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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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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Advanced Modeling and Simulation to Characterize Advanced Boiling Water Reactor Source Terms to Support a Regulatory Approval Pathway for Right-Sized Emergency Planning Zone. Advanced Boiling Water Reactor (A-BWR) Project Phase 2

The United States Department of Energy (US DOE) is currently supporting the development of various small modular reactor (SMR), microreactor and advanced reactor designs. These reactors have improved safety features as compared to conventional Large Light Water Reactors (LLWRs), which include features that improve potential reduction of radiological source terms in the event of design and beyond-design basis accidents. Specifically, some reactors feature a relatively smaller containment volume with respect to the available surface area for fission product deposition; these include Integrated Pressurized Water Reactors (iPWRs), such as the NuScale SMR and SMR-type Boiling Water Reactors (BWRs) such as General Electric-Hitachi’s BWRX-300 design.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

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

The poster, presented at the American Geophysical Union (AGU) 2023 Conference, highlights NETL's National Energy Water Treatment & Speciation (NEWTS) Database & Dashboard. This poster reviews the work done to aggregate disparate water quality data for energy-related wastewater streams, to process and integrate the datasets, and enable easy integration with aqueous chemistry modeling software to support water management and beneficial reuse decision-making.

Wenzlick, Madison↗
DOE OSTI2020

Columbia River Surface Water and Pore Water Unaligned FTICR-MS Data Associated with “Using Community Assembly Metrics from Metacommunity Ecology to Understand Environmental Metabolomes”

Surface water and pore water samples were collected at five sites along a shoreline transect of the Columbia River, southeastern WA, USA in 2017. This dataset is comprised of (1) high resolution characterization of dissolved organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) and (2) a metadata csv file. The FTICR-MS files are .xml, and the data package includes instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user’s specific needs. The data are associated with the publication “Using community assembly metrics from metacommunity ecology to understand environmental metabolomes” that will be published in Nature Communications (Danczak et al.). The study aimed to investigate gaps in understanding the spatiotemporal organization of environmental metabolomes to improve the ability to predict ecosystem function. Associated sequencing data will be published via NCBI. The access information for NCBI and the publication DOI will be added to this abstract when they are available. Please use the data package’s DOI to cite the data package. We ask that you acknowledge the U.S. Department of Energy (DOE) Biological and Environmental Research (BER) Subsurface Biogeochemical Research (SBR) program when using the data. All data are free to be used for any purpose, such as for manuscripts, presentations, and grant proposals. There is no obligation to include data package authors as co-authors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Partially-Reflected Water-Moderated Square-Pitched U(6.90)O 2 Fuel Rod Lattices with 0.52 Fuel to Water Volume Ratio (0.855 CM Pitch)

The US Department of Energy (DOE) Nuclear Energy Research Initiative funded the design and construction of the Seven Percent Critical Experiment (7uPCX) at Sandia National Laboratories. The start-up of the experiment facility and the execution of the experiments described here were funded by the DOE Nuclear Criticality Safety Program. The 7uPCX is designed to investigate critical systems with fuel for light water reactors in the enrichment range above 5 % 235 U. The 7uPCX assembly is a water-moderated and -reflected array of aluminum-clad square-pitched U(6.90 %)0 2 fuel rods. Other critical experiments performed in the 7uPCX assembly are documented in LEU-COMP-THERM-078, LEU-COMP-THERM-080, LEU-COMP-THERM-096, and LEU-COMP-THERM-097.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Soil Water Chemistry and Water and Nitrogen Isotopes, Teller Road Site and Kougarok Hillslope, Seward Peninsula, Alaska, 2016 - 2019

Data includes results from soil pore-water ions and isotopes sampled from July 2016 through August 2019 at Kougarok Hillslope at mile marker 64 (KG_MM64), Kougarok Road at mile marker 51 (KG_MM51), and the Teller site at mile marker 27 (TL_MM27) in the Seward Peninsula, Alaska. Water was collected using rhizons, wicks, and a sipper. This dataset is used in the Conroy et al., in prep.NGEE Arctic Project SummaryThe Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Spatiotemporal Changes in Trace Metal Bioavailability in the Sediment Pore water of a Constructed Wetland Using Passive Pore water Samplers

Sediments in aquatic systems often act as a major sink for contaminants. Diffusive gradient in thin films (DGTs) and in situ equilibrium dialysis samplers (peepers) are two major in situ pore water sampling devices that overcome the problems associated with conventional pore water sampling methods. In the present study, DGTs and peepers were used to study the spatial and seasonal effects (cool months, October–February; warm months, May–September) on metal bioavailability in the H‐02 constructed wetland and the sink versus source role of the sediments by calculating the metal resupply capacity. Data showed similar seasonal trends in metal concentrations using passive samplers, peepers, and DGTs. Pooled Cu and Zn concentrations measured using DGTs were lower in warm months (1.67 ± 1.50 and 2.62 ± 0.68 μg L –1 , respectively, p < 0.001) versus in cool months (2.12 ± 0.65 and 5.58 ± 1.33 μg L –1 , respectively, p < 0.001; mean ± 95% confidence interval). Sulfate (SO 4 2− ) concentrations were significantly (p = 0.0139) lower in warm months (averaged at 0.22 ± 0.05 mg L –1 ) compared to in cool months (0.16 ± 0.05 mg L –1 ). The increase in SO 4 2− concentration is an indicator of the lower activity of sulfate‐reducing bacteria, which need SO 4 2− during anaerobic respiration, in which SO 4 2− is reduced to sulfide (S 2– ) that forms insoluble salts with Cu and Zn, which could partially explain the higher bioavailability of these metals in the cool season. Metal resupply capacity of the sediments was mostly <0.2 for Cu and Zn. Taken together, the H0‐2 wetland sediments mostly acted as a sink to both Cu and Zn over the course of the present study. Environ Toxicol Chem 2023;42:2726–2736. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

New opportunities in produced water management: A market-based approach to produced water trading

Produced water (PW) is a byproduct of oil and gas (O&G) production. Obtained alongside the more valuable energy products, PW is usually characterized by high levels of salinity and often contains many contaminants (chemicals, soluble and insoluble oil, organics, etc.) making it unsuitable for release without substantial treatment. Couple this with the fact that PW is typically obtained at multiple times the rate of oil or gas, and the added transport, treatment, and disposal costs become a serious challenge for operators. These realities have led to ad-hoc practices including cooperation between industry competitors to recycle, share, or otherwise mitigate PW costs. The National Energy Technology Laboratory (NETL) in partnership with the Ground Water Protection Council (GWPC) is pursuing novel technology solutions to address PW issues that complement or improve ad-hoc practices adopted by operators. In this paper, we observe that well-established market management practices used in electrical power generation have natural analogues in the PW supply chain. These parallels open up a new line of research where we view PW management as a market equilibrium problem, and explore solutions that foster active and data-based collaboration among operators through market structures similar to power markets, with the ultimate objective of improving PW management costs and recycling rates. Here, we make a case for our observations, present a PW market clearing optimization model that shows how such a market system could operate in the O&G space, and provide an illustrative case study for demonstration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Phase Equilibrium of Water with Hexagonal and Cubic Ice Using the SCAN Functional

Machine learning models are rapidly becoming widely used to simulate complex physicochemical phenomena with ab initio accuracy. Here, we use one such model as well as direct density functional theory (DFT) calculations to investigate the phase equilibrium of water, hexagonal ice (Ih), and cubic ice (Ic), with an eye toward studying ice nucleation. The machine learning model is based on deep neural networks and has been trained on DFT data obtained using the SCAN exchange and correlation functional. We use this model to drive enhanced sampling simulations aimed at calculating a number of complex properties that are out of reach of DFT-driven simulations and then employ an appropriate reweighting procedure to compute the corresponding properties for the SCAN functional. This approach allows us to calculate the melting temperature of both ice polymorphs, the driving force for nucleation, the heat of fusion, the densities at the melting temperature, the relative stability of ices Ih and Ic, and other properties. We find a correct qualitative prediction of all properties of interest. In some cases, quantitative agreement with experiment is better than for state-of-the-art semiempirical potentials for water. Furthermore, our results also show that SCAN correctly predicts that ice Ih is more stable than ice Ic.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Neural Network Water Model Based on the MB-Pol Many-Body Potential

The MB-pol many-body potential accurately predicts many properties of water, including cluster, liquid phase, and vapor–liquid equilibrium properties, but its high computational cost can make applying it in large-scale simulations quite challenging. Here, in order to address this limitation, we developed a “deep potential” neural network (DPMD) model based on the MB-pol potential for water. We find that a DPMD model trained on mostly liquid configurations yields a good description of the bulk liquid phase but severely underpredicts vapor–liquid coexistence densities. By contrast, adding cluster configurations to the neural network training set leads to a good agreement for the vapor coexistence densities. Liquid phase densities under supercooled conditions are also represented well, even though they were not included in the training set. These results confirm that neural network models can combine accuracy and transferability if sufficient attention is given to the construction of a representative training set for the target system.

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

Specific Ion Effects in Lanthanide–Amphiphile Structures at the Air–Water Interface and Their Implications for Selective Separation

The use of surfactants to attract dissolved ions to water surfaces and interfaces is an essential step in both solvent-based and solvent-free separation processes. Here, we have studied the interactions of lanthanide ions in the aqueous subphase with monolayers of dihexadecyl phosphate at air–water interfaces. With heavier lanthanides (atomic number Z ≥ 65) in the subphase, the floating layer can be compressed to an area/molecule of about half the molecular cross section, indicating bilayer formation. X-ray fluorescence and reflectivity data support this conclusion. In the presence of lighter lanthanides (Z < 65), only monolayers are observed. Subphase-concentration-dependent studies using Er 3+ (heavier) and Nd 3+ (lighter) lanthanides show a stepwise progression, with ions attaching to the monolayer only when the solution concentration is >3 × 10 –7 M. Above ~10 –5 M, bilayers form but only in the presence of the heavier lanthanide. Grazing incidence X-ray diffraction shows evidence of lateral ion–ion correlations in the bilayer structure but not in monolayers. Explicit solvent all-atom molecular dynamics simulations confirm the elevated ion–ion correlation in the bilayer system. This bilayer structure isolates heavier lanthanides but not lighter lanthanides from an aqueous solution and is therefore a potential mechanism for the selective separation of heavier lanthanides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Visualizing Overall Water Splitting on Single Microcrystals of Phosphorus-Doped BiVO 4 by Photo-SECM

Particulate bismuth vanadate (BiVO4) has attracted considerable interest as a promising photo(electro)catalyst for visible-light-driven water oxidation, however, overall water splitting (OWS) has been difficult to attain because its conduction band is too positive for efficient hydrogen evolution. Using photo-scanning electrochemical microscopy (photo-SECM) with a chemically modified nanotip, we visualized for the first time the OWS at a single truncated bipyramidal microcrystal of phosphorus-doped BiVO 4 . The tip simultaneously served as a light guide to illuminate the photocatalyst and as an electrochemical nanoprobe to observe and quantitatively measure local oxygen and hydrogen fluxes. The obtained current patterns for both O 2 and H 2 agree well with the accumulation of photogenerated holes and electrons on {010} basal and {110} lateral facets, respectively. Furthermore, the developed experimental approach is an important step towards nanoelectrochemical mapping of the activity of photocatalyst particles at the sub-facet level.

bismuth vanadate↗
DOE OSTI2020

Water Promotion (or Inhibition) of Condensation Reactions Depends on Exposed Cerium Oxide Catalyst Facets

Nanoparticles with well-defined facets enable quantitative correlations between surface features and catalytic activity. In this work, we explore the role of geometric and acid–base properties in the mechanism of aldol condensation catalyzed by ceria nanoshapes. In the crucial C–C coupling step, the two carbonyl adsorbates are bound to two adjacent cations. On the CeO 2 (110) plane, all atoms lie on the same layer, favoring the interaction between adsorbates and facilitating the bimolecular C–C coupling. Thus, the initial unimolecular deprotonation is rate-limiting. In contrast, the (100) and (111) planes have an open structure with O on the top layer and Ce on the layer below. The former O layer interferes between adsorbates linked to Ce sites, making the C–C coupling rate-limiting. Water helps in overcoming this spatial hindrance by remote bond polarization via H-bonds. Therefore, water promotion is only observed on those planes for which the bimolecular step is rate-limiting.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Reinforcement-Learning-Based Smart Water Heater Control: An Actual Deployment

Utilizing smart control algorithms for electric water heaters (EWHs) is essential for fully harnessing the demand response (DR) potential of EWHs. For this reason, the use of reinforcement learning (RL) algorithms for EWHs has received increasing attention in recent years. However, existing RL approaches are either simulation-based or use pretrained RL agents. To this end, this paper presents the real-world deployment of a set of model-free RL approaches that aim to minimize the electricity cost of a EWH under a time-of-use electricity pricing policy using standard DR commands (e.g., shed, load up). The experiment results showed that the RL agents can help save electricity cost in the range of 11% to 14% compared to the baseline operation. This study demonstrated that RL-based EWH controllers can be deployed in real world without any prior training and can still save electricity cost.

deep learning↗