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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Structure Formation Limits on Axion-Like Dark Matter

We derive structure formation limits on dark matter (DM) composed of keV-scale axion-like particles (ALPs), produced via freeze-in through the interactions with photons and Standard Model (SM) fermions. We employ Lyman-alpha (Ly-α) forest data sets as well as the observed number of Milky Way (MW) subhalos. We compare results obtained using Maxwell-Boltzmann and quantum statistics for describing the SM bath. It should be emphasized that the presence of logarithmic divergences complicates the calculation of the production rate, which can not be parameterized with a simple power law behaviour. The obtained results, in combination with X-ray bounds, exclude the possibility for a photophilic “frozen-in” ALP DM with mass below ~ 19. For the photophobic ALP scenario, in which DM couples primarily to SM fermions, the ALP DM distribution function is peaked at somewhat lower momentum and hence for such realization we find weaker limits on DM mass. Future facilities, such as the upcoming Vera C. Rubin observatory, will provide measurements with which the current bounds can be significantly improved to ~ 80.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Solubility Predictions for Hanford Tank Concentrates with HSC - 20459

The commercially available Outotec HSC 9.9.0{sup R} provides excellent predictions for the solubilities of many species for Hanford waste tank concentrates. The HSC solubility predictions with a Harvie activity model agreed well with five boildowns that showed solubility limits for NaNO{sub 3}, NaNO{sub 2}, Na{sub 2}CO{sub 3}, NaF, Na{sub 2}SO{sub 4}, and Na{sub 3}PO{sub 4}. However, the HSC did not predict density and therefore water content very well and therefore we used the measured densities and derived water content from the difference between measured density and assays. Furthermore, we adjusted the HSC enthalpy for the minor species Na{sub 3}PO{sub 4}*NaF double salt in order to fit the five boildowns as well. Previous work has shown that gibbsite becomes and remains supersaturated in all of these boildowns and so there was no alumina precipitation despite supersaturation. Furthermore, an equilibrium model like HSC always shows complete oxidation of any TOC in the presence of nitrate and nitrite. We therefore suppressed the HSC oxidation of acetate and oxalate in order to fit measured acetate and oxalate solubilities as TOC. Space in Hanford waste tanks is very limited and therefore evaporator campaigns continue to recover needed tank space from dilute tank liquids. Prior to each evaporator campaign, a boildown of a sample of tank liquid for each campaign provides a basis for planning by measuring density, water activity, soluble species, and solids precipitation as a function of concentration at 18 deg. C. These boildowns then provide validations and calibrations for the HSC solubility prediction for Hanford wastes. Previous work has shown the solubilities of minor electrolytes in these five boildowns follow rather simple power law solubility products. Hanford's 222-S laboratory has reported each of five boildowns for concentrated liquids from five waste tanks and tank blends. All boildowns eventually showed the precipitation of the dominant electrolyte, NaNO{sub 3}, and overall solution activity largely drives all solubility. (authors)

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

Lens Model Accuracy in the Expected LSST Lensed AGN Sample

Strong gravitational lensing of active galactic nuclei (AGN) enables measurements of cosmological parameters through time-delay cosmography (TDC). With data from the upcoming LSST survey, we anticipate using a sample of O(1000) lensed AGN for TDC. To prepare for this dataset and enable this measurement, we construct and analyze a realistic mock sample of 1300 systems drawn from the OM10 (Oguri & Marshall 2010) catalog of simulated lenses with AGN sources at $z<3.1$ in order to test a key aspect of the analysis pipeline, that of the lens modeling. We realize the lenses as power law elliptical mass distributions and simulate 5-year LSST i-band coadd images. From every image, we infer the lens mass model parameters using neural posterior estimation (NPE). Focusing on the key model parameters, $θ_E$ (the Einstein Radius) and $γ_{lens}$ (the projected mass density profile slope), with consistent mass-light ellipticity correlations in test and training data, we recover $θ_E$ with less than 1% bias per lens, 6.5% precision per lens and $γ_{lens}$ with less than 3% bias per lens, 8% precision per lens. We find that lens light subtraction prior to modeling is only useful when applied to data sampled from the training prior. If emulated deconvolution is applied to the data prior to modeling, precision improves across all parameters by a factor of 2. Finally, we combine the inferred lens mass models using Bayesian Hierarchical Inference to recover the global properties of the lens sample with less than 1% bias.

Venkatraman, Padmavathi [Illinois U., Urbana; KIPA↗
DOE OSTI2023

Evaluating Impacts of the Inflation Reduction Act and Bipartisan Infrastructure Law on the U.S. Power System

The Inflation Reduction Act of 2022 (IRA) and the Infrastructure Investment and Jobs Act of 2021, commonly referred to as the 'Bipartisan Infrastructure Law (BIL),' collectively represent the largest commitment of the U.S. Federal Government to invest in the modernization and decarbonization of the U.S. energy system. The Congressional Budget Office (CBO) estimates that total support for the broad range of climate and clean energy programs, tax credits, and other incentives authorized through the two laws will exceed $430 billion from 2022 through 2031 (CRS 2022; CBO 2021, 2022). While the climate and clean energy provisions are numerous and have the potential to impact all aspects of the U.S. energy system from fuel and electricity production to final consumption in industry, transportation, and buildings, the provisions relevant to the electricity sector - in particular the suite of tax credits for clean generation, storage, and carbon dioxide ( CO 2 ) capture and storage - are expected to be some of the most consequential in terms of emissions reduction and clean energy deployment (Larsen et al. 2022; Jenkins, Mayfield, et al. 2022; Mahajan et al. 2022; Zhao et al. 2022). In this report, we detail the methods and results of a study estimating the potential impacts of key provisions of IRA and BIL on the contiguous U.S. power sector from present day through 2030. The analysis employs an advanced power system planning model, the Regional Energy Deployment System (ReEDS), to evaluate how major provisions from both laws impact investment in and operation of utility-scale generation, storage, and transmission, and, in turn, how those changes impact power system costs, emissions, and climate and health damages. While not exhaustive in capturing every provision, the analysis estimates the possible scale of power-sector impacts that could result from the modeled provisions in IRA and BIL. The study is structured around two scenarios to evaluate the potential impacts of both laws on the power sector: 1) No New Policy: A counter-factual scenario that reflects all Federal and state policies enacted as of September 2022, with exception to IRA and BIL, and assumes load growth consistent with the Energy Information Administration's Annual Energy Outlook 2022 (AEO22) Reference case (EIA 2022a); 2) IRA-BIL: A scenario reflecting all Federal and state policies enacted as of September 2022, including key IRA and BIL provisions, most notably the investment and production tax credits for zero-carbon emitting electricity generation and storage (ITC and PTC), the tax credit for CO 2 capture and storage (45Q), and the tax credit for existing nuclear plants (described further in Section 2.3). To account for the impacts of IRA and BIL on electrification, assumes increased load growth consistent with a scaled version of the Medium Electrification scenario from the Electrification Futures Study (Mai et al. 2018). These scenarios are simulated across seven sets of assumptions with varying projected future electricity market conditions, including technology costs and performance, natural gas prices, and the degree of availability, feasibility, and cost of development of renewable resources, electricity transmission, and CO 2 pipeline, injection, and storage infrastructure. In addition, we simulate two sensitivities on the 'policy' treatment in which we vary key assumptions pertaining to the realized value of the clean electricity ITC and PTC: 1) the cost of monetization of tax credits, and 2) the level of bonus crediting realized by project developers. We demonstrate that IRA and BIL have the collective potential to drive substantial growth in clean electricity by 2030, while reducing costs for consumers, mitigating climate change, and decreasing the human health impacts of power sector emissions. However, we also demonstrate that if expected cost improvements of clean technologies are not realized and/or constraints on deployment driven by factors such as supply-chain challenges, regulatory hurdles, and the social acceptability of energy infrastructure development limit the rate of clean energy and associated infrastructure deployment (such as transmission), then the share of clean generation achieved and the associated emissions benefits realized may be substantively reduced.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Investigating the Impact of Power-Take-Off System Parameters and Control Law on a Rotational Wave Energy Converter’s Peak-to-Average Power Ratio Reduction

Due to the irregular nature of real waves, the power captured in a wave energy converter (WEC) system is highly variable. This is an important barrier to the effective use of WECs. To address this challenge, this study focuses on a rotational WEC power-take-off system in which high-speed and high-efficiency generators along with a torque/power smoothing inertia element can be effectively utilized. In the first phase of this study, the U.S. Department of Energy’s reference model 3 (WEC-Sim RM3; two-body point absorber), along with a slider-crank WEC, were integrated for linear to rotational conversion. Relative motion between the float and spar in RM3 was the driving force for this slider-crank WEC, which is connected to a motor/generator set through a gearbox. RM3 geometry was scaled down by 25 times to work within the limits of the physical motor/generator set used in the experimentation. Once the integration in a hardware-in-the-loop simulation environment was successfully completed, data on the peak-to-average power ratio was collected for various wave conditions including regular and irregular waves. The control algorithm designed to keep the system in resonance with waves was able to maintain relatively high speed depending on the specific gear ratio and wave period. Initial results with hardware-in-the-loop simulations reveal that gear ratio and crank radius have a strong impact on the peak-to-average power ratio. In addition, it was found that output power from the generator was maximized at a larger gear ratio, as the crank radius was increased.

50 EE - Wind and Water Power Program - Water (EE-4↗
DOE OSTI2021

Diverted Negative Triangularity plasmas on DIII–D: The benefit of high confinement without the liability of an edge pedestal

Diverted discharges at negative triangularity on the DIII-D tokamak sustain normalized confinement and pressure levels typical of standard H-mode scenarios (H 98y,2 ≅1, β N ≅3) without developing an edge pressure pedestal, despite the auxiliary power far exceeding the L → H power threshold expected from conventional scaling laws. The power degradation of confinement is substantially weaker than the ITER-89P scaling, resulting in a confinement factor that improves with increasing auxiliary power. Furthermore, the absence of the edge pedestal is beneficial in several aspects, such as eliminating the need for active mitigation or suppression of edge localized modes, low impurity retention and a reconstructed scrape-off layer heat flux width at the mid-plane that exceeds the ITPA multi-machine scaling law by up to 50%. Together with technological advantages granted by placing the divertor at larger radii, plasmas at Negative Triangularity without an edge pedestal feature both core confinement and power handling characteristics that are potentially suitable for operation in future fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Water transport properties of virtual fractal porous media: Implications for the unsaturated transport properties of cement-based materials

Cement-based materials are more and more recognized as fractal materials. From a practical point of view, fractality means that the pore size distribution can be described using fractal scaling law (i.e. power functions). Here, the simplest scaling law making use of a single fractal dimension was used to generate simple and virtual fractal porous media (based on bundles of parallel cylindrical pores). The capillary curve and permeability (relative and intrinsic) of the virtual porous media were then estimated through theoretical and numerical approaches. The results show that: (1) although bereft of any physical basis, van Genuchten equation bears some fractal information; (2) although highly flexible, van Genuchten equation fails to perfectly fit the capillary curves and can thus generate error in inverse analysis (for intrinsic permeability evaluation) and (3) there seems to be a relation between the intrinsic permeability and van Genuchten pressure parameter.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The Bipartisan Infrastructure Law Provides Opportunities for Water Power Across Several Programs

President Biden signed the Infrastructure Investment and Jobs Act into law on November 15, 2021. The $1.2 trillion deal, commonly called the Bipartisan Infrastructure Law (BIL), is a long-term investment in the nation’s infrastructure, workers, families, and competitiveness. The investment is historic for the U.S. Department of Energy (DOE), which will receive more than $62 billion from the BIL to stand up 60 new programs, including 16 demonstration and 32 deployment programs, and expand funding for 12 existing research, development, demonstration, and deployment programs. The BIL-funded programs outlined in this fact sheet are most relevant for hydropower and marine energy.

BIL↗
DOE OSTI2020

Correlating inter-particle forces and particle shape to shear-induced aggregation/fragmentation and rheology for dilute anisotropic particle suspensions: A complementary study via capillary rheometry and in-situ small and ultra-small angle X-ray scattering

Predicting the stability of suspensions composed of anisotropic particles is difficult due to the complexity and interplay of hydrodynamic and colloidal forces. For example, it is not well understood how non-spherical particle shapes affect suspension-rheological responses. This study presents evidence showing how the stacking of boehmite platelets dispersed in aqueous solution leads to moderate shear thinning, even at low boehmite mass fractions. Wide angle X-ray, small angle X-ray, and ultra-small angle X-ray scattering were used to simultaneously monitor changes to the size and fractal dimensions of boehmite aggregates from 6 – 10,000 Å as the sample was recirculated through an in situ capillary rheometer. The latter also provided simultaneous measurements of the viscosity of the suspensions. Computational fluid dynamics modeling of the apparatus was used to provide a more rigorous analysis of the fluid flow. In addition to shear-induced aggregation/fragmentation correlated to a complicated balance between hydrodynamic and colloidal forces, the results indicate that orientationally-dependent interactions, arising from non-spherical boehmite aggregate sub-units, may explain the relatively large experimental viscosity when the hydrodynamic force is small compared to colloidal forces. Ultimately, the results from this study can provide a foundation for future work investigating particle shape effects on colloidal and hydrodynamics forces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Hydrologic connectivity and dynamics of solute transport in a mountain stream: Insights from a long-term tracer test and multiscale transport modeling informed by machine learning

The movement of solutes in a watershed is a complex process with multiple interactions and feedbacks across spatial and temporal scales. Modeling the dynamics of solute transport along diverse hydrologic pathways within watersheds – from hillslopes to stream channels and in and out of the hyporheic zones – is challenging but critically important, as these processes integrate and contribute to the biogeochemical functioning of the river corridor up to the river network scale. Here we use results from a long-term network-scale tracer test at the H.J. Andrews experimental forest in western Cascade Mountains, Oregon, USA to inform a multiscale framework for transport in stream corridors. The framework uses a Lagrangian-based subgrid model to represent the effects of hyporheic exchange flow and advective transport at stream network scales. The spatially and temporally resolved stream discharge needed for the transport model is imputed across the river system by an entity-aware long short-term memory network. Modeled concentrations show good agreements with the observations and exhibit power scaling laws indicative of a very wide range of timescales over which hyporheic exchange flow occurs. Our results demonstrate a data-informed modeling framework that links dynamical processes occurring at small scales to a network context to help understand how changes at reach scale cascade into network-scale effects, providing a useful tool for sustainable river basin management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Cluster mediated conversion of amorphous Al(OH) 3 to γ-AlOOH

In this work, we report a synthetic pathway by which amorphous Al(OH) 3 is converted to γ-AlOOH through hydrothermal reaction in the presence of water at temperature T = 473 K. X-ray pair distribution function measurements reveal that the initially amorphous Al(OH) 3 possesses a locally γ-Al(OH) 3 -like structure, while nanocrystalline γ-AlOOH precipitates within 1 h of continuous hydrothermal exposure. Solid state nuclear magnetic resonance measurements show that resonant features associated with four- and five-member Al clusters persist through 20 min of hydrothermal treatment, and ultraviolet (UV) spectra mark the onset of UV-induced photoluminescent features characteristic to γ-AlOOH with 10 min of exposure, indicating a coexistence region of γ-Al(OH) 3 -like and γ-AlOOH-like amorphous species. Furthermore, powder x-ray diffraction measurements of desiccated powders reveal that the conversion process takes place in distinct, power law-defined stages with initial γ-AlOOH nucleation occurring within the first 20 min, followed by a ~ 1 h period of rapid grain coarsening and the subsequent onset of Lifshitz-Slyozov-Wagner-like coalescence.

36 MATERIALS SCIENCE↗
DOE OSTI2025

An accelerated framework for predicting creep rupture lifetimes in engineering alloys

Confidently predicting high-temperature deformation, including creep and creep rupture, is paramount for the design and commercialization of candidate materials for advanced nuclear energy systems. To accelerate creep quantification, we introduce a framework that enables rapid, cost-effective, and reliable prediction of creep rupture lifetimes, minimizing reliance on time-intensive bulk creep testing. Unlike conventional creep analysis, which requires extensive time and resources, our method leverages a maximum of four short-term bulk creep tests as training data for prediction. This framework combines high-throughput nanoindentation up to 700 °C with these targeted bulk tests to inform our creep rupture model in order to predict rupture lifetimes. The strong agreement between our predictions and conventional experimental data demonstrates the effectiveness of our approach for accelerated creep analysis and lifetime prediction of structural components in high-temperature applications. Our multi-pronged approach motivates further integration of computational tools and advanced instrumentation to establish a universal framework for understanding high-temperature material responses.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Detecting Permafrost Active Layer Thickness Change From Nonlinear Baseflow Recession

We report permafrost underlies about one fifth of the global land area and affects ground stability, freshwater runoff, soil chemistry, and surface-atmosphere gas exchange. The depth of thawed ground overlying permafrost (active layer thickness) has broadly increased across the Arctic in recent decades, coincident with a period of increased streamflow, especially the lowest flows (baseflow). Mechanistic links between active layer thickness and baseflow have recently been explored using linear reservoir theory, but most watersheds behave as nonlinear reservoirs. We derive theoretical nonlinear relationships between long-term average saturated soil thickness $\bar{η}$(proxy for active layer thickness) and long-term average baseflow. When applied to 38 years of daily streamflow data for the Kuparuk River basin on the North Slope of Alaska, the theory predicts $\bar{η}$ increased 0.17 ± 0.22[2σ] cm a -1 between 1983 and 2020 (6.4 ± cm total). The rate of increase nearly doubled to 0.29 ± 0.31 cm a -1 between 1990 and 2020, during which time local field measurements from Circumpolar Active Layer Monitoring sites indicate the active layer increased 0.31 ± 0.22 cm a -1 . The predicted rate of increase more than doubled again between 2002 and 2020, outpacing a near doubling of observed active layer thickening, consistent with trends in terrestrial water storage inferred from Gravity Recovery and Climate Experiment satellite gravimetry and Modern-Era Retrospective Analysis for Research and Applications climate reanalysis. Overall, hydrologic change is accelerating in the Kuparuk River basin, and we provide a theoretical framework for estimating basin-scale changes in active layer water storage from streamflow measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

On assurance testing for repairable systems

In this work, we consider assurance testing for repairable systems when supplementary information is available in addition to the data collected in the assurance test. The supplementary information is incorporated using a Bayesian inferential framework. Assurance testing is considered for both a homogeneous Poisson process and a nonhomogenous Poisson process and is illustrated with examples.

42 ENGINEERING↗
DOE OSTI2023

Degree-preserving graph dynamics: a versatile process to construct random networks

Real-world networks evolve over time via the addition or removal of vertices and edges. In current network evolution models, vertex degree varies or grows arbitrarily. A recently introduced degree-preserving network growth (DPG) family of models preserves vertex degree, resulting in structures significantly different from and more diverse than previous models. Despite its degree preserving property, the DPG model is able to replicate the output of several well-known real-world network growth models. Simulations showed that many real-world networks can also be constructed from small seed graphs via the DPG process. Here, we start the development of a rigorous mathematical theory underlying the DPG family of network growth models. We prove that the degree sequence of the output of some of the well-known, real-world network growth models can be reconstructed via the DPG process, using proper parametrization. We also show that the general problem of deciding whether a simple graph can be obtained via the DPG process from a small seed (DPG feasibility) is, however, NP-complete. In conclusion, it is an intriguing open problem to uncover whether there is a structural reason behind the DPG-constructability of real-world networks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Learning-Based Real-Time Event Identification Using Rich Real PMU Data

A large-scale deployment of phasor measurement units (PMUs) that reveal the inherent physical laws of power systems from a data perspective enables an enhanced awareness of power system operation. However, the high-granularity and non-stationary nature of PMU data and imperfect data quality could bring great technical challenges for real-time system event identification. To address these challenges, this paper proposes a two-stage learning-based framework. In the first stage, a Markov transition field (MTF) algorithm is exploited to extract the latent data features by encoding temporal dependency and transition statistics of PMU data in graphs. Then, a spatial pyramid pooling (SPP)-aided convolutional neural network (CNN) is established to efficiently and accurately identify power events. The proposed method fully builds on and is also tested on a large real-world dataset from several tens of PMU sources (and the corresponding event logs), located across the U.S., with a time span of two consecutive years. We report the numerical results validate that our method has high identification accuracy while showing good robustness against poor data quality.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

baseflow: a MATLAB and GNU Octave package for baseflow recession analysis

baseflow is a MATLAB® toolbox designed for baseflow recession analysis, a technique used in hydrologic science to infer aquifer properties from streamflow. By leveraging widely available streamflow data, baseflow can be used to estimate aquifer properties such as hydraulic conductivity and drainable porosity over the modern instrumental stream gage record. The toolbox is intended for analysis of measured streamflow values recorded on a daily timestep, and is tailored for shallow, unconfined riparian aquifers that discharge groundwater laterally into adjacent streams. Additionally, baseflow can analyze the collective behavior of individual hillslope aquifers constituting hydrologic catchments, known as “watersheds”, from a nonlinear dynamical systems perspective. The toolbox incorporates recent advances in baseflow recession analysis to enable objective estimations of aquifer properties, and their sensitivity to methodological decisions, at both hillslope and catchment scales.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Fermilab Automation of Coil Winding System

The automated coil winder project creates a repeatable, scalable method for producing superconducting magnet coils with increased accuracy and efficiency. The design uses an ortho cyclic winding method to achieve high fill factors by combining computer numerical control (CNC), microcontroller-based controls, and sophisticated optimization techniques. The method optimizes coil turns, core geometry, and current consumption by utilizing analytical models based on magnetic moment, Ohm’s law, and power constraints. For particle accelerator applications, prototype testing using a 3D-printed coil winder has shown enhanced winding repeatability, thermal management, and manufacturability.

Dzida, Rafal [Northern Illinois U.]↗