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At least 613 records · Page 34

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DOE OSTI2026

A Hybrid Biophysical‐Machine Learning Framework for Diurnal Surface Energy Flux Estimation Using Proximal Sensing

Thermal infrared-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy ( LE ) and sensible heat ( H ) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal infrared data sets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of a ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R 2 = 0.81–0.94) and H (R 2 = 0.46–0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical-machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.

evapotranspiration↗

DOE OSTI2025

SPECTER: an instrument concept for CMB spectral distortion measurements with enhanced sensitivity

Deviations of the cosmic microwave background (CMB) energy spectrum from a perfect blackbody uniquely probe a wide range of physics, ranging from fundamental physics in the primordial Universe (μ-distortion) to late-time baryonic feedback processes (y-distortion). While the y-distortion can be detected with a moderate increase in sensitivity over that of COBE/FIRAS, the ΛCDM-predicted μ-distortion is roughly two orders of magnitude smaller and requires substantial improvements, with foregrounds presenting a serious obstacle. Within the standard model, the dominant contribution to μ arises from energy injected via Silk damping, yielding sensitivity to the primordial power spectrum at wavenumbers k ≈ 1-10 4 Mpc -1 . Here, we present a new instrument concept, SPECTER, with the goal of robustly detecting μ. The instrument technology is similar to that of LiteBIRD, but with an absolute temperature calibration system. Using a Fisher approach, we optimize the instrument's configuration to target μ while marginalizing over foreground contaminants. Unlike Fourier-transform-spectrometer-based designs, the specific bands and their individual sensitivities can be independently set in this instrument, allowing significant flexibility. We forecast SPECTER to observe the ΛCDM-predicted μ-distortion at ≈ 5σ (10σ) assuming an observation time of 1 (4) year(s) (corresponding to mission duration of 2 (8) years), after foreground marginalization. Our optimized configuration includes 16 bands spanning 1–2000 GHz with ∼degree-scale angular resolution at ∼ 150 GHz and 1100 total detectors. SPECTER will additionally measure the y-distortion at sub-percent precision and its relativistic correction at percent-level precision, yielding tight constraints on the total thermal energy and mean temperature of ionized gas.

CMBR experiments↗

DOE OSTI2024

Suppressed electric quadrupole collectivity in Si 32

Lying between O 16 and Ca 40 , the s d shell is well described by robust phenomenological and nuclear theories. In this work, however, we highlight an unexplained reduction in electric-quadrupole strength in the rare isotope Si 32 , studied through sub-barrier Coulomb excitation. It is found that the oblate nature of the deformation is well reproduced, while the absolute scale of quadrupole deformation, however, is inhibited by approximately a factor of 2 compared to theoretical predictions. Through comparison with shell-model and calculations, we present a number of possible explanations for this inhibited E 2 strength. By comparing the results of these calculations to multiple observables, we conclude that there is a reduced role for out-of-space excitations in Si 32 , resulting in a reduction in the corrections normally applied to both models. Published by the American Physical Society 2024

20 ≤ A ≤ 38↗

DOE OSTI2020

10 MWE CDCL Large Pilot Plant – pre-FEED Study

Coal Direct Chemical Looping (CDCL) is an advanced oxy-combustion technology that has the potential to substantially reduce the energy penalty and the cost of electricity (COE) for coal-fired power generation with CO₂ capture. The Babcock & Wilcox Company (B&W) and The Ohio State University (OSU) have been collaborating on the development of an iron oxide oxygen-carrier based chemical looping technology for clean power generation with inherent carbon capture. In this process, coal is dried and pulverized prior to being transported into a moving-bed reducer. In the reducer, coal reacts with the oxygen-carrier particles, forming combustion byproducts, predominantly CO₂ and H₂O, while reducing the iron oxide oxidation state from Fe₂O₃ to a mixture of FeO and Fe. The reduced state particles are then transported to a combustor reactor and re-oxidized with air. Following the oxidation, the oxygen-carrier particles are regenerated, and a large amount of heat is released for steam production. The produced steam is sent to a turbine for electricity generation. Meanwhile, the CO₂–rich stream leaving the reducer is cooled, cleaned, and compressed for subsequent pipeline transportation and sequestration. By combining air separation and fuel conversion into a single system, the CDCL technology enables the intensification of oxy-combustion processes by eliminating the energy and cost intensive cryogenic air separation unit and thereby results in higher overall plant efficiencies and lower COE’s. The use of a moving-bed reducer results in high conversions of volatile hydrocarbons and high CO₂ purity, which reduces the cost of downstream CO₂ purification for sequestration or utilization. The Babcock & Wilcox Company in collaboration with The Ohio State University, Johnson & Matthey, The Electric Power Research Institute, and Dover Light & Power completed a Preliminary Front-End Engineering and Design (Pre-FEED) study of a 10 MWe coal-direct chemical looping (CDCL) pilot plant. The planned system is a modular 10 MWe CDCL large pilot facility consisting in 4 modules of 2.5 MWe each, working in parallel and to be hosted within the current structure at the City of Dover’s Municipal Power Plant. The CDCL system can achieve auto-thermal operation and includes a sub-critical steam cycle for power generation. The pilot system was designed to demonstrate full commercial operation at a reduced scale. The coal distribution per plan area is a representative slice of larger commercial arrangements. The system includes a CO₂ recycle system, but it does not include a compression system. The large pilot includes all the environmental control equipment and oxygen carrier and ash handling systems. As part of the project, the Team performed laboratory testing and carried out multiple pilot test campaigns to obtain design and performance information at the 250 kWth CDCL pilot facility at the Babcock & Wilcox Company’s Research Center. The Team demonstrated sustained operations at designed coal inputs, high coal conversion, high CO₂ purity, heat generation on the combustor, low carbon carryover between reactors and low particle attrition. Emissions generated in the reducer reactor were identified as SO₂ and NO x . The commercial manufacturing cost of oxygen carrier particle was evaluated by JM. A particle manufacturing report was generated and submitted to the DOE. Based on the results from the pilot tests and the pre-FEED design efforts, a techno-economic analysis was performed. The study shows that the CDCL process is a promising carbon-friendly technology capable of producing electricity with high efficiency. The estimated COE of the supercritical CDCL plant is $83.3 / MWh, which meets DOE’s target of less than 30% increase in COE when compared to a supercritical PC plant without CO₂ capture. This is the lowest among the existing carbon capture technologies (post-combustion and oxy-combustion) for fossil fuel power plant. CDCL is evaluated to be the most promising technology for carbon capture from the economic aspect.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2020

Demand Response Potential from the Bulk Grid Perspective

Gain insight from an exploration of the potential value of demand response (DR) in future power systems. Using hourly DR resource estimates by sub-sector, electrical end-use, and grid service, we incorporate virtual generator models of DR resources into large-scale production cost models, and analyze the grid-level impacts in terms of the ability of DR to reduce system costs and potentially help integrate renewables or reduce system emissions. Additionally, we examine the value of DR, its revenue, and how these change under different system conditions. In this panel session, we will describe our input data and modeling methods, provide an overview of the production cost models used, and summarize key results from analyses in Florida and the western United States. Findings include variations in DR value by end-use and geography, an ability to increase economic PV deployment potential in high penetration systems, and mixed emissions outcomes depending on system composition and fuel prices.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

An adaptive scalable fully implicit algorithm based on stabilized finite element for reduced visco-resistive MHD

The magnetohydrodynamics (MHD) equations are continuum models used in the study of a wide range of plasma physics systems, including the evolution of complex plasma dynamics in tokamak disruptions. However, efficient numerical solution methods for MHD are extremely challenging due to disparate time and length scales, strong hyperbolic phenomena, and nonlinearity. Additionally, therefore the development of scalable, implicit MHD algorithms and high-resolution adaptive mesh refinement strategies is of considerable importance. In this work, we develop a high-order stabilized finite-element algorithm for the reduced visco-resistive MHD equations based on the MFEM finite element library (mfem.org). The scheme is fully implicit, solved with the Jacobian-free Newton-Krylov (JFNK) method with a physics-based preconditioning strategy. Our preconditioning strategy is a generalization of the physics-based preconditioning methods in Chacón et al. (2002) to adaptive, stabilized finite elements. Algebraic multigrid methods are used to invert sub-block operators to achieve scalability. A parallel adaptive mesh refinement scheme with dynamic load-balancing is implemented to efficiently resolve the multi-scale spatial features of the system. Our implementation uses the MFEM framework, which provides arbitrary-order polynomials and flexible adaptive conforming and non-conforming meshes capabilities. Results demonstrate the accuracy, efficiency, and scalability of the implicit scheme in the presence of large scale disparity. The potential of the AMR approach is demonstrated on an island coalescence problem in the high Lundquist-number regime (≥ 10 7 ) with the successful resolution of plasmoid instabilities and thin current sheets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

LightMAT - Continuous fiber malleable thermoset composites with sub-1-minute dwell times; validation of impact performance and evaluation of the efficacy of the compression forming process (CRADA 409 Final Report)

In spite of carbon fiber composite materials’ significant impact on light-weighting, performance, and efficiency in the aerospace industry, adoption of these materials has been slow in high-volume industries such as automotive. Two major barriers to adoption are cost and cycle-time. Current approaches to thermoset composite part production are dependent on in-mold curing of thermosets which are not optimal for high volume, high throughput production due to limitations and inefficiencies associated with the in-mold cure itself. In addition, ancillary activities, such as transport and storage of shelf-life-limited uncured, or B-staged prepreg materials typically necessitate refrigerated transport and storage which significantly impacts the economic and energy costs associated with manufacturing. Furthermore, limited out-life means that trimmings cannot typically be used as they partially cure during initial production leading to high scrap rates (+20% is common). Finally, the need to cure in-mold drives cycle times to multiple minutes in the best cases, and 10’s of minutes to hours in most cases. Mallinda is developing polyimine malleable thermoset prepreg composite materials which have excellent mechanical properties (100 GPa tensile modulus, 2 GPA tensile strength, 2.4% elongation at break) and high operating temperatures (Tg>200°C). At scale, polyimine resins are commensurate in price with commodity epoxy resins. What distinguishes malleable thermoset prepreg from traditional thermoset prepreg materials, is that they are fully cured during Mallinda’s roll-to-roll production of prepreg laminate. This results in 5 key value-differentiating benefits. First, it simplifies manufacturing logistics by enabling ambient transportation and storage, and by significantly extending out-life and shelf-life almost indefinitely. Second, elimination of autoclave curing reduces the economic and energy costs to the customer. Third, scrap rates can be reduced as malleable thermoset prepreg materials are directly reusable. Fourth, the manufacturing consolidation step can be roughly 10x faster than traditional thermosets, because the resin is already cured. Parts can be made via compression forming by the application of heat and pressure to quickly vitrify and consolidate a multilayer part – easily leading to sub 3-minute cycle times (at lab scale we have demonstrated a 20 second dwell time, with room for further optimization). Finally, the closed-loop cradle-to-cradle solution-based recyclability of malleable thermoset composites can also contribute significantly to the future of sustainable lightweight materials. The focus of this project was the development, optimization and validation of malleable thermoset composite materials which exhibit manufacturing cycle times of 3-minute or less, high speed impact performance on par with incumbent technologies, and defect-free consolidation of 3 dimensional parts. Government funding is required on this project because Mallinda is a start-up company whose focus is the development and scale-up of the described technology for introduction to the transportation segment. Unlike incumbent industry players, Mallinda is bringing a completely new and highly relevant malleable thermoset technology to bear on the problem of high throughput composites. As a small business, Mallinda relies on a combination of government R&D funding and private capital to perform development work.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Celestial-body focused dark matter annihilation throughout the Galaxy

Indirect detection experiments typically measure the flux of annihilating dark matter (DM) particles propagating freely through galactic halos. We consider a new scenario where celestial bodies “focus” DM annihilation events, increasing the efficiency of halo annihilation. In this setup, DM is first captured by celestial bodies, such as neutron stars or brown dwarfs, and then annihilates within them. If DM annihilates to sufficiently long-lived particles, they can escape and subsequently decay into detectable radiation. This produces a distinctive annihilation morphology, which scales as the product of the DM and celestial body densities, rather than as DM density squared. We show that this signal can dominate over the halo annihilation rate in γ -ray observations in both the Milky Way Galactic center and globular clusters. We use Fermi and H.E.S.S. data to constrain the DM-nucleon scattering cross section, setting powerful new limits down to ~10 -39 cm 2 for sub-GeV DM using brown dwarfs, which is up to 9 orders of magnitude stronger than existing limits. We demonstrate that neutron stars can set limits for TeV-scale DM down to about 10 -47 cm 2 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

The AMUSING++ Nearby Galaxy Compilation. I. Full Sample Characterization and Galactic-scale Outflow Selection

We present here AMUSING++: the largest compilation of nearby galaxies observed with the MUSE integral-field spectrograph so far. This collection consists of 635 galaxies from different MUSE projects covering the redshift interval 0.0002 < z < 0.1. The sample and its main properties are characterized and described here. It includes galaxies of almost all morphological types, with a good coverage in its color–magnitude diagram, within the stellar mass range between 10{sup 8} and 10{sup 12} M {sub ⊙}, and with properties resembling those of a diameter-selected sample. The AMUSING++ sample is, therefore, suitable for studying, with unprecendented detail, the properties of nearby galaxies at global and local scales, providing us with more than 50 million individual spectra. We use this compilation to investigate the presence of galactic outflows. We exploit the use of combined emission-line images to explore the shape of the different ionized components and the distribution along classical diagnostic diagrams to disentangle the different ionizing sources across the optical extension of each galaxy. We use the cross-correlation function to estimate the level of symmetry of the emission lines as an indication of the presence of shocks and/or active galactic nuclei. We uncovered a total of 54 outflows, comprising ∼8% of the sample. A large number of the discovered outflows correspond to those driven by active galactic nuclei (∼60%), suggesting some bias in the selection of our sample. No clear evidence was found that outflow host galaxies are highly star-forming, and outflows appear to be found within all galaxies around the star-formation sequence.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Elucidating Hydrogen Reaction-Induced Water Desorption from Oxide-Passivated Metal Surfaces for Plasma Applications

Elucidating the mechanisms responsible for sub-microsecond desorption of water and other impurities from electrode surfaces at high heating rates is crucial for understanding pulsed power behavior. Ionization of desorbed impurities in the vacuum regions causes power or current loss; devising methods to limit such desorption during the short time scale of pulsed power is needed to improve corresponding applications. Previous molecular modeling studies have strongly suggested that, under high vacuum conditions, the amount of water impurity desorbing from oxide surfaces on metal electrodes is at a sub-monolayer level at room temperature, which appears insufficient to explain observed pulsed power energy losses at high current densities. In this work, we apply Density Functional Theory (DFT) techniques to show that hydrogen trapped inside iron metal can diffuse into hematite (α-Fe 2 O 3 ) on the metal surface, ultimately reacting with the oxide to form Fe(II) and H 2 O. The latter desorbs at elevated temperature and may explain the anomalous amount of desorbed impurity inferred from pulsed-power experiments. We also apply a suite of characterization techniques to demonstrate that when iron metal is heated to 650 °C, the dominant surface oxide component becomes α-Fe 2 O 3 . The oxide facets exposed are found to be a mixture of (0001), (10-10), and others, in agreement with the DFT models used.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2026

Self-interacting sub-GeV dark matter with strong MeV gamma-ray

Sub-GeV dark matter (DM) with s-channel resonant self-scattering provides a promising framework for addressing small-scale structure problems. However, models that also account for the observed relic abundance through the same resonance are strongly constrained by current γ-ray observations, since the associated signals are significantly enhanced. To overcome this limitation, we propose a framework in which the relic abundance and self-scattering are governed independently by two distinct mediators. As a concrete realization, we present a singlet scalar DM model in which self-scattering is mediated by a vector boson associated with a gauged baryon number, while the relic density is determined by forbidden annihilation into dark Higgs bosons that generate the gauge boson mass. By imposing cosmological, experimental, and theoretical constraints, We identify viable parameter regions that reproduce the observed relic density, alleviate small-scale problems, and remain consistent with current bounds. Notably, the model predicts multiple distinctive MeV γ-ray signals, a significant fraction of which will be testable with next-generation MeV γ-ray telescopes, including the Compton Spectrometer and Imager (COSI).

Models for Dark Matter↗

DOE OSTI2023

Topography and electrostatic interactions of electret fibres in N95 facemasks

Facemasks have been a critical line of defense in the Covid-19 pandemic and have been used for decades to reduce the inhalation of sub-micron aerosols, including bacteria, viruses and nano-materials. These facemasks leverage electrostatic charge properties of non-woven electret fibre mats to remove sub-micron aerosols. However, the topographical and electrostatic properties of these mats have not been well characterized at the nano-scale. In this study, we use atomic force microscopy (AFM) to examine the surface topography of the electret fibres within a commercial respirator fibre mat, use electrostatic force microscopy to map the electrostatic interactions emanating from these fibres, and use synchrotron X-ray scattering to probe polymer morphology. We find that within these mats the fibres exhibit significant heterogeneity in surface topography, electrostatic interactions and polypropylene phase composition. The surface topographies ranged from nano-smooth surfaces to ordered spherulitic structures. Furthermore, the electrostatic interactions varied across fibre length and circumference and are only weakly correlated with surface topographical features. Finally, we use AFM to characterize fibres after filtering a NaCl aerosol and find that the deposited particles are heterogeneous in size and distributed over the fibre surfaces.

36 MATERIALS SCIENCE↗

DOE OSTI2025

A Participation Factor-Based Approach for Defining the EMT Model Boundary for Power System Simulations with Inverter-Based Resources

The increasing penetration of inverter-based resources (IBRs) introduces new challenges to power system simulations, particularly with the emergence of fast electromagnetic transient (EMT) dynamics and sub-synchronous oscillations (SSO) that require time-consuming EMT simulations. To reduce the time cost for simulating a large-scale power grid with IBRs, this paper proposes a novel participation factor-based approach for defining a critical zone for detailed EMT modeling and simulations, which includes the IBRs, synchronous generators, and the network components participating significantly in simulated contingencies. Both model-based and response-based methods are introduced for the estimation of participation factors (PFs). The case study on the 240-bus Western Electricity Coordinating Council (WECC) system demonstrates that the EMT zone determined by the proposed approach can effectively capture power system dynamics involving IBRs.

EMT simulation↗

DOE OSTI2020

Supersymmetric proton decay revisited

Encouraged by the advent of a new generation of underground detectors – JUNO, DUNE and Hyper-Kamiokande – that are projected to improve significantly on the present sensitivities to various baryon decay modes, we revisit baryon decay in the minimal supersymmetric SU(5) GUT. We discuss the phenomenological uncertainties associated with hadronic matrix elements and the value of the strong coupling αs – which are the most important – the weak mixing angle θ W , quark masses including one-loop renormalization effects, quark mixing and novel GUT phases that are not visible in electroweak interaction processes. We apply our analysis to a variety of CMSSM, super- and sub-GUT scenarios in which soft supersymmetry-breaking parameters are assumed to be universal at, above and below the GUT scale, respectively. In many cases, we find that the next generation of underground detectors should be able to probe models with sparticle masses that are O(10) TeV, beyond the reach of the LHC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

A massively parallel time-domain coupled electrodynamics–micromagnetics solver

We present a high-performance coupled electrodynamics–micromagnetics solver for full physical modeling of signals in microelectronic circuitry. The overall strategy couples a finite-difference time-domain approach for Maxwell’s equations to a magnetization model described by the Landau–Lifshitz–Gilbert equation. The algorithm is implemented in the Exascale Computing Project software framework, AMReX, which provides effective scalability on manycore and GPU-based supercomputing architectures. Furthermore, the code leverages ongoing developments of the Exascale Application Code, WarpX, which is primarily being developed for plasma wakefield accelerator modeling. Our temporal coupling scheme provides second-order accuracy in space and time by combining the integration steps for the magnetic field and magnetization into an iterative sub-step that includes a trapezoidal temporal discretization for the magnetization. The performance of the algorithm is demonstrated by the excellent scaling results on NERSC multicore and GPU systems, with a significant (59×) speedup on the GPU using a node-by-node comparison. We demonstrate the utility of our code by performing simulations of an electromagnetic waveguide and a magnetically tunable filter.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Collaborative Research: The Evolution of Magnetic Skeletons During 3D Reconnection. Final report

We investigated how the plasmoid instability affects the evolution of topological features of a magnetic field and the process of magnetic reconnection with three sub-projects. (i) We extensively studied the criterion for plasmoid-mediated current sheet disruption and the onset of fast reconnection. Scaling relations with respect to plasma parameters have been established, using both direct numerical simulations and analytic theories, for the disruption time, the current sheet width, the instability linear growth rate, and the dominant mode wavenumber. (ii) We applied the theories of plasmoid-mediated current sheet disruption to magnetohydrodynamic turbulence and predicted a steepening of the turbulence energy spectrum. This steepening has been confirmed by direct numerical simulations. (iii) We performed numerical simulations of ultraviolet burst events in the solar atmosphere with a spine-dome magnetic topology. The plasmoid instability leads to unsteady reconnection, which is consistent with solar observations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Investigating Electro-Nuclear Interactions in a New Dark Matter Search

Electro-nuclear (EN) interactions are interactions in which an incident electron collides with a nucleus, scattering the electron and creating byproduct particles. Such interactions are of interest to neutrino physicists, who use EN interactions to inform model building of neutrino-nucleus interactions. The Light Dark Matter Experiment (LDMX) is a small-scale, fixed-target, electron beam experiment which seeks to probe for dark matter and mediator particle production in the sub-GeV mass region. The 8GeV LDMX electron beam will serve as an opportunity to study electro-nuclear interactions in their final states in the multi-GeV region. LDMX’s missing energy trigger however, will not be sufficient to efficiently capture EN interactions. An additional trigger needs to be created. Using simulated background events, including EN interactions, for the LDMX experiment, a trigger on momentum was developed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Quantum computing based hybrid solution strategies for large-scale discrete-continuous optimization problems

Technologies for a quantum/classical hybrid approach to solving optimization problems is disclosed. In the illustrative embodiment, an optimization problem is decomposed into two sub-problems. The first sub-problem is solved on a classical computer, and a result from the first sub-problem is provided to a quantum computer. The quantum computer then solves the second sub-problem based on the result of the first sub-problem from the classical computer. The quantum computer can then provide a result to the classical computer to re-solve the first problem. The iterative calculation is continued until an end condition is met.

You, Fengqi↗