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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Particle Physics of the Dark Sector

The mystery associated with a proposed Dark Sector of phenomena that are separate from the standard model of particle physics is described. A Dark Sector may possess matter particles, force carriers which mediate their interactions, and new interactions and symmetries that are beyond the standard model of particle physics. Various approaches for Dark Sector searches are described, including those at the energy frontier at the Large Hadron Collider, in astrophysical interactions with both terrestrial experiments and those in space-born platforms. Searches using low energy photons from microwave energies in cryogenic environments to x-ray energies are also described. While there is no noncontroversial evidence for Dark Sector phenomena presently, new searches with more modern equipment and analysis methods are exploring regions of phase space that have not been available before now, indicating ongoing interest and excitement in this research.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Modeling impacts of ice-nucleating particles from marine aerosols on mixed-phase orographic clouds during 2015 ACAPEX field campaign

Abstract. A large fraction of annual precipitation over the western United States comes from wintertime orographic clouds associated with atmospheric rivers (ARs). Transported African and Asian dust and marine aerosols from the Pacific Ocean may act as ice-nucleating particles (INPs) to affect cloud and precipitation properties over the region. Here we explored the effects of INPs from marine aerosols on orographic mixed-phase clouds and precipitation at different AR stages for an AR event observed during the 2015 ACAPEX field campaign under low dust (<0.02 cm−3) conditions. Simulations were conducted using the chemistry version of the Weather Research and Forecasting Model coupled with the spectral-bin microphysics at 1 km grid spacing, with ice nucleation connected with dust and marine aerosols. By comparing against airborne and ground-based observations, accounting for marine INP effects improves the simulation of AR-precipitation. The marine INPs enhance the formation of ice and snow, leading to less shallow warm clouds but more mixed-phase and deep clouds, as well as to a large spillover effect of precipitation after AR landfall. The responses of cloud and precipitation to marine INPs vary with the AR stages, with more significant effects before AR landfall and post-AR than after AR landfall, mainly because the moisture and temperature conditions change with the AR evolution. This work suggests weather and climate models need to consider the impacts of marine INPs since their contribution is notable under low dust conditions despite the much lower relative ice nucleation efficiency of marine INPs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Artificial Intelligence Applications in Renewable Energy

Addressing new methodologies in deep learning (DL), machine learning (ML) and artificial intelligence (AI), the webinar speakers will provide an overview of the literature spanning these three overlapping fields as applied to energy systems research. The audience will learn how developments in these areas have added new capabilities for pattern recognition and predictive modeling that are complementary to more traditional modeling approaches used in energy systems research. The speakers will illustrate several use cases of these new approaches in the energy space, such as physics-guided neural networks to improve ML regressions for solar data and how AI agents can be used to explore power plant operations.

40 EE - Geothermal Technologies Office (EE-4G)↗
DOE OSTI2021

Accessibility and Availability of Gas Stations for Liquid Fuel Supply During Severe Weather Events

Energy infrastructure is a pivotal lifeline with wider inter-dependencies. Electric power is essential to the continued functioning of critical assets; liquid fuels and other physical primary energy commodities that are used to supply the local energy needs of these assets during extreme events when electricity infrastructure is compromised. During Superstorm Sandy, the disruption of fuel supplies in the Tri-state area necessitated increasing situational awareness about oil and natural gas (ONG) systems to redirect fuel supplies to first responders and for restoration efforts. During winter storm events over the past several years, the demand for ONG for heating and power generation has skyrocketed in the north-east, which subsequently had caused ONG price to hit their highest level in years. ONG is a major energy source for restoration and recovery activities. However, very little, if any, situational awareness information about ONG supply and demand is available to those coordinating emergency efforts. Often this lack of information is due to the decentralized nature of the ONG supply chain and proprietary data maintained by private entities. To understand the impact of fuel availability on response and recovery efforts, this research focuses on (i) determining the accessibility to gas stations for liquid fuel supply across space and time, and (ii) examining the spatio-temporal variation of fuel availability and demand during extreme weather events. The broader scope of the project focuses on providing spatio-temporal situational awareness information about ONG availability and demand across the fuel supply chain for positioning of resources for response activities.

Kar, Bandana↗
DOE OSTI2022

Snowmass2021: Vera C. Rubin Observatory as a Flagship Dark Matter Experiment

Establishing that Vera C. Rubin Observatory is a flagship dark matter experiment is an essential pathway toward understanding the physical nature of dark matter. In the past two decades, wide-field astronomical surveys and terrestrial laboratories have jointly created a phase transition in the ecosystem of dark matter models and probes. Going forward, any robust understanding of dark matter requires astronomical observations, which still provide the only empirical evidence for dark matter to date. We have a unique opportunity right now to create a dark matter experiment with Rubin Observatory Legacy Survey of Space and Time (LSST). This experiment will be a coordinated effort to perform dark matter research, and provide a large collaborative team of scientists with the necessary organizational and funding supports. This approach leverages existing investments in Rubin. Studies of dark matter with Rubin LSST will also guide the design of, and confirm the results from, other dark matter experiments. Supporting a collaborative team to carry out a dark matter experiment with Rubin LSST is the key to achieving the dark matter science goals that have already been identified as high priority by the high-energy physics and astronomy communities.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

In Hot Water! The Challenges and Barriers of Decarbonizing Water Heating in Multifamily Buildings: Preprint

Domestic hot water heating is responsible for 32% of the total energy consumption in multifamily buildings and offers a significant decarbonization opportunity. An extensive market assessment was conducted to understand and document key technical and economic barriers to electrification of domestic water heating in multifamily buildings throughout the U.S. Through the program, 77 interviews were conducted to understand key market drivers and technical challenges associated with electrification of water heating systems in both retrofit and new construction scenarios. Interviewees encompassed a wide range of stakeholders in the ecosystem surrounding water heating systems, including suppliers, manufacturers, designers, owners, utilities, and developers. This paper documents key interview takeaways, including an extensive list of market barriers, technical challenges, and sought-after technology attributes that can inform pertinent design criteria for electric water heating research, development, and deployment efforts. Among economics and energy efficiency features, interviewees overwhelmingly alluded to space constraints, cold air exhaust, and lack of clear guidance regarding distributed versus centralized design selections as key challenges associated with mass adoption of electric water heating. Owners and developers seek systems with minimal footprint, which maximize rentable space and profits. Moreover, distributed heat pump solutions should balance ducting costs that mitigate cold exhaust entrainment into conditioned zones. Lastly, the market needs clear guidance regarding the selection of distributed versus central electric hot water systems.

challenges of water heating electrification↗
DOE OSTI2025

Corrigendum to “The Emissions Model Intercomparison Project (Emissions-MIP): quantifying model sensitivity to emission characteristics” published in Atmos. Chem. Phys., 23, 14779–14799, 2023

Anthropogenic emissions of aerosols and precursor compounds are known to significantly affect the energy balance of the Earth–atmosphere system, alter the formation of clouds and precipitation, and have a substantial impact on human health and the environment. Global models are an essential tool for examining the impacts of these emissions. In this study, we examine the sensitivity of model results to the assumed height of SO 2 injection, seasonality of SO 2 and black carbon (BC) particulate emissions, and the assumed fraction of SO 2 emissions that is injected into the atmosphere as particulate phase sulfate (SO 4 ) in 11 climate and chemistry models, including both chemical transport models and the atmospheric component of Earth system models. We find large variation in atmospheric lifetime across models for SO 2 , SO 4 , and BC, with a particularly large relative variation for SO 2 , which indicates that fundamental aspects of atmospheric sulfur chemistry remain uncertain. Of the perturbations examined in this study, the assumed height of SO 2 injection had the largest overall impacts, particularly on global mean net radiative flux (maximum difference of -0.35?W?m-2), SO2 lifetime over Northern Hemisphere land (maximum difference of 0.8?d), surface SO 2 concentration (up to 59?% decrease), and surface sulfate concentration (up to 23?% increase). Emitting SO 2 at height consistently increased SO 2 and SO 4 column burdens and shortwave cooling, with varying magnitudes, but had inconsistent effects across models on the sign of the change in implied cloud forcing. The assumed SO 4 emission fraction also had a significant impact on net radiative flux and surface sulfate concentration. Because these properties are not standardized across models this is a source of inter-model diversity typically neglected in model intercomparisons. These results imply a need to ensure that anthropogenic emission injection height and SO 4 emission fraction are accurately and consistently represented in global models.

Ahsan, Hamza [Pacific Northwest National Laborator↗
DOE OSTI2024

Astrometric Microlensing by Primordial Black Holes with the Roman Space Telescope

Abstract Primordial black holes (PBHs) could explain some fraction of dark matter and shed light on many areas of early-Universe physics. Despite over half a century of research interest, a PBH population has so far eluded detection. The most competitive constraints on the fraction of dark matter comprised of PBHs ( f DM ) in the (10 −9 –10) M ⊙ mass ranges come from photometric microlensing and bound f DM ≲ 10 −2 –10 −1 . With the advent of the Roman Space Telescope with its submilliarcsecond astrometric capabilities and its planned Galactic Bulge Time Domain Survey (GBTDS), detecting astrometric microlensing signatures will become routine. Compared with photometric microlensing, astrometric microlensing signals are sensitive to different lens masses–distance configurations and contain different information, making it a complimentary lensing probe. At submilliarcsecond astrometric precision, astrometric microlensing signals are typically detectable at larger lens–source separations than photometric signals, suggesting a microlensing detection channel of pure astrometric events. We use a Galactic simulation to predict the number of detectable microlensing events during the GBTDS via this pure astrometric microlensing channel. Assuming an absolute astrometric precision floor for bright stars of 0.1 mas for the GBTDS, we find that the number of detectable events peaks at ≈10 3 f DM for a population of 1 M ⊙ PBHs and tapers to ≈10 f DM and ≈100 f DM at 10 −4 M ⊙ and 10 3 M ⊙ , respectively. Accounting for the distinguishability of PBHs from stellar lenses, we conclude the GBTDS will be sensitive to a PBH population at f DM down to ≈10 −1 –10 −3 for (10 −1 –10 2 ) M ⊙ likely yielding novel PBH constraints.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Extending the Air and Moisture Leakage Calculator to add Residential Buildings and Additional Commercial Buildings

The DOE Windows and Building Envelope Research and Development Roadmap for Emerging Technologies shows that in 2010, infiltration was responsible for 4 quads of space conditioning primary energy use in the residential and commercial sectors. The relative contribution of air leakage in building heating and cooling load is increasing with improvement in the thermal resistance of building envelopes. Advanced air barrier technologies and construction practices have been developed to reduce air leakage in buildings. However, limited information on the impact of air barrier technologies on energy consumption and the durability of buildings has hindered their adoption. In the past Oak Ridge National Laboratory (ORNL), the National Institute of Standards and Technology (NIST), Air Barrier Association of America (ABBA), and U.S.-China Clean Energy Research Center for Building Energy Efficiency (CERC-BEE) collaborated to develop an online calculator that estimates the potential energy and cost savings in major U.S., Canadian and Chinese cities from improvement in air tightness in commercial buildings. In 2018–2019, the calculator was expanded to add moisture transfer calculations given that air leakage through the building envelope can have a significant impact on moisture transfer and associated impacts. In this study, the calculator is expanded further by adding data for two additional commercial buildings (strip mall and primary school) and a residential building. The team investigated the impact of airtightness on energy consumption and moisture transfer of the added buildings. The study includes the analysis of air tightness in 52 major cities in the U.S. and 5 cities in Canada.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Characteristics of Precipitation and Mesoscale Convective Systems Over the Peruvian Central Andes in Multi 5‐Year Convection‐Permitting Simulations

Abstract Using the Weather Research and Forecasting model with two planetary boundary layer schemes, ACM2 and MYNN, convection‐permitting model (CPM) regional climate simulations were conducted for a 6‐year period, including a one‐year spin‐up period, at a 15‐km grid spacing covering entire South America and a nested convection‐permitting 3‐km grid spacing covering the Peruvian central Andes region. These two CPM simulations along with a 4‐km simulation covering South America produced by National Center for Atmospheric Research (NCAR), three gridded precipitation products, and rain gauge data in Peru and Brazil, are used to document the characteristics of precipitation and mesoscale convective systems (MCSs) in the Peruvian central Andes region. Results show that all km‐scale simulations generally capture the spatiotemporal patterns of precipitation and MCSs at both seasonal and diurnal scales, although biases exist in aspects such as precipitation intensity and MCS frequency, size, propagation speed, and associated precipitation intensity. The 3‐km simulation using MYNN scheme generally outperforms the other simulations in capturing seasonal and diurnal precipitation over the mountain, while both it and the 4‐km simulation demonstrate superior performance in the western Amazon Basin, based on the comparison to the gridded precipitation products and gauge data. Dynamic factors, primarily low‐level jet and terrain‐induced uplift, are the key drivers for precipitation and MCS genesis along the east slope of the Andes, while thermodynamic factors control the precipitation and MCS activity in the western Amazon Basin and over elevated mountainous regions. The study suggests model improvements and better model configurations for future regional climate projections.

Meteorology & Atmospheric Sciences↗
DOE OSTI2024

Addressing Experimental Challenges in Probing Dark Energy with Accuracy and Precision with the Rubin Observatory Legacy Survey of Space & Time (LSST)

With support from this award, the Stanford group under the leadership of PI Patricia Burchat focused on pixel-level algorithms that are key to the investigation of dark energy with the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). The work was carried out through strong engagement in the DOE-supported LSST Dark Energy Science Collaboration (DESC), for which the PI served as Deputy Spokesperson (07/2019 - 07/2021) and Technical Coordinator (07/2021 - 07/2023). Members of the Burchat group are Full DESC members and are among scientists who have been accepted to join the Rubin Observatory System Integration, Test, and Commissioning (SIT-Com) effort. The specific intellectual focus of the group was the optimization of gravitational lensing as a probe of the evolution of the distribution of dark matter in space and time to learn about the nature of dark energy. The Stanford group pursued an integrated research program to understand in detail, and then remediate or calibrate, systematic effects that could limit the sensitivity of the LSST to cosmic shear as a dark energy probe -- particularly those related to our understanding of the atmospheric point spread function (PSF), challenges associated with blended galaxy images, and impacts of residual camera artifacts. Key to this work was developing, enhancing, and validating the fidelity of simulations that play a key role in the development of our understanding of subtle systematic biases and then using these simulations to develop techniques to characterize and mitigate biases, and associated algorithms for implementation in the LSST or DESC science pipelines. The group’s work included contributions to the open-source GalSim simulation package, which is widely used in the community; simulations and studies of spatial correlations of atmospheric PSFs; studies of temporal correlations of the atmospheric PSF; impacts of chromatic PSFs on cosmic shear calibration; continued studies of anisotropic Gaussian process interpolation of PSF models across the focal plane; and measuring and mitigating impacts of residual camera artifacts on cosmic shear. A primary impact of this work is that it increases the scientific discovery potential of the DOE and NSF investments in the Rubin Observatory Legacy Survey of Space \& Time, by addressing challenges in interpreting astronomical images through more accurate descriptions of the blurring of images due to the atmosphere. Specifically, this work impacts our ability to understand the fundamental nature of dark energy.

Burchat, Patricia Rose↗
DOE OSTI2026

Short‐Term Hourly Weather Forecasting Using PredRNN With Image Preprocessing

Global weather forecast models are vital tools with numerous applications, including public safety, agriculture, and transportation. Recent advancements in artificial intelligence (AI) and deep learning (DL) have shown the potential to enhance weather forecasting accuracy and speed. In this study, we developed a short-term hourly weather forecast framework with a wavelet transform function for data preprocessing and a spatiotemporal DL model, PredRNN, for predicting five surface atmospheric variables, including wind speed and direction, mean sea level pressure (MSLP), temperature, and precipitation. The framework demonstrated promising results. It produces global forecasts at 0.25° (∼25 km) with a 1-day lead time RMSE of 1.8 m/s for wind components, 180 Pa for MSLP, and 1.8 K for temperature. Although our model does not surpass state-of-the-art AI weather forecast models across all metrics, it outperforms these models in precipitation forecasting and wind prediction at short lead times and achieves comparable accuracy for MSLP. Its native hourly forecasting capability, together with training on widely accessible GPU hardware, contributes meaningfully to the advancement of accessible DL weather forecasting methods. Our work highlights the importance of integrating temporal components and data transformation techniques to improve the predictability and accuracy of weather forecasts.

Tran, Hoang [Pacific Northwest National Laboratory↗
DOE OSTI2021

Effects of pillar design on the thermal performance of vacuum-insulated glazing

Vacuum-insulated glazing (VIG) with a low-emittance coating has a great market potential as an effective transparent insulator. The thermal insulating performance of VIG is determined by its design, including material selection and configuration of different components. Thermal conductance of the vacuum gap as a transport bottleneck is one of the primary factors controlling the thermal transport across VIG. In particular, because support pillars provide the main thermal transport channels across the vacuum gap, increasing the pillar thermal resistance is a key strategy for creating effective thermal insulation while maintaining the vacuum space. Here, the effects of various pillar design parameters, such as thermal conductivity, geometry, and arrangement, on the VIG thermal performance were comprehensively investigated via the finite element method. In addition, analytical models for thermal transport were examined and thermal conductance across the VIG unit was experimentally measured for validation. The pillar design parameters, especially the height, shape, spacing, and arrangement of the pillars, showed significant effects on the thermal performance of VIG. This research also shows that the smaller contact area for horizontal pillars can effectively decrease the heat loss by more than 30%. Because current VIG analytical equations of thermal performance are only applicable to cylindrical pillars, an analytical equation that can better describe the thermal performance of rectangular parallelepiped pillars is presented, along with a discussion about the mechanism of thermal transfer for different pillar shapes. Thermo-mechanical analyses based on 3D FEM simulations can provide valuable insights into the effect of various design parameters on the overall performance the VIG, allowing for the development of an optimal VIG design.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Momentum-resolved superconducting energy gaps of Sr 2 RuO 4 from quasiparticle interference imaging

Sr 2 RuO 4 has long been the focus of intense research interest because of conjectures that it is a correlated topological superconductor. It is the momentum space ( k -space) structure of the superconducting energy gap Δ i ( k ) on each band i that encodes its unknown superconducting order parameter. However, because the energy scales are so low, it has never been possible to directly measure the Δ i ( k ) of Sr 2 RuO 4 . In this work, we implement Bogoliubov quasiparticle interference (BQPI) imaging, a technique capable of high-precision measurement of multiband Δ i ( k ). At T = 90 mK,we visualize a set of Bogoliubov scattering interference wave-vectors q j : j = 1 – 5 consistent with eight gap nodes/minima that are all closely aligned to the (±1, ±1) crystal lattice directions on both the α and β bands. Taking these observations in combination with other very recent advances in directional thermal conductivity, temperature-dependent Knight shift, time-reversal symmetry conservation, and theory, the BQPI signature of Sr 2 RuO 4 appears most consistent with Δ i ( k ) having d x 2 – y 2 ( B 1 g ) symmetry.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Integrated design of aluminum-enriched high-entropy refractory B2 alloys with synergy of high strength and ductility

Refractory high-entropy alloys (RHEAs) are promising high-temperature structural materials. Their large compositional space poses great design challenges for phase control and high strength-ductility synergy. The present research pioneers using integrated high-throughput machine learning with Monte Carlo simulations supplemented by ab initio calculations to effectively navigate phase selection and mechanical property predictions, developing single-phase ordered B2 aluminum-enriched RHEAs (Al-RHEAs) demonstrating high strength and ductility. These Al-RHEAs achieve remarkable mechanical properties, including compressive yield strengths up to 1.7 gigapascals, fracture strains exceeding 50%, and notable high-temperature strength retention. They also demonstrate a tensile yield strength of 1.0 gigapascals with a ductility of 9%, albeit with B2 ordering. Furthermore, we identify valence electron count domains for alloy ductility and brittleness with the explanation from density functional theory and provide crucial insights into elemental influence on atomic ordering and mechanical performance. The work sets forth a strategic blueprint for high-throughput alloy design and reveals fundamental principles governing the mechanical properties of advanced structural alloys.

Science & Technology - Other Topics↗