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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Modeling Isothermal Reduction of Iron Ore Pellet Using Finite Element Analysis Method: Experiments & Validation

Iron ore pellet reduction experiments were performed with pure hydrogen (H2) and mixtures with carbon monoxide (CO) at different ratios. For direct reduction processes that switch dynamically between reformed natural gas and hydrogen as the reductant, it is important to understand the effects of the transition on the oxide reduction kinetics to optimize the residence time of iron ore pellets in a shaft reactor. Hence, the reduction rates were studied by varying experimental parameters such as the temperature (800, 850 & 900 °C), reactant gas flow rate (100, 150 & 200 cm3/min), pellet size and composition of the reactant gas mixture. The rate of reduction was observed to increase with an increase in temperature and reactant gas flow rate, but it decreased with an increase in pellet size. SEM greyscale analysis was performed to analyze the porosity and phase composition of partially reduced pellets. The porosity of the pellets was observed to increase from 0.3 for unreacted pellet to 0.42 for a completely reduced pellet. Energy-dispersive X-ray spectroscopy (EDAX) analysis was performed to identify the phases observed in the SEM images. The fraction of iron phase was observed to increase from the shell region of the pellet to the core region with an increase in the degree of reduction. A 2D-axisymmetric numerical model was developed on COMSOL Multiphysics, and it was validated using the conversion (X) vs. time curves obtained from each experiment. The model was able to accurately predict the total time needed for the complete conversion of a single iron ore pellet for multiple experiments. Effects of changes in the porosity and tortuosity of the pellet on the model were also studied and the rate of reduction was observed to be sensitive to changes in both porosity and tortuosity. The SEM analysis and the model results show that tortuosity is higher for pellets reduced with H2 than for pellets reduced with H2-CO gas mixtures.

08 HYDROGEN↗
DOE OSTI2026

Compressive Response and Energy Absorption of Additively Manufactured Elastomers with Varied Simple Cubic Architectures

Additive manufacturing, and particularly the vat photopolymerization process, enables the fabrication of complex geometries at high resolution and small length scales, making it well-suited for fabricating cellular structures (e.g., foams and lattices). Among these, elastomeric cellular structures are of growing interest due to their tunable compliance and energy dissipation. However, comprehensive data on the compressive behavior of these structures remains limited, especially for investigating the structure-property effects from changing the density and distribution of material within the cellular structure. This study explores how the mechanical response of polyurethane-based simple cubic structures changes when varying volume fraction, unit cell length, and unit cell patterning, which have not been systematically investigated previously in additively manufactured elastomers. Increasing volume fraction from 10% to 50% yielded significant changes in compressive stress–strain performance (decreasing strain at 0.5 MPa by 41.6% and increasing energy absorption density by 3962.5%). Although changing the unit cell length between 2.5 and 7 mm in ~30 mm parts did not result in statistically different stress–strain responses, modifying the configuration of struts of different thicknesses across designs with 30% volume fraction altered the stress–strain behavior (differences of 12.5% in strain at 0.5 MPa and 109.4% for energy absorption density). Power law relationships were developed to understand the interactions between volume fraction, unit cell length, and elastic modulus, and experimental data showed strong fits (R 2 > 0.91). These findings enhance the understanding of how multiple structural design aspects influence the performance of elastomeric cellular materials, providing a foundation for informing strategic design of tailorable materials for diverse mechanical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Wildfire Smoke Particle Properties and Evolution, from Space-Based Multi-Angle Imaging

Emitted smoke composition is determined by properties of the biomass burning source and ambient ecosystem. However, conditions that mediate the partitioning of black carbon (BC) and brown carbon (BrC) formation, as well as the spatial and temporal factors that drive particle evolution, are not understood adequately for many climate and air-quality related modeling applications. In situ observations provide considerable detail about aerosol microphysical and chemical properties, although sampling is extremely limited. Satellites offer the frequent global coverage that would allow for statistical characterization of emitted and evolved smoke, but generally lack microphysical detail. However, once properly validated, data from the National Aeronautics and Space Administration (NASA) Earth Observing System’s Multi-Angle Imaging Spectroradiometer (MISR) instrument can create at least a partial picture of smoke particle properties and plume evolution. We use in situ data from the Department of Energy’s Biomass Burning Observation Project (BBOP) field campaign to assess the strengths and limitations of smoke particle retrieval results from the MISR Research Aerosol (RA) retrieval algorithm. We then use MISR to characterize wildfire smoke particle properties and to identify the relevant aging factors in several cases, to the extent possible. The RA successfully maps qualitative changes in effective particle size, light absorption, and its spectral dependence, when compared to in situ observations. By observing the entire plume uniformly, the satellite data can be interpreted in terms of smoke plume evolution, including size-selective deposition, new-particle formation, and locations within the plume where BC or BrC dominates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

An Impedance-Loaded Surface Acoustic Wave Corrosion Sensor for Infrastructure Monitoring

Passive surface acoustic wave (SAW) devices are attractive candidates for continuous wireless monitoring of corrosion in large infrastructures. However, acoustic loss in the aqueous medium and limited read range usually create challenges in their widespread use for monitoring large systems such as oil and gas (O&G) pipelines, aircraft, and processing plants. This paper presents the investigation of impedance-loaded reflective delay line (IL-RDL) SAW devices for monitoring metal corrosion under O&G pipeline-relevant conditions. Specifically, we studied the effect of change in resistivity of a reflector on the backscattered signal of an RDL and investigated an optimal range through simulation. This was followed by the experimental demonstrations of real-time monitoring of Fe film corrosion in pressurized (550 psi) humid CO 2 conditions. Additionally, remote monitoring of Fe film corrosion in an acidic solution inside a 70 m carbon steel pipe was demonstrated using guided waves. This paper also suggests potential ways to improve the sensing response of IL-RDLs.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning

Stream temperature (Ts) is an important water quality parameter that affects ecosystem health and human water use for beneficial purposes. Accurate Ts predictions at different spatial and temporal scales can inform water management decisions that account for the effects of changing climate and extreme events. In particular, widespread predictions of Ts in unmonitored stream reaches can enable decision makers to be responsive to changes caused by unforeseen disturbances. In this study, we demonstrate the use of classical machine learning (ML) models, support vector regression and gradient boosted trees (XGBoost), for monthly Ts predictions in 78 pristine and human-impacted catchments of the Mid-Atlantic and Pacific Northwest hydrologic regions spanning different geologies, climate, and land use. The ML models were trained using long-term monitoring data from 1980–2020 for three scenarios: (1) temporal predictions at a single site, (2) temporal predictions for multiple sites within a region, and (3) spatiotemporal predictions in unmonitored basins (PUB). In the first two scenarios, the ML models predicted Ts with median root mean squared errors (RMSE) of 0.69–0.84 °C and 0.92–1.02 °C across different model types for the temporal predictions at single and multiple sites respectively. For the PUB scenario, we used a bootstrap aggregation approach using models trained with different subsets of data, for which an ensemble XGBoost implementation outperformed all other modeling configurations (median RMSE 0.62 °C).The ML models improved median monthly Ts estimates compared to baseline statistical multi-linear regression models by 15–48% depending on the site and scenario. Air temperature was found to be the primary driver of monthly Ts for all sites, with secondary influence of month of the year (seasonality) and solar radiation, while discharge was a significant predictor at only 10 sites. The predictive performance of the ML models was robust to configuration changes in model setup and inputs, but was influenced by the distance to the nearest dam with RMSE <1 °C at sites situated greater than 16 and 44 km from a dam for the temporal single site and regional scenarios, and over 1.4 km from a dam for the PUB scenario. Our results show that classical ML models with solely meteorological inputs can be used for spatial and temporal predictions of monthly Ts in pristine and managed basins with reasonable (<1 °C) accuracy for most locations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Slant, Fan, and Narrow: The Response of Stellar Streams to a Tilting Galactic Disk

Stellar streams are sensitive tracers of the gravitational potential, which is typically assumed to be static in the inner Galaxy. However, massive mergers like Gaia-Sausage-Enceladus can impart torques on the stellar disk of the Milky Way that result in the disk tilting at rates of up to 10°–20° Gyr –1 . Here, we demonstrate the effects of disk tilting on the morphology and kinematics of stellar streams. Through a series of numerical experiments, we find that streams with nearby apocenters (r apo ≲ 20 kpc) are sensitive to disk tilting, with the primary effect being changes to the stream's on-sky track and width. Interestingly, disk tilting can produce both more diffuse streams and more narrow streams, depending on the orbital inclination of the progenitor and the direction in which the disk is tilting. Our model of Pal 5's tidal tails for a tilting rate of 15° Gyr –1 is in excellent agreement with the observed stream's track and width, and reproduces the extreme narrowing of the trailing tail. We also find that failure to account for a tilting disk can bias constraints on shape parameters of the Milky Way's local dark matter distribution at the level of 5%–10%, with the direction of the bias changing for different streams. Disk tilting could therefore explain discrepancies in the Milky Way's dark matter halo shape inferred using different streams.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Scout Benchmark Scenarios for U.S. Building Energy and CO2 Emissions to 2050

Overview and Intended Use Cases: These scenarios establish a range of futures for U.S. buildings sector energy use and CO2 emissions to 2050 using Scout (scout.energy.gov), a reproducible and granular model of U.S. building energy use, emissions, and consumer costs developed by the U.S. national labs for the U.S. Department of Energy's Building Technologies Office (BTO). Scout benchmark scenario data are suitable for the following example use cases: setting high-level policy goals for the U.S. buildings sector to 2050 (e.g., X% building CO2 emissions reductions vs. 2005 levels by 2030, Y% reductions vs. 2005 levels by 2050); exploring the effects of key dynamics driving U.S. buildings sector energy and CO2 emissions to 2050 that could be affected by policy levers (e.g., raising minimum technology performance levels; accelerating electrification and/or retrofit rates; introducing breakthrough technologies to the market); determining priority segments (regions, building types, and end use/technology types) and sequencing of U.S. buildings sector energy and CO2 emissions reductions to 2050 under a given set of assumptions; and/or identifying the energy and emissions impacts or cost effectiveness of specific technologies or operational approaches of interest—in isolation or after considering competition with other measures in a scenario portfolio. Scenario Summary: A total of 8 scenarios explore the effects of changes across both the demand- and supply-side of building energy use on annual U.S. building energy use and CO2 emissions from 2022–2050. Scenarios are organized into three groups representing low, moderate, and best-case potentials for building decarbonization, respectively.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Modeling Wind in Agrivoltaics and its Impact on Eddy Covariance Flux Measurements

Silicon Ranch is conducting a research study at their 138MW Bancroft Station agrivoltaics site, the largest agrivoltaics research array in the US, in which they are using an eddy covariance flux tower to measure the carbon budget. They are interested in finding out if the presence of the panels changes the effectiveness of these measurements. To investigate this topic, NLR performed numerical simulations of wind through the agrivoltaic array to identify under what environmental conditions (wind speed, wind direction, temperatures) and panel tilt angles the mean wind speeds at the measurement heights are significantly altered by the presence of the solar panels. NLR adapted and used the PVade simulation tool [1] to model wind in Silicon Ranch's agrivoltaic array and found that at the height of the flux tower (6m), the wind speed measured is not significantly altered by the presence of solar panels. The percent difference is less than 4% and is generally greatest during daytime conditions at higher wind speeds and perpendicular wind direction. Closer to the ground, the flow is significantly altered (wind speeds are reduced) by the presence of solar panels and the percent difference increases in strong winds. The work confirmed that eddy covariance flux towers can be used within the context of a solar array field.

14 SOLAR ENERGY↗
NASA NTRS1970

Multipass holographic interferometer improves image resolution

Multipass holographic interferometer forms a hologram of high diffraction efficiency, and hence provides a bright and high contrast interferogram. It is used to study any effect which changes the index of refraction and to study surface deformations of a flat reflecting surface.

Brooks, R. E.↗