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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Oblique and rippled heliosphere structures from the Interstellar Boundary Explorer

Abstract Past analysis has shown that the heliosphere structure can be deduced from correlations between long-scale solar wind pressure evolution and energetic neutral atom emissions. However, this required spatial and temporal averaging that smoothed out small or dynamic features of the heliosphere. In late 2014, the solar wind dynamic pressure increased by roughly 50% over a period of 6 months, causing a time and directional-dependent rise in around 2–6 keV energetic neutral atom fluxes from the heliosphere observed by the Interstellar Boundary Explorer. Here, we use the 2014 pressure enhancement to provide a simultaneous derivation of the three-dimensional heliospheric termination shock (HTS) and heliopause (HP) distances at high resolution from Interstellar Boundary Explorer measurements. The analysis reveals rippled HTS and HP surfaces that are oblique with respect to the local interstellar medium upwind direction, with significant asymmetries in the heliosphere structure compared to steady-state heliosphere models. We estimate that the heliosphere boundaries contain roughly ten astronomical unit-sized spatial variations, with slightly larger variations on the HTS surface than the HP and a large-scale, southwards-directed obliquity of the surfaces in the meridional plane. Comparisons of the derived HTS and HP distances with Voyager observations indicate substantial differences in the heliosphere boundaries in the northern versus southern hemispheres and their motion over time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Generalized Relationship Linking Water Balance and Vegetation Productivity across Site-to-Regional Scales

Evapotranspiration (ET) is a pivotal component in catchment-scale water balance and is essential for informed watershed management. Nevertheless, uncertainties in ET observation or modeling have been hindering effective water resources management. This study addresses this gap by establishing a robust, generalized linear relationship between ET and gross primary productivity (GPP) at the catchment scale. We test the linearity of the relationships between monthly GPP and ET data at 380 near-natural catchments across various climatic and landscape conditions in the contiguous U.S., yielding Pearson’s r ≥ 0.6 for 97% of the 380 catchments. We then develop a regionalization strategy to parameterize this GPP-ET relationship at the catchment scale by identifying and utilizing the linkages between the parameter values and extensively available hydroclimatic and landscape data. We demonstrate the efficacy of the proposed GPP-ET relationship and parameter regionalization strategy by their combined predictive capacity, where the predicted monthly GPP matches well with remote-sensing-based GPP product, achieving Kling-Gupta Efficient (KGE) values ≥ 0.5 for 92% of the catchments. In addition, we verify the relationship and its parameter regionalization at 35 AmeriFlux sites with KGE ≥ 0.5 for 25 sites, suggesting that the new relationship is transferable across the site, catchment, and regional scales. Furthermore, our findings are valuable for improving remote-sensing-based estimation of monthly ET and diagnosing coupled water–carbon simulations in land surface and Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Measuring a Low Horizontal Hydraulic Gradient in a High Transmissivity Aquifer

Abstract High transmissivity aquifers typically have low hydraulic gradients (i.e., a flat water table). Measuring low gradients using water levels can be problematic because measurement error may be greater than the true difference in water levels (i.e., a low signal‐to‐noise ratio). In this study, the feasibility of measuring a hydraulic gradient in the range of 10 −6 to 10 −5 m/m was demonstrated. The study was performed at a site where the depth to water from land surface ranged from 40.1 to 94.2 m and the aquifer transmissivity was estimated at 41,300 m 2 /d (hydraulic conductivity of 18,800 m/d). The goals of the study were to reduce measurement error as much as practicable and assess the importance of factors affecting water level measurement accuracy. Well verticality was the largest source of error (0.000 to 0.168 m; median of 0.014 m), and geodetic survey of casing elevations was the next most important source of error (0.002 to 0.013 m; median of 0.005 m). Variability due to barometric pressure fluctuations was not an important factor at the site. Hydraulic heads were measured to an accuracy of ±0.0065 m, and the average hydraulic gradient was estimated to be 8.0 × 10 −6 (±0.9 × 10 −6 ) m/m. The improvement in accuracy allowed for two reversals in the groundwater flow direction to be identified, after which the gradient averaged 2.5 × 10 −5 (±0.4 × 10 −5 ) m/m. This study showed it is possible to sufficiently control sources of error to measure hydraulic gradients in the 10 −6 to 10 −5 m/m range.

McDonald, John P.↗
DOE OSTI2020

GEOPHIRES v2.0

GEOPHIRES v2.0 is a geothermal techno-economic simulation tool upgraded from GEOPHIRES v1.2. The name stands for "GEOthermal energy for Production of Heat and electricity (“IR”) Economically Simulated". GEOPHIRES combines reservoir, wellbore, and surface plant technical models with cost correlations and levelized cost models to estimate the capital and operation and maintenance costs, instantaneous and lifetime energy production, and overall levelized cost of energy of a geothermal plant. In addition to electricity generation, direct-use heat applications and combined heat and power or cogeneration can be modeled. Various upgrades have been implemented to develop GEOPHIRES v2.0, including: updating the built-in cost correlations, coupling to the external reservoir simulator TOUGH2, enhancing the built-in wellbore simulator, converting the programming language to Python, and making the code open-source. Users are encouraged to build upon the tool, e.g. by implementing their own correlations or coupling to other simulators.

Beckers, Koenraad↗
DOE OSTI2025

Source Characterization at Low Yields from Physics Experiment One A

The detonation of a well-recorded coupled explosion at the well-characterized Nevada National Security Site, as part of Physics Experiment One, has provided us with an opportunity to compare and contrast methods and results of yield estimation and other event characterization methods. Yield estimates are made using several methods, including local/regional magnitudes, waveform envelopes, acoustic amplitudes, joint seismoacoustic yield, and moment tensors. We include in our analysis a discussion and comparison of applicability, calibrations, assumptions, and uncertainties involved in each. With the exception of magnitude-based methods, all the techniques were more or less successful in recovering the known yield. It is, however, useful to be cognizant of requirements and calibrations, such as station coverage, emplacement conditions, propagation characterization, and uncertainties, to apply the methods to other areas with less complete information. We demonstrate that we can be successful at monitoring low-yield explosions using a variety of methods assuming that the signal-to-noise ratio is adequate at recording stations, and that the material properties are taken into account. Depth estimates are also important, particularly if one allows the possibility of a surface explosion.

Pasyanos, Michael E. [Lawrence Livermore National ↗
DOE OSTI2020

Best Practices for the Validation of U.S. Offshore Wind Resource Models

This report presents a comprehensive set of best practices for working with both modeled and measured US offshore wind resource data sets. We specifically target two key questions in this report. First, what are the best data sources and methods for validating modeled wind resource estimates? Second, what are the best methods for vertically extrapolating near-surface wind speed measurements to heights that span the rotor-swept area of modern offshore wind turbines?

17 WIND ENERGY↗
DOE OSTI2021

Sensitivity Analysis of Particle-In-Cell Modeling Parameters in Settling Bed, Bubbling Fluidized Bed and Circulating Fluidized Bed

The objective of the work presented is to perform a preliminary sensitivity analysis of particle-in-cell (PIC) model parameters when applied to settling bed, bubbling fluidized bed, and circulating fluidized bed simulations. These examples correspond to widely different flow conditions commonly seen in chemical engineering applications. Simulations were performed using the PIC method in the open-source software Multiphase Flow with Interphase eXchanges (MFiX) developed by the National Energy Technology Laboratory (NETL). As part of the non-intrusive uncertainty quantification (UQ) analysis, simulation campaigns were generated using Nodeworks. Sampling locations or settings for PIC model parameters were determined using the Latin Hypercube method. Response surfaces were created using radial basis functions (RBF), and Sobol’ indices were estimated to quantify the influence of model parameters on the quantities of interest (QoI). This study marks a first step towards systematically determining optimal ranges for model parameters used in MFiX-PIC. Based on limited experience, it is expected that these values would depend strongly on flow conditions. Given the complexity of the multiphase flow systems under analysis, a non-intrusive UQ based approach is used to identify the most influential parameters in each case. This prior knowledge will help in proposing an effective design of experiments (DoE) and determine optimal parameters through techniques such as deterministic or Bayesian calibration, which will be pursued in the future.

42 ENGINEERING↗
DOE OSTI2022

Effects of plasma on physical properties of water: nanocrystalline-to-amorphous phase transition and improving produce washing

Recently is was discovered in various applications that many physical and chemical properties of water change their temperature dependence between about 35 and 60 degrees Celsius. In particular, heat conductance, light absorption, and surface tension all change their temperature dependence. These drastic changes were associated with water gradually changing its mesoscopic structure: while at the higher temperatures water is a uniform media (amorphous state), at the temperatures below transition it consists of many nano-to-micro-scale clusters (crystalline state). This transition is similar to the second order phase transition. In the present paper we show that treating water with non-thermal plasma (adding plasma-created active compounds) can lower the temperature of the transition and thus cause a significant change in such physical quantities as surface tension, viscosity, freezing rate, and wettability and washability. We present analytical estimates of the transition temperature shift based on the Debye-Hückel theory. We discuss the produce-washing experiments that illustrate the predicted effects.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Tethered Balloon System Merged Data (TBSMERGED) Value-Added Product Report

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Tethered Balloon System Merged Data (TBSMERGED) Value-Added Product (VAP) integrates data from instruments flown on ARM’s tethered balloon system missions that collect in situ measurements of temperature, humidity, wind speed, wind direction, and aerosol properties with estimates of cloud base and boundary-layer height from a surface-based ceilometer to improve the ease of use of tethered balloon system (TBS) data sets. The TBSMERGEDINCLOUD VAP, a variation of TBSMERGED, includes supercooled liquid water content (tbsslwc) measurements collected within the cloud.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Small-Scale Drying: FY2020 Interim Report

This report documents the interim experimental status of small-scale drying tests currently being performed at Pacific Northwest National Laboratory. These small-scale drying tests are to develop the technical bases for sensors, techniques, and approaches that will be used to address the challenges faced when determining moisture content from gas samples taken at the North Anna Nuclear Generating Station for the High Burnup Demonstration Project. Specifically, the purpose of these tests is to support Sandia National Laboratories gas sample methods and analyses through a series of small-scale experiments. Key focus areas include performing tests to: • Correlate sample bottle measurements to in-cask conditions • Estimate the amount of trapped and absorbed water on cask features and surfaces that can contribute to water vapor • Assess the accuracy of the hygrometer used in the measurements under similar conditions • Identify additional methods for measuring humidity in casks easily and accurately using lessons-learned from Sandia National Laboratories, including direct gravimetric and isotopic tracer techniques. To address these topics this report outlines a series of five tests and any data collected to date that were planned for FY 2020 that include 1) humidity measurement method development, 2) gas bottle sampling tests, 3) surface drying tests on cladding, 4) small-scale drying of cladding, and 5) small-scale drying of guide-tube/dashpots. This interim report documents the experimental background, design and progress of these small-scale drying tests. Further data gathered will be summarized in the FY 2021 report.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Implementation of a High-Mach Integral Boundary Layer Method for Arbitrary Streamlined Body Geometry

The Momentum-Energy Integral Technique (MEIT) is an integral boundary layer method for the high-Mach flow regime used to approximate heat transfer and viscous force quantities of interest along streamlines of an inviscid flow solution on the surface of a flight vehicle. This method allows rapid mid-fidelity estimation of these quantities which would otherwise require a much more expensive viscous flow solution to produce. Integral boundary layer methods like MEIT have been around for decades, though usually only formulated for simple geometries such as 2-dimensional wing shapes or axi-symmetric nose shapes. The implementation discussed herein has been generalized to apply to any 3-dimensional streamlined body geometry through correct treatment of the curvilinear axes (streamline attached) momentum and energy entrainment terms, and handling of arbitrary stagnation region geometry. This implementation is provided as a software package for the Python environment, along with readers for common inviscid flow solution providers such as NASA’s CART3D flow solver.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

The MASSIVE Survey. XVI. The Stellar Initial Mass Function in the Center of MASSIVE Early-type Galaxies

The stellar initial mass function (IMF) is a fundamental property in the measurement of stellar masses and galaxy star formation histories. In this work, we focus on the most massive galaxies in the nearby universe $\mathrm{log}({M}_{\star }/\,{M}_{\odot })\gt 11.2$. We obtain high-quality Magellan/LDSS-3 long-slit spectroscopy with a wide wavelength coverage of 0.4–1.01 μm for 41 early-type galaxies (ETGs) in the MASSIVE survey and derive high signal-to-noise spectra within an aperture of R e /8. Using detailed stellar synthesis models, we constrain the elemental abundances and stellar IMF of each galaxy through full spectral modeling. All the ETGs in our sample have an IMF that is steeper than a Milky Way (Kroupa) IMF. The best-fit IMF mismatch parameter, α IMF = (M/L)/(M/L) MW , ranges from 1.1 to 3.1, with an average of $\langle$α IMF $\rangle$ = 1.84, suggesting that on average, the IMF is more bottom heavy than Salpeter. Comparing the estimated stellar masses with the dynamical masses, we find that most galaxies have stellar masses that are smaller than their dynamical masses within the 1σ uncertainty. We complement our sample with lower-mass galaxies from the literature and confirm that $\mathrm{log}({\alpha }_{\mathrm{IMF}})$ is positively correlated with $\mathrm{log}(\sigma )$, $\mathrm{log}({M}_{\star })$, and $\mathrm{log}({M}_{\mathrm{dyn}})$. From the combined sample, we show that the IMF in the centers of more massive ETGs is more bottom heavy. In addition, we find that $\mathrm{log}({\alpha }_{\mathrm{IMF}})$ is positively correlated with both [Mg/Fe] and the estimated total metallicity [Z/H]. We find suggestive evidence that the effective stellar surface density Σ Kroupa might be responsible for the variation of α IMF . We conclude that σ, [Mg/Fe], and [Z/H] are the primary drivers of the global stellar IMF variation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Radar-based Snow Property Profile Retrievals for NSA

The product contains estimated snow microphysical properties retrieved primarily from vertically-profiling radar observations using a priori constraints that are dependent on atmospheric state. The product provides data at 1-minute time resolution, including snowfall rate at the surface and vertical profiles at 300-meter resolution of snow particle size distribution parameters and snow water contents. Estimated uncertainties for the snowfall rates and snow water contents are also provided. The product is obtained using an optimal estimation retrieval in which radar forward model and a priori state characteristics are based on expected snow particle microphysical and radar scattering properties evaluated from field experiment data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Development of PFLOTRAN Transport Capability for Use in the Waste Isolation Pilot Plant Performance Assessment - 20545

Waste Isolation Pilot Plant (WIPP) performance assessment (PA) calculations estimate the probability of radionuclide release from the repository to the land surface and across the land withdrawal boundary for a regulatory period of 10,000 years after facility closure. Simulations of flow and transport in the repository and the surrounding Salado Formation are foundational to the PA. Because proposed additional waste emplacement panels would result in an asymmetric repository layout, the US Department of Energy (DOE) is preparing to transition to use of a three-dimensional (3-D) model domain for simulation of flow and transport instead of the two-dimensional (2-D) flared grid domain currently used. DOE has charged Sandia National Laboratories with developing the capability necessary to simulate processes affecting flow and transport in the WIPP in PFLOTRAN, an open-source massively parallel multi-phase flow and reactive transport code. The new flow and transport capabilities developed in PFLOTRAN incorporate WIPP-specific process models and will replace the 2-D simulators (BRAGFLO and NUTS) that are currently utilized for Salado flow and transport calculations in WIPP PA. The focus of this paper is on the development of a new Nuclear Waste Transport (NWT) mode in PFLOTRAN that has all of the capabilities necessary for Salado transport simulations, including the ability to handle complete dry-out (100% gas saturation) of arbitrary cells in the model domain, radionuclide mass conservation at step changes in porosity associated with borehole intrusion, and the ability to calculate fluxes on a flared grid. The new PFLOTRAN transport capability and a suite of verification tests were designed around a list of functional requirements for WIPP PA calculations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Characterizing juvenile salmon predation risk during early marine residence

Predation mortality can influence the distribution and abundance of fish populations. While predation is often assessed using direct observations of prey consumption, potential predation can be predicted from co-occurring predator and prey densities under varying environmental conditions. Juvenile Pacific salmon Oncorhynchus spp. (i.e., smolts) from the Columbia River Basin experience elevated mortality during the transition from estuarine to ocean habitat, but a thorough understanding of the role of predation remains incomplete. We used a Holling type II functional response to estimate smolt predation risk based on observations of piscivorous seabirds (sooty shearwater [ Ardenna griseus ] and common murre [ Uria aalge ]) and local densities of alternative prey fish including northern anchovy ( Engraulis mordax ) in Oregon and Washington coastal waters during May and June 2010–2012. We evaluated predation risk relative to the availability of alternative prey and physical factors including turbidity and Columbia River plume area, and compared risk to returns of adult salmon. Seabirds and smolts consistently co-occurred at sampling stations throughout most of the study area (mean = 0.79 ± 0.41, SD), indicating that juvenile salmon are regularly exposed to avian predators during early marine residence. Predation risk for juvenile coho ( Oncorhynchus kisutch ), yearling Chinook salmon ( O . tshawytscha ), and subyearling Chinook salmon was on average 70% lower when alternative prey were present. Predation risk was greater in turbid waters, and decreased as water clarity increased. Juvenile coho and yearling Chinook salmon predation risk was lower when river plume surface areas were greater than 15,000 km 2 , while the opposite was estimated for subyearling Chinook salmon. These results suggest that plume area, turbidity, and forage fish abundance near the mouth of the Columbia River, all of which are influenced by river discharge, are useful indicators of potential juvenile salmon mortality that could inform salmonid management.

Phillips, Elizabeth M. (ORCID:0000000327752563)↗
DOE OSTI2024

Street-level temperature estimation using graph neural networks: Performance, feature embedding and interpretability

Estimating street-level air temperature is a challenging task due to the highly heterogeneous urban surfaces, canyon-like street morphology, and the diverse physical processes in the built environment. Though pioneering studies have embarked on investigations via data-driven approaches, many questions remain to be answered. Here, in this study, we leveraged an innovative framework and redefined the street-level temperature estimation problem using Graph Neural Networks (GNN) with spatial embedding techniques. The results showed that GNN models are more capable and consistent of estimating street-level temperature among tested locations, benefiting from its unique strength in handling extensive data over unstructured graph topology. In addition, we conducted in-depth analysis of feature importance to enhance the model interpretability. Among the urban features analyzed in this study, the time-variant canopy density and meter-level land use data emerge as crucial factors. Our findings highlight GNN 's high potential in capturing the complex dynamics between urban elements and their impacts on microclimate, thus offering valuable insights for comprehensive urban data collection and urban climate modeling in general. Collectively, this study also contributes to urban planning and policy by providing avenues to enhance city resilience against climate change, thereby advancing the agenda for environmental stewardship and urban sustainability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A U.S. Scientific Community Vision for Sustained Earth Observations of Greenhouse Gases to Support Local to Global Action

Managing carbon stocks in the land, ocean, and atmosphere under changing climate requires a globally‐integrated view of carbon cycle processes at local and regional scales. The growing Earth Observation (EO) record is the backbone of this multi‐scale system, providing local information with discrete coverage from surface measurements and regional information at global scale from satellites. Carbon flux information, anchored by inverse estimates from spaceborne Greenhouse Gas (GHG) concentrations, provides an important top‐down view of carbon emissions and sinks, but currently lacks global continuity at assessment and management scales (<100 km). Partial‐column data can help separate signals in the boundary layer from the overlying atmosphere, providing an opportunity to enhance surface sensitivity and bring flux resolution down from that of column‐integrated data (100–500 km). Based on a workshop held in September 2024, the carbon cycle community envisions a carbon observation system leveraging GHG partial columns in the lower and upper troposphere to weave together information across scales from surface and satellite EO data, and integration of top‐down/bottom‐up analyses to link process understanding to global assessment.

Parazoo, Nicholas C. [California Institute of Tech↗
DOE OSTI2022

Surface parameters and bedrock properties covary across a mountainous watershed: Insights from machine learning and geophysics

Bedrock property quantification is critical for predicting the hydrological response of watersheds to climate disturbances. Estimating bedrock hydraulic properties over watershed scales is inherently difficult, particularly in fracture-dominated regions. Our analysis tests the covariability of above- and belowground features on a watershed scale, by linking borehole geophysical data, near-surface geophysics, and remote sensing data. We use machine learning to quantify the relationships between bedrock geophysical/hydrological properties and geomorphological/vegetation indices and show that machine learning relationships can estimate most of their covariability. Although we can predict the electrical resistivity variation across the watershed, regions of lower variability in the input parameters are shown to provide better estimates, indicating a limitation of commonly applied geomorphological models. Our results emphasize that such an integrated approach can be used to derive detailed bedrock characteristics, allowing for identification of small-scale variations across an entire watershed that may be critical to assess the impact of disturbances on hydrological systems.

58 GEOSCIENCES↗