas source to operate. Sustainable Energy Solutions (SES) has scaled this technology through several levels, the largest of which captures nominally 1 tonne of CO2/day and is called the skid system. Skid system field tests include utility-scale power plants, cement plants, heating plants, and other utility or industrial sites that burn natural gas, biomass, coal, shredded tires, municipal waste, and combinations of these fuels. These field tests produced 95-99% CO2 capture with CO2 purities of 99+% and initial CO2 contents that range from 4 to 28%. SES currently seeks to scale the system to merchant scale (10-80 tonnes of CO2 per day). In the process of doing so, SES has demonstrated the potential for CCC to contribute to energy storage and direct air capture in innovative and cost-effective ways. This presentation discusses the overall process and highlights results from field and in-house tests. These include (a) measured CO2 capture rates and operating conditions from in-house and field tests, and (b) predicted utility-scale costs and energy demands. This discussion also includes the application of the CCC technology to energy storage and direct air capture.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

Encryption of Signal Pulses to Replace Tamper-indicating Conduit

In order to verify signal integrity and point of origin for TTL pulse data used in IAEA systems, and to avoid the need for expensive tamper-indicating conduit or electronic techniques, we propose the development of a signal pulse signing and encryption in-line device. In measurement applications in which the data acquisition electronics is separate from the enclosed, sealed detector, tamper-indicating techniques are required to protect raw TTL pulse streams between the detector and the data acquisition module, i.e UMSR. The goal of this proposed project is to design a rad-tolerant transmitter that would mount inside the sealed detector system and a receiver in the sealed electronics cabinet with the data acquisition instrument. This transmitter/receiver pair would digitally sign and encrypt the pulse stream data at the detector then transmit the data to the sealed cabinet where the receiver would decrypt the data and reproduce the original pulse stream. Existing tamper indicating techniques, such as LiveWire’s spread spectrum time domain reflectometry rely on detecting physical changes to the wiring system and can be blind to fast coupling of micro-second wide pulses. Digital signing and encryption techniques such as the Sandia Laboratories Enhanced Data Authentication System (EDAS) are capable of encrypting communications data, i.e. RS-232, but are not capable reproducing a critical time correlated data streams. Recent NA-241 Safeguards Technology supported developments have reduced the need for special conduit to transmit data via Ethernet by incorporating the IAEA RAINSTORM data encryption and authentication protocol, a tamper indicator is still required to protect raw pulse data from detectors to the acquisition electronics. Encrypting pulse data is especially complicated for radiation detection instruments due to the time correlation data analysis that is performed on this data stream. Any corruption in the timing information will produce errors in measurement values.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Removal of High Specific Activity Fission Products from Uranyl Sulfate Waste Solutions

The Savannah River National Laboratory (SRNL) is currently providing support to SHINE Medical Technologies (SHINE) which plans to deploy a low energy, accelerator-based neutron source to fission low enriched U in a uranyl sulfate target solution for 99 Mo production. The 99 Mo is initially separated from the fission products and target solution by an extraction column. Subsequent washing of the column will generate waste solutions containing residual U and fission product activity. A small number of high specific activity fission products (e.g., 90 Sr, 137 Cs, and 144 Ce) in these streams will likely control the classification of the low level waste (LLW). If a sufficient amount of the high specific activity isotopes are separated from the SHINE waste streams and concentrated into a waste form, it would be possible to treat a majority of the wash solutions from the column operations as a lower class of LLW (Class A versus Class B or C or Class B versus Class C). The high specific activity fission product elements could then be dispositioned as a much smaller volume of waste rather than requiring the disposal of the entire waste stream at the higher waste classification. The Savannah River Site (SRS) has experience with using monosodium titanate (MST) and crystalline silicotitanate (CST) to remove Cs and Sr from high salt content waste solutions generated during the reprocessing of nuclear fuels and targets. Both of these materials have worked very well for their intended purposes at the SRS where the fission product elements are removed from highly alkaline waste. On the other hand, SHINE waste streams from the extraction column contain H 2 SO 4 which makes the solution acidic. Additionally, the SRS waste streams do not contain other fission product elements such as transition metals or lanthanides because they precipitate upon neutralization of the SRS waste and are not present in the supernate which is dispositioned as LLW following treatment. As such, there are inherent differences between SHINE and SRS waste treatment strategies. Savannah River National Laboratory was tasked with performing scoping studies to see if MST and CST would remove Sr, Cs, and Ce from an acidic mixed metal simulant solution. Batch contact experiments were performed using MST and two CST type materials. The MST material is a 15 wt % powder in 0.15 M NaOH slurry. The MST showed low adsorption for elements of interest from acidic solution. Furthermore, the powder size makes MST non-ideal for column operations. A CST IE-911 ion exchange material had high Cs adsorption, moderate Sr, and marginal Ce adsorption. Based on adsorption of all species, the ion exchange capacity was found to be 0.032 meq/mL. A bench-top column experiment to measure elemental breakthrough curves was performed using CST IE-911 where chromatographic separations of the mixed simulant were expected to occur. While most elements behaved as expected, the lanthanide series, containing Ce, broke though the column earlier than expected. The second CST material, CST R9120, displayed high adsorption for all elements in the acidic mixed simulant solutions in a batch contact study, and had a calculated loading capacity of 0.091 meq/mL. Future studies to develop a waste treatment flowsheet should focus on CST R9120 to treat SHINE waste solutions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

NH 4 OH Looping with Membrane CO 2 Absorber and Distributed Stripper for Enhanced Algae Growth

The University of Kentucky Center for Applied Energy (UK CAER) has devised a unique, integrated CO2 capture and utilization technology. CO2 from coal-fired power generation flue gas is first captured at half the operating cost of a typical aqueous CO2 capture system (CCS), distributed in an aqueous stream and then fixed by algae in bioreactors where the algae production is increased by 50% over that with a typical intermittent nutrient feeding system. Lower CCS operating cost is achieved by eliminating the flue gas pretreatment step for cooling and SO2 removal, eliminating steam extraction from the power generation steam cycle for solvent regeneration, and eliminating CO2 compression. Higher algae production is achieved by continuous, just-in-time nutrient feed to the bioreactors directly from a distributed solvent regenerator, which maintains the bioreactor pH for optimum growth. The process starts with a uniquely configured membrane absorber, where the flue gas is indirectly contacted with an ammonium hydroxide (NH4OH) solvent. Dissolved NH3 is attractive for both CO2 capture and as an algae nutrient. For CO2 capture it is inexpensive, has a low regeneration energy, is thermally- and oxidatively-stable and has a viscosity near that of water, which makes is easy to transport. Numerous studies have shown that the scrubbing capacity of NH3 is approximately 0.9-1.2 kg of CO2/kg of NH3, with a CO2 removal efficiency of ~99% and half the solvent regeneration energy than that of 30 wt% MEA[1, 2, 3]. NH3 is attractive as an algae nutrient due to its low cost. The rich NH4OH solvent is pumped to a set of distributed regenerators which are co-located with the algae bioreactors. Solvent pumping, transport and distribution reduces the balance of plant (BOP) cost compared to a typical aqueous CCS related to the flue gas duct and boost fan required to transport the flue gas. The energy required for the distributed solvent regeneration is supplied by solar-thermal panels eliminating the need for steam extraction from the power generation steam cycle. After solvent regeneration, the product stream contains both the CO2 captured from the flue gas and volatized NH3 from the solvent. This product stream is fed directly to the bioreactors, eliminating the need for compression of the CO2 stream. The relative amounts of CO2 and NH3 in the product stream are adjusted and controlled by a controlling the regeneration conditions (pressure and temperature). The continuous feed of the right ratio of nutrients overcomes the typical inhibition of algae growth resulting from frequent pH swings in the bioreactor due to unbalanced (intermittent) feeding systems for CO2 and N. Also, because the regenerators will operate at pressure and be located in close proximity to the bioreactors, there is no worry about pressure drop when sparging the gas into the algae. Sparging produces small bubbles which is beneficial for mass transfer efficiency. One known challenge when using an NH4OH solvent is high NH3 emission. Hydrophobic membranes are used for CO2 capture using an aqueous NH3 solution[4, 5] without the direct contact between flue gas and aqueous solution. Additionally, UK CAER CO2 capture and utilization process manages NH3 slip in three extra measures. First, NH3 slip is minimized by working with minimal species partial pressure, which is proportional to the concentration in the liquid. Hence, lowering the capture solvent concentration will lower the NH3 partial pressure. Second, UK CAER’s previous work has demonstrated that the addition of Zn2+ into NH3 solutions to chelate the NH3 can reduce NH3 volatility. Third, the configuration of the membrane CO2 absorber utilizes condensed water from the flue gas to continually wash the gas-side of the membrane to reduce fouling and recapture NH3 slip. Additional details about the UK CAER unique, integrated CO2 capture and utilization technology will be presented along with technology development plans. Diao, N., Q. Li, and Z. Fang. 2004. Heat transfer in ground heat exchangers with groundwater advection. International Journal of Thermal Sciences. 43: 1203-1211, He, Q., M. Chen, L. Meng, K. Liu, and W. Pan. 2004. Study on Carbon Dioxide Removal from Flue Gas by Absorption of Aqueous Ammonia. Western Kentucky University. Yeh, A.C., and H. Bai. 1999. Comparison of ammonia and monoethanolamine solvents to reduce CO2 greenhouse gas emissions. The Science of the Total Environment. 228: 121-133, Villeneuve, K., D. Roizard, J.C. Remigy, M. Iacono, and S. Rode. 2018. CO2 capture by aqueous ammonia with hollow fiber membrane contactors: Gas phase reactions and performance stability. Separation and Purification Technology, 199: 189-197, Toro Molina, C., and C. Bouallou. 2016. Carbon dioxide absorption by ammonia intensified with membrane contactors. Clean Techn Environ Policy 18, 2133–2146 (2016)

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

An Evaluation of the Impact of Glycolate and Glycolate Mitigation on the Defense Waste Processing Facility Recycle Diversion Project Flowsheet

The Savannah River Site (SRS) Defense Waste Processing Facility (DWPF) processes radioactive High Level Waste (HLW) sludge solids from the Concentration, Storage, and Transfer Facilities (CSTF); which includes the SRS Tank Farm and Evaporator facilities, and a concentrated Cs-137 laden stream and a Monosodium Titanate (MST) and sludge solids stream from the SRS Salt Waste Processing Facility (SWPF). The waste is chemically adjusted with acids and reductant (currently with 50 wt.% nitric acid and ~90 wt.% formic acid, but eventually formic acid will be substituted with ~70 wt.% glycolic acid), and frit is added so that a durable, borosilicate glass waste form can be produced when the material is vitrified in the melter. As a result of the evaporation of water during both the melter feed preparation and the melter feed vitrification steps in DWPF, a recycle waste stream is generated, neutralized, and sent back to the CSTF. The recycle waste is a dilute aqueous stream originating from the collection of condensate liquids containing some minor sludge, MST, and frit solids and other waste components resulting from melter feed entrainment during foamover events and transfer of volatile species into the condensate. The recycle stream volume is significant and is expected to approach 3 million gallons per year once SWPF reaches full operation, requiring the use of multiple large CSTF tanks for storage. The recycle waste is currently collected in the SRS Tank Farm and periodically evaporated in the 242-16H (2H) Evaporator to conserve storage space.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Initial Assessment of TeF 6 Adsorption

Research and development that supports the management of off-gases from nuclear fuel reprocessing has historically been focused on the off-gas streams that arise from aqueous reprocessing technology. However, as Gen-IV reactor development pathways move toward deployment, alternative spent nuclear fuel (SNF) processing and disposition pathways have been considered more actively. This work is focused upon aspects of fluoride volatility (FV) processing. The versatility of this method for deployment against multiple types of spent fuel encourages the continued advancement of both the primary separations processes and the secondary processes, including waste treatment, material control and accountability, and engineering designs. Recent work noted that TeF 6 , the most highly volatile fluorinated compound produced during FV processing, did not have a clear abatement technology recommended in the literature. Thus, this work performed scoping tests on activated alumina and copper shot to assess whether they could be used to remove TeF 6 from gas streams that bear F 2 . Previous work on this topic was not well described in the literature and was not performed with excess F 2 in the stream as would be typical of spent fuel processing via FV. To support an understanding of the concentration of TeF 6 contacting the adsorbent beds, a series of preliminary testing identified the TeF 6 production rate and the equilibrium concentration of TeF 6 in the gas stream contacting the adsorbent. Excess F 2 was determined to not affect the ability of activated alumina to remove TeF 6 from the gas stream quickly and completely. A determination of whether excess F 2 affected the distribution depth of Te in the sorbent bed is still pending analysis of the used sorbent. Literature suggests that when activated alumina is near saturation, TeF 6 could migrate from the sorbent bed. Future testing should investigate this possibility. Copper metal did not adsorb TeF 6 in the presence of F 2 across the sorbent temperature range of 50 to 335°C. F 2 was fully removed by the copper bed. Although preliminary thermodynamics would indicate adsorption to be energetically favorable, other factors that impact adsorption (e.g., slow kinetics, excess fluorine on the copper surface, an unfavorable transition state) are likely preventing the adsorption of TeF 6 at an easily measurable rate. The work also investigated TeF 6 production from multiple forms of Te in the temperature range of 100 to 250°C. No previous study had assessed the initial reaction rates for this process. A carefully designed study allowed determination of the activation energy for the production of TeF 6 from Te metal. The substantial amount of data collected during this study merits analysis beyond what is described here. A more in-depth kinetic analysis will be pursued. Additional analytical results will provide the ability to benchmark adsorption coefficients for TeF 6 , understand the distribution of TeF 6 within the alumina bed, and better understand the effect of F 2 partial pressure on Te fluorination. The data from this report, as supplemented by these additional analyses, will be submitted to a peer-reviewed journal.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

FY2020 Rotating Bed Reactor for Iodine Removal from WTP Melter Effluent to Support DFLAW Start-Up

In Performance Assessment (PA) of the Hanford Integrated Disposal Facility (IDF), 129 I is a significant contributor to the risk. The 2017 IDF PA accounted for 0.22% of the total 129 I inventory in Hanford tank waste as residing in the solidified liquid waste from the Effluent Treatment Facility (ETF). However, recent estimates suggest that higher percentages of the iodine processed at the Hanford Waste Treatment and Immobilization Plant (WTP) may be present in the liquid waste routed to the Liquid Effluent Retention Facility (LERF) for eventual treatment at the ETF. In addition, a recent integrated melter test performed at the Vitreous State Laboratory (VSL) at The Catholic University of America (CUA) showed the possibility that a significant fraction (>50%) of the total iodine in the melter feed could be present in the aqueous waste stream destined for the ETF. This stream represents a combination of the Effluent Management Facility (EMF) evaporator overhead condensate and the liquid waste from the WTP off-gas caustic scrubber. Higher levels of 129 I in this stream could affect the LERF and ETF Hazard Categorizations as well as the acceptability of the solidified ETF liquid secondary waste brine for disposal at the IDF. Accordingly, there is a need to investigate and develop potential methods and processes to mitigate this risk. Washington River Protection Solutions, LLC (WRPS) tasked Atkins and VSL to perform development and testing work to evaluate potential methods for removal of iodine species from the waste stream routed to the LERF. In particular, the testing investigated the use of an Atkins-SpinIonic™ Rotating Bed Reactor (RBR) system as a potential alternative to conventional column-based ion exchange or absorption processes. The present report provides results obtained from testing with an RBR system for the removal of iodine from simulants of the projected WTP waste stream that discharges to the LERF.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Technical Assessment of Off-Gas System Technologies for Potential Use in Molten Salt Reactors

Molten salt reactors (MSRs) are a class of Generation IV advanced reactor technologies aimed to enhance and improve the safety, fuel utilization and cost-effectiveness of nuclear power generation. MSR concepts are based on using a molten salt mixture as a primary nuclear reactor coolant, while the fuel can be either directly dissolved in the coolant (i.e., fluid-fueled) or can be in a separate solid form (i.e., salt-cooled solid-fueled). MSRs can be operated in either thermal or fast neutron spectra, as simple fissile convertors, or breeder reactors (e.g., utilizing both fissile and fertile fuels), as well as accelerator-driven sub-critical reactors or transuranic element burners. Operation of MSRs will necessitate management and treatment of the off-gas streams released to the headspace of the reactor where, in some designs, a cover gas can be circulated to remove certain fission products and maintain an inert atmosphere. An inert MSR cover gas swept over or sparged into the salt will confine radionuclides emerging from the free surface, including radioactive noble and non-noble gases, aerosols, and volatile species. The elements and compounds of these species will have a wide range of thermochemical and physical properties, some of which will decay to different products in the off-gas stream. Therefore, system components used to manage and treat MSR off-gas streams will need to be robust under dynamic reactor and chemistry conditions to support adequate reactor performance by managing the composition and species in the salt coolant and cover gas space. Off-gas system components would perform as a radionuclide boundary to the reactor vessel and a primary means for preventing radionuclide release; therefore, they are of high safety significance for MSR operations. This report reviews various technologies and materials for potential implementation in the design of an MSR off-gas system per a general conceptual framework. The reviewed technologies operate based on scrubbing, capture, delay, or separation of species in the off-gas stream. These include molten hydroxide scrubbers, solid sorbents, delay off-gas systems, particle traps, and cryogenic distillation. Since aspects of an off-gas system will be design-specific, the approach is to provide general discussions on attributes of these technologies and materials, including target off-gas stream species, operational parameters and conditions of importance to decontamination factors, implementation maturity, system component monitoring, potential off-normal conditions and considerations for waste products. The information aims to support the U.S. Nuclear Regulatory Commission in their safety evaluations for MSR designs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

National Energy Water Treatment & Speciation (NEWTS): A Water & Critical Mineral Database and Dashboard

The scarcity of water resources, the need for beneficial water reuse, and the challenges of wastewater treatment are becoming increasingly pressing in economic, social, and environmental domains. Addressing these concerns requires effective treatment strategies to manage wastewater streams and tackle environmental and economic issues. Furthermore, the recovery of critical minerals from the waste streams associated with energy production holds the promise of offsetting treatment costs and securing local sources of valuable minerals. However, relevant data on these waste streams are dispersed and challenging to locate. The process of ingesting such data into modeling software often involves multiple steps, requiring data restructuring to meet software-input requirements. The non-standardized reporting of water data makes data aggregation and reformatting a time-consuming process. Additionally, essential attributes necessary for modeling water treatment and mineral scale formation are frequently missing. Moreover, data gaps vary depending on the region of interest. Consequently, there is a pressing need for high-quality energy-water composition data that can be easily imported into water chemistry modeling software. To address this need, the National Energy Technology Laboratory has created the National Energy Water Treatment and Speciation (NEWTS) Database and Dashboard—a free online tool catering to community leaders and water researchers. NEWTS facilitates a comprehensive understanding of the composition of energy-related wastewater streams in the United States. The datasets provide detailed concentrations and speciation of major and minor aqueous compounds in energy-related wastewater streams, including power plant leachate, acid mine drainage, brackish water, and oil and gas produced water across the United States. Many of the aqueous species are critical minerals (Li, REEs) in high demand to modernize the world’s energy infrastructure. Many of the datasets also contain volumetric flow-rates needed to model the treatment and reuse scenarios in advanced aqueous chemistry software programs. The NEWTS Database and Dashboard offer public access to hitherto challenging-to-access datasets, presented in a standardized format that is tailored for easy input into aqueous chemistry modeling software. By performing the work needed to transform dispersed, disparate data sources into unified, model-ready datasets, NEWTS serves as an essential resource in advancing water treatment research and sustainable water resource management.

produced water management↗
DOE OSTI2025

PFAS Waste Management for Industrial, Water, and Wastewater Treatment Facilities

Per- and polyfluoroalkyl substances (PFAS), including perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA), are widely used in industrial and consumer products due to their unique water and oil repelling properties. These slow-degrading and bio-accumulating compounds, often called "forever chemicals," are not typically removed by conventional industrial and municipal water/wastewater (W/WW) treatment. This tip of the month provides comprehensive strategies for managing PFAS-contaminated waste streams. Understanding the various types of PFAS waste streams is the first step in managing them. Primary PFAS waste includes contaminated process W/WW and solid materials directly from the production and processing of PFAS-containing materials. These might come from manufacturing facilities, firefighting training areas, or other industrial operations where PFAS compounds are used or were historically present. Secondary PFAS waste results from treatment and disposal mechanisms of primary PFAS waste streams, including spent activated carbon, used ion exchange resins, membrane reject streams, PFAS-laden backwash water, landfill leachate, incineration residuals, etc. TABLE 1 lists examples of the most common PFAS waste streams in different industrial facilities.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Deployment and Evaluation of SciStream on OLCF's Advanced Computing Ecosystem (ACE)

The growing demand for real-time analysis, experimental steering, and decision-making in scientific workflows has created a need for tightly coupled integrations between experimental facilities and high-performance computing (HPC) systems. The Department of Energy’s Integrated Research Infrastructure (IRI) initiative highlights data streaming as a key capability for enabling memory-to-memory data transfers, bypassing the limitations of traditional store-and-forward models. SciStream is a toolkit developed by researchers at Argonne National Laboratory (ANL) to support such streaming by addressing cross-domain security, delegated authentication, and application transparency. We deployed and evaluated SciStream on the Oak Ridge Leadership Computing Facility’s (OLCF) Advanced Computing Ecosystem (ACE) infrastructure, leveraging the Olivine OpenShift cluster and its high-bandwidth Data Streaming Nodes (DSNs) as gateway nodes. Our evaluation included synthetic streaming workloads derived from IRI science workflows, a streaming simulator, and integration with RabbitMQ to handle low-level messaging. This report documents the deployment process, performance evaluation, and challenges encountered, along with opportunities for future improvements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Quasi-periodic Oscillations in the TESS Light Curve of TX Col, a Diskless Intermediate Polar on the Precipice of Forming an Accretion Disk

One of the fundamental properties of an intermediate polar is the dynamical nature of the accretion flow as it encounters the white dwarf’s (WD’s) magnetosphere. Many works have presumed a dichotomy between disk-fed accretion, in which the WD accretes from a Keplerian disk, and stream-fed accretion, in which the matter stream from the donor star directly impacts the WD’s magnetosphere without forming a disk. However, there is also a third, poorly understood regime in which the accretion flow consists of a torus of diamagnetic blobs that encircles the WD. This mode of accretion is expected to exist at mass-transfer rates below those observed during disk-fed accretion, but above those observed during pure stream-fed accretion. We invoke the diamagnetic-blob regime to explain the exceptional Transiting Exoplanet Survey Satellite light curve of the intermediate polar TX Col, which transitioned into and out of states of enhanced accretion during Cycles 1 and 3. Power-spectral analysis reveals that the accretion was principally stream fed. However, when the mass-transfer rate spiked, large-amplitude quasi-periodic oscillations (QPOs) abruptly appeared and dominated the light curve for weeks. The QPOs have two striking properties: they appear in a stream-fed geometry at elevated accretion rates, and they occur preferentially within a well-defined range of frequencies (∼10–25 cycle day{sup −1}). We propose that during episodes of enhanced accretion, a torus of diamagnetic blobs forms near the binary’s circularization radius and that the QPOs are beats between the white dwarf’s spin frequency and unstable blob orbits within the WD’s magnetosphere. We discuss how such a torus could be a critical step in producing an accretion disk in a formerly diskless system.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Variations in the Width, Density, and Direction of the Palomar 5 Tidal Tails

Stars that escape globular clusters form tidal tails that are predominantly shaped by the global distribution of mass in the Galaxy, but also preserve a historical record of small-scale perturbations. Using deep grz photometry from DECaLS, we present highly probable members of the tidal tails associated with the evaporating globular cluster Palomar 5. These data yield the cleanest view of a stellar stream beyond ≈20 kpc and reveal: (1) a wide, low surface-brightness extension of the leading tail; (2) significant density variations along the stream; and (3) sharp changes in the direction of both the leading and the trailing tail. In the fiducial Milky Way model, a rotating bar perturbs the Palomar 5 tails and can produce streams with similar width and density profiles to those observed. However, the deviations of the stream track in this simple model do not match those observed in the Palomar 5 trailing tail, indicating the need for an additional source of perturbation. These discoveries open up the possibility of measuring the population of perturbers in the Milky Way, including dark-matter subhalos, with an ensemble of stellar streams and deep photometry alone.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

FUN-BioCROP model with litter decomposition parameters derived from the LIDET dataset

This repository contains the code and data necessary to run the FUN-BioCROP (Fixation and Uptake of Nitrogen-Bioenergy Carbon, Rhizosphere, Organisms, and Protection) model with litter decomposition parameters derived from a modified Monte Carlo simulation that used the Long-term Intersite Decomposition Experiment Team dataset. Related publication:Juice, S.M., Ridgeway, J.R., Hartman, M.D., Parton, W.J., Berardi, D.M., Sulman, B.N., Allen, K.E., & Brzostek, E.R. Reparameterizing litter decomposition using a simplified Monte Carlo method improves litter decay simulated by a microbial model and alters bioenergy soil carbon estimates. Description of Files: FUNBioCROP_LIDET Study.Rmd R code with FUN-BioCROP model that can be run with 10 different sets of parameters for litter decomposition (Baseline, LIDET, or eight other best parameter sets identified in the modified Monte Carlo simulation. CORPSE Functions_Bioenergy_V2.R Code with CORPSE model functions, called by FUNBioCROP_LIDET Study.Rmd Model Input Data: bulk.csv, bulk_till.csv, rhizo.csv, rhizo_till.csv, litter.csv Initial C and N (kg C or N/m2) pool values for each soil compartment, final values from spin up. All five files have the same columns: (Column - Description - Units) uFastC - Unprotected fast decomposing carbon - kg carbon/m2 uSlowC - Unprotected slow decomposing carbon - kg carbon/m2 uNecroC - Unprotected necromass carbon - kg carbon/m2 pFastC - Protected fast decomposing carbon - kg carbon/m2 pSlowC - Protected slow decomposing carbon - kg carbon/m2 pNecroC - Protected necromass carbon - kg carbon/m2 livingMicrobeC - Carbon in living microbial biomass - kg carbon/m2 uFastN - Unprotected fast decomposing nitrogen - kg nitrogen/m2 uSlowN - Unprotected slow decomposing nitrogen - kg nitrogen/m2 uNecroN - Unprotected necromass nitrogen - kg nitrogen/m2 pFastN - Protected fast decomposing nitrogen - kg nitrogen/m2 pSlowN - Protected slow decomposing nitrogen - kg nitrogen/m2 pNecroN - Protected necromass nitrogen - kg nitrogen/m2 inorganicN - Inorganic nitrogen - kg nitrogen/m2 CO2 - Carbon in carbon dioxide - kg carbon/m2 livingMicrobeN - Nitrogen in living microbial biomass - kg nitrogen/m2 Model Input Data: FluxTower_AvgSoilT.csv: Average daily soil temperature (oC) at 10 cm depth at University of Illinois Urbana-Champaign (UIUC) Energy Farm flux tower from 7/2008-3/2016. (One year of averaged data) Model Input Data: FluxTower_AvgSoilVWC.csv: Average daily soil volumetric water content (VWC) at 10 cm depth at UIUC Energy Farm flux tower from 7/2008-3/2016. (One year of averaged data) Model Input Data: input_CCS_LIDET Study.csv: This file has daily data to run FUN-BioCROP (Column - Description - Units): yr - calendar year - year doy - day of year (1 to 365) (no leap year) - day anpp - aboveground NPP (DayCent) - kg C/m2/day bnpp - belowground NPP (DayCent) - kg C/m2/day aglivc - live aboveground biomass carbon (DayCent) - kg C/m2 bglivcj - live juvenile fine root biomass carbon (DayCent) - kg C/m2 bglivcm - live mature fine root biomass carbon (DayCent) - kg C/m2 aglivn - live aboveground biomass nitrogen (DayCent) - kg N/m2 bglivnj - live juvenile fine root biomass nitrogen (DayCent) - kg N/m2 bglivnm - live mature fine root biomass nitrogen (DayCent) - kg N/m2 nyr - simulation year - year cult - indicates a cultivation event (0 or 1) crop - indicates a new crop (0 or 1) fert - indicates a fertilizer event (0 or 1) frst - indicates the first day of the growing season (0 or 1) harv - indicates a harvest event (0 or 1) last - indicates the end of the growing season (0 or 1) croptype - crop type (0=none; 1=alfalfa; 2=corn; 3=grass clover pasture; 4=soybean; 5=wheat) cropsrl - crop specific root length - mm/g root cultrhizmix - fraction of rhizosphere mixed with bulk soil during cultivation (0.0-1.0) - fraction cultlitmix - fraction of litter mixed with bulk soil during cultivation (0.0-1.0) - fraction harvremov - fraction of above ground biomass removed during harvest (0.0-1.0) - fraction fertamt - fertilization amount - g N/m2 lifehist - plant life history (0 = annual, 1 = perennial) froot_turnover_c - amount of C in fine root turnover - kg C/m2 froot_turnover_n - amount of N in fine root turnover - kg N/m2 agrd_turnover_c - amount of C in aboveground biomass turnover - kg C/m2 agrd_turnover_n - amount of N in aboveground biomass turnover - kg N/m2 leaf_litter_fastfrac - Fast decomposing fraction of leaf litter (0.0-1.0) - fraction root_litter_fastfrac - Fast decomposing fraction of root litter (0.0-1.0) - fraction root_diameter - root diameter - mm root_length - root length - mm root/m2 rhizo_frac - fraction of total soil volume that is rhizosphere (0.0 - 1.0) - fraction date - date in format YYYY-MM-DD Instructions: Save the model code ("FUN-BioCROP_LIDET Study.Rmd") and accompanything files (data streams and CORPSE function code) in the same folder. In model code "Chunk 3: Load CORPSE Data Streams" set the working directory (setwd) to the folder with the files saved in step #1. In "Chunk 5: Define LIDET parameter sets" select the litter decomposition parameter set to be used in the run, and comment out all other sets. If changing any parameter values, edit them in "Chunk 6: Load parameters." Run all chunks up to and including "Chunk 10: Prepare Data for Export." In "Chunk 11: Export Output Data" edit data frames for export and filenames, as necessary. "Chunk 12: Graph Total Soil C" makes a figure of C remaining over the model run period. Description of each model chunk (in file FUN-BioCROP_LIDET Study.Rmd): Chunk 1: Remove all functions, clear memory. Removes all functions from R environment, clears the memory. Chunk 2: Load Packages. Loads packages necessary to run the code. Chunk 3: Load CORPSE Data Streams. Sets the working directory and loads the data files necessary to run CORPSE. Chunk 4: Load CORPSE Functions. Loads the R script with CORPSE functions from the working directory, "CORPSE Functions_Bioenergy_V2.R". Chunk 5: Define LIDET parameter sets. Has ten different parameter sets for litter decomposition tested in this study: Baseline parameters, LIDET parameters, and the other 8 best performing parameter sets identified in the modified Monte Carlo. To run the model, all but one parameter set must be commented out. Chunk 6: Load Parameters. Loads all fixed parameters to run the model. Data frame with definitions of parameters is in the CORPSE function script "CORPSE Functions_Bioenergy_V2.R" Chunk 7: Prepare Data Streams. Takes data streams loaded in Chunk 3 and puts them in the format necessary to run the model. The model is coded to run at least two sites at a time, so if only one site is being run it must be run in duplicate. Individual data tables of daily values are created in this chunk from the input data file. Chunk 8: Set Initial Conditions. Creates data tables of soil C and N pools for each soil compartment (rhizo_till, rhizo, bulk_till, bulk, litter) and loads initial values into the data tables. Creates lists for each soil compartment to hold model output. Chunk 9: Load FUN Data and Set Up Matrices. Uses DayCent data to calculate FUN input data: root and leaf N demand, total N demand, plant CN, leaf N available for retranslocation, and litter production. Creates matrices for FUN model outputs. Chunk 10: Run Model. Runs the model. Chunk 11: Prepare Data for Export. Combines data from each day saved as lists into data frames for each soil compartment. Adds values from all soil compartments together to calculate total soil values, creates separate data frames for each soil C and N pool (e.g., protected slow C) for the total soil value. Adds different C and N pools together to calculate total soil C and N for all layers. Creates data frame of ratio of protected to unprotected SOC. Organizes FUN data for export. Chunk 12: Export Results. Exports CSV files of model results to the working directory. Chunk 13: Graph Total Soil C. Makes figure of C remaining over time. Related Links: Original FUN-BioCROP model: https://github.com/BrzostekEcologyLab/FUN-BioCROP LIDET dataset: https://andlter.forestry.oregonstate.edu/data/abstract.aspx?dbcode=TD023

Juice, Stephanie↗