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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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The presentation contains research findings of the expansion planning subtask within the IDAES core activity. The presentation highlights the expansion planning capabilities applied to a case study in the San Diego County area. The research findings were presented at the AIChE Annual Meeting.
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The CG-2 beamline at the High Flux Isotope Reactor (HFIR) exhibits a notable discrepancy between observed count rates and the count rates we would expect based on a Monte-Carlo neutron ray-trace simulation. These simulations consistently predict count rates approximately five times greater than those observed in four separate experimental runs involving different instrument configurations. This discrepancy suggests that certain factors are causing losses in measurements that are not adequately accounted for in the simulation, in particular guide reflectivity or misalignment. To investigate these discrepancies, a high-dimensional simulation parameter approach is applied in order to understand the losses. Region of Interest (ROI) groups along the instrument are assigned to different surfaces of the guide components within the simulation. This allows the parameters of those guide components to be varied as a group to minimize the complexity of the search space. The result is an optimization of simulation parameters using an iterative scheme that aims to minimize the difference between experimentally measured count rates and simulated count rates across all tested collimator combinations. This proposed methodology holds the potential to reveal previously unrecognized sources of intensity loss in the CG-2 beamline at HFIR and improve the accuracy of simulations, leading to enhanced understanding and performance of the beamline for various scientific applications.
Re-analyzed acoustic Doppler current profiler (ADCP) data originally collected by NOAA CO-OPS (Center for Operational Oceanographic Products and Services) and equivalent point data from Pacific Northwest National Laboratory's FVCOM (Finite Volume Community Ocean Model) model of the region. Data are processed to products describing characteristics of tidal currents relevant to tidal turbines, as well as power output estimates for a notional turbine deployed from a surface platform or from the seabed at each location. These data underpin the results presented in their associated paper - see below.
Optical case-2 waters near an ocean outfall were examined, using a combination fo AVIRIS imagery and ship-based surface and profile bio-optical measurements. Bio-optical mooring data were useful in determining the hydrodynamics of the area.
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ERS-1 radar images acquired 14 months apart studied by differential radar interferometry show the wide area distribution of aseismic creep along the fault segment northwest of Parkfield, California.
Heat transfer behavior in sCO2 power cycles when firing solid fuels
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This study focuses on an agricultural region in California’s Central Valley, USA, where Managed Aquifer Recharge (MAR) is widely implemented to mitigate groundwater depletion under increasing water demand and climate variability. A deep learning and machine learning framework was developed to identify infiltration-MAR locations using satellite imagery and environmental data. The framework integrates surface water detection from Sentinel-2 imagery, geospatial delineation of water bodies, spatiotemporal tracking of water body dynamics, and supervised classification using meteorological, environmental, and topographic variables. The framework was applied to a 2379 km² study area southwest of Fresno, where 765 water bodies were detected, including 139 identified MAR sites based on publicly available datasets and expert knowledge. The classification model achieved an accuracy of 0.94 and an F1 score of 0.85. Feature importance analysis indicates that cropland, normalized difference vegetation index (NDVI), and evaporation are among the most influential predictors for infiltration-MAR. Notably, the framework suggests that engineered water management in infiltration-MAR systems can disrupt or even reverse the expected positive correlation between surface water extent and precipitation. These findings provide physically interpretable insights into the characteristics of existing infiltration-MAR facilities and demonstrate the potential of the proposed framework as a reproducible, interpretable, and potentially transferable tool for data-driven infiltration-MAR identification and inventory development under growing climatic and hydrological uncertainty.
In-situ and operando measurements are done to gain a better understanding of the precipitation mechanisms during charge and discharge in lithium sulfur batteries. A carbon felt networked with microfibers consisting of pores, 2 nm and smaller, is used as a freestanding sulfur host. Three different methods of sulfur infiltration are explored in order to determine the best one to fill most of the pores. It was identified to be a melt infiltration method in a vacuum oven, where the pores including the ultra-micropores, are successfully filled. In-situ electrochemical impedance spectroscopy measurements show a solid product formation occurring at the sulfur cathode, both during the high voltage plateau and at the end of discharge. In a 3-electrode EIS measurement, a similar solid product formation on the Li counter electrode due to its reaction with polysulfides is also observed. Operando small angle neutron scattering measurements show the solid product formation, in the carbon, both near the beginning and at the end of discharge, confirming the precipitation data via contrast changes as a function of charge and discharge. It is shown that Li 2 S precipitates in the pores at the beginning and the end of discharge, whereas S8 precipitates on the surface of the carbon felt. Finally, this lithium sulfur system shows both the quasi-solid-state and the solid-liquid-solid reactions in a typical ethereal electrolyte solution with a two-plateau discharge profile.
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Fullerene derivatives are used in a wide range of applications including as electron acceptors in solution-processable organic photovoltaics. We report agglomeration of fullerene derivatives in optically opaque solutions of PC 61 BM and PC 71 BM, with concentrations ranging from 30 mg mL -1 up to 90 mg mL -1 , in different solvents with relevance to organic photovoltaics, using a novel neutron scattering technique, Spin-Echo Small Angle Neutron Scattering (SESANS). From SESANS, agglomerates with correlation lengths larger than 1 μm are found in some PC 61 BM solutions, in contrast no agglomerates are seen in PC 71 BM solutions. These results clearly show that PC 71 BM is fundamentally more soluble than PC 61 BM in the solvents commonly used in photovoltaic inks and corroborating similar observations previously achieved using other experimental techniques. Computer models are presented to study the energetics of solution and agglomeration of both species, ascribing the difference to a kinetic effect probably related to the larger anisotropy of PC 71 BM. Also, this work showcases the power of SESANS to probe agglomerates of fullerene derivatives in completely opaque solutions for agglomerates of the order of one to several microns.