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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 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Spatio-temporal and weather characterization of road loads of electrified heavy-duty commercial vehicles across U.S. interstate roads

Adoption of battery electric vehicles (BEV) in heavy duty (HD) commercial freight transportation is difficult due to technological and economic hurdles. Beyond safety and compliance, fleet and operational logistics necessitate both high uptime and parity with diesel system productivity/Total Cost of Ownership to support widespread deployment of electric powertrains. However, relatively high energy storage costs, along with the higher weight of BEV systems, limit the viability of HD commercial freight transport to shorter-range applications where smaller batteries will serve for mission energy requirements (single operational shift). Knowing the energy consumption and operating variations of these commercial vehicle systems is crucial for effectively sizing the energy storage systems. This paper is the first in a series of studies to understand the regional specific operating design domain variations of commercial Class 8 HD trucks and the associated impact to their energy requirements. In particular, the local weather conditions are shown to influence the total vehicle energy usage. Further, the impact of temperature, pressure, and humidity changes are shown to impact the local air density. This is needed to calculate aerodynamic drag on vehicles and has been found to play a significant role in the overall performance of a vehicle. Although the methodology of calculating air density varies only slightly throughout the literature, the application to transportation has still been limited. This study provides a means by which air density can be estimated for the contiguous U.S. using the NOAA MADIS dataset. These air density estimates were then used to determine vehicle performance in varying regions of the country to highlight the importance of consideration of weather variables when monitoring vehicle performance, but also to provide recommendations based on these locales upon fleet conversion to BEVs.

Moore, Amy↗
DOE OSTI2023

Techno Economic Analysis Development for Enhanced Weathering and Marine Carbon Dioxide Removal

Enhanced weathering and marine carbon dioxide removal (CDR) are emerging technologies that can aid in the direct removal of CO2 from the atmosphere. This poster presents on NETL’s active (ongoing) work on the techno-economic analysis (TEA) of enhanced weathering and marine CDR. Financial assumptions will be common with already released Direct Air Capture Case Studies

Leptinsky, Sarah↗
DOE OSTI2023

Weather-detecting devices and related methods

A weather-detecting device (100) can include a substrate (102) and a detection region (106) exposed to an environment within which the weather-detecting device (100) is situated when in use. An array (110) of heating elements (112) can be mounted at a first side of the substrate (102), with at least one surface of each heating element (112) in the array (110) being positioned within the detection region (106). A controller can be electrically coupled to the array (110) of heating elements (112), and the controller can individually address each heating element (112) in the array (110) to selectively pass electrical current through each heating element (112).

Garrett, Timothy John↗
DOE OSTI2025

The relative importance of building design parameters in reducing energy use and sensible heat release from buildings in light of forecasted future weather data and building coverage ratio

Buildings typically have a 60-to-75-year lifespan before they require significant maintenance or modifications. However, most builders evaluate the performance of their new buildings using whole-building energy simulation tools based on the current typical meteorological year (TMY) file or actual meteorological year. The energy use consumption and sensible heat release pattern observed from buildings could potentially change based on shifting global climates. Therefore, the recommended energy-efficiency design parameters might also change during these periods. In this study, we evaluate the role of different building design parameters, such as material reflectivity, HVAC COP, and insulation values, on building energy usage and sensible heat release from buildings with different building coverage ratios (BCR), based on the current and future weather file TMY (fTMY) for the middle of the century (2040–2060). The role of sensible heat release from buildings is not accounted for accurately while estimating building energy usage in most whole-building energy simulations. The study conducts a series of whole-building energy simulation analyses using EnergyPlus to evaluate the role of different design parameters based on TMY and fTMY weather conditions. The analysis is conducted for two hot desert climatic cities: Phoenix (USA) and Abu Dhabi (UAE). The results show that, for the base case in a future climate, the sensible heat release is reduced by an average of 30% due to the reduced delta T between the surface and ambient air. Further, the results show an increase in total energy consumption by 5% annually. The results also show that, for buildings with traditional coatings, shorter buildings release more heat than taller buildings. On the other hand, for buildings with reflective paints, shorter buildings release less heat than taller buildings. The findings from this study can be used by policymakers, utility companies, and builders to better understand the relative role of different building design parameters while constructing new and retrofitting existing buildings.

Alhazmi, Mansour [King Fahd University of Petroleu↗
DOE OSTI2024

Exascale Computing and Data Handling: Challenges and Opportunities for Weather and Climate Prediction

The emergence of exascale computing and artificial intelligence offer tremendous potential to significantly advance Earth system prediction capabilities. However, enormous challenges must be overcome to adapt models and prediction systems to use these new technologies effectively. A 2022 WMO report on exascale computing recommends “urgency in dedicating efforts and attention to disruptions associated with evolving computing technologies that will be increasingly difficult to overcome, threatening continued advancements in weather and climate prediction capabilities.” Further, the explosive growth in data from observations, model and ensemble output, and postprocessing threatens to overwhelm the ability to deliver timely, accurate, and precise information needed for decision-making. Artificial intelligence (AI) offers untapped opportunities to alter how models are developed, observations are processed, and predictions are analyzed and extracted for decision-making. Given the extraordinarily high cost of computing, growing complexity of prediction systems, and increasingly unmanageable amount of data being produced and consumed, these challenges are rapidly becoming too large for any single institution or country to handle. This paper describes key technical and budgetary challenges, identifies gaps and ways to address them, and makes a number of recommendations.

Atmosphere↗
DOE OSTI2012

Attic or Roof? An Evaluation of Two Advanced Weatherization Packages

This project examines implementation of advanced retrofit measures in the context of a large-scale weatherization program and the archetypal Chicago brick bungalow. One strategy applies best practice air sealing methods and a standard insulation method to the attic floor. The other strategy creates an unvented roof assembly using materials and methods typically available to weatherizationcontractors. Through implementations of the retrofit strategies in a total of eight (8) test homes, the research found that the two different strategies achieve similar reductions in air leakage measurement (55%) and predicted energy performance (18%) relative to the pre-retrofit conditions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

STFM: Accurate Spatio-Temporal Fusion Model for Weather Forecasting

Meteorological prediction is crucial for various sectors, including agriculture, navigation, daily life, disaster prevention, and scientific research. However, traditional numerical weather prediction (NWP) models are constrained by their high computational resource requirements, while the accuracy of deep learning models remains suboptimal. In response to these challenges, we propose a novel deep learning-based model, the Spatiotemporal Fusion Model (STFM), designed to enhance the accuracy of meteorological predictions. Our model leverages Fifth-Generation ECMWF Reanalysis (ERA5) data and introduces two key components: a spatiotemporal encoder module and a spatiotemporal fusion module. The spatiotemporal encoder integrates the strengths of convolutional neural networks (CNNs) and recurrent neural networks (RNNs), effectively capturing both spatial and temporal dependencies. Meanwhile, the spatiotemporal fusion module employs a dual attention mechanism, decomposing spatial attention into global static attention and channel dynamic attention. This approach ensures comprehensive extraction of spatial features from meteorological data. The combination of these modules significantly improves prediction performance. Experimental results demonstrate that STFM excels in extracting spatiotemporal features from reanalysis data, yielding predictions that closely align with observed values. In comparative studies, STFM outperformed other models, achieving a 7% improvement in ground and high-altitude temperature predictions, a 5% enhancement in the prediction of the u/v components of 10 m wind speed, and an increase in the accuracy of potential height and relative humidity predictions by 3% and 1%, respectively. This enhanced performance highlights STFM’s potential to advance the accuracy and reliability of meteorological forecasting.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

DRAW: Dynamic Routes for Arrivals in Weather

Presentation to National Air Traffic Controllers Association (NATCA) describing the Dynamic Routes for Arrivals in Weather (DRAW) concept and technology of the ATD-3 (Air Traffic Management Technology Demonstration-3) program. This presentation is a part of a NASA-NATCA technical interchange meeting for ATD-3 at NATCA HQ in Washington DC.

Weather↗
DOE OSTI2018

Weatherization and Intergovernmental Programs Office Fact Sheet

One of the Department of Energy’s (DOE) primary forums for helping state and local governments implement costeffective and productive energy systems for American homes, communities, businesses, and industries is the Weatherization and Intergovernmental Programs Office (WIP). WIP is part of DOE’s Office of Energy Efficiency and Renewable Energy’s “all of the above” national energy strategy to create greater energy affordability, security and resiliency.

weatherization and intergovernmental program offic↗
DOE OSTI2019

Helping Businesses and Communities Better Cope with Extreme Weather

The U.S. Department of Energy's Argonne National Laboratory is helping organizations – including AT&T – and communities better prepare for and adapt to the impacts of climate change and extreme weather events. Argonne's cutting-edge climate science and infrastructure analysis/resilience capabilities have helped a range of organizations (companies, federal agencies and cities) make more informed decisions and minimize negative impacts. To learn how your organization might collaborate with Argonne in this space, contact partners@anl.gov.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Climatic effects of irrigation over the Huang-Huai-Hai Plain in China simulated by the weather research and forecasting model: Simulated Irrigation Effects in China

In this study, we apply the Weather Research and Forecasting model coupled with an operational-like irrigation scheme to investigate the climatic effects of irrigation over the Huang-Huai-Hai plain (3HP) in China. Multiple numerical experiments with irrigation off/on during spring, summer and both spring and summer are conducted, respectively. Our results show that the warm bias in surface temperature and dry bias in soil moisture are reduced over the 3HP region during growing seasons when irrigation is turned on in the model. Air temperature during non-growing seasons is also affected by irrigation due to the persistent effects of soil moisture on land-air energy exchanges and ground heat storage. Irrigation can induce a cooler planetary boundary layer (PBL) during growing seasons, causing a wetter PBL with more low-level clouds during spring but relatively dryer PBL in summer. Further analyses indicate that the dryer summer is highly related to the changes in the East Asian summer monsoon (EASM) circulation that is modified by irrigation effect. Spring irrigation may induce a decreased land-ocean thermal contrast, leading to a possible weaker EASM. Summer irrigation, however, evidently cools the atmosphere column and forces a southward shift of the upper-level jet, which results in more precipitation in Yangtze River basin but less over southern and northern China during summer.

3HP↗
DOE OSTI2024

Reduced accrual of mineral-associated organic matter after two years of enhanced rock weathering in cropland soils, though no net losses of soil organic carbon

Abstract Enhanced rock weathering (ERW), the application of crushed silicate rock to soil, can remove atmospheric carbon dioxide by converting it to (bi) carbonate ions or solid carbonate minerals. However, few studies have empirically evaluated ERW in field settings. A critical question remains as to whether additions of crushed rock might positively or negatively affect soil organic matter (SOM)—Earth’s largest terrestrial organic carbon (C) pool and a massive reservoir of organic nitrogen (N). Here, in three irrigated cropland field trials in California, USA, we investigated the effect of crushed meta-basalt rock additions on different pools of soil organic carbon and nitrogen (i.e., mineral-associated organic matter, MAOM, and particulate organic matter, POM), active microbial biomass, and microbial community composition. After 2 years of crushed rock additions, MAOM stocks were lower in the upper surface soil (0–10 cm) of plots with crushed rock compared to unamended control plots. At the 2 sites where baseline pre-treatment data were available, neither total SOC nor SON decreased over the 2 years of study in plots with crushed rock or unamended control plots. However, the accrual rate of MAOM-C and MAOM-N at 0–10 cm was lower in plots with crushed rock vs. unamended controls. Before ERW is deployed at large scales, our results suggest that field trials should assess the effects of crushed rock on SOM pools, especially over multi-year time scales and in different environmental contexts, to accurately assess changes in net C and understand the mechanisms driving interactions between ERW and SOM cycling.

58 GEOSCIENCES↗
DOE OSTI2016

A case study of the Weather Research and Forecasting model applied to the Joint Urban 2003 tracer field experiment. Part 2: Gas tracer dispersion

Here, the Quick Urban & Industrial Complex (QUIC) atmospheric transport, and dispersion modelling, system was evaluated against the Joint Urban 2003 tracer-gas measurements. This was done using the wind and turbulence fields computed by the Weather Research and Forecasting (WRF) model. We compare the simulated and observed plume transport when using WRF-model-simulated wind fields, and local on-site wind measurements. Degradation of the WRF-model-based plume simulations was cased by errors in the simulated wind direction, and limitations in reproducing the small-scale wind-field variability. We explore two methods for importing turbulence from the WRF model simulations into the QUIC system. The first method uses parametrized turbulence profiles computed from WRF-model-computed boundary-layer similarity parameters; and the second method directly imports turbulent kinetic energy from the WRF model. Using the WRF model’s Mellor-Yamada-Janjic boundary-layer scheme, the parametrized turbulence profiles and the direct import of turbulent kinetic energy were found to overpredict and underpredict the observed turbulence quantities, respectively. Near-source building effects were found to propagate several km downwind. These building effects and the temporal/spatial variations in the observed wind field were often found to have a stronger influence over the lateral and vertical plume spread than the intensity of turbulence. Correcting the WRF model wind directions using a single observational location improved the performance of the WRF-model-based simulations, but using the spatially-varying flow fields generated from multiple observation profiles generally provided the best performance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Sensitivity of Turbine-Height Wind Speeds to Parameters in the Planetary Boundary-Layer Parametrization Used in the Weather Research and Forecasting Model: Extension to Wintertime Conditions

This work extends the model sensitivity analysis of Yang et al. (Boundary-Layer Meteorology, 2017, Vol. 162, 117-142) to include results for February 2011, in addition to May of the same year. We investigated the sensitivity of simulated hub-height wind speeds to the selection of 26 parameters applied in the Mellor-Yamada-Nakanishi-Niino (MYNN) planetary boundary-layer parameterization in the Weather Research and Forecasting (WRF) model, including parameters used to represent the dissipation of turbulence kinetic energy (TKE), Prandtl number (Pr), and turbulence length scales. Differences in the sensitivity of the ensemble of simulated wind speed to the various parameters can largely be explained by changes in the static stability. The largest monthly differences were found during the day, while the sensitivity to many of the parameters during the night were similar regardless of the month. This finding is consistent with an increased frequency of day-time stable conditions in February compared to May. The spatial variability of the sensitivity to TKE dissipation, Pr, and k can also be attributed to variability in the static stability across the domain at any point in time.

parametrization schemes, Parametric sensitivity, P↗
DOE OSTI2019

Silicate weathering in anoxic marine sediment as a requirement for authigenic carbonate burial

We emphasize the importance of marine silicate weathering (MSiW) reactions in anoxic sediment as fundamental in generating alkalinity and cations needed for carbonate precipitation and preservation along continental margins. We use a model that couples thermodynamics with aqueous geochemistry to show that the CO 2 released during methanogenesis results in a drop in pH to 6.0; unless these protons are buffered by MSiW, carbonate minerals will dissolve. We present data from two regions: the India passive margin and the active subduction zone off Japan, where ash and/or rivers supply the reactive silicate phase, as reflected in strontium isotope data. Offshore India and Korea, alteration of continent-derived silicates results in pore water enriched in radiogenic 87 Sr, with 87 Sr/ 86 Sr ratios as high as 0.7095 and 0.7104, respectively. Off Japan, strontium in pore water influenced by ash alteration is depleted in 87 Sr, with 87 Sr/ 86 Sr as low as 0.7065. Carbonate minerals formed by alkalinity and cations generated through MSiW carry these strontium isotopic signals, and are typically dolomite, siderite, and Fe-rich calcite. These contrast with the aragonite and high-magnesium calcite that form during anaerobic oxidation of methane and incorporate the coeval seawater 87 Sr/ 86 Sr signal. We show that MSiW is necessary for authigenic carbonate formation and preservation along continental margins, which remove carbon from Earth’s surface at rates previously estimated to be at least 10 12 mol yr -1 . In addition, these authigenic carbonates are of relevance to studies of the deep biosphere, fluid flow, seismogenesis, slope stability, and reservoir characteristics.

54 ENVIRONMENTAL SCIENCES↗