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DOE OSTI2022

Kimberlina 1.2 CCUS Geophysical Models and Synthetic Data Sets

This synthetic multi-scale and multi-physics data set was produced in collaboration with teams at the Lawrence Berkeley National Laboratory, National Energy Technology Laboratory, Los Alamos National Laboratory, and Colorado School of Mines through the Science-informed Machine Learning for Accelerating Real-Time Decisions in Subsurface Applications (SMART) Initiative. Data are associated with the following publication: Alumbaugh, D., Gasperikova, E., Crandall, D., Commer, M., Feng, S., Harbert, W., Li, Y., Lin, Y., and Samarasinghe, S., “The Kimberlina Synthetic Geophysical Model and Data Set for CO2 Monitoring Investigations”, The Geoscience Data Journal, 2023, DOI: 10.1002/gdj3.191. The dataset uses the Kimberlina 1.2 CO2 reservoir flow model simulations based on a hypothetical CO2 storage site in California (Birkholzer et al., 2011; Wainwright et al., 2013). Geophysical properties models (P- and S-wave seismic velocities, saturated density, and electrical resistivity) were produced with an approach similar to that of Yang et al. (2019) and Gasperikova et al. (2022) for 100 Kimberlina 1.2 reservoir models. Links to individual resources are provided below: [CO2 Saturation Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-co2-saturation-models); Resistivity Models – [part 1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-1), [part 2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-2), and [part 3](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-3); [Vp Velocity Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vp-velocity-models); [Vs Velocity Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vs-velocity-models); [Density Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-density-models). The 3D distributions of geophysical properties for the 33 time stamps of the SIM001 model were used to generate synthetic seismic, gravity, and electromagnetic (EM) responses for 33 times between zero and 200 years. Synthetic surface seismic data were generated using 2D and 3D finite-difference codes that simulate the acoustic wave equation (Moczo et al., 2007). 2D data were simulated for six point-pressure sources along a 2D line with 10 m receiver spacing and a time spacing of 0.0005 s. 3D simulations were completed for 25 surface pressure sources using a source separation of 1 km in both the x and y directions and a time spacing of 0.001 s. Links to individual resources are provided below: [2D velocity models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-2d-velocity-models) and [2D surface seismic data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-2d-surface-seismic-data). [3D velocity models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-velocity-models), and 3D seismic data [year0](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year0), [year1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year1), [year2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year2), [year5](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year5), [year10](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year10), [year15](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year15), [year20](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year20), [year25](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year25), [year30](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year30), [year35](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year35), [year40](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year40), [year45](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year45), [year49](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year49), [year50](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year50), [year51](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year51), [year52](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year52), [year55](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year55), [year60](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year60), [year65](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year65), [year70](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year70), [year75](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year75), [year80](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year80), [year85](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year85), [year90](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year90), [year95](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year95), [year100](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year100), [year110](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year110), [year120](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year120), [year130](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year130), [year140](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year140), [year150](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year150), [year175](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year175), [year200](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year200). The Python scripts to read these models and data are provided [here](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-python-scripts). EM simulations used a borehole-to-surface survey configuration, with the source located near the reservoir level and receivers on the surface using the code developed by Commer and Newman (2008). Pseudo-2D data for the source at [2500 m](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-pseudo-2d-csem-data-tz2500m) and [3025 m](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-pseudo-2d-csem-data-tz3025m), used a 2D inline receiver configuration to simulate a response over 3D resistivity models. The [3D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-csem-data) contain electric fields generated by borehole sources at monitoring well locations and measured over a surface receiver grid. Vector gravity data, both on the surface and in boreholes, were simulated using a modeling code developed by Rim and Li (2015). The simulation scenarios were parallel to those used for the EM: [pseudo-2D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-gravity-data) were calculated along the same lines and within the same boreholes, and [3D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-gravity-data) were simulated over 3D models on the surface and in three monitoring wells. A series of [synthetic well logs](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-well-logs) of CO2 saturation, acoustic velocity, density, and induction resistivity in the injection well and three monitoring wells are also provided at 0, 1, 2, 5, 10, 15, and 20 years after the initiation of injection. These were constructed by combining the low-frequency trend of the geophysical models with the high-frequency variations of actual well logs collected in the Kimberlina 1 well that was drilled at the proposed site. Measurements of permeability and pore connectivity were made on cores of Vedder Sandstone, which forms the primary reservoir unit: [CT micro scans](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-ct-micro-scans-of-vedder-formation) and [Industrial CT Images](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-industrial-ct-images-vedder-formation). These measurements provide the range of scales in the otherwise synthetic data set to be as close to a real-world situation as possible. References: Birkholzer, J.T., Zhou, Q., Cortis, A. and Finsterle, S., 2011. A sensitivity study on regional pressure buildup from large-scale CO2 storage projects. Energy Procedia, 4, 4371-4378. Commer, M., and Newman, G.A., 2008. New advances in three-dimensional controlled-source electromagnetic inversion, Geophysical Journal International, 172, 513-535. Gasperikova, E., Appriou, D., Bonneville, A., Feng, Z., Huang, L., Gao, K., Yang, X., Daley, T., 2022, Sensitivity of geophysical techniques for monitoring secondary CO2 storage plumes, Int. J. Greenh. Gas Control, Volume 114, 103585, ISSN 1750-5836, https://doi.org/10.1016/j.ijggc.2022.103585. Moczo, P., J.O. Robertsson and L. Eisner, 2007, The finite-difference time-domain method for modeling of seismic wave propagation: Advances in geophysics, 48, 421-516. Rim, H., and Y. Li, 2015, Advantages of borehole vector gravity in density imaging, Geophysics, 80, G1-G13. Wainwright, H. M.; Finsterle, S.; Zhou, Q.; Birkholzer, J. T., 2013. Modeling the Performance of Large-Scale CO2 Storage Systems: A Comparison of Different Sensitivity Analysis Methods. International Journal of Greenhouse Gas Control, 17, 189205. https://doi.org/10.1016/j.ijggc.2013.05.007, DOI: 10.18141/1603331. Yang, X., Buscheck, T.A., Mansoor, K., Wang, Z., Gao, K., Huang, L., Appriou, D., and Carroll, S.A., 2019. Assessment of geophysical monitoring methods for detection of brine and CO2 leakage in drinking water aquifers, International Journal of Greenhouse Gas Control, 90, 102803, https://doi.org/10.1016/j.ijggc.2019.102803.

CCUS↗
NASA NTRS1999

Mapping the Martian Meteorology

The Mars-adapted version of the NASA/GISS general circulation model (GCM) has been applied to the hourly/daily simulation of the planet's meteorology over several seasonal orbits. The current running version of the model includes a diurnal solar cycle, CO2 sublimation, and a mature parameterization of upper level wave drag with a vertical domain extending from the surface up to the 6microb level. The benchmark simulations provide a four-dimensional archive for the comparative evaluation of various schemes for the retrieval of winds from anticipated polar orbiter measurements of temperatures by the Pressure Modulator Infrared Radiometer. Additional information is contained in the original extended abstract.

Allison, M.↗
NASA NTRS2020

Changes in the Surface Broadband Shortwave Radiation Budget During the 2017 Eclipse

While solar eclipses are known to greatly diminish the visible radiation reaching the surface of the Earth, less is known about the magnitude of the impact. We explore both the observed and modeled levels of change in surface radiation during the eclipse of 2017. We deployed a pyranometer and Pandora spectrometer instrument to Casper, Wyoming, and Columbia, Missouri, to measure surface broadband shortwave (SW) flux and atmospheric properties during the 21 August 2017 solar eclipse event. We performed detailed radiative transfer simulations to understand the role of clouds in spectral and broadband solar radiation transfer in the Earth’s atmosphere for the normal (non-eclipse) spectrum and red-shift solar spectra for eclipse conditions. The theoretical calculations showed that the non-eclipse-to-eclipse surface flux ratio depends strongly on the obscuration of the solar disk and slightly on the cloud optical depth. These findings allowed us to estimate what the surface broadband SW flux would be for hypothetical non-eclipse conditions from observations during the eclipse and further to quantify the impact of the eclipse on the surface broadband SW radiation budget. We found that the eclipse caused local reductions of time-averaged surface flux of about 379 W m−2 (50 %) and 329Wm-2 (46 %) during the ∼3 h course of the eclipse at the Casper and Columbia sites, respectively. We estimated that the Moon’s shadow caused a reduction of approximately 7 %–8% in global average surface broadband SW radiation. The eclipse has a smaller impact on the absolute value of surface flux reduction for cloudy conditions than a clear atmosphere; the impact decreases with the increase in cloud optical depth. However, the relative time-averaged reduction of local surface SW flux during a solar eclipse is approximately 45 %, and it is not sensitive to cloud optical depth. The reduction of global average SW flux relative to climatology is proportional to the non-eclipse and eclipse flux difference in the penumbra area and depends on cloud optical depth in the Moon’s shadow and geolocation due to the change in solar zenith angle. We also discuss the influence of cloud inhomogeneity on the observed SW flux. Our results not only quantify the reduction of the surface solar radiation budget, but also advance the understanding of broadband SW radiative transfer under solar eclipse conditions.

surface radiation↗
NASA NTRS1975

Radio detection of thunderstorm activity with an earth-orbiting satellite

A study was made to determine the feasibility of using artificial earth satellites to monitor thunderstorm activity. The nighttime noise-temperature measurements made with the earth-oriented vee antenna of the Radio Astronomy Explorer (RAE 1) satellite in the frequency range 0.2-9.2 MHz were correlated with reported surface thunderstorm activity. Analysis shows that the minimum nighttime HF noise level (in the absence of surface thunderstorms) at an altitude of 5850 km over the United States is fixed by man-made noise. When thunderstorms are active below the satellite, the noise level is increased by about 6-12 dB. The highest level is associated with the most intense storms. It is concluded that thunderstorm regions can be detected by an orbiting satellite using HF radio techniques, but ionospheric effects must be taken into account.

Herman, J. R.↗
NASA NTRS2010

An Analysis of the Environments of Intense Convective Systems in West Africa in 2003

We investigated the local- and regional-scale thermodynamical and dynamical environments associated with intense convective systems in West Africa during 2003. We identified convective system cases from TRMM microwave imagery, classifying each case by the system minimum 85-GHz brightness temperature and by the estimated elapsed time of propagation from high terrain. The speed of the mid-level jet, the magnitude of the low-level shear, and the surface equivalent potential temperature (theta(sub e)) were greater for the intense cases compared to the non-intense cases, although the differences between the means tended to be small, less than 3K for surface theta(sub e). Hypothesis testing of a series of commonly used intensity prediction metrics resulted in significant results only for low-level metrics such as convective available potential energy and not for any of the mid- or upper-level metrics such as 700-hPa theta(sub e). None of the environmental variables or intensity metrics by themselves or in combination appeared to be reliable direct predictors of intensity. In the regional scale analysis, the majority of intense convective systems occurred in the surface baroclinic zone where surface theta(sub e) exceeded 344 K and the 700-hPa zonal wind speeds were less than -6/ms. Fewer intense cases compared to non-intense cases were associated with African easterly wave troughs. Fewer than 25% of our cases occurred in environments with detectable Saharan dust loads, and the results for intense and non-intense cases were similar. Our results for the regional analysis were consistent with the seasonal movement of the WAM and the intertropical front, regional differences in topography, and AEW energetics.

Nicholls, Stephen D.↗
NASA NTRS1975

Interior noise considerations for powered-lift STOL aircraft

Powered-jet configuration which are under development for use on STOL aircraft involve impingement of the jet engine exhaust onto wing and flap surfaces. The impinging jet produces higher noise levels at lower frequencies than does the jet alone. These higher levels, together with the close proximity of the engine and flap noise sources to the fuselage sidewall, suggest that the noise levels in these aircraft may be high enough to interfere with passenger comfort. To investigate this possibility, interior noise levels were estimated for both an upper surface blown and an externally blown flap configuration. This paper describes the procedure used to estimate the interior noise levels is described these levels are compared with levels on existing jet aircraft and on ground transportation vehicles. These estimates indicate high levels in the STOL aircraft; therefore, areas of possible improvements in technology for control of STOL interior noise are also discussed.

Barton, C. K.↗
DOE OSTI2026

Correlating Surface Processing of Nb Superconducting RF Cavities with the Evolution of Surface Electronic States

Superconducting-radio frequency (RF) cavities provide an efficient way to accelerate particle beams with extremely high acceleration gradients while generating very small power dissipation. The few nanometers of the surface play a critical role in defining the RF performance of superconducting Nb based cavities. Over the past two decades, several pioneering surface treatment and processing methods have emerged, enabling remarkable improvements in superconducting cavity performance by simultaneously achieving high quality factors with increasing maximum acceleration gradients. These processing approaches include chemical polishing, distinct multi-step thermal treatments under ultra-high vacuum (UHV) conditions over low to high temperature regimes, as well as high-temperature treatments under controlled nitrogen atmospheres. Beyond their macroscopic impact on RF performance, these methods produce distinct surface oxide configurations characterized by different valence states, oxide thicknesses, chemical uniformity, and oxygen concentration profiles extending into the near-surface bulk of niobium. In this work, we are trying to understand how the surface-processing methods and the resulting oxide/oxygen profiles affect the electronic structure of surface and the mechanism of superconductivity. Using a combination of X-ray photoemission and X-ray absorption spectroscopies, we investigate how the valence-band structure and the electronic density of states (DoS) near the Fermi level evolve under different surface treatments. By employing tunable photon energies across multiple elemental absorption edges, we use resonant photoemission to disentangle and identify the elemental contributions to specific valence-band features. Our observations show that different surface-processing methods lead to distinct temperature evolutions of the DoS and valence-band states near the Fermi level. Our results suggest variations in different Nb-O orbital hybridizations in distinct processes and point towards the possibility of different underlying mechanisms of superconductivity governed by surface chemistry and oxide configuration. We also correlate these distinct superconducting mechanisms with RF cavity performance, specifically focusing on measured surface resistance, the nature of the Q-slope, and quench fields observed in superconducting RF measurements. These results will enable us to identify the potential limiting factors and relevant controllable parameters that can be further optimized to improve the performance of superconducting RF cavities.

Tripathi, Malvika [Fermilab] (ORCID:00000001989251↗
DOE OSTI2026

Electronic structure of the kagome compound CaTi 3⁢ Bi 4 using high-field torque magnetometry and density functional theory

Here, we report systematic torque magnetometry measurements to investigate the electronic properties of the newly discovered kagome compound CaTi 3 ⁢Bi 4 . Electrical transport, magnetic susceptibility, and thermal measurements reveal no evidence of a magnetic ground state in this material. Torque data obtained in magnetic fields up to 41.5 T exhibit clear de Haas–van Alphen (dHvA) oscillations, with nine distinct frequencies ranging from 13 to 6164 T. Angular-dependent dHvA measurements show that, with the exception of the lowest frequency (13 T), all observed frequencies nearly follow a 1/cos ⁡𝜃 dependence, where 𝜃 is the angle between the crystallographic 𝑐 axis and the magnetic field direction. This behavior is characteristic of quasi-two-dimensional Fermi-surface sheets with nearly circular cross sections. To further elucidate the electronic structure, we performed density functional theory (DFT) calculations of the band structure and Fermi surface. The calculated bands reveal the presence of multiple Dirac points (DP), flat bands (FB), and van Hove singularities (VHS) near the Fermi level. The resulting Fermi surface consists of several quasi-two-dimensional cylindrical sheets, consistent with the experimentally observed 1/cos⁡ 𝜃 dependence. Notably, the theoretical dHvA frequencies, derived from extremal Fermi-surface cross-sectional areas, agree well with the experimental values and reproduce their angular dependence. Remarkably, all experimentally observed frequencies are captured by the DFT predictions. Pressure-dependent calculations up to 10 GPa show that the electronic features—DP, FB, and VHS—evolve systematically with pressure. In particular, the VHS shifts closer to the Fermi level, demonstrating that pressure acts as an effective tuning parameter in this material. These combined experimental and theoretical results provide a comprehensive understanding of the electronic structure of CaTi 3 ⁢Bi 4 and demonstrate how pressure can be used to tune its key electronic features, offering valuable guidance for exploring related kagome materials.

Shtefiienko, Kyryl [West Texas A & M University, C↗
NASA NTRS2022

High-Vacuum Triboelectric Charging of Space Materials

In the high-vacuum environment of space and the surface of the moon, static electricity on surfaces lacks the atmospheric dissipation mechanisms found on earth. As a result, the ubiquitous triboelectric charging mechanism can lead to high levels of charge on surfaces. This static charge can result in damage to sensitive devices, interfere with communications, and electrostatic levitation of lunar dust. At the NASA Electrostatics and Surface Physics Laboratory (ESPL), we use different apparatuses and techniques to tribo-charge materials in high-vacuum (10-5 torr), including a tribo-robot and a triboelectric regolith-material stage (TRMS). The tribo-robot is used to rub two materials together, and fieldmeters and electrometers can be used to determine how much charge is on the materials. The TRMS is used to drag different materials onto a bed of lunar simulant. This system is used to characterize how materials may interact with lunar dust using fieldmeters, electrometers, and laser scattering. Using these methods, we are building a database of how different space materials charge when contacting each other at high-vacuum, and how materials triboelectrically interact with the lunar surface.

Joseph Toth↗
DOE OSTI2021

Solvent-induced electrochemistry at an electrically asymmetric carbon Janus particle

Chemical doping through heteroatom substitution is often used to control the Fermi level of semiconductor materials. Doping also occurs when surface adsorbed molecules modify the Fermi level of low dimensional materials such as carbon nanotubes. A gradient in dopant concentration, and hence the chemical potential, across such a material generates usable electrical current. This opens up the possibility of creating asymmetric catalytic particles capable of generating voltage from a surrounding solvent that imposes such a gradient, enabling electrochemical transformations. In this work, we report that symmetry-broken carbon particles comprised of high surface area single-walled carbon nanotube networks can effectively convert exothermic solvent adsorption into usable electrical potential, turning over electrochemical redox processes in situ with no external power supply. The results from ferrocene oxidation and the selective electro-oxidation of alcohols underscore the potential of solvent powered electrocatalytic particles to extend electrochemical transformation to various environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1979

Experimental study of acoustic loads on an upper-surface-blown STOL airplane configuration

Fluctuating pressure levels were measured on the flap and fuselage of an upper-surface-blown jet-flap airplane configuration in a wind tunnel. The model tested had turbofan engines with a bypass ratio of 3 and a thrust rating of 10 kN. Rectangular nozzles were mounted flush with the upper surface at 35 percent of the wing chord. Test parameters were flap deflection angle, jet impingement angle, angle of attack, free-stream velocity, spanwise location of the engine, and jet dynamic pressure. Load levels were high throughout the jet impingement region, with the highest levels (about 159 dB) occurring on the fuselage and near the knee of the flap. The magnitude of the forward-velocity effect appeared to depend upon the ratio of free-stream and jet velocities. Good agreement was obtained between fluctuating pressure spectra measured at jet dynamic pressures of 7 and 22 kPa when the spectra were scaled by nondimensional functions of dynamic pressure, velocity, and the empirical relationship between dynamic pressure and overall fluctuating pressure level.

Willis, C. M.↗
NASA NTRS2000

BOREAS Level-4c AVHRR-LAC Ten-Day Composite Images: Surface Parameters

The BOReal Ecosystem-Atmosphere Study (BOREAS) Staff Science Satellite Data Acquisition Program focused on providing the research teams with the remotely sensed satellite data products they needed to compare and spatially extend point results. Manitoba Remote Sensing Center (MRSC) and BOREAS Information System (BORIS) personnel acquired, processed, and archived data from the Advanced Very High Resolution Radiometer (AVHRR) instruments on the NOAA-11 and -14 satellites. The AVHRR data were acquired by CCRS and were provided to BORIS for use by BOREAS researchers. These AVHRR level-4c data are gridded, 10-day composites of surface parameters produced from sets of single-day images. Temporally, the 10-day compositing periods begin 11-Apr-1994 and end 10-Sep-1994. Spatially, the data cover the entire BOREAS region. The data are stored in binary image format files. Note: Some of the data files on the BOREAS CD-ROMs have been compressed using the Gzip program.

Cihlar, Josef↗
NASA NTRS1992

Genesis of mobile troughs in the upper westerlies

Stability calculations on basic-state velocity profiles representative of the preferred regions for the development of the upper-level disturbances active in Type B cyclogenesis show that conditions in these regions (weak low-level baroclinicity, large low-level static stability, and large surface roughness) are favorable for the growth of baroclinic waves with maximum amplitude near the tropopause. The structure of these waves compares favorably with observations of developing short-wavelength upper-level troughs in the atmosphere. Basic states characteristic of the storm track regions (strong low-level baroclinicity and small surface roughness) favor the development of baroclinic waves with maximum amplitude at the surface. The dynamics of both the surface-trapped and the upper-tropospheric waves can be interpreted concisely using concepts of potential vorticity. Based on these results, a possible mechanism for Type B cyclogenesis in the storm track regions is proposed that involves the propagation and structural modification of baroclinic wave packets in a zonally varying basic flow.

Whitaker, Jeffrey S.↗
NASA NTRS2019

A Control Framework for Autonomous Smart Grids for Space Power Applications

With the National Aeronautics and Space Administration's (NASA) rising interest in lunar surface operations and deep space exploration, there is a growing need to move from traditional ground-based mission operations to more autonomous vehicle level operations. In lunar surface operations, there are periods of time where communications with ground-based mission control could not occur, forcing vehicles and a lunar base to completely operate independent of the ground. For deep space exploration missions, communication latency times increase to greater than 15 minutes making real-time control of critical systems difficult, if not near impossible. These challenges are driving the need for an autonomous power control system that has the capability to manage power and energy. This will ensure that critical loads have the necessary power to support life systems and carry out critical mission objectives. This paper presents a flexible, hierarchical, distributed control methodology that enables autonomous operation of smart grids and can integrate into a higher level autonomous architecture.

Csank, Jeffrey T.↗
NASA NTRS2019

A Control Framework for Autonomous Smart Grids for Space Power Applications

With the National Aeronautics and Space Administration's (NASA) rising interest in lunar surface operations and deep space exploration, there is a growing need to move from traditional ground-based mission operations to more autonomous vehicle level operations. In lunar surface operations, there are periods of time where communications with ground-based mission control could not occur, forcing vehicles and a lunar base to completely operate independent of the ground. For deep space exploration missions, communication latency times increase to greater than 15 minutes making real-time control of critical systems difficult, if not near impossible. These challenges are driving the need for an autonomous power control system that has the capability to manage power and energy. This will ensure that critical loads have the necessary power to support life systems and carry out critical mission objectives. This paper presents a flexible, hierarchical, distributed control methodology that enables autonomous operation of smart grids and can integrate into a higher level autonomous architecture.

Carbone, Marc A.↗
DOE OSTI2025

Correlating Nb-SRF Surface Processing with Evolution of Surface Electronic States

The few nanometers of the surface exposed to RF field plays a major role in defining the RF performance of superconducting cavities. Over the past two decades, several pioneering surface treatment and processing methods have emerged, enabling remarkable improvements in cavity performance by simultaneously achieving high Q with increasing Eacc. These processing methods include: thermal treatment under ultra-high vacuum (UHV) conditions across lo¬¬¬¬¬¬¬w-, mid-, and high-temperature ranges and high temperature treatments under controlled N2 atmosphere. These processes also produce distinct surface oxide configurations with different valence states, thicknesses, and uniformity, as well as different oxygen concentration profiles in bulk Nb. In this work, we are trying to understand how do surface-processing methods and the resulting oxide/oxygen profiles affect the electronic structure of surface and the mechanism of superconductivity? With the help of Fermilab’s in-house X-ray photoemission facility and, in collaboration with the synchrotron-based angle-resolved photoemission (ARPES) facility at Argonne National Laboratory, we are investigating how the valence band structure and density of states (DoS) near the Fermi level modify with different surface treatments. Our observations show that different surface-processing methods lead to distinct evolutions of the valence-band states near the Fermi level during the superconducting transition. This behavior suggests variations in Nb-O orbital hybridizations and points towards the possibility of different underlying mechanisms of superconductivity governed by the surface chemistry and oxide configuration. We also correlate these distinct superconducting mechanisms with RF cavity performance, specifically focusing on measured surface resistance, the nature of the Q-slope, and quench fields observed in SRF measurements. These results will enable us to identify the potential limiting factors and relevant controllable parameters that can be further optimized to improve the performance of SRF cavities.

Tripathi, Malvika [Fermilab]↗