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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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NASA NTRS2003

Transonic Unsteady Aerodynamics of the F/A-18E at Conditions Promoting Abrupt Wing Stall

A transonic wind tunnel test of an 8% F/A-18E model was conducted in the NASA Langley Research Center (LaRC) 16-Foot Transonic Tunnel (16-Ft TT) to investigate the Abrupt Wing Stall (AWS) characteristics of this aircraft. During this test, both steady and unsteady measurements of balance loads, wing surface pressures, wing root bending moments, and outer wing accelerations were performed. The test was conducted with a wide range of model configurations and test conditions in an attempt to reproduce behavior indicative of the AWS phenomenon experienced on full-scale aircraft during flight tests. This paper focuses on the analysis of the unsteady data acquired during this test. Though the test apparatus was designed to be effectively rigid. model motions due to sting and balance flexibility were observed during the testing, particularly when the model was operating in the AWS flight regime. Correlation between observed aerodynamic frequencies and model structural frequencies are analyzed and presented. Significant shock motion and separated flow is observed as the aircraft pitches through the AWS region. A shock tracking strategy has been formulated to observe this phenomenon. Using this technique, the range of shock motion is readily determined as the aircraft encounters AWS conditions. Spectral analysis of the shock motion shows the frequencies at which the shock oscillates in the AWS region, and probability density function analysis of the shock location shows the propensity of the shock to take on a bi-stable and even tri-stable character in the AWS flight regime.

Schuster, David M.↗
NASA NTRS2008

Effects of Wall Cooling on Hypersonic Boundary Layer Receptivity Over a Cone

Effects of wall cooling on the receptivity process induced by the interaction of slow acoustic disturbances in the free-stream are numerically investigated for a boundary layer flow over a 5-degrees straight cone. The free-stream Mach number is 6.0 and the Reynolds number is 7.8x10(exp 6)/ft. Both the steady and unsteady solutions are obtained by solving the full Navier-Stokes equations using 5th-order accurate weighted essentially non-oscillatory (WENO) scheme for space discretization and using 3rd-order total variation diminishing (T VD) Runge-K utta scheme for time integration. Computations are performed for a cone with nose radius of 0.001 inch for adiabatic wall temperature (T(sub aw)), 0.75*T(sub aw), 0.5*T(sub aw), 0.40*T(sub aw), 0.30*T(sub aw), and 0.20*T(sub aw). Once the mean flow field is computed, disturbances are introduced at the upstream end of the computational domain. Generation of instability waves from leading edge region and receptivity of boundary layer to slow acoustic waves are investigated. Computations showed that wall cooling has strong stabilization effect on the first mode disturbances as was observed in the experiments. T ransition location moved to upstream when wall cooling was applied It is also found that the boundary layer is much more receptive to fast acoustic wave (by almost a factor of 50). When simulations performed using the same forcing frequency growth of the second mode disturbances are delayed with wall cooling and they attained values two times higher than that of adiabatic case. In 0.20*T(sub aw) case the transition Reynolds number is doubled compared to adiabatic conditions. The receptivity coefficient for adiabatic wall case (804 R) is 1.5225 and for highly cooled cones (241, and 161 R); they are in the order of 10(exp -3).

Kara, K.↗
NASA NTRS2021

On-demand Command and Control of ASTERIA with Cloud-based Ground Station Services

ASTERIA (Arcsecond Space Telescope Enabling Research in Astrophysics) was a 6-unit CubeSat technology demonstration mission that deployed from the International Space Station on November 20th, 2017. After successfully completing its 90-day primary mission that demonstrated arcsecond-level line-of-sight pointing and focal plane thermal stability for exoplanet detection, it entered an extended mission performing onboard software demonstrations to mature technology both in space and on the ground. One of the technologies was a completely cloud-based ground system leveraging Amazon Web Services (AWS) Ground Station service.Announced in December 2018 and launched in May 2019, AWS Ground Station is a fully managed ground station service that aims to reduce the overhead associated with developing and maintaining ground system infrastructure throughout the mission lifecycle. AWS Ground Station makes available the suite of features required for any ground system in support of low-Earth orbit (LEO) and medium-Earth Orbit (MEO) satellite operations on-demand and without setting up or maintaining long-term contracts. Charges are incurred on a per-minute basis for antenna usage during scheduled tracks. Support is available for S-band uplink and downlink, along with X-band narrowband and wideband downlink. Missions that use the service may reserve tracks with any licensed AWS Ground Station antennas located across each service region and have direct access to any AWS services in support of mission operations.The cloud-based architecture built around the AWS Ground Station service greatly enhanced ASTERIA mission operations by enabling end-to-end pass automation, on-demand contact scheduling and contingency planning, along with more efficient data downlink through station availability and station-to-station handovers. It incorporated open-source software, particularly NASA's AMMOS Instrument Toolkit (AIT) and Open Mission Control Technologies (OpenMCT), along with the AWS application programming interfaces (API) to the Ground Station, Elastic Compute Cloud (EC2) and Simple Storage Service (S3) services. After showcasing operability in August 2019, the team continued using and improving this novel ground system architecture until the end of mission in December 2019. This paper describes the cloud-based ground system, how it was designed, tested, and evaluated with an in-orbit spacecraft, the operational capabilities that it enabled, along with lessons learned and recommendations for future missions.

Fesq, Lorraine↗
NASA NTRS2021

On-demand Command and Control of ASTERIA with Cloud-based Ground Station Services

ASTERIA (Arcsecond Space Telescope Enabling Research in Astrophysics) was a 6-unit CubeSat technology demonstration mission that deployed from the International Space Station on November 20th, 2017. After successfully completing its 90-day primary mission that demonstrated arcsecond-level line-of-sight pointing and focal plane thermal stability for exoplanet detection, it entered an extended mission performing onboard software demonstrations to mature technology both in space and on the ground. One of the technologies was a completely cloud-based ground system leveraging Amazon Web Services (AWS) Ground Station service. Announced in December 2018 and launched in May 2019, AWS Ground Station is a fully managed ground station service that aims to reduce the overhead associated with developing and maintaining ground system infrastructure throughout the mission lifecycle. AWS Ground Station makes available the suite of features required for any ground system in support of low-Earth orbit (LEO) and medium-Earth Orbit (MEO) satellite operations on-demand and without setting up or maintaining long-term contracts. Charges are incurred on a per-minute basis for antenna usage during scheduled tracks. Support is available for S-band uplink and downlink, along with X-band narrowband and wideband downlink. Missions that use the service may reserve tracks with any licensed AWS Ground Station antennas located across each service region and have direct access to any AWS services in support of mission operations. The cloud-based architecture built around the AWS Ground Station service greatly enhanced ASTERIA mission operations by enabling end-to-end pass automation, on-demand contact scheduling and contingency planning, along with more efficient data downlink through station availability and station-tostation handovers. It incorporated open-source software, particularly NASA's AMMOS Instrument Toolkit (AIT) and Open Mission Control Technologies (OpenMCT), along with the AWS application programming interfaces (API) to the Ground Station, Elastic Compute Cloud (EC2) and Simple Storage Service (S3) services. After showcasing operability in August 2019, the team continued using and improving this novel ground system architecture until the end of mission in December 2019. This paper describes the cloud-based ground system, how it was designed, tested, and evaluated with an inorbit spacecraft, the operational capabilities that it enabled, along with lessons learned and recommendations for future missions.

Fesq, Lorraine↗
NASA NTRS2023

The Historical Greenland Climate Network (GC-Net) Curated and Augmented Level-1 Dataset

The Greenland Climate Network (GC-Net) consists of 31 automatic weather stations (AWSs) at 30 sites across the Greenland Ice Sheet. The first site was initiated in 1990, and the project has operated almost continuously since 1995 under the leadership of the late Konrad Steffen. The GC-Net AWS measured air temperature, relative humidity, wind speed, atmospheric pressure, downward and reflected shortwave irradiance, net radiation, and ice and firn temperatures. The majority of the GC-Net sites were located in the ice sheet accumulation area (17 AWSs), while 11 AWSs were located in the ablation area, and two sites (three AWSs) were located close to the equilibrium line altitude. Additionally, three AWSs of similar design to the GC-Net AWS were installed by Konrad Steffen's team on the Larsen C ice shelf, Antarctica. After more than 3 decades of operation, the GC-Net AWSs are being decommissioned and replaced by new AWSs operated by the Geological Survey of Denmark and Greenland (GEUS). Therefore, making a reassessment of the historical GC-Net AWS data is necessary. We present a full reprocessing of the historical GC-Net AWS dataset with increased attention to the filtering of erroneous measurements, data correction and derivation of additional variables: continuous surface height, instrument heights, surface albedo, turbulent heat fluxes, and 10 m ice and firn temperatures. This new augmented GC-Net level-1 (L1) AWS dataset is now available at https://doi.org/10.22008/FK2/VVXGUT (Steffen et al., 2023) and will continue to be refined. The processing scripts, latest data and a data user forum are available at https://github.com/GEUS-Glaciology-and-Climate/GC-Net-level-1-data-processing (last access: 30 November 2023). In addition to the AWS data, a comprehensive compilation of valuable metadata is provided: maintenance reports, yearly pictures of the stations and the station positions through time. This unique dataset provides more than 320 station years of high-quality atmospheric data and is available following FAIR (findable, accessible, interoperable, reusable) data and code practices.

Greenland Climate Network↗
DOE OSTI2021

Biosorption of copper from aqueous solutions utilizing agricultural wastes

Abstract The purpose of this study was to determine the copper (Cu) biosorption capacities of several agricultural wastes from aqueous solutions. Samples of agricultural wastes were tested unaltered and after hydrochloric acid (HCl) treatment. Additional parameters tested include sample dose, contact time, particle size, mixing temperature, and the concentrations and pH of the Cu solutions. Desorption studies were performed to determine if the removed Cu could be recovered. In addition, tests were conducted to determine if the agricultural waste samples (AWS) could be reused for additional Cu biosorption cycles. The results of this study demonstrate a wide range of Cu biosorption proficiencies ranging from 0% to 100% removal. The parameters that resulted in higher Cu removal include higher pH and lower Cu solution concentration. Desorption results showed a 58% to 86% Cu recovery rate. Three of the five reused AWS were effective at removing Cu during subsequent trials. Therefore, these AWS types can be reused for additional Cu biosorption cycles. Hence, it is possible that using those AWS for metal treatment could reduce hazardous waste disposal inefficiencies and costs by avoiding disposing of spent AWS following each Cu biosorption cycle.

Rizzuti, Anthony M.↗
DOE OSTI2025

A two-fluid solar-wind model with intermittent Alfvénic turbulence

In one of the leading theories for the origin of the solar wind, photospheric motions launch Alfvén waves (AWs) that propagate along open magnetic-field lines through the solar atmosphere and into the solar wind. The radial variation in the Alfvén speed causes some of the AWs to reflect, and counter-propagating AWs subsequently interact to produce Alfveńic turbulence, in which AW energy cascades from long wavelengths to short wavelengths and dissipates, heating the plasma. In this paper we develop a one-dimensional two-fluid solar-wind model that includes Alfvénic turbulence, proton temperature anisotropy and a novel method for apportioning the turbulent heating rate between parallel proton heating, perpendicular proton heating and electron heating. We employ a turbulence model that accounts for recent observations from NASA’s Parker Solar Probe, which find that AW fluctuations in the near-Sun solar wind are intermittent and less anisotropic than in previous models of anisotropic magnetohydrodynamic turbulence. Our solar-wind model reproduces a wide range of remote observations of the corona and in-situ measurements of the solar wind, and our turbulent heating model consists of analytic equations that could be usefully incorporated into other solar-wind models and numerical models of more distant astrophysical plasmas.

astrophysical plasmas↗
NASA NTRS1976

The prospects for life on Mars: A pre-Viking assessment

Mariner 9 provided a reinterpretation of several historical claims for Martian biology, and permitted an important further characterization of the environmental constraints on possible Martian organisms. Four classes of conceivable Martian organisms are identified, depending on the environmental temperature, T, and water activity, aw: Class 1, high T, high aw; Class 2, low T, high aw; Class 3, high T, low aw; and Class 4, low T, low aw. Organisms which extract their water requirements from hydrated minerals or from ice are considered possible on Mars, and the high ultraviolet flux and low oxygen partial pressure are considered to be negligible impediments to Martian biology. Large organisms are not only possible on Mars, they may be favored. The surface distribution of Martian organisms and future search strategies for life on Mars are discussed.

Sagan, C.↗
NASA NTRS2003

Historical Review of Uncommanded Lateral-Directional Motions at Transonic Conditions

This paper presents the results of a survey of past experiences with uncommanded lateral-directional motions at transonic speeds during specific military aircraft programs. The effort was undertaken to provide qualitative and quantitative information on past airplane programs that might be of use to the participants in the joint NASA/Navy/Air Force Abrupt Wing Stall (AWS) Program. The AWS Program was initiated because of the experiences of the F/A-l8E/F development program, during which unexpected, severe wing-drop motions were encountered by preproduction aircraft at transonic conditions. These motions were judged to be significantly degrading to the primary mission requirements of the aircraft. Although the problem was subsequently solved for the production version of the F/A-l8E/F, a high-level review panel emphasized the poor understanding of such phenomena and issued a strong recommendation to: "Initiate a national research effort to thoroughly and systematically study the wing drop phenomena." A comprehensive, cooperative NASA/Navy/Air Force AWS Program was designed to respond to provide the required technology requirements. As part of the AWS Program, a work element was directed at a historical review of wing-drop experiences in past aircraft development programs at high subsonic and transonic speeds. In particular, information was requested regarding: specific aircraft configurations that exhibited uncommanded motions and the nature of the motions; geometric characteristics of the air- planes; flight conditions involved in occurrences; relevant data, including wind-tunnel, computational, and flight sources; figures of merit used for analyses; and approaches used to alleviate the problem. An attempt was also made to summarize some of the more important lessons learned from past experiences, and to recommend specific research efforts. In addition to providing technical information to assist the AWS research objectives, the study produced fundamental information regarding the historical challenge of uncommanded lateral-directional motions at transonic conditions and the associated aerodynamic phenomena.

Chambers, Joseph R.↗
NASA NTRS2003

Historical Review of Uncommanded Lateral-Directional Motions At Transonic Conditions (Invited)

This paper presents the results of a survey of past experiences with uncommanded lateral-directional motions at transonic speeds during specific military aircraft programs. The effort was undertaken to provide qualitative and quantitative information on past airplane programs that might be of use to the participants in the joint NASA/Navy/Air Force Abrupt Wing Stall (AWS) Program. The AWS Program was initiated because of the experiences of the F/A-18E/F development program, during which unexpected, severe wing-drop motions were encountered by preproduction aircraft at transonic conditions. These motions were judged to be significantly degrading to the primary mission requirements of the aircraft. Although the problem was subsequently solved for the production version of the F/A-l8E/F, a high-level review panel emphasized the poor understanding of such phenomena and issued a strong recommendation to: Initiate a national research effort to thoroughly and systematically study the wing drop phenomena. A comprehensive, cooperative NASA/Navy/Air Force AWS Program was designed to respond to provide the required technology requirements. As part of the AWS Program, a work element was directed at a historical review of wing-drop experiences in past aircraft development programs at high subsonic and transonic speeds. In particular, information was requested regarding: specific aircraft configurations that exhibited uncommanded motions and the nature of the motions; geometric characteristics of the air- planes; flight conditions involved in occurrences; relevant data, including wind-tunnel, computational, and flight sources; figures of merit used for analyses; and approaches used to alleviate the problem. An attempt was also made to summarize some of the more important lessons learned from past experiences, and to recommend specific research efforts. In addition to providing technical information to assist the AWS research objectives, the study produced fundamental information regarding the historical challenge of uncommanded lateral-directional motions at transonic conditions and the associated aerodynamic phenomena.

Chambers, Joseph R.↗
NASA NTRS2008

Comparison of Satellite-Derived and In-Situ Observations of Ice and Snow Surface Temperatures over Greenland

The most practical way to get a spatially broad and continuous measurements of the surface temperature in the data-sparse cryosphere is by satellite remote sensing. The uncertainties in satellite-derived LSTs must be understood to develop internally-consistent decade-scale land-surface temperature (LST) records needed for climate studies. In this work we assess satellite-derived "clear-sky" LST products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and LSTs derived from the Enhanced Thematic Mapper Plus (ETM+) over snow and ice on Greenland. When possible, we compare satellite-derived LSTs with in-situ air-temperature observations from Greenland Climate Network (GC-Net) automatic-weather stations (AWS). We find that MODIS, ASTER and ETM+ provide reliable and consistent LSTs under clear-sky conditions and relatively-flat terrain over snow and ice targets over a range of temperatures from -40 to 0 C. The satellite-derived LSTs agree within a relative RMS uncertainty of approx.0.5 C. The good agreement among the LSTs derived from the various satellite instruments is especially notable since different spectral channels and different retrieval algorithms are used to calculate LST from the raw satellite data. The AWS record in-situ data at a "point" while the satellite instruments record data over an area varying in size from: 57 X 57 m (ETM+), 90 X 90 m (ASTER), or to 1 X 1 km (MODIS). Surface topography and other factors contribute to variability of LST within a pixel, thus the AWS measurements may not be representative of the LST of the pixel. Without more information on the local spatial patterns of LST, the AWS LST cannot be considered valid ground truth for the satellite measurements, with RMS uncertainty approx.2 C. Despite the relatively large AWS-derived uncertainty, we find LST data are characterized by high accuracy but have uncertain absolute precision.

Hall, Dorothy K.↗
DOE OSTI2022

Scalability Testing Approach for Internet of Things for Manufacturing SQL and NoSQL Database Latency and Throughput

The proliferation of low-cost sensors and industrial data solutions has continued to push the frontier of manufacturing technology. Machine learning and other advanced statistical techniques stand to provide tremendous advantages in production capabilities, optimization, monitoring, and efficiency. The tremendous volume of data gathered continues to grow, and the methods for storing the data are critical underpinnings for advancing manufacturing technology. This work aims to investigate the ramifications and design tradeoffs within a decoupled architecture of two prominent database management systems (DBMS): sql and NoSQL. A representative comparison is carried out with Amazon Web Services (AWS) DynamoDB and AWS Aurora MySQL. The technologies and accompanying design constraints are investigated, and a side-by-side comparison is carried out through high-fidelity industrial data simulated load tests using metrics from a major US manufacturer. The results support the use of simulated client load testing for comparing the latency of database management systems as a system scales up from the prototype stage into production. As a result of complex query support, MySQL is favored for higher-order insights, while NoSQL can reduce system latency for known access patterns at the expense of integrated query flexibility. Here, by reviewing this work, a manufacturer can observe that the use of high-fidelity load testing can reveal tradeoffs in IoTfM write/ingestion performance in terms of latency that are not observable through prototype-scale testing of commercially available cloud DB solutions.

AWS↗
DOE OSTI2022

Direct Multimodal Nanoscale Visualization of Early Phosphorus-Based Antiwear Tribofilm Formation

Understanding the mechanism of antiwear (AW) tribofilm formation and how to tune surface chemistry to control functionality is essential for the development of the next generation of oil lubricants. In particular, understanding and optimizing early AW tribofilm formation can increase the energy efficiency of mechanical systems. However, the mechanism for how these films form is not well understood. The majority of prior work has focused on analyzing only end-of-test surfaces long after the film has formed. In this work, we develop an in situ multimodal chemical imaging methodology to directly visualize the early formation of AW films on steel surfaces. We investigate an oil formulation containing a phosphorus-based additive commonly used to protect surfaces from wear and fatigue processes in machine elements, such as gears, bearings, and sliding contacts. Using nanoscale multimodal chemical imaging on combined platforms of atomic force microscopy (AFM) coupled directly with in situ nano-infrared (nano-IR) spectroscopy, and further combined ex situ with time-of-flight secondary ion mass spectrometry (ToF-SIMS), we demonstrate a direct correlation between changes in friction and local surface chemistry. In these experiments, the AFM probe acts as a single asperity contact to generate the tribofilm as well as a tool to analyze it in situ as it is forming. To verify our in situ measurements, we compare these results to the ex situ ToF-SIMS of macroscale block-on-ring tribometer-formed samples. We report the understanding gained here on how AW films form and how film properties can be modified by tuning the chemistry of the additives will facilitate developing transmission fluids to meet increasing demands for vehicle performance and efficiency.

36 MATERIALS SCIENCE↗
NASA NTRS2010

Functional Testing and Evaluation of Actiwatch Spectrum Devices for Launch on STS-133/ULF5

The Actiwatch Spectrum (AWS) is a wrist-worn device that may be used for obtaining ground or on-orbit light exposure patterns and movement data. The objective of this project was to prepare AWS devices for launch on STS-133/ULF5 by a means of implementing functional tests and engineering evaluations. The data obtained from these tests and evaluations served as a means for detecting any plausible issues that the AWS may encounter while on-orbit. Subsequent steps after detecting anomalies with AWS devices encompassed identifying their root causes and taking the steps needed to mitigate them. As a result of this study, the overall success of sleep/wake research studies for STS-133/ULF5 and future missions will be enhanced.

Rollins, Selisa F.↗
NASA NTRS2011

Validation of the MODIS "Clear-Sky" Surface Temperature of the Greenland Ice Sheet

Surface temperatures on the Greenland Ice Sheet have been studied on the ground, using automatic weather station (AWS) data from the Greenland-Climate Network (GC-Net), and from analysis of satellite sensor data. Using Advanced Very High Frequency Radiometer (AVHRR) weekly surface temperature maps, warming of the surface of the Greenland Ice Sheet has been documented from 1981 to present. We extend and refine this record using higher-resolution Moderate-Resolution Imaging Spectroradiometer (MODIS) data from March 2000 to the present. To permit changes to be observed over time, we are developing a well-characterized monthly climate-data record (CDR) of the "clear-sky" surface temperature of the Greenland Ice Sheet using data from both the Terra and Aqua satellites. We use the MODIS ice-surface temperature (IST) algorithm. Validation of the CDR consists of several facets: 1) comparisons between the Terra and Aqua IST maps; 2) comparisons between ISTs and in-situ measurements; 3) comparisons between ISTs and AWS data; and 4) comparisons of ISTs with surface temperatures derived from other satellite instruments such as the Thermal Emission and Reflection Radiometer. In this work, we focus on 1) and 2) above. Surface temperatures on the Greenland Ice Sheet have been studied on the ground, using automatic weather station (AWS) data from the Greenland-Climate Network (GC-Net), and from analysis of satellite sensor data. Using Advanced Very High Frequency Radiometer (AVHRR) weekly surface temperature maps, warming of the surface of the Greenland Ice Sheet has been documented from 1981 to present. We extend and refine this record using higher-resolution Moderate-Resolution Imaging Spectroradiometer (MODIS) data from March 2000 to the present. To permit changes to be observed over time, we are developing a well-characterized monthly climate-data record (CDR) of the "clear-sky" surface temperature of the Greenland Ice Sheet using data from both the Terra and Aqua satellites. We use the MODIS ice-surface temperature (IST) algorithm. Validation of the CDR consists of several facets: 1) comparisons between the Terra and Aqua IST maps; 2) comparisons between ISTs and in-situ measurements; 3) comparisons between ISTs and AWS data; and 4) comparisons of ISTs with surface temperatures derived from other satellite instruments such as the Thermal Emission and Reflection Radiometer. In this work, we focus on 1) and 2) above. First we provide comparisons between Terra and Aqua swath-based ISTs at approximately 14:00 Local Solar Time, reprojected to 12.5 km polar stereographic cells. Results show good correspondence when Terra and Aqua data were acquired within 2 hrs of each other. For example, for a cell centered over Summit Camp (72.58 N, 38.5 W), the average agreement between Terra and Aqua ISTs is 0.74 K (February 2003), 0.47 K (April 2003), 0.7 K (August 2003) and 0.96 K (October 2003) with the Terra ISTs being generally lower than the Aqua ISTs. More precise comparisons will be calculated using pixel data at the swath level, and correspondence between Terra and Aqua IST is expected to be closer. (Because of cloud cover and other considerations, only a few common cloud-free swaths are typically available for each month for comparison.) Additionally, previous work comparing land-surface temperatures (LSTs) from the standard MODIS LST product and in-situ surface-temperature data at Summit Camp on the Greenland Ice Sheet show that Terra MODIS LSTs are about 3 K lower than in-situ temperatures at Summit Camp, during the winter of 2008-09. This work will be repeated using both Terra and Aqua IST pixel data (in place of LST data). In conclusion, we demonstrate that the uncertainties in the CDR will be well characterized as we work through the various facets of its validation.

Hall, Dorothy K.↗
NASA NTRS2019

Jumping the Queue: From NASA to the Commercial Cloud

NASA's High-End Computing Capability (HECC) Project has made it possible for its users to run on commercial cloud resources in a seamless way. In the first of three phases, we implemented a pilot project for a few users, enabling them to “jump the queue” and burst jobs from the HECC environment to Amazon Web Services (AWS). By using GPU-accelerated nodes at AWS, the users were able to make significant advances in their research. The second phase of the project made AWS access available to all HECC users and added accounting to make users responsible for cloud charges. We are also enabling export-controlled work through the use of AWS GovCloud. In the third phase, we will add web-based mechanisms to permit non-HECC users to access cloud resources for their HPC projects.

Hood, Robert↗
NASA NTRS2023

Pypromice: A Python Package for Processing Automated Weather Station Data

The pypromice Python package is for processing and handling observation datasets from automated weather stations (AWS). It is primarily aimed at users of AWS data from the Geological Survey of Denmark and Greenland (GEUS), which collects and distributes in situ weather station observations to the cryospheric science research community. Functionality in pypromice is primarily handled using two key open-source Python packages, xarray (Hoyer & Hamman, 2017) and pandas (The pandas development team, 2020). A defined processing workflow is included in pypromice for transforming original AWS observations (Level 0, L0) to a usable, CF-convention-compliant dataset (Level 3, L3) (Figure 1). Intermediary processing levels (L1,L2) refer to key stages in the workflow, namely the conversion of variables to physical measurements and variable filtering (L1), cross-variable corrections and user-defined data flagging and fixing (L2), and derived variables (L3). Information regarding the station configuration is needed to perform the processing, such as instrument calibration coefficients and station type (one-boom tripod or two-boom mast station design, for example), which are held in a toml configuration file. Two example configuration files are provided with pypromice , which are also used in the package’s unit tests. More detailed documentation of the AWS design, instrumentation, and processing steps are described in Fausto et al. (2021).

pypromice↗
DOE OSTI2026

How Cloud is Accelerating Research at NREL

This presentation coincides with AWS's announcement of their new Parallel Computing Service (PCS) which allows for easy creation of HPC-style clusters in their AWS cloud computing platform. I helped them beta test this service before it was made generally available in August. AWS asked if we would be interested in discussing our experience with the PCS service, and our experience with HPC workloads in the cloud in general, so this slideshow discusses a brief history of scientific computing at NREL and shares a bit of our experiences and approach to utilizing cloud services for HPC-style workloads.

97 MATHEMATICS AND COMPUTING↗