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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Chronology and Petrology of Silicates From IIE Iron Meteorites: Evidence of a Complex Parent Body Evolution

IIE iron meteorites contain silicate inclusions whose characteristics suggest a parent body similar to that of H-chondrites. However, these silicates show a wide range of alteration, ranging from Netschadvo and Techado, whose inclusions are little altered. to highly differentiated silicates like-those in Kodaikanal, Weekeroo Station and Colomera, which have lost metal and sulfur and are enriched in feldspar. We find these inclusions to show varying degrees of shock alteration. Because only a limited amount of data on - isotopic ages of HE silicates were available, we made Ar-39 - Ar-40 age determinations of Watson, Techado, miles Colomera, and Sombrerete. Watson has an Ar-Ar age of 3.653 +/- 0.012 Gyr, similar to previously reported ages for Kodaikanal and Netschadvo. We suggest that the various determined radiometric ages of these three meteorites were probably reset by a common impact event. The space exposure ages for these three meteorites are also similar to each other and are considerably younger than exposure ages of other IIEs. Ar-39 - Ar-40 ages inferred for the other four meteorites analyzed are considerably older than Watson and are: Techado =4.49 +/- 0.01 Gyr, Miles =4.412 +/- 0.016 Gyr, Colomera =4.469 +/- 0.012 Gyr, and Sombrerete =4.535 +/- 0.005 Gyr. These ages are in fair agreement with previously reported Rb-Sr isochron ages for Colomera and Weekeroo Station. Although several mechanisms to form HE meteorites previously were suggested, it is not obvious that a single mechanism could produce a suite of meteorites with very different degrees of silicate differentiation and with isotopic ages that differ by >0.8 Gyr. We suggest that those IIEs with older isotopic ages are a product of partial melting and differentiation within the parent body, followed by mixing of silicate and metal while both were relatively hot. Netschadvo and Watson may have formed by this same process or by impact mixing about 4.5 Gyr ago, but their isotopic ages were subsequently reset by shock heating. Kodaikanal apparently is required to have formed more recently, in which case impact melting and differentiation seems the only viable process. We see no compelling reasons to believe that IIE silicate and metal derived from different parent bodies or that the parent body of IIEs was the same as that of H-chondrites.

Bogard, Donald D.↗
NASA NTRS2022

Diffusion in Melts and Magmas

Diffusion results from random motion of particles and entities. Diffusion in melts and magmas is due to thermally excited random motion of atoms, ions, and clusters, and plays a critical role in magmatic and volcanic processes. In melts and magmas, diffusion is one of the two mechanisms of mass transfer; the other being bulk flow (referred to as convection or advection). When both are present, diffusion refers to the dispersive motion relative to the mean bulk flow in a given reference frame (Richter et al. 1998). Diffusion plays critical roles in controlling magma mixing (Watson 1982; Koyaguchi 1985, 1989; Lesher 1994; Huber et al. 2009; Guo and Zhang 2020), mineral growth and dissolution rates in magmas (e.g., Watson 1982; Harrison and Watson 1983; Zhang et al. 1989; Newcombe et al. 2014; Macris et al. 2018), bubble growth and dissolution rate in magmas (Sparks 1978; Proussevitch and Sahagian 1998; Liu and Zhang 2000; Zhang 2013), and elemental and isotope fractionation during mineral 2 growth and dissolution (Jambon 1980; Richter et al. 1999, 2003; Watson and Muller 2009; Chopra et al. 2012; Watkins et al. 2014, 2017; Holycross et al. 2016, 2018). As a result, diffusion also plays an essential role in explosive volcanic eruptions and magma crystallization. Furthermore, diffusion has important applications in geospeedometry (Lasaga 1983, 1998; Zhang 1994, 2008; Trail et al. 2016; Zhang and Xu 2016). Experimental investigation of diffusion in geologically relevant silicate melts began to flourish in the 1970’s when micro-analytical measurements of diffusion profiles became available. In addition to the vast number of papers published since then, numerous books and reviews are available for diffusion in silicate melts. Hofmann et al. (1974) edited a book titled “Geochemical Transport and Kinetics” published by Carnegie Institution of Washington. This was the first landmark book summarizing the field. Lasaga and Kirkpatrick (1981) edited a book “Kinetics of Geochemical Processes” as volume 8 of the Reviews in Mineralogy (later becoming Reviews in Mineralogy and Geochemistry) series. Zhang and Cherniak (2010) edited “Diffusion in Minerals and Melts” as volume 72 of Reviews of Mineralogy and Geochemistry series, in which one chapter focused on diffusion theory, five chapters on diffusion in silicate melts (Behrens 2010; Lesher 2010; Liang 2010; Zhang and Ni 2010; Zhang et al. 2010), and other chapters were on experimental, analytical, and computational methods, and diffusion in minerals. Several textbooks covered the principles and applications of diffusion theories (Kirkaldy and Young 1987; Shewmon 1989; Cussler 1997; Lasaga 1998; Zhang 2008; Vrentas and Vrentas 2016), and two classic books covered the mathematics of diffusion (Carslaw and Jaeger 1959; Crank 1975). In preparing for this review chapter, we thought carefully about what to cover for this vast field, and decided to briefly go through the fundamentals of diffusion (more complete review can be found in Chakraborty 1995; Zhang 2008, 2010) and solutions to often-encountered 3 diffusion problems, and then focus on post-2010 diffusion studies on silicate melts and magmas. Here, melts refer to (mostly natural) silicate liquid, and magmas refer to crystal-bearing and/or bubble-bearing melts in which the continuous phase is the melt. There is a large body of work on diffusion in glasses, especially in the materials science literature, which is not covered in this review.

Youxue Zhang↗
NASA NTRS2022

How do we get robots to take self-portraits on Mars? – Perseverance-Ingenuity and Curiosity selfies

The Perseverance rover landed in Jezero crater,Mars, on 18 February 2021. It carried with it a technologydemonstration, the Ingenuity helicopter, which hasdemonstrated the first controlled, powered flight on anotherplanet. This paper describes how an iconic, April 2021 imageof the Perseverance rover with the Ingenuity helicopter wasdesigned and executed as the rover was getting ready todeploy the helicopter. WATSON is a camera mounted at theend of the rover’s robotic arm and was used to acquire theself-portrait. WATSON is designed to take close up picturesof rocks and regolith on Mars but can also provide views ofthe terrain. A single image covers a small portion of thescene. In order to a create a mosaic covering the full roverand helicopter, 62 WATSON images were acquired. To allowthe images to be mosaicked together, the camera needs to bekept in the same spot. The robotic arm has five degrees offreedom for motion; small changes in orientation can requiresignificant repositioning of the robotic arm joints. Todocument this, a movie of the arm motion was acquired bythe rover’s mast-mounted left navigation camera pointed atthe WATSON and robotic arm while it was simultaneouslymoving to acquire the selfie. For the first time, we alsocaptured the sound of the arm motion as it was acquiring theselfie. In the case of the Perseverance selfie with the Ingenuity helicopter, we also had to think about how toposition the rover with respect to the helicopter and fit theselfie acquisition into the helicopter prime mission timeline.This paper also describes the history of NASA Mars roverselfies.

Beegle, Luther↗
DOE OSTI2023

Anionic G•U pairs in bacterial ribosomal rRNAs

Wobble GU pairs (or G•U) occur frequently within double-stranded RNA helices interspersed between standard G=C and A-U Watson–Crick pairs. Another type of G•U pair interacting via their Watson–Crick edges has been observed in the A site of ribosome structures between a modified U34 in the tRNA anticodon triplet and G + 3 in the mRNA. In such pairs, the electronic structure of the U is changed with a negative charge on N3(U), resulting in two H-bonds between N1(G)…O4(U) and N2(G)…N3(U). Here, we report that such pairs occur in other highly conserved positions in ribosomal RNAs of bacteria in the absence of U modification. An anionic cis Watson–Crick G•G pair is also observed and well conserved in the small subunit. These pairs are observed in tightly folded regions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Ab initio leading order effective potential for elastic proton scattering based on the symmetry-adapted no-core shell model

Calculating microscopic optical potentials for elastic scattering at intermediate energies from light nuclei in an ab initio fashion within the Watson expansion has been established within the last few years. Based on the Watson expansion of the multiple scattering series, we employ a nonlocal translationally invariant nuclear density derived within the symmetry-adapted no-core shell model (SA-NCSM) framework from a chiral next-to-next-to-leading order (NNLO) nucleon-nucleon interaction and the very same interaction for a consistent full-folding calculation of the effective (optical) potential for nucleon-nucleus scattering for medium-heavy nuclei. The leading order effective (optical) folding potential is computed by integrating over a translationally invariant SA-NCSM one-body scalar density, spin-projected momentum distribution, and the Wolfenstein amplitudes 𝐴, 𝐶, and 𝑀. The resulting nonlocal potentials serve as input for a momentum space Lippmann-Schwinger equation. In the SA-NCSM, the model space is systematically up-selected using Sp⁡(3,ℝ) symmetry considerations. For the light nucleus of 6 He, we establish a systematic selection scheme in the SA-NCSM for scattering observables. Then, we apply this scheme to calculations of scattering observables, such as differential cross sections, analyzing powers, and spin rotation functions for elastic proton scattering from 20 Ne and 40 Ca in the energy regime between 65 and 200 MeV, and compare to available data. Furthermore, our calculations show that the leading order effective nucleon-nucleus potential in the Watson expansion of multiple scattering theory obtained from an up-selected SA-NCSM model space describes 40 Ca elastic scattering observables reasonably well to about 60 degrees in the center-of-mass frame, which coincides roughly with the validity of the NNLO chiral interaction used to calculate both the nucleon-nucleon amplitudes and the one-body scalar and spin nuclear densities.

Ab initio calculations↗
DOE OSTI2023

Chiral uncertainties in ab initio elastic nucleon-nucleus scattering

The effective interaction between a nucleon and a nucleus is one of the most important ingredients for reaction theories. Theoretical formulations were introduced early by Feshbach and Watson, and efforts of deriving and computing those ‘optical potentials’ in a microscopic fashion have a long tradition. However, only recently the leading order term in the Watson multiple scattering approach could be calculated fully ab initio, meaning that the same nucleon-nucleon (NN) interaction enters both the structure as well as the reaction pieces on equal footing. This allows the uncertainties from the underlying chiral effective NN interaction to be systematically explored in nucleon-nucleus elastic scattering observables. In this contribution the main ingredients for arriving at the ab initio leading order of the effective nucleon-nucleus interaction in the Watson approach will be reviewed. Concentrating on one specific chiral NN interaction from the LENPIC collaboration and light nuclei with a 0 + ground state, the leading order nucleon-nucleus interaction is calculated using up to the third chiral order (N2LO) in the nucleon-nucleon potential, and elastic scattering observables are extracted. Then pointwise as well as correlated uncertainty quantification is used for the estimation of the chiral truncation error. Elastic scattering observables for 4 He, 12 C, and 16 O for between 65 and 200 MeV projectile energy will be analyzed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRSDate not supplied

Calibration and Validation of the SHERLOC Instrument Operating in Jezero Crater, Mars

The Scanning Habitable Environments with Raman and Luminescence for Organics and Chemistry (SHERLOC) is an instrument onboard the Mars 2020 Perseverance rover. It consists of a spectrometer that measures deep ultraviolet (DUV) resonance Raman and native fluorescence photons generated through surface interactions with a 248.6 nm pulsed laser. Two microscopic imagers, the Autofocus Context Imager (ACI) and the Wide-Angle Topographic Sensor for Operations and eNgineering (WATSON), provide high-resolution context images of SHERLOC targets. The ACI is co-boresighted with the spectrometer. To ensure proper calibration, the SHERLOC calibration target (SCT) is mounted on the front of the rover and consists of ten different materials. The SCT was designed, fabricated, assembled, and tested by Jacobs Technology, Inc., and NASA Johnson Space Center. The dimensions of the calibration target housing are 150 x 89 x 33 mm and it weighs ~437 g. The ten targets are arranged in two rows; the first six are hard targets (AlGaN for Raman and fluorescence, diffuse transmission target, a slice of the SaU008 Mars meteorite, an intensity maze, and polycarbonate over geocache coin) and the remaining four are soft-goods targets (Vectran, Ortho-Fabric, Teflon, and nGimat-coated Teflon). The hard targets calibrate the spectrometer’s Raman and fluorescence spectral accuracy, ambient light reflection, and Raman response curve, while the soft-goods targets are spacesuit materials that function as human exploration targets, some of which are also used for spectral calibration. SHERLOC also has an internal calibration target consisting of AlGaN on sapphire (275 nm) located inside the ACI opaque dust cover to ensure proper instrument functioning between calibration target analyses. Initial SHERLOC, ACI, and WATSON calibration and validation on Mars was performed using the internal calibration target on sols 59, 83, 98, and 141; WATSON imaging of the SCT on sols 26 and 62, and SHERLOC spectroscopy and ACI imaging of the SCT on sol 59. These early data provide initial insights into instrument performance and the stability and degradation of the calibration target materials relative to the Martian surface and dust environment. Early observations also have implications for future astronaut spacesuit materials.

Trevor G Graff↗
DOE OSTI2024

Global Geo-processed Data of Aquifer Properties by 0.5° Grid, Country and Water Basins

This repository of global hydrogeologic datasets contains aquifer properties on 0.5° scale, including depth to groundwater (Fan et al., 2013), aquifer thickness (de Graaf et al., 2015), WHYMap aquifer classes (Richts et al., 2011), porosity and permeability (Gleeson et al., 2014), digitized and geo-processed from their respective sources. Globally gridded aquifer properties could be used independently to estimate global groundwater availability or used as critical inputs to the superwell model to simulate groundwater extraction and provide estimates of pumped volumes and unit costs under user-specific scenarios. Key resources related to this data are: Niazi, H., Ferencz, S., Graham, N., Yoon, J., Wild, T., Hejazi, M., Watson, D., & Vernon, C. (2024; In-prep). Long-term Hydro-economic Assessment Tool for Evaluating Global Groundwater Cost and Supply: Superwell v1. Geoscientific Model Development. superwell model repository which uses this data to simulate groundwater extraction and provides estimates of the global extractable volumes and unit-costs ($/km3) of accessible groundwater production under user-specified extraction scenarios. Repository Overview Main output: aquifer_properties.csv contains all processed outputs, including aquifer properties like porosity, permeability, aquifer thickness, and depth to groundwater. shapefiles.zip: contains all digitized GIS databases and shapefile for all aquifer properties prep_inputs.R: R script that processes the shapefiles to produce the aquifer_properties file plot_inputs.R: R script for plotting the maps and conducting preliminary analysis on the available groundwater volume basin_to_country_mapping.csv, basin_country_region_mapping.csv and continent_county_mapping.csv provide the mapping between continents, 32 energy-economic macro regions, countries, and water basins for post-processing aquifer_properties.csv Maps: Each map visualizes the spatial distribution of one of the aquifer properties across the globe map_in_Porosity.png map_in_Permeability.png map_in_Aquifer_thickness.png map_in_Depth_to_water.png map_in_Grid_area_km.png map_in_WHYClass.png Sample inputs sample_inputs.py: this script samples inputs from the aquifer_properties dataset, ensuring the sampled and original inputs maintain the same distributions sampled_data_100.csv contains 100 sampled data points and sampled_data_100.png compares their distributions Dataset Overview The main outputs are consolidated in a comprehensive aquifer_properties.csv file and include the following fields: GridCellID: Unique identifier for each (roughly 0.5°) grid cell Continent: Continent name Country: Country name GCAM_basin_ID: Identifier for GCAM hydrologic basin Basin_long_name: Full name of the basin WHYClass: Hydrogeologic classification based on WHYMap aquifer classes (Richts et al., 2011) Porosity: Soil porosity (%) (Gleeson et al., 2014) Permeability: Soil permeability (in square meters; Gleeson et al., 2014) Aquifer_thickness: Thickness of the aquifer (in meters; de Graaf et al., 2015) Depth_to_water: Depth to groundwater (in meters; Fan et al., 2013) Grid_area: Area of the grid cell (in square meters) Key References The datasets are digitized versions of global hydrogeologic properties from the following key literature sources: Depth to Groundwater: Fan, Y., Li, H., & Miguez-Macho, G. (2013). Global Patterns of Groundwater Table Depth. Science, 339(6122), 940-943. https://doi.org/10.1126/science.1229881 Aquifer Thickness: de Graaf, I. E. M., Sutanudjaja, E. H., van Beek, L. P. H., & Bierkens, M. F. P. (2015). A high-resolution global-scale groundwater model. Hydrol. Earth Syst. Sci., 19(2), 823-837. https://doi.org/10.5194/hess-19-823-2015 Porosity and Permeability: Gleeson, T., Moosdorf, N., Hartmann, J., & van Beek, L. P. H. (2014). A glimpse beneath earth's surface: GLobal HYdrogeology MaPS (GLHYMPS) of permeability and porosity. Geophysical Research Letters, 41(11), 3891-3898. https://doi.org/10.1002/2014GL059856 Aquifer classes: Richts, A., Struckmeier, W. F., & Zaepke, M. (2011). WHYMAP and the Groundwater Resources Map of the World 1:25,000,000. In J. A. A. Jones (Ed.), Sustaining Groundwater Resources: A Critical Element in the Global Water Crisis (pp. 159-173). Springer Netherlands. https://doi.org/10.1007/978-90-481-3426-7_10 Cite as Niazi, H., Watson, D., Hejazi, M., Yonkofski, C., Ferencz, S., Vernon, C., Graham, N., Wild, T., & Yoon, J. (2024). Global Geo-processed Data of Aquifer Properties by 0.5° Grid, Country and Water Basins. MSD-LIVE Data Repository. https://doi.org/10.57931/2307831 Contact Reach out to Hassan Niazi or open an issue in superwell repository for questions or suggestions.

aquifer thickness↗
DOE OSTI2024

Global Geo-processed Data of Aquifer Properties by 0.5° Grid, Country and Water Basins

This repository of global hydrogeologic datasets contains aquifer properties on 0.5° scale, including depth to groundwater (Fan et al., 2013), aquifer thickness (de Graaf et al., 2015), WHYMap aquifer classes (Richts et al., 2011), recharge (Döll and Fiedler, 2008; Gleeson et al., 2016), lakes (Messager et al., 2016), porosity and permeability (Gleeson et al., 2014), digitized and geo-processed from their respective sources. Globally gridded aquifer properties could be used independently to estimate global groundwater availability or used as critical inputs to the superwell model to simulate groundwater extraction and provide estimates of pumped volumes and unit costs under user-specific scenarios. Key resources related to this data are: Niazi, H., Ferencz, S. B., Graham, N. T., Yoon, J., Wild, T. B., Hejazi, M., Watson, D. J., & Vernon, C. R. (2025). Long-term hydro-economic analysis tool for evaluating global groundwater cost and supply: Superwell v1.1. Geoscientific Model Development, 18(5), 1737-1767. https://doi.org/10.5194/gmd-18-1737-2025 superwell model repository which uses this data to simulate groundwater extraction and provides estimates of the global extractable volumes and unit-costs ($/km3) of accessible groundwater production under user-specified extraction scenarios. Repository Overview Main output: aquifer_properties_rec.csv contains all processed outputs, including aquifer properties like porosity, permeability, recharge, lake areas, aquifer thickness, and depth to groundwater. shapefiles.zip: contains all digitized GIS databases and shapefile for all aquifer properties prep_inputs.R and prep_inputs_recharge_lakes.R: R scripts that process the shapefiles to produce the aquifer_properties_rec.csv file plot_inputs.R: R script for plotting the maps and conducting preliminary analysis on the available groundwater volume basin_to_country_mapping.csv, basin_country_region_mapping.csv and continent_county_mapping.csv provide the mapping between continents, 32 energy-economic macro regions, countries, and water basins for post-processing aquifer_properties_rec.csv Maps: Each map visualizes the spatial distribution of one of the aquifer properties across the globe map_in_Porosity.png map_in_Permeability.png map_in_Aquifer_thickness.png map_in_Depth_to_water.png map_in_Recharge.png map_in_Grid_area_km.png map_in_Lake_area_km.png map_in_WHYClass.png Sample inputs sample_inputs.py: this script samples inputs from the aquifer_properties_rec dataset, ensuring the sampled and original inputs maintain the same distributions sampled_data_100.csv contains 100 sampled data points and sampled_data_100.png compares their distributions Dataset Overview The main outputs are consolidated in a comprehensive aquifer_properties_rec.csv file and include the following fields: GridCellID: Unique identifier for each (roughly 0.5°) grid cell Continent: Continent name Country: Country name GCAM_basin_ID: Identifier for GCAM hydrologic basin Basin_long_name: Full name of the basin WHYClass: Hydrogeologic classification based on WHYMap aquifer classes (Richts et al., 2011) Porosity: Soil porosity (%) (Gleeson et al., 2014) Permeability: Soil permeability (in square meters; Gleeson et al., 2014) Aquifer_thickness: Thickness of the aquifer (in meters; de Graaf et al., 2015) Depth_to_water: Depth to groundwater (in meters; Fan et al., 2013) Recharge: long-term annual averaged recharge rates (in m/yr; Döll and Fiedler, 2008; Gleeson et al., 2016) Grid_area: Area of the grid cell (in square meters) Lakes_area: Area of inland lakes (in square meters; Messager et al., 2016) Key References The datasets are digitized versions of global hydrogeologic properties from the following key literature sources: Depth to Groundwater: Fan, Y., Li, H., & Miguez-Macho, G. (2013). Global Patterns of Groundwater Table Depth. Science, 339(6122), 940-943. https://doi.org/10.1126/science.1229881 Aquifer Thickness: de Graaf, I. E. M., Sutanudjaja, E. H., van Beek, L. P. H., & Bierkens, M. F. P. (2015). A high-resolution global-scale groundwater model. Hydrol. Earth Syst. Sci., 19(2), 823-837. https://doi.org/10.5194/hess-19-823-2015 Porosity and Permeability: Gleeson, T., Moosdorf, N., Hartmann, J., & van Beek, L. P. H. (2014). A glimpse beneath earth's surface: GLobal HYdrogeology MaPS (GLHYMPS) of permeability and porosity. Geophysical Research Letters, 41(11), 3891-3898. https://doi.org/10.1002/2014GL059856 Aquifer classes: Richts, A., Struckmeier, W. F., & Zaepke, M. (2011). WHYMAP and the Groundwater Resources Map of the World 1:25,000,000. In J. A. A. Jones (Ed.), Sustaining Groundwater Resources: A Critical Element in the Global Water Crisis (pp. 159-173). Springer Netherlands. https://doi.org/10.1007/978-90-481-3426-7_10 Recharge: Döll, P., & Fiedler, K. (2008). Global-scale modeling of groundwater recharge. Hydrol. Earth Syst. Sci., 12(3), 863-885. https://doi.org/10.5194/hess-12-863-2008; Gleeson, T., Befus, K. M., Jasechko, S., Luijendijk, E., & Cardenas, M. B. (2016). The global volume and distribution of modern groundwater. Nature Geoscience, 9(2), 161-167. https://doi.org/10.1038/ngeo2590 Inland Lakes: Messager, M. L., Lehner, B., Grill, G., Nedeva, I., & Schmitt, O. (2016). Estimating the volume and age of water stored in global lakes using a geo-statistical approach. Nature Communications, 7(1), 13603. https://doi.org/10.1038/ncomms13603 Cite as Niazi, H., Watson, D., Hejazi, M., Yonkofski, C., Ferencz, S., Vernon, C., Graham, N., Wild, T., & Yoon, J. (2024). Global Geo-processed Data of Aquifer Properties by 0.5° Grid, Country and Water Basins. MultiSector Dynamics-Living, Intuitive, Value-adding, Environment. https://doi.org/10.57931/2484226 Contact Reach out to Hassan Niazi or open an issue in the superwell repository for questions or suggestions.

aquifer thickness↗
NASA NTRS1983

Reduction of display artifacts by random sampling

The application of random-sampling techniques to remove visible artifacts (such as flicker, moire patterns, and paradoxical motion) introduced in TV-type displays by discrete sequential scanning is discussed and demonstrated. Sequential-scanning artifacts are described; the window of visibility defined in spatiotemporal frequency space by Watson and Ahumada (1982 and 1983) and Watson et al. (1983) is explained; the basic principles of random sampling are reviewed and illustrated by the case of the human retina; and it is proposed that the sampling artifacts can be replaced by random noise, which can then be shifted to frequency-space regions outside the window of visibility. Vertical sequential, single-random-sequence, and continuously renewed random-sequence plotting displays generating 128 points at update rates up to 130 Hz are applied to images of stationary and moving lines, and best results are obtained with the single random sequence for the stationary lines and with the renewed random sequence for the moving lines.

Ahumada, A. J., Jr.↗
NASA NTRS2011

Updating the Standard Spatial Observer for Contrast Detection

Watson and Ahmuada (2005) constructed a Standard Spatial Observer (SSO) model for foveal luminance contrast signal detection based on the Medelfest data (Watson, 1999). Here we propose two changes to the model, dropping the oblique effect from the CSF and using the cone density data of Curcio et al. (1990) to estimate the variation of sensitivity with eccentricity. Dropping the complex images, and using medians to exclude outlier data points, the SSO model now accounts for essentially all the predictable variance in the data, with an RMS prediction error of only 0.67 dB.

Ahumada, Albert J.↗
NASA NTRS2014

Applied Meteorology Unit (AMU) Quarterly Report Fourth Quarter FY-14

Ms. Crawford completed the final report for the dual-Doppler wind field task. Dr. Bauman completed transitioning the 915-MHz and 50-MHz Doppler Radar Wind Profiler (DRWP) splicing algorithm developed at Marshall Space Flight Center (MSFC) into the AMU Upper Winds Tool. Dr. Watson completed work to assimilate data into model configurations for Wallops Flight Facility (WFF) and Kennedy Space Center/Cape Canaveral Air Force Station (KSC/CCAFS). Ms. Shafer began evaluating the a local high-resolution model she had set up previously for its ability to forecast weather elements that affect launches at KSC/CCAFS. Dr. Watson began a task to optimize the data-assimilated model she just developed to run in real time.

Applied Meteorology Unit↗
NASA NTRS2015

Real-Time Kennedy Space Center and Cape Canaveral Air Force Station High-Resolution Model Implementation and Verification

Customer: NASA's Launch Services Program (LSP), Ground Systems Development and Operations (GSDO), and Space Launch System (SLS) programs. NASA's LSP, GSDO, SLS and other programs at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) use the daily and weekly weather forecasts issued by the 45th Weather Squadron (45 WS) as decision tools for their day-to-day and launch operations on the Eastern Range (ER). For example, to determine if they need to limit activities such as vehicle transport to the launch pad, protect people, structures or exposed launch vehicles given a threat of severe weather, or reschedule other critical operations. The 45 WS uses numerical weather prediction models as a guide for these weather forecasts, particularly the Air Force Weather Agency (AFWA) 1.67 kilometer Weather Research and Forecasting (WRF) model. Considering the 45 WS forecasters' and Launch Weather Officers' (LWO) extensive use of the AFWA model, the 45 WS proposed a task at the September 2013 Applied Meteorology Unit (AMU) Tasking Meeting requesting the AMU verify this model. Due to the lack of archived model data available from AFWA, verification is not yet possible. Instead, the AMU proposed to implement and verify the performance of an ER version of the AMU high-resolution WRF Environmental Modeling System (EMS) model (Watson 2013) in real-time. The tasking group agreed to this proposal; therefore the AMU implemented the WRF-EMS model on the second of two NASA AMU modeling clusters. The model was set up with a triple-nested grid configuration over KSC/CCAFS based on previous AMU work (Watson 2013). The outer domain (D01) has 12-kilometer grid spacing, the middle domain (D02) has 4-kilometer grid spacing, and the inner domain (D03) has 1.33-kilometer grid spacing. The model runs a 12-hour forecast every hour, D01 and D02 domain outputs are available once an hour and D03 is every 15 minutes during the forecast period. The AMU assessed the WRF-EMS 1.33-kilometer domain model performance for the 2014 warm season (May-September). Verification statistics were computed using the Model Evaluation Tools, which compared the model forecasts to observations. The mean error values were close to 0 and the root mean square error values were less than 1.8 for mean sea-level pressure (millibars), temperature (degrees Kelvin), dewpoint temperature (degrees Kelvin), and wind speed (per millisecond), all very small differences between the forecast and observations considering the normal magnitudes of the parameters. The precipitation forecast verification results showed consistent under-forecasting of the precipitation object size. This could be an artifact of calculating the statistics for each hour rather than for the entire 12-hour period. The AMU will continue to generate verification statistics for the 1.33-kilometer WRF-EMS domain as data become available in future cool and warm seasons. More data will produce more robust statistics and reveal a more accurate assessment of model performance. Once the formal task was complete, the AMU conducted additional work to better understand the wind direction results. The results were stratified diurnally and by wind speed to determine what effects the stratifications would have on the model wind direction verification statistics. The results are summarized in the addendum at the end of this report. In addition to verifying the model's performance, the AMU also made the output available in the Advanced Weather Interactive Processing System II (AWIPS II). This allows the 45 WS and AMU staff to customize the model output display on the AMU and Range Weather Operations AWIPS II client computers and conduct real-time subjective analyses. In the future, the AMU will implement an updated version of the WRF-EMS model that incorporates local data assimilation. This model will also run in real-time and be made available in AWIPS II.

Numerical Weather Prediction↗
DOE OSTI2022

Highly Symmetric, Self-Assembling 3D DNA Crystals with Cubic and Trigonal Lattices

The rational design of nanoscopic DNA tiles has yielded highly ordered crystalline matter in 2D and 3D. The most well-studied 3D tile is the DNA tensegrity triangle, which is known to self-assemble into macroscopic crystals. However, contemporary rational design parameters for 3D DNA crystals nearly universally invoke integer numbers of DNA helical turns and Watson–Crick (WC) base pairs. Here, in this study, 24-bp edges are substituted into a previously 21-bp (two helical turns of DNA) tensegrity triangle motif to explore whether such unconventional motif can self-assemble into 3D crystals. The use of noncanonical base pairs in the sticky ends results in a cubic arrangement of tensegrity triangles with exceedingly high symmetry, assembling a lattice from winding helical axes and diamond-like tessellation patterns. Reverting this motif to sticky ends with Watson–Crick pairs results in a trigonal hexagonal arrangement, replicating this diamond arrangement in a hexagonal context. These results showcase that the authors can generate unexpected, highly complex, pathways for materials design by testing modifications to 3D tiles without prior knowledge of the ensuing symmetry. This study expands the rational design toolbox for DNA nanotechnology; and it further illustrates the existence of yet-unexplored arrangements of crystalline soft matter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Management and Operation of the Oak Ridge National Laboratory

ThermaMatrix, Inc provides novel vision inspection solutions for a wide range of manufacturers and industries, providing and implementing the leading technologies for nondestructive inspection (NDI) and material characterization. Many other inspection solutions are either not adequate or are not approachable due to implementation barriers needing expert level operators, excessive inspection time, and high cost. ThermaMatrix’sadvanced vision inspection technology addresses all of these limitations. The Lab Embedded Entrepreneurial Program (LEEP) opportunity by the Department of Energy (DOE) allows small-business start-ups to leverage national laboratory capabilities and skilled scientists to rapidly develop their technology that aligns with DOE goals. ThermaMatrix, Inc.was positioned in the Innovation Crossroads program at Oak Ridge National Laboratory to further develop thenovel Watson Vision Inspection System to support manufacturing quality control efforts. Theresearch goals were (1) explore fundamental parameters that would improve preexisting capabilities, (2) full-scale industrial setup for demonstration, and (3) capability testing and verification. Manufacturing is demanding more NDI implementation to support their quality control needs, which this technology development would support. Figure 1: Ryan Spencer of ThermaMatrix with Watson Vision Inspection System.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Understanding the Origin of Structural Diversity of DNA Double Helix

Deciphering the contribution of DNA subunits to the variability of its 3D structure represents an important step toward the elucidation of DNA functions at the atomic level. In the pursuit of that goal, our previous studies revealed that the essential conformational characteristics of the most populated “canonic” BI and AI conformational families of Watson–Crick duplexes, including the sequence dependence of their 3D structure, preexist in the local energy minima of the elemental single-chain fragments, deoxydinucleoside monophosphates (dDMPs). Those computations have uncovered important sequence-dependent regularity in the superposition of neighbor bases. The present work expands our studies to new minimal fragments of DNA with Watson–Crick nucleoside pairs that differ from canonic families in the torsion angles of the sugar-phosphate backbone (SPB). To address this objective, computations have been performed on dDMPs, cdDMPs (complementary dDMPs), and minimal fragments of SPBs of respective systems by using methods of molecular and quantum mechanics. These computations reveal that the conformations of dDMPs and cdDMPs having torsion angles of SPB corresponding to the local energy minima of separate minimal units of SPB exhibit sequence-dependent characteristics representative of canonic families. In contrast, conformations of dDMP and cdDMP with SPB torsions being far from the local minima of separate SPB units exhibit more complex sequence dependence.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1982

Regression methods for spatial data

The kriging approach, a parametric regression method used by hydrologists and mining engineers, among others also provides an error estimate the integral of the regression function. The kriging method is explored and some of its statistical characteristics are described. The Watson method and theory are extended so that the kriging features are displayed. Theoretical and computational comparisons of the kriging and Watson approaches are offered.

Yakowitz, S. J.↗
NASA NTRS1991

In-phase and out-of-phase axial-torsional fatigue behavior of Haynes 188 at 760 C

Isothermal, in-phase and out-of-phase axial-torsional fatigue experiments have been conducted at 760 C on uniform gage section, thin-walled tubular specimens of a wrought cobalt-base superalloy, Haynes 188. Test-control and data acquisition were accomplished with a minicomputer. Fatigue lives of the in- and out-of-phase axial-torsional fatigue tests have been estimated with four different multiaxial fatigue life prediction models that were developed primarly for predicting axial-torsional fatigue lives at room temperature. The models investigated were: (1) the von Mises equivalent strain range; (2) the Modified Multiaxiality Factor Approach; (3) the Modified Smith-Watson-Topper Parameter; and (4) the critical shear plane method of Fatemi, Socie, and Kurath. In general, life predictions by the von Mises equivalent strain range model were within a factor of 2 for a majority of the tests and the predictions by the Modified Multiaxiality Factor Approach were within a factor of 2, while predictions of the Modified Smith-Watson-Topper Parameter and of the critical shear plane method of Fatemi, Socie, and Kurath were unconservative and conservative, respectively, by up to factors of 4. In some of the specimens tested under combined axial-torsional loading conditions, fatigue cracks initiated near extensometer indentations. Two design modifications have been proposed to the thin-walled tubular specimen to overcome this problem.

Kalluri, Sreeramesh↗