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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

A review of satellite altimeter measurement of sea surface wind speed - With a proposed new algorithm

The scheduled February 1985 launch of a radar altimeter aboard the U.S. Navy satellite Geosat has motivated an in-depth investigation of wind speed retrieval from satellite altimeters. The accuracy of sea surface wind speed estimated by the Seasat altimeter is examined by comparison with wind speed estimated by the Seasat scatterometer. The intercomparison is based on globally distributed spatial and temporal averages of the estimated wind speed. It is shown that there are systematic differences between altimeter and scatterometer wind speed estimates. These differences are traced to errors in the Seasat altimeter geophysical data record wind speed algorithm. A new algorithm is proposed which yields consistent estimates from the two satellite sensors. Using this new algorithm, the rms difference between spatial and temporal averages of the two wind speed estimates is less than 1 m/s, and their correlation is greater than 0.9.

Chelton, D. B.↗
NASA NTRS2014

How Well Do Satellite AOD Observations Represent the Spatial and Temporal Variability of PM2.5 Concentration for the United States?

Due to their extensive spatial coverage, satellite Aerosol Optical Depth (AOD) observations have been widely used to estimate and predict surface PM2.5 concentrations. While most previous studies have focused on establishing relationships between collocated, hourly or daily AOD and PM2.5 measurements, in this study, we instead focus on the comparison of the large-scale spatial and temporal variability between satellite AOD and PM2.5 using monthly mean measurements. A newly developed spectral analysis technique e Combined Maximum Covariance Analysis (CMCA) is applied to Moderate Resolution Imaging Spectroradiometer (MODIS), Multi-angle Imaging Spectroradiometer (MISR), Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Ozone Monitoring Instrument (OMI) AOD datasets and Environmental Protection Agency (EPA) PM2.5 data, in order to extract and compare the dominant modes of variability. Results indicate that AOD and PM2.5 agree well in terms of interannual variability. An overall decrease is found in both AOD and PM2.5 across the United States, with the strongest signal over the eastern US. With respect to seasonality, good agreement is found only for Eastern US, while for Central and Western US, AOD and PM2.5 seasonal cycles are largely different or even reversed. These results are verified using Aerosol Robotic Network (AERONET) AOD observations and differences between satellite and AERONET are also examined. MODIS and MISR appear to have the best agreement with AERONET. In order to explain the disagreement between AOD and PM2.5 seasonality, we further use Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) extinction profile data to investigate the effect of two possible contributing factors, namely aerosol vertical distribution and cloud-free sampling. We find that seasonal changes in aerosol vertical distribution, due to the seasonally varying mixing height, is the primary cause for the AOD and PM2.5 seasonal discrepancy, in particular, the low AOD but high PM2.5 observed during the winter season for Central and Western US. In addition, cloud-free sampling by passive sensors also induces some bias in AOD seasonality, especially for the Western US, where the largest seasonal change in cloud fraction is found. The seasonal agreement between low level (below 500 m AGL), all sky CALIOP AOD and PM2.5 is significantly better than column AOD from MODIS, MISR, SeaWiFS and OMI. In particular, the correlation between low level, all sky AOD and PM2.5 seasonal cycles increases to above 0.7 for Central and Western US, as opposed to near zero or negative correlation for column, clear sky AOD. This result highlights the importance of accounting for the seasonally varying aerosol profiles and cloud-free sampling bias when using column AOD measurements to infer surface PM2.5 concentrations.

MODIS (radiometry)↗
DOE OSTI2022

A Double Sided LGAD-Based Detector Providing Timing, Position, and Track Angle Information

We describe a detector concept which combines small pixels enabled by 3D sensor-electronics integration with gain produced by a Low Gain Avalanche Diode (LGAD) layer. The detector is double-sided, with electrons collected by the cathode, which provides timing information, and an anode with small pixels to provide position and angle information. The cathode can be coarse grained, providing timing with fewer fast amplifiers to limit power consumption. The anode layer benefits from the gain of the LGAD, with larger signals that also limit the power needed. Position can be reconstructed by measuring the pattern of total charge deposited on the anode. Angle and depth of charge deposit can be measured by the shapes of the anode pulses. We describe a possible assembly technology based on 3D integration.

3D Integration↗
DOE OSTI2023

Cyber and Physical Security Analysis of GSI and Noventum Application for IoT Communications

We present our findings of the red team exercise conducted on the device and application developed by Guardian Sensors, Inc. (GSI) and Noventum. The app is used for situational awareness and control of photovoltaics (PV) and microgrid energy systems. The assessments performed are practical case scenarios that assess the risks and vulnerabilities posed by the app through targeted activities that could be engaged by an adversary. The assessment team’s results and recommendations are provided to inform on and mitigate the identified weaknesses to improve secure user authentication, connections, and communications. The recommendations in this report are not intended to be a security panacea but will add the desired defense-in-depth layer to securing communication of such interconnected systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRSDate not supplied

The Material Response of PICA-NuSil to a Hypersonic Flow Environment

Phenolic Impregnated Carbon Ablator (PICA) is NASA’s baseline thermal protection system for missions to Mars. PICA is friable; therefore, NuSil ® CV-1144-0 is applied to the surface of flight hardware to mitigate the contamination of spacecraft sensors. NuSil is composed of a polysiloxane resin system that can transform into an oxidation-resistant coating upon heating. Therefore, a pathfinder campaign was conducted at the Hypersonic Materials Environmental Test System (HyMETS) at the NASA Langley Research Center to investigate the material response of instrumented sphere-cone models made from PICA coated with NuSil ® . Analysis of the post-test data is presented and suggests that NuSil ® impacts the material response of test articles subjected to oxidizing atmospheres, as evidenced by a reduction of the measured surface temperature and in-depth temperature response. Finally, a four-step ablation mechanism is proposed based on observations from high-speed video, optical emission spectroscopy, thermal analysis, and post-test surface characterization.

PICA PICA-NuSil Siloxane Silicone↗
DOE OSTI2019

Liquid Metal Diagnostics

Liquid metal (LM) plasma-facing components (PFCs) (LM-PFCs) within next-generation fusion reactors are expected to enhance plasma confinement, facilitate tritium breeding, improve reactor thermal efficiency, and withstand large heat and particle fluxes better than solid components made from tungsten, molybdenum, or graphite. Some LM divertor concepts intended for long-pulse operation at >20 MW/m 2 incorporate thin (~1 cm), fast-moving (~5 to 10 m/s), free-surface flows. Such systems will require a range of diagnostics to monitor and control the velocity, flow depth, temperature, and impurity concentration of the LM. As such, this paper will highlight technologies developed for the fission and casting/metallurgical industries that can be adapted to meet the needs of LM-PFC research. This paper is divided into four major parts. The first part will look at noncontact flowmeter technologies that are suitable for high-temperature alkali metal systems. These technologies include rotating Lorentz-force flowmeters for bulk flow rate measurements and particle tracking techniques for surface velocity measurements. Second, this paper will detail the operation of a new inductive level sensor that can be used within free-surface LM-PFCs. This robust level sensor can be mounted below the substrate that supports the LM, so it is simple to install and is protected from the damaging conditions inside a fusion reactor. It has been shown that this level sensor can be calibrated using either numerical or experimental techniques. Third, distributed temperature sensors based on fiber-optic technologies will be discussed. This advanced measurement technique provides temperature data with high spatial resolution and has recently been successfully tested in LM systems. Last, diagnostics to measure impurity concentration, such as electrochemical cells, plugging meters, and spectroscopic systems, will be addressed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2014

SWIM: A Semi-Analytical Ocean Color Inversion Algorithm for Optically Shallow Waters

In clear shallow waters, light that is transmitted downward through the water column can reflect off the sea floor and thereby influence the water-leaving radiance signal. This effect can confound contemporary ocean color algorithms designed for deep waters where the seafloor has little or no effect on the water-leaving radiance. Thus, inappropriate use of deep water ocean color algorithms in optically shallow regions can lead to inaccurate retrievals of inherent optical properties (IOPs) and therefore have a detrimental impact on IOP-based estimates of marine parameters, including chlorophyll-a and the diffuse attenuation coefficient. In order to improve IOP retrievals in optically shallow regions, a semi-analytical inversion algorithm, the Shallow Water Inversion Model (SWIM), has been developed. Unlike established ocean color algorithms, SWIM considers both the water column depth and the benthic albedo. A radiative transfer study was conducted that demonstrated how SWIM and two contemporary ocean color algorithms, the Generalized Inherent Optical Properties algorithm (GIOP) and Quasi-Analytical Algorithm (QAA), performed in optically deep and shallow scenarios. The results showed that SWIM performed well, whilst both GIOP and QAA showed distinct positive bias in IOP retrievals in optically shallow waters. The SWIM algorithm was also applied to a test region: the Great Barrier Reef, Australia. Using a single test scene and time series data collected by NASA's MODIS-Aqua sensor (2002-2013), a comparison of IOPs retrieved by SWIM, GIOP and QAA was conducted.

shallow waters↗
NASA NTRS2021

Melt Pool Imaging using a Configurable Architecture Additive Testbed System

This paper describes the inline (coaxial to laser) near infrared (NIR) camera sensor on the Configurable Architecture Additive Testbed (CAAT). The CAAT is an instrument that provides the capability to investigate laser based additive manufacturing (AM) processes and is configured for the metal powder bed fusion process. A low cost NIR camera is radiometrically calibrated to obtain coaxial, inline, imagery of laser generated melt pools. The camera capabilities, system optical path, and the uncertainty in the temperature measurement from NIR surface area scans on a bare titanium alloy plate are presented and discussed. The surface radiance measurements are compared to optical microscopy images of the melt pool width and depth. A metallic additive manufacturing process thermal model is developed in order to predict thermal distributions during laser scanning. The predicted thermal distributions by the model for different configurations are compared to the coaxial NIR measurements and discussed.

Additive manufacturing↗
DOE OSTI2025

Root genetics in the field to understand drought adaptation and carbon sequestration (Final Scientific/Technical Report)

For all crop plants, roots play a critical role in growth. Roots anchor the plants, and are the primary site of nutrient and water uptake. Roots are also the main source of C to soil in the form of root tissues and exudates, and thus greatly influence SOM stocks. To perform these functions, primary roots extend into soil, producing a network of branching roots of characteristic form, known as its root system architecture (RSA). RSA varies among species, and among varieties within a species that are adapted to different environments. Root traits are major targets for the second green revolution because of their potential to improve crop productivity, increase drought tolerance and nutrient acquisition, and increase C capture of soil. Improving the quality of roots in maize will be particularly valuable, since this crop is planted on over 92 million acres annually in the US. The future sustainability of agricultural systems relies on their ability to enhance soil organic matter (SOM) storage and reduce GHG emissions, while maintaining or enhancing productivity. This program had two components, Sensors and Models. For the first component, we designed and built a high-throughput phenotyping platform for root pulling of maize plants. This eliminated the physical labor of manually pulling up plants and reduced the number of personnel required down to one. The standardized pulling mechanism allowed recording force curves during the pulling process, providing additional information. We validated that the maximum force for pulling the root system was well-correlated with the root system mass and provided root crowns for further RSA analysis. These root crowns identified significant correlations with 2D root area and root depth, along with 3D root volume, total root length and number of root tips. We then used this system for field-based studies in maize on the genetics of root system architecture and its relation to nitrogen-use efficiency (NUE), including using lines relevant to the Corteva breeding program. Varieties were also evaluated at Corteva sites in the cornbelt and Danforth farm in Missouri, to establish responses across sites. From these studies we have identified genetic loci associated with root traits and created mutant lines for these loci and correlations of root traits with NUE. For the Models component, we worked to incorporate root and soil characteristics into the MEMS 2.0 soil and ecosystem biogeochemical model. Existing soil C models, such as Century, are unable to represent specific root trait interactions with the soil environment and therefore to accurately forecast the potential C sequestration benefits of root breeding under different climatic and soil type conditions. We have developed the MEMS 2.0 ecosystem biogeochemical model to improve quantification of farm-scale soil carbon and greenhouse gas emissions. The new knowledge and large datasets produced by this project will be used to develop and drive an innovative model capable of forecasting the impacts on soil C stocks and nutrient dynamics. An innovation was to use the empirical data from the field studies (in 1, above) to model genetic variation in nitrogen use efficiencies and soil C input. Our work demonstrated that maize root-derived C rapidly replaces existing soil C and after 3 years of continuous maize, up to 20% of soil organic C in the topsoil (0-15cm) and 3% in the subsoil (15-30cm) was contributed by maize. However, this contribution did not entirely represent a net increase. Root C contribution to soil was affected by maize genetics. We have analyzed soils derived from the CSU field trials for C and N stocks, in the different soil physical fractions represented by the MEMS model, using both physical fractionation with elemental analyses, and Fourier transformed infrared spectroscopy. Data will be used to link crop nitrogen use efficiencies with soil C sequestration and provide data to bridge the field trials with the model development, for verification of model predictions. The project had a number of successful outcomes: we have used the new phenotyping platform to identify new genetic loci that can enhance root phenotypes; we have partnered with multiple maize seed companies phenotype varieties in their breeding programs; we have developed the MEMS model that can help inform industry on the potential for carbon sequestration in the agricultural sector, and which is now available at the CSU Soil Carbon Solutions Center for use.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1987

Development of a facility using robotics for testing automation of inertial instruments

The Integrated Robotics System Simulation (ROBSIM) was used to evaluate the performance of the PUMA 560 arm as applied to testing of inertial sensors. Results of this effort were used in the design and development of a feasibility test environment using a PUMA 560 arm. The implemented facility demonstrated the ability to perform conventional static inertial instrument tests (rotation and tumble). The facility included an efficient data acquisitions capability along with a precision test servomechanism function resulting in various data presentations which are included in the paper. Analysis of inertial instrument testing accuracy, repeatability and noise characteristics are provided for the PUMA 560 as well as for other possible commercial arm configurations. Another integral aspect of the effort was an in-depth economic analysis and comparison of robot arm testing versus use of contemporary precision test equipment.

Greig, Joy Y.↗
DOE OSTI2025

Filling the Gaps: A Bayesian Mixture Model for Imputing Missing Soil Water Content Data

ABSTRACT Soil water content (SWC) data are central to evaluating how soil moisture varies over time and space and influences critical plant and ecosystem functions, especially in water‐limited drylands. However, sensors that record SWC at high frequencies often malfunction, leading to incomplete timeseries and limiting our understanding of dryland ecosystem dynamics. We developed an analytical approach to impute missing SWC data, which we tested at six eddy flux tower sites along an elevation gradient in the southwestern United States. We impute missing data as a mixture of linearly interpolated SWC between the observed endpoints of a missing data gap and SWC simulated by an ecosystem water balance model (SOILWAT2). Within a Bayesian framework, we allowed the relative utility (mixture weight) of each component (linearly interpolated vs. SOILWAT2) to vary by depth, site and gap characteristics. We explored “fixed” weights versus “dynamic” weights that vary as a function of cumulative precipitation, average temperature, and time since the start of the gap. Both models estimated missing SWC data well ( R 2 = 0.70–0.88 vs. 0.75–0.91 for fixed vs. dynamic weights, respectively), but the utility of linearly interpolated versus SOILWAT2 values depended on site and depth. SOILWAT2 was more useful for more arid sites, shallower depths, longer and warmer gaps and gaps that received greater precipitation. Overall, the mixture model reliably gap‐fills SWC, while lending insight into processes governing SWC dynamics. This approach to impute missing data could be adapted to accommodate more than two mixture components and other types of environmental timeseries.

Ogle, Kiona [School of Informatics, Computing, and↗
DOE OSTI2021

Modeling Subsurface Explosions Recorded on a Distributed Fiber Optic Sensor

Fiber optic distributed acoustic sensors (DAS) are becoming a widely used tool for seismic sensing. Here we examine recordings of two subsurface chemical explosions, DAG-1 and DAG-3, each of which was about one metric ton (TNT equivalent), that were recorded from a helical fiber installed in two boreholes 80 m away from the source location. Several clear phases including the initial P wave, a weak S wave, and a surface reflected P wave are observed on the helical DAS data. We estimate a velocity model using arrival times measured from the fiber. The DAS waveform data were compared with colocated accelerometers at specific depths in both frequency and time domains. Furthermore, the spectra of the DAS data matched spectra estimated from the accelerometer records. Comparisons of observed waveform shape between the accelerometer records and the fiber measurements (strain-rate) show reasonable agreement except for the data near the event depth. The DAS data and the accelerometer agreed in relative amplitudes but we had difficulties in matching absolute amplitudes, possibly due to errors in metadata. Synthetic strain-rate waveforms were calculated using a 2D wavenumber algorithm and matched the waveform shape and relative amplitudes. In general, DAS is effective at recording strong ground motions at high spatial density. Comparison of the synthetic seismograms with observed data indicate that the waveforms are not consistent with a pure isotropic explosion source and that the observed S waves originate from very near the source region.

58 GEOSCIENCES↗
NASA NTRS1974

A review of initial investigations to utilize ERTS-1 data in determining the availability and distribution of living marine resources

This study was initiated in July 1972 to determine the reliability of satellite and high altitude sensors to provide data about oceanographic parameters in coastal waters; demonstrate the use of remotely sensed oceanographic information to predict the distribution and abundance of adult menhaden; and, demonstrate the potential of using satellite acquired information for improving the harvest and management of a fishery resource. The study focused on coastal are as in the north central portion of the Gulf of Mexico including parts of Alabama, Mississippi and Louisiana. The area used in the final analysis was limited to the Mississippi Sound, which is approximately 145 kilometers (90 miles) long and 16 kilometers (10 miles) wide, has an average water depth of about 3.7 meters (12 feet), and in general characterizes an estuarine environment.

Stevenson, W. H.↗
NASA NTRS2016

Optical Extinction Measurements of Dust Density in the GMRO Regolith Test Bin

A regolith simulant test bin was constructed and completed in the Granular Mechanics and Regolith Operations (GMRO) Lab in 2013. This Planetary Regolith Test Bed (PRTB) is a 64 sq m x 1 m deep test bin, is housed in a climate-controlled facility, and contains 120 MT of lunar-regolith simulant, called Black Point-1 or BP-1, from Black Point, AZ. One of the current uses of the test bin is to study the effects of difficult lighting and dust conditions on Telerobotic Perception Systems to better assess and refine regolith operations for asteroid, Mars and polar lunar missions. Low illumination and low angle of incidence lighting pose significant problems to computer vision and human perception. Levitated dust on Asteroids interferes with imaging and degrades depth perception. Dust Storms on Mars pose a significant problem. Due to these factors, the likely performance of telerobotics is poorly understood for future missions. Current space telerobotic systems are only operated in bright lighting and dust-free conditions. This technology development testing will identify: (1) the impact of degraded lighting and environmental dust on computer vision and operator perception, (2) potential methods and procedures for mitigating these impacts, (3) requirements for telerobotic perception systems for asteroid capture, Mars dust storms and lunar regolith ISRU missions. In order to solve some of the Telerobotic Perception system problems, a plume erosion sensor (PES) was developed in the Lunar Regolith Simulant Bin (LRSB), containing 2 MT of JSC-1a lunar simulant. PES is simply a laser and digital camera with a white target. Two modes of operation have been investigated: (1) single laser spot - the brightness of the spot is dependent on the optical extinction due to dust and is thus an indirect measure of particle number density, and (2) side-scatter - the camera images the laser from the side, showing beam entrance into the dust cloud and the boundary between dust and void. Both methods must assume a mean particle size in order to extract a number density. The optical extinction measurement yields the product of the 2nd moment of the particle size distribution and the extinction efficiency Qe. For particle sizes in the range of interest (greater than 1 micrometer), Qe approximately equal to 2. Scaling up of the PES single laser and camera system is underway in the PRTB, where an array of lasers penetrate a con-trolled dust cloud, illuminating multiple targets. Using high speed HD GoPro video cameras, the evolution of the dust cloud and particle size density can be studied in detail.

lunar simulant↗
NASA NTRS2015

Mars2020 Entry, Descent, and Landing Instrumentation (MEDLI2): Science Objectives and Instrument Requirements

NASAs exploration and technology roadmaps call for capability advancements in Mars entry, descent, and landing (EDL) systems to enable increased landed mass, a higher landing precision, and a wider planetary access. It is also recognized that these ambitious EDL performance goals must be met while maintaining a low mission risk in order to pave the way for future human missions. As NASA is engaged in developing new EDL systems and technologies via testing at Earth, instrumentation of existing Mars missions is providing valuable engineering data for performance improvement, risk reduction, and an improved definition of entry loads and environment. The most notable recent example is the Mars Entry, Descent and Landing Instrument (MEDLI) suite hosted by Mars Science Laboratory for its entry in Aug 2012. The MEDLI suite provided a comprehensive dataset for Mars entry aerodynamics, aerothermodynamics and thermal protection system (TPS) performance. MEDLI data has since been used for unprecedented reconstruction of aerodynamic drag, vehicle attitude, in-situ atmospheric density, aerothermal heating, and transition to turbulence, in-depth TPS performance and TPS ablation. [1,2] In addition to validating predictive models, MEDLI data has demonstrated extra margin available in the MSL forebody TPS, which can potentially be used to reduce vehicle parasitic mass. The presentation will introduce a follow-on MEDLI instrumentation suite (called MEDLI2) that is being developed for Mars-2020 mission. MEDLI2 has an enhanced scope that includes backshell instrumentation, a wider forebody coverage, and instruments that specifically target supersonic aerodynamics. Similar to MEDLI, MEDLI2 uses thermal plugs with embedded thermocouples and ports through the TPS to measure surface pressure. MEDLI2, however, also includes heat flux sensors in the backshell and a low range pressure transducer to measure afterbody pressure.

Aerothermodynamics↗
DOE OSTI2018

Observed Boundary Layer Controls on Shallow Cumulus at the ARM Southern Great Plains Site

Abstract The boundary layer controls on shallow cumulus (ShCu) convection are examined using a suite of remote and in situ sensors at ARM Southern Great Plains (SGP). A key instrument in the study is a Doppler lidar that measures vertical velocity in the CBL and along cloud base. Using a sample of 138 ShCu days, the composite structure of the ShCu CBL is examined, revealing increased vertical velocity (VV) variance during periods of medium cloud cover and higher VV skewness on ShCu days than on clear-sky days. The subcloud circulations of 1791 individual cumuli are also examined. From these data, we show that cloud-base updrafts, normalized by convective velocity, vary as a function of updraft width normalized by CBL depth. It is also found that 63% of clouds have positive cloud-base mass flux and are linked to coherent updrafts extending over the depth of the CBL. In contrast, negative mass flux clouds lack coherent subcloud updrafts. Both sets of clouds possess narrow downdrafts extending from the cloud edges into the subcloud layer. These downdrafts are also present adjacent to cloud-free updrafts, suggesting they are mechanical in origin. The cloud-base updraft data are subsequently combined with observations of convective inhibition to form dimensionless “cloud inhibition” (CI) parameters. Updraft fraction and liquid water path are shown to vary inversely with CI, a finding consistent with CIN-based closures used in convective parameterizations. However, we also demonstrate a limited link between CBL vertical velocity variance and cloud-base updrafts, suggesting that additional factors, including updraft width, are necessary predictors for cloud-base updrafts.

54 ENVIRONMENTAL SCIENCES↗