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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Constraining solar electron number density via neutrino flavor data at Borexino

Understanding the physics of the deep solar interior, and the more exotic environs of core-collapse supernovae (CCSN) and binary neutron-star (NS) mergers, is of keen interest in many avenues of research. To date, this physics is based largely on simulations via forward integration. While these simulations provide valuable constraints, it could be insightful to adopt the "inverse approach" as a point of comparison. Within this paradigm, parameters of the solar interior are not output based on an assumed model, but rather are inferred based on real data. Here, we take the specific case of solar electron number density, which historically is taken as output from the standard solar model. We show how one may arrive at an independent constraint on that density profile based on available neutrino flavor data from the Earth-based Borexino experiment. The inference technique's ability to offer a unique lens on physics can be extended to other datasets, and to analogous questions for CCSN and NS mergers, albeit with simulated data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1997

Radiative heating of interstellar grains falling toward the solar nebula: 1-D diffusion calculations

As the dense molecular cloud that was the precursor of our Solar System was collapsing to form a protosun and the surrounding solar-nebula accretion disk, infalling interstellar grains were heated much more effectively by radiation from the forming protosun than by radiation from the disk's accretion shock. Accordingly, we have estimated the temperatures experienced by these infalling grains using radiative diffusion calculations whose sole energy source is radiation from the protosun. Although the calculations are 1-dimensional, they make use of 2-D, cylindrically symmetric models of the density structure of a collapsing, rotating cloud. The temperature calculations also utilize recent models for the composition and radiative properties of interstellar grains (Pollack et al. 1994. Astrophys. J. 421, 615-639), thereby allowing us to estimate which grain species might have survived, intact, to the disk accretion shock and what accretion rates and molecular-cloud rotation rates aid that survival. Not surprisingly, we find that the large uncertainties in the free parameter values allow a wide range of grain-survival results: (1) For physically plausible high accretion rates or low rotation rates (which produce small accretion disks), all of the infalling grain species, even the refractory silicates and iron, will vaporize in the protosun's radiation field before reaching the disk accretion shock. (2) For equally plausible low accretion rates or high rotation rates (which produce large accretion disks), all non-ice species, even volatile organics, will survive intact to the disk accretion shock. These grain-survival conclusions are subject to several limitations which need to be addressed by future, more sophisticated radiative-transfer models. Nevertheless, our results can serve as useful inputs to models of the processing that interstellar grains undergo at the solar nebula's accretion shock, and thus help address the broader question of interstellar inheritance in the solar nebula and present Solar System. These results may also help constrain the size of the accretion disk: for example, if we require that the calculations produce partial survival of organic grains into the solar nebula, we infer that some material entered the disk intact at distances comparable to or greater than a few AU. Intriguingly, this is comparable to the heliocentric distance that separates the C-rich outer parts of the current Solar System from the C-poor inner regions.

NASA Center ARC↗
NASA NTRS1996

Determination of Thermal State of Charge in Solar Heat Receivers

The research project at Howard University seeks to develop analytical and numerical capabilities to study heat transfer and fluid flow characteristics, and the prediction of the performance of solar heat receivers for space applications. Specifically, the study seeks to elucidate the effects of internal and external thermal radiation, geometrical and applicable dimensionless parameters on the overall heat transfer in space solar heat receivers. Over the last year, a procedure for the characterization of the state-of-charge (SOC) in solar heat receivers for space applications has been developed. By identifying the various factors that affect the SOC, a dimensional analysis is performed resulting in a number of dimensionless groups of parameters. Although not accomplished during the first phase of the research, data generated from a thermal simulation program can be used to determine values of the dimensionless parameters and the state-of-charge and thereby obtain a correlation for the SOC. The simulation program selected for the purpose is HOTTube, a thermal numerical computer code based on a transient time-explicit, axisymmetric model of the total solar heat receiver. Simulation results obtained with the computer program are presented the minimum and maximum insolation orbits. In the absence of any validation of the code with experimental data, results from HOTTube appear reasonable qualitatively in representing the physical situations modeled.

Glakpe, E. K.↗
DOE OSTI2023

Investigation of Best-Practices and Computationally Inexpensive Radiative Exchange Models for Discrete Element Method Modeling of Aluminosilicate Particles in Concentrating Solar Power Environments

Chemically inert, aluminosilicate based particles have been investigated as both a thermal transport and sensible energy storage medium for concentrating solar power facilities. These particles will experience a wide range of operating temperatures (300-1000 K) and handling conditions (dense to dilute falling particle curtains, dense granular flows, or dense structures), requiring specially-designed and optimized infrastructures. The relative influence of collisional and frictional interactions between particles varies based on temperature-dependent particulate properties and greatly impacts the bulk, granular flow behavior. These underlying physics are captured using discrete element method modeling tools. However, this modeling method is computationally expensive as each particle position and interaction is tracked during the simulation. These modeling methods are further complicated by introducing temperature-dependent particle properties, high-temperature radiative exchange, and directional irradiation sources experienced by granular flows in concentrating solar power environments. In this study, coupled experimental and numerical slump testing of aluminosilicate particles was performed and computationally efficient radiative exchange models were evaluated to establish best-practices for discrete element method models for concentrating solar power environments. The three particle types investigated included Carbobead HSP 30 /60, Carbobead CP 30/60, and Granusil 4030. Existing modeling limitations and computationally-efficient multi-modal heat transfer models were evaluated using Aspherix®, a commercial discrete element method software. High-temperature (< 1073 K) slump testing of aluminosilicate particles was performed to investigate the deviation between experimentally-observed and numerically-predicted angles of repose introduced by computation-time reduction practices including the relaxation of the particle elastic modulus and coarse-graining. Coarse-graining is used to use a single modeled particle that is representative of a collection of smaller particles, decreasing the computational cost at the expense of geometric accuracy. Additionally, relaxation of the elastic modulus is used to reduce computational time at the expense of an increased, modeled particle overlap. Prior studies have determined that aluminosilicate particles retain a high elastic modulus at high temperatures (< 1073 K), requiring small simulation timesteps to ensure resolved contact forces resemble appropriate solid mechanics. A parametric study was performed to evaluate the influence of computation time improvements on the deviation between experimental and modeled angle of repose across high temperatures < 1073 K. Additionally, numerical case studies were performed on candidate particle systems at varying porosities and temperatures. These studies were performed to investigate the influence of computationally-efficient radiative-exchange modeling methods coupled to Aspherix® on modeled accuracy and computation time. The recently-developed distance-based approximation was evaluated in estimating radiative exchange between particles and participating surfaces located in close proximity. The distance based approximation was developed to use tabulated estimates of the radiative distribution factor between individual particles and surfaces in close proximity (< 40 particle radii). These methods were expanded to the aluminosilicate particles of interest, including the influence of particle size distributions. To capture radiative exchange between particles and surfaces not in close proximity (> 40 particle radii) and to capture the absorption of directional irradiation from concentrating solar resources, a volumetrically-averaged radiative distribution factor was calculated between the modeled granular flow and surfaces using Monte Carlo ray-tracing for participating media. Volume-averaged absorption and scattering coefficients were predicted using a volumetric discretization of the modeled domain with monodisperse approximations based on geometric optics and experimentally-determined scattering phase functions for aluminosilicate particles.

14 SOLAR ENERGY↗
DOE OSTI2023

Modeling and control of nuclear–renewable integrated energy systems: Dynamic system model for green electricity and hydrogen production

The need for decarbonization and diversification of energy resources has led to the development of integrated energy systems (IESs), where multiple resources supply more than one energy sector. Here, one such IES with small modular nuclear reactors and renewables (wind and solar) as generating resources, catering to the demand of the electric grid while producing hydrogen for industries, is modeled in this paper. The physics-based component models are represented using the Modelica language and interconnected to form the IES. The control and coordination of the overall system are ensured by designing a suitable control architecture composed of individual subsystem-level controls and supervisory control. The dynamic performance and the load-following capability of the IES are evaluated, while satisfying the safe operational limits of the components. Different configurations and modes of IES operation are considered, where the adaptability of the control system in the presence of varying demands and renewable generations is validated. The simulation results indicate that hydrogen as a flexible load facilitates the supply of varying grid demand. Additionally, the renewables are also accommodated into the IES owing to the flexibility of the balance of plant associated with the nuclear reactors.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2012

Integrating Kinetic Effects into Global Models for Reconnection

Magnetic reconnection is the most striking example of how the coupling between global and kinetic scales can lead to fast energy release. Explosive solar activity, such as coronal mass ejections and flares for example, is widely believed to be due to the release of magnetic energy stored on global scales by magnetic reconnection operating on kinetic scales. Understanding how processes couple across spatial scales is one of the most difficult challenges in all of physics, and is undoubtedly the main obstacle to developing predictive models for the Sun's activity. Consequently, the NASA Living With a Star Program selected a Focused Science Team to attack the problem of cross-scale coupling in reconnection. In this talk I will present some of the results of the Team and review our latest theories and methods for modeling the global-local coupling in solar reconnection.

Antiochos, S. K.↗
DOE OSTI2023

Machine learning surrogate of physics-based building-stock simulator for end-use load forecasting

Building energy models are used to simulate heat and mass transfer and estimate end-use load in buildings. With the proliferation of solar photovoltaics on residential and commercial buildings, increasingly, buildings are expected to provide grid services, for which accurate and computationally efficient building energy simulations and end-use load prediction are imperative. Existing building energy simulation tools, however, have significant computational overhead that make them less practical in real-time deployment for optimization, design, uncertainty quantification and control in building energy management systems. Here this article presents a data-driven machine learning model based on light gradient boosting method (LightGBM) as a surrogate for a physics-based simulator for residential buildings to predict end-use load. The machine learning based surrogate model accounts for time-series related variables, seasonality and trend component of end-use load, and history of end-use load. The accuracy of the surrogate model is assessed on the prediction of the load profiles of 100 different houses in Cook County, Illinois, USA. The LightGBM surrogate model is shown to reduce the root-mean-squared error by 53% relative to a reference decision tree (DT) based model reported previously in the literature. Moreover, the model predicts the load spikes and high-ramp rate events throughout the year which are often the Achilles heel of other models in the literature. The machine learning based surrogate model is demonstrated to be computationally efficient, with a ten-fold reduction in the computational time compared to a physics-based building energy simulation, and suitable for uncertainty analysis and real-time control of building characteristics in response to uncertainty.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1975

Development of flat-plate solar collectors for the heating and cooling of buildings

The relevant design parameters in the fabrication of a solar collector for heating liquids were examined. The objective was to design, fabricate, and test a low-cost, flat-plate solar collector with high collection efficiency, high durability, and requiring little maintenance. Computer-aided math models of the heat transfer processes in the collector assisted in the design. The preferred physical design parameters were determined from a heat transfer standpoint and the absorber panel configuration, the surface treatment of the absorber panel, the type and thickness of insulation, and the number, spacing and material of the covers were defined. Variations of this configuration were identified, prototypes built, and performance tests performed using a solar simulator. Simulated operation of the baseline collector configuration was combined with insolation data for a number of locations and compared with a predicted load to determine the degree of solar utilization.

Ramsey, J. W.↗
DOE OSTI2023

Coupled Experimental and High-Temperature Discrete-Element Method Modeling Studies of Aluminosilicate Particle Handling in Concentrated Solar Power Environments

Chemically inert, aluminosilicate based particles have been investigated as both a thermal transport and sensible energy storage medium for concentrated solar power facilities. These particles will experience a wide range of operating temperatures (300-1000 K) and handling conditions (dense to dilute falling particle curtains, dense granular flows, or dense structures), requiring specially-designed and optimized infrastructures. The relative influence of collisional and frictional interactions between particles varies based on temperature-dependent particulate properties and greatly impacts the bulk, granular flow behavior. These underlying physics are captured using discrete element method modeling tools. However, this modeling method is computationally expensive as each particle position and interaction is tracked during the simulation. These modeling methods are further complicated by introducing temperature-dependent particle properties, high-temperature radiative exchange, and directional irradiation sources experienced by granular flows in concentrated solar power environments. Coupled experimental and numerical studies of aluminosilicate particles in rotary kilns and dense particle curtains were performed for bulk temperatures up to 1073 K. The three particle types investigated included Carbobead HSP 30 /60, Carbobead CP 30/60, and Granusil 4030. Temperature, spatial, and velocity profile data were extracted from experimental runs using embedded K-type thermocouple probes and particle image velocimetry techniques. Experimental and numerical studies were compared using spatial temperature profiles, velocity fields, and shape profiles of the bulk, granular flows. Numerical models were developed using commercially available discrete element method modeling software, Aspherix®. Existing Aspherix® functionality was expanded by introducing coupled radiative exchange modeling tools. The laboratory-scale rotary kiln was developed to investigate the steady-state heat and mass transfer performance of aluminosilicate particles based on particle type, bulk handling temperature, and wall roughness. The rotational speed of the rotary kiln was varied to control the relative impact of collisional and frictional effects upon the granular flow behavior. Heat and mass transfer performance was categorized based on the Froude number and the observed flow regimes of slipping, rolling, cascading, and centrifuging. Coupled discrete element method modeling studies were used to evaluate the effects of temperature-dependent, particulate mechanical properties upon bulk flow behavior and upon the relative effects of radiative, advective, and/or conductive heat transfer. A high-temperature (< 1073 K) falling particle curtain was similarly fabricated to investigate the heat and mass transfer performance of aluminosilicate particles in particle handling situations dominated by inter-particle collisions. The impact of particle type, flow preheat temperatures (< 1073K), and bulk mass flow rates were investigated upon the particle curtain shape, temperature, and velocity profiles. Coupled discrete element method modeling studies were performed to evaluate the varying impact of temperature-dependent, particulate mechanical properties on the bulk flow behavior and the temperature profile of the particle curtain.

14 SOLAR ENERGY↗
DOE OSTI2024

Solar neutrinos and ν 2 visible decays to ν 1

Experimental bounds on the neutrino lifetime depend on the nature of the neutrinos and the details of the potentially new physics responsible for neutrino decay. In the case where the decays involve active neutrinos in the final state, the neutrino masses also qualitatively impact how these manifest themselves experimentally. In order to further understand the impact of nonzero neutrino masses, we explore how observations of solar neutrinos constrain a very simple toy model. We assume that neutrinos are Dirac fermions and there is a new massless scalar that couples to neutrinos such that a heavy neutrino— ν 2 with mass m 2 —can decay into a lighter neutrino— ν 1 with mass m 1 —and a massless scalar. We find that the constraints on the new physics coupling depend, sometimes significantly, on the ratio of the daughter-to-parent neutrino masses and that, for large-enough values of the new physics coupling, the “dark side” of the solar neutrino parameter space— sin 2 θ 12 ∼ 0.7 —provides a reasonable fit to solar neutrino data, if only B 8 or Be 7 neutrino data alone are considered, but no allowed region is found in the combined analysis. Our results generalize to other neutrino-decay scenarios, including those that mediate ν 2 → ν 1 ν ¯ 3 ν 3 when the neutrino mass ordering is inverted mass and m 2 > m 1 ≫ m 3 , the mass of ν 3 . Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2025

Solar Neutrino Detection with a Pixelated Liquid-Argon Time Projection Chamber

This thesis presents a study of low-energy solar neutrino detection using large-scale LArTPCs, focussing on novel pixelated readout technologies. Solar neutrinos offer a unique probe of fundamental neutrino properties and solar physics, but their detection in the MeV range is challenged by backgrounds. We investigate two complementary technologies: SoLAr, which integrates LArPix-based pixelated charge collection with Silicon Photomultipliers (SiPMs) in a hybrid anode design for simultaneous charge and light detection; and Q-Pix, a triggerless pixelated readout architecture based on charge integrate-reset circuits with local clocks, where Reset Time Differences encode ionisation waveforms via time-to-charge conversion. Two SoLAr prototypes were developed and operated, demonstrating VUV-sensitive SiPM performance in liquid argon and accurate charge-light signal matching with a charge detection threshold of $\sim 100 \mathrm{keV}$. We also implement a complete simulation and reconstruction framework, incorporating realistic detector geometry, electron transport, readout response, and detailed signal and background models, including intrinsic argon and radon progeny, as well as site-specific $\gamma$-ray and neutron fluxes. For Q-Pix, we demonstrate that with a pixel size of $4\times 4$ mm$^2$ and a reset threshold of 1 fC ($\sim 0.1475$ MeV), full-scale operation produces data volumes below 1 PB per 10 ktonne-year. For SoLAr, assuming a shielded DUNE-like detector and 100 ktonne-year exposure, we project uncertainties of $0.90\times 10^{-5}$ eV$^2$ on $\Delta m^2_{21}$ and 0.033 on $\sin^2\theta_{12}$, improving to $0.46\times 10^{-5}$ eV$^2$ and 0.025 with 400 kilotonne-year. At this higher exposure, we also obtain a day–night flux asymmetry at the level of $( -5.6 \pm 3.6 ) \%$. Combining Monte Carlo modelling, hardware validation, and advanced reconstruction techniques, this work establishes a path toward next-generation ktonne-scale LArTPCs as observatories for precision solar neutrino physics.

Ruiz Ferreira, Guilherme [Manchester U.] (ORCID:00↗
NASA NTRS1991

Evidence of chaotic pattern in solar flux through a reproducible sequence of period-doubling-type bifurcations

Presented here is a preliminary study of the limits to solar flux intensity prediction, and of whether the general lack of predictability in the solar flux arises from the nonlinear chaotic nature of the Sun's physical activity. Statistical analysis of a chaotic signal can extract only its most gross features, and detailed physical models fail, since even the simplest equations of motion for a nonlinear system can exhibit chaotic behavior. A recent theory by Feigenbaum suggests that nonlinear systems that can be led into chaotic behavior through a sequence of period-doubling bifurcations will exhibit a universal behavior. As the control parameter is increased, the bifurcation points occur in such a way that a proper ratio of these will approach the universal Feigenbaum number. Experimental evidence supporting the applicability of the Feigenbaum scenario to solar flux data is sparse. However, given the hypothesis that the Sun's convection zones are similar to a Rayleigh-Bernard mechanism, we can learn a great deal from the remarkable agreement observed between the prediction by theory (period doubling - a universal route to chaos) and the amplitude decrease of the signal's regular subharmonics. The authors show that period-doubling-type bifurcation is a possible route to a chaotic pattern of solar flux that is distinguishable from the logarithm of its power spectral density. This conclusion is the first positive step toward a reformulation of solar flux by a nonlinear chaotic approach. The ultimate goal of this research is to be able to predict an estimate of the upper and lower bounds for solar flux within its predictable zones. Naturally, it is an important task to identify the time horizons beyond which predictability becomes incompatible with computability.

Ashrafi, S.↗
DOE OSTI2026

The Energy Exascale Earth System Model Version 3: 2. Overview of the Coupled System

The Energy Exascale Earth System Model version 3 (E3SMv3) represents the latest advancement in Earth system modeling developed by the U.S. Department of Energy (DOE). Building upon previous versions, E3SMv3 introduces significant updates across its coupled components to enhance capability and improve fidelity. The atmosphere component incorporates advancements in chemistry, aerosol-cloud interactions, convection, and microphysics. The ocean features a new time-stepping scheme and a higher-resolution unstructured mesh with sub-ice-shelf cavities, while the sea ice model integrates advanced snow and ice physics for more realistic cryospheric simulations. The land model introduces prognostic vegetation dynamics and a new sub-grid topographic treatment of solar radiation. A new tri-grid configuration harmonizes the horizontal grids of the land and river components for improved process coupling. It is enabled by a new non-linear remapping between the atmosphere and land. E3SMv3 underwent extensive testing through a comprehensive simulation campaign, including pre-industrial control, idealized CO 2 experiments, and historical simulations spanning 1850–2024. The model demonstrates significant improvements in simulating the evolution of the historical surface temperature, particularly addressing the “pothole cooling” bias in earlier versions. Reduced aerosol-related forcing contributes to more realistic radiative forcing and better alignment with the observational record. Ocean heat content (OHC) and sea ice trends are also improved as a result.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Soft x-ray spectroscopy of ammonium sulfate aerosols at varied pH conditions

Aqueous aerosols are useful model systems for understanding the physical chemistry that takes place in the Earth’s atmosphere, as well as the chemistry of other solar system objects. Ammonium sulfate aerosols are impacted by anthropogenic sources such as farming and shipping and are understood to be important seeds of cloud nucleation in the atmosphere, affecting climate. X-ray photoelectron spectroscopy and near edge x-ray absorption fine structure spectroscopy were used in tandem to probe the surface and bulk properties of aqueous (NH 4 ) 2 SO 4 , respectively. Aerosolized solutions of (NH 4 ) 2 SO 4 , some altered with NaOH to modify pH, were introduced via an aerodynamic lens to a velocity map imaging instrument for detection. The results show that as pH and sodium cation concentration increase, sulfate anion and ammonia become more prevalent at the surface, and the aerosol surface appears to become drier. However, most of the aerosol remains aqueous, with ion concentrations insensitive to the addition of NaOH. Density functional theory calculations were also performed to probe the coordination environment at the aerosol surfaces to understand the underlying phenomena. Finally, the changes seen on the surface of the aerosol underscore the importance of pH in regulating the structure and chemical properties of atmospherically relevant aerosols.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Particle trajectory representation learning with masked point modeling

Liquid argon time projection chambers (LArTPCs) offer millimeter-scale 3D images of particle trajectories, enabling precision studies of neutrino oscillation, detection of supernova and solar neutrinos, searches for exotic dark matter, and proton decay. Current approaches utilize supervised machine learning models, requiring extensive simulations of particle physics and detector response that can introduce bias. Self-supervised learning (SSL), a machine learning approach that learns useful representations of unlabeled data from the data itself, has significantly advanced how large datasets are utilized for representation learning; however, its potential for applications to sensory data in high precision particle physics experiments remains largely unexplored. We introduce the Point-based liquid argon masked autoencoder (PoLAr-MAE), a self-supervised framework that learns physically meaningful representations directly from unlabeled LArTPC images. PoLAr-MAE achieves remarkable data efficiency for a point-level segmentation task, outperforming fully supervised methods in low data regimes. Linear classifiers on model outputs demonstrate robust performance across multiple downstream tasks. Our results position sensor-level SSL as a practical foundation model strategy for LArTPCs.

Young, Samuel [Stanford Univ., CA (United States)]↗
NASA NTRS1975

Applications of numerical codes to space plasma problems

Solar wind, earth's bowshock, and magnetospheric convection and substorms were investigated. Topics discussed include computational physics, multifluid codes, ionospheric irregularities, and modeling laser plasmas.

Northrop, T. G.↗
NASA NTRS1977

Computer simulations of planetary accretion dynamics - Sensitivity to initial conditions

A computer simulation program which generates mature planetary systems using only Newtonian physics and accretion with unit sticking efficiency is examined. The dependence of the simulation on a variety of radial and vertical density distribution laws, on the ratio of gas to dust in the solar nebula, on the total nebular mass, and on the orbital eccentricity of the accreting grains is explored. To approach physically realistic models, these parameters are altered according to various empirically- and theoretically-suggested criteria. The program is found to generate many recognizable planetary systems, including multiple-star systems with accompanying planets; single stars surrounded only by asteroids; and systems with large Jovian planets, planets similar to Pluto, or objects of asteroidal mass, as well as the usual terrestrial planets. Planetary spacing in the simulation obeys a relation of the Titius Bode variety; in general, the number of planets per system is inversely proportional to the orbital eccentricity. Some reservations about the simulation program are expressed; however, it does support the idea of abundant and diverse planetary systems throughout the galaxy.

Isaacman, R.↗
NASA NTRS1979

Elementary analytic models of climate. 1: The mean global heat balance

Climate models based on global radiative equilibrium are normally so complicated that they require extensive computer codes to provide adequate accuracy. However, by simply modifying the concept of a gray atmosphere, a reasonably correct mean global temperature is obtained. This elementary model is then used to estimate the effects of changes in the abundances of minor infrared absorbers and changes in the solar constant or earth albedo. When applied to a Budyko-Sellers zonally averaged model, the quasi-gray model could give a physical basis for the latitude dependence of outgoing radiation and of opacity due to H2O vapor content. The latter effect constitutes an important positive feedback on surface temperature.

Chamberlain, J. W.↗