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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

NOAA Air Resources Laboratory Atmospheric Turbulence and Diffusion Division Contribution to LAFE Field Campaign Report

The Land-Atmosphere Feedback Experiment (LAFE) was conducted between 1 and 31 August, 2017 at the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observatory. The main scientific goal of LAFE was to investigate feedbacks occurring between different land surface types and the overlying atmosphere to improve turbulence parameterizations in numerical weather prediction models. LAFE collaborators included scientists from the following institutions: Cleveland State University Cooperative Institute for Meteorological Satellite Studies (CIMSS) Cooperative Institute for Research in Environmental Sciences (CIRES) Leibniz University Institute of Meteorology and Climatology Marquette University NASA Goddard Space Flight Center National Center for Atmospheric Research (NCAR) National Severe Storms Laboratory (NSSL) NOAA Earth System Research Laboratory (ESRL) Pacific Northwest National Laboratories (PNNL) University of Hohenheim Institute of Physics and Meteorology University of Tennessee Space Institute (UTSI). In addition to helping plan the scientific objectives of LAFE, collaborators deployed several lidars (i.e., temperature, water, vapor, and wind) and remote-sensing instruments (e.g., microwave radiometers, atmospheric emitted radiance interferometers [AERIs], etc.) to complement the suite of instrument platforms already present at the SGP site. The measurement platforms, as well as scientific objectives of LAFE, are summarized in Wulfmeyer et al. (2018). To complement these platforms, the NOAA Atmospheric Turbulence and Diffusion Division (ATDD) installed micrometeorological towers to continuously measure fluxes of momentum, sensible heat, latent heat, and CO 2 at 2 m and 10 m above ground level (AGL) at three sites during LAFE. Tower measurements also included temperature, humidity, wind speed and direction, pressure, rainfall, soil temperature, and soil moisture. The three micrometeorological towers were installed between 9 and 13 July, 2017 and were removed between 12 and 14 September, 2017. During the experiment, the footprint of Tower 1 included a mixture of soybean and grassland that transitioned to mature soybean crop during the second half of the experiment. Tower 2’s footprint encompassed a field of grazed pasture, and Tower 3’s footprint was a mature soybean crop. The meteorological and flux measurements from these towers were/are being used to: Increase the spatial density of measurement platforms that were already available at the ARM facility and that were deployed during LAFE Improve the characterization of surface fluxes around the SGP site Explore the validity of applying Monin-Obukhov Similarity Theory (MOST) over different land surface types and improve knowledge of flux-gradient relationships Provide initial conditions and be used for verification for large-eddy simulations (LES) Evaluate numerical weather prediction models, e.g., the High-Resolution Rapid Refresh (HRRR), to identify and correct for biases within these models Evaluate the role of low-level advection at each site, which would be present in the flux-divergence data sets obtained from the three towers.

Southern Great Plains, unmanned aerial systems, su↗
DOE OSTI2019

Polarized Radar for Detection and Automatic Non-Visual Assessment of Unmanned Aerial Systems

This Laboratory Directed Research and Development (LDRD) effort performed fundamental Research and Development (R&D) to develop a robust radar processing algorithm capable of assessing the difference between an Unmanned Aerial System (UAS) and a biological target such as a bird, based on mathematics applied to the polarized radar returns of the target object, alone. The current threats of using such a UAS as a delivery platform for a host of destructive components is a major concern for the protection of various assets. Most recently, on 14th Sept. 2019, dozens of suicide or kamikaze drones (UAV-X) coordinated an attack on two Saudi oil facilities that demonstrated the potential to disrupt global oil supplies. While radar-based UAS detection systems can detect UAS at ranges greater than 1-km, the issues of excessive Nuisance/False Alarm Rates (NAR/FAR) from natural sources (birds in particular) has not been sufficiently addressed. In this effort we describe and utilize the Adaptive Polarization Difference Imaging-based (APDI) algorithms for the detection and automatic non-visual assessment of Unmanned Aerial System applications. Originally developed for optical imaging and sensing of polarization information in nature, the algorithms developed here are modified to serve for the target detection purposes in counter-UAS (cUAS) environments. We exploit the polarization statistics of the observing scene for detection and identification of changes within the scene and assess from these changes for UAS/bird classifications. Several cases are considered from independent data sources, including numerically generated data, anechoic chamber data as well as experimental radar data, to show the applicability of the techniques developed here. The methods developed in this effort are designed to be used in cUAS setups but have shown promise for a multitude of other radar-based classification uses as well.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Characterizing Near-Surface Moisture Increase during the Clear-Sky Afternoon-to-Evening Transition Using a Single-Column Model

The afternoon-to-evening transition is the period when the atmospheric boundary layer transitions from convective to stable conditions. One noticeable feature during this transition period is the rapid increase in water vapor concentration near the surface. However, the mechanism behind the increase in water vapor remains poorly understood. This study investigated the processes contributing to the water vapor increase and the impacts of the land cover and horizontal advection on the water vapor increase using a single-column model for the clear-sky condition. Numerical experiments were conducted on three cases at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site. Evapotranspiration was found to be the main moisture source to the water vapor increase, and that change of the near-surface vertical temperature gradient from negative to positive is the trigger for this increase during the afternoon-to-evening transition. This is because the near-surface turbulence divergence term decreases due to the change in the buoyancy profile caused by vertical temperature gradient change. The impact of horizontal advection on water vapor varies, and it can either lead to an increase or a decrease in water vapor, depending on the spatial horizontal water vapor gradient. This study also found that land cover can influence the timing of the water vapor increase since different land covers may have different Bowen ratios. Water vapor increases earlier under conditions with smaller Bowen ratios compared to those with larger values.

Atmosphere-land interaction↗
DOE OSTI2023

Siderophore-Mediated Mobilization of Manganese Limits Iron Solubility in Mixed Mineral Systems

Recent laboratory and field studies show the need to consider the formation of aqueous Mn(III)-siderophore complexes in manganese (Mn) and iron (Fe) geochemical cycling, a shift from the historical view that aqueous Mn(III) species are unstable and thus unimportant. In this study, we quantified Mn and Fe mobilization by desferrioxamine B (DFOB), a terrestrial bacterial siderophore, in single (Mn or Fe) and mixed (Mn and Fe) mineral systems. We selected manganite (γ-MnOOH), δ-MnO 2 , lepidocrocite (γ-FeOOH), and 2-line ferrihydrite (Fe 2 O 3 ·0.5H 2 O) as relevant mineral phases. We found that DFOB mobilized Mn(III) as Mn(III)-DFOB complexes to varying extents from both Mn(III,IV) oxyhydroxides but reduction of Mn(IV) to Mn(III) was required for the mobilization of Mn(III) from δ-MnO 2 . The initial rates of Mn(III)-DFOB mobilization from manganite and δ-MnO 2 were not affected by the presence of lepidocrocite but decreased by a factor of 5 and 10 for manganite and δ-MnO 2 , respectively, in the presence of 2-line ferrihydrite. Additionally, the decomposition of Mn(III)-DFOB complexes through Mn-for-Fe ligand exchange and/or ligand oxidation led to Mn(II) mobilization and Mn(III) precipitation in the mixed-mineral systems (~10% (mol Mn/mol Fe)). As a result, the concentration of Fe(III) mobilized as Fe(III)-DFOB decreased by up to 50% and 80% in the presence of manganite and δ-MnO 2 , respectively, compared to the single mineral systems. Our results demonstrate that siderophores, through their complexation of Mn(III), reduction of Mn(III,IV), and mobilization of Mn(II), can redistribute Mn to other soil minerals and limit the bioavailability of Fe in natural systems.

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

Hourly PM 2.5 Estimates across California from 2018 to 2023

This study presents a new data set of hourly PM 2.5 concentrations across California from 2018 to 2023 at a three-kilometer resolution. This data set was developed by assimilating observations from PurpleAir and the U.S. EPA Air Quality System monitors into wildfire smoke forecasts from the High-Resolution Rapid Refresh Smoke (HRRR-Smoke) model using the Gridpoint Statistical Interpolation (GSI) three-dimensional variational data assimilation framework. Archived forecasts of modeled wildfire smoke PM 2.5 from HRRR-Smoke create the background field for assimilation, which is then corrected using surface observations of total PM 2.5 . The resulting reanalysis from GSI provides an estimate of total PM 2.5 that minimizes error from both the observational and the model data. Validation results indicate strong performance, with monthly R 2 values ranging from 0.73 to 0.91 across the six-year data set, comparable to other PM 2.5 data sets. Case studies are presented for three major fire events, the 2018 Camp Fire, 2019 Kincade Fire, and 2020 Lightning Complex Fires to demonstrate the data set’s fidelity in resolving plume dynamics and local exposure patterns. Root-mean-squared error averaged over each month scales with average PM 2.5 concentrations, resulting in a low error under typical conditions but higher absolute errors during extreme smoke events. This is the first long-term, hourly PM 2.5 data set of its kind for California and enables the generation of subdaily exposure metrics, such as peak hourly concentrations, exceedance durations, and time-of-day exposure peaks. The novelty and strong validation of this data set make it a compelling resource for future studies on the impact and significance of subdaily PM 2.5 exposure.

PM2.5↗
DOE OSTI2026

A total of 19 months of daily weather logging on the US east coast: the WFIP3 event log

The Third Wind Forecast Improvement Project (WFIP3) is a multi-institutional field campaign designed to advance the understanding and prediction of the offshore atmospheric boundary layer along the US east coast. Extending from February 2024 through August 2025, WFIP3 combines long-term coastal and offshore measurements with targeted modeling and forecasting efforts. This data paper presents the WFIP3 event log, a curated record of 578 d of meteorological phenomena and field observations that complements the campaign's extensive high-frequency datasets. The event log provides both manually documented daily weather discussions and automatically derived indicators of atmospheric processes – including low-level jets, wind ramps, extreme wind veer, and weak wind conditions – based on observations from scanning lidars deployed at three coastal and offshore sites. The dataset offers structured metadata, standardized time and site identifiers, and consistent terminology to facilitate its integration with WFIP3's observational and modeling data products. The log supports diverse applications, from model evaluation and forecast verification to the selection of case studies on offshore boundary-layer dynamics. The WFIP3 event log is publicly available through the US Department of Energy's Wind Data Hub, providing the research community with a transparent and enduring contextual reference for the interpretation and use of WFIP3 measurements.

17 WIND ENERGY↗
DOE OSTI2025

Low-Power, Load-Balancing Whole Home Electrification Solution: Cooperative Research and Development (Final Report)

Testing was conducted at the Systems Performance Laboratory in NREL’s Energy Systems Integration Facility to test the performance of 120V wall-mounted heat pumps, 120V heat pump water heaters (HPWH), Electric Vehicle Supply Equipment (EVSE), and other plug-in loads, using NeoCharge Smart Splitters and whole home energy software as appropriate. Four different simulated occupancy scenarios were used to evaluate the package of technology and controls.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

The laboratory environmental algae pond simulator (LEAPS) photobioreactor: Validation using outdoor pond cultures of Chlorella sorokiniana and Nannochloropsis salina

A bench-scale photobioreactor system, the Laboratory Environmental Algae Pond Simulator (LEAPS), was designed and constructed to simulate outdoor pond cultivation for a wide range of geographical locations and seasons. The LEAPS consists of six well-mixed glass column photobioreactors submerged in a temperature controlled waterbath (-2 °C to >60 °C) and illuminated from above by a programmable multicolor LED lighting system (0 to 2,500 µmol/m 2 -sec). Measured incident light intensities and water temperatures deviated from the respective light and temperature setpoints on average only 2.3% and 0.9%, demonstrating accurate simulation of light and temperature conditions measured in outdoor ponds. In order to determine whether microalgae strains cultured in the LEAPS exhibit the same linear phase biomass productivity as in outdoor ponds, Chlorella sorokiniana and Nannochloropsis salina were cultured in the LEAPS bioreactors using light and temperature scripts measured previously in the respective outdoor pond studies. For Chlorella sorokiniana, the summer season biomass productivity in the LEAPS was 6.6% and 11.3% lower than in the respective outdoor ponds in Rimrock, Arizona, and Delhi, California; however, these differences were not statistically significant. For Nannochloropsis salina, the winter season biomass productivity in the LEAPS was 9.2% higher than in the respective outdoor ponds in Tucson, Arizona, a difference shown to be not statistically significant. Potential reasons for the positive or negative divergence in LEAPS performance, relative to outdoor ponds, are discussed. To demonstrate the utility of the LEAPS in predicting productivity, two other strains – Scenedesmus obliquus and Stichococcus minor – were evaluated using the summer season script for Rimrock, Arizona. For both strains, the productivity was around 11.6 g/m 2 -day at 25 cm culture depth. In conclusion, the LEAPS is an accurate pond simulator and thus offers a reliable, fast, and cost-effective way to screen microalgae strains and operating conditions for high biomass productivity and co-product yields.

59 BASIC BIOLOGICAL SCIENCES↗