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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

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 OSTI2025

Batch contact testing with variable Na AN-107 and AP-105

The Hanford Site stores an estimated 56 million gallons of mixed radioactive and chemically hazardous waste in large underground tanks. In support of the Direct Feed Low-Activity Waste (DFLAW) program for expediting Hanford tank waste supernate treatment, laboratory-scale ion exchange processing using prototypic unit operations was conducted on AW-105 tank waste at the Pacific Northwest National Laboratory Radiochemical Processing Laboratory. This report describes the batch contact testing for tanks AN-107 and AP-105 to help evaluate CST performance on tanks waste supernate after processing it in the ion exchange columns. Batch columns were performed with the wastes at six Na concentrations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRSDate not supplied

Cloud-Based Demodulation and Data Distribution of a Satellite Downlink

Ground station networks connected to the cloud allow space missions to have global communications coverage without operating their own infrastructure. In this work, we describe the communications architecture for the TechEdSat-13 mission, which performed the first in-space characterization of a neuromorphic processor. The mission utilizes a commercial provider for S-band downlinks. A suite of cloud services and open-source software such as GNU Radio are leveraged to demodulate signals received by an AWS ground station during passes with TechEdSat-13 and store recovered data. Once a pass is scheduled, the entire process takes place without human intervention. On-orbit results the past year of operations are presented, demonstrating the advantages of this approach over traditional operator-owned ground stations. Use of software-defined radio makes possible custom signal processing. The homogeneity of apertures and their interfaces to the cloud simplifies scaling across many sites. This abundance of candidate links lays the groundwork for intelligent scheduling agents to optimize pass selection across several factors, automatically recover from failed contacts, and gather metrics to learn from past performance.

cloud demodulation↗

NASA NTRS2017

Evaluation of VIIRS and MODIS Thermal Emissive Band Calibration Stability Using Ground Target

The S-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) instrument, a polar orbiting Earth remote sensing instrument built using a strong MODIS background, employs a similarly designed on-board calibrating source - a V-grooved blackbody for the thermal emissive bands (TEB). The central wavelengths of most VIIRS TEBs are very close to those of MODIS with the exception of the 10.7 micron channel. To ensure the long term continuity of climate data records derived using VIIRS and MODIS TEB, it is necessary to assess any systematic differences between the two instruments, including scenes with temperatures significantly lower than blackbody operating temperatures at approximately 290 K. Previous work performed by the MODIS Characterization Support Team (MCST) at NASAGSFC used the frequent observations of the Dome Concordia site located in Antarctica to evaluate the calibration stability and consistency of Terra and Aqua MODIS over the mission lifetime. The near-surface temperature measurements from an automatic weather station (AWS) provide a direct reference useful for tracking the stability and determining the relative bias between the two MODIS instruments. In this study, the same technique is applied to the VIIRS TEB and the results are compared with those from the matched MODIS TEB. The results of this study show a small negative bias when comparing the matching VIIRS and Aqua MODIS TEB, implying a higher scene temperature retrieval for S-VIIRS at the cold end. Statistically no significant drift is observed for VIIRS TEB performance over the first 3.5 years of the mission.

Madhavan, Sriharsha↗

DOE OSTI2023

Nanocone-Modified Surface Facilitates Gas Bubble Detachment for High-Rate Alkaline Water Splitting

The significant amount of gas bubbles generated during high-rate alkaline water splitting (AWS) can be detrimental to the process. The accumulation of bubbles will block the active catalytic sites and hinder the ion and electrolyte diffusion, limiting the maximum current density. Furthermore, the detachment of large bubbles can also damage the electrode's surface layer. Here, a general strategy for facilitating bubble detachment is demonstrated by modifying the nickel electrode surface with nickel nanocone nanostructures, which turns the surface into underwater superaerophobic. Simulation and experimental data show that bubbles take a considerably shorter time to detach from the nanocone-modified nickel foil than the unmodified foil. As a result, these bubbles also have a smaller detachment size and less chance for bubble coalescence. The nanocone-modified electrodes, including nickel foil, nickel foam, and 3D-printed nickel lattice, all show substantially reduced overpotentials at 1000 mA cm -2 compared to their pristine counterpart. The electrolyzer assembled with two nanocone-modified nickel lattice electrodes retains >95% of the performance after testing at ≈900 mA cm -2 for 100 h. In conclusion, the surface NC structure is also well preserved. The findings offer an exciting and simple strategy for enhancing the bubble detachment and, thus, the electrode activity for high-rate AWS.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

NASA NTRS2002

Flaw Tolerance in Lap Shear Brazed Joints

Vacuum brazing is a viable process to achieve strong permanent and hermetic joints in space. As in any joining process, brazed Joints have various imperfections and defects. It is important to understand the impact that flaws have on the load carrying capacity and performance of the brazed joints. This study focuses on the behavior of lap shear joints due to their engineering importance in brazed aerospace structures. In Part 1 an average shear strength capabilitY and failure modes of the single lap joints are explored. Specimens comprised of 0.090 inch thick 347 stainless steel sheet brazed with pure silver are tested in accordance with the AWS C3.2 standard. Comparison of the measured loads and average shear stresses at failure with the Finite Element Analysis (FEA) of the same specimens as a function of the overlap lengths shows excellent correlation between the experimental and calculated values for the defect-free lap joints. In Part 2, various flaws will be introduced in the test specimens to simulate lack of braze coverage in the lap joints. Mechanical testing and FEA will be performed on these joints to verify if behavior of ductile ]appoints containing flaws is similar to the joints with the reduced braze area. Finally, in Part 3, the results obtained in Part 1 and 2 will be applied to the brazed assembly to evaluate a load carrying capability of the structural lap joint containing defects.

Flom, Yury↗

DOE OSTI2025

Flexible Pilot Jobs Framework for Distributed High Throughput Computing

Experimental particle physics has been at the forefront of analyzing the world’s largest datasets for decades. The high-energy physics (HEP) community was among the first to develop suitable software and computing tools for this purpose. GlideinWMS is a Glidein-based workload management system whose purpose is to provide experiments like CMS at CERN, DUNE at Fermilab, and others, a way to access and efficiently use vast amounts of computing resources. This system wants to provide a simple way to submit jobs to a set of computing resources, that will be provided to users behind the scenes. Glideins are the pilot jobs executed on the worker nodes at the grid sites, performing operations such as hardware detection, environment setup, and error handling. After all these operations, they will launch the actual user job. Many grid sites are supported, such as shared clusters, Google CE, and AWS. My internship aimed to design and code a flexible pilot jobs framework that will replace the one used by GlideinWMS, developing a modular and flexible skeleton of the Glidein and adding further functionalities. My project also focused on the application of machine learning techniques as support to this management system.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Exotanium DOE SBIR Phase I Results Summary

Exotanium demonstrated this technology with the Idaho National Laboratory’s MASTODON application, a Multiphysics environment designed to run typical high-performance computing (HPC) simulations for structural dynamics, seismic analysis, and risk assessment. The MASTODON application was packaged into a container using Docker, Deployed on Amazon ECS, and managed through a custom Scale-Out Compute on AWS (SOCA) implementation.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Automatic Generation of High-Performance Convolution Kernels on ARM CPUs for Deep Learning

In this work, we present FastConv, a template-based code auto-generation open source library that can automatically generate high-performance deep learning convolution kernels of arbitrary matrices/tensors shapes. FastConv is based on the Winograd algorithm, which is reportedly the highest performing algorithm for the time-consuming convolution layers of convolutional neural networks. ARM CPUs cover a wide range designs and specifications, from embedded devices to HPC-grade CPUs. The leads to the dilemma of how to consistently optimize Winograd-based convolution solvers for convolution layers of different shapes. FastConv addresses this problem by using templates to auto-generate multiple shapes of tuned kernels variants suitable for skinny tall matrices. As a performance portable library, FastConv transparently searches for the best combination of kernel shapes, cache tiles, scheduling of loop orders, packing strategies, access patterns, and online/offline computations. Auto-tuning is used to search the parameter configuration space for the best performance for a given target architecture and problem size. The experiments with layer-wise evaluation on the VGG--16 model confirms a 1.25x performance gains is got by tuning the Winograd library. Integrated comparison results shows 1.02x to 1.40x, 1.14x to 2.17x, and 1.22x and 2.48x speedup is achieved over NNPACK, Arm NN, and FeatherCNN on the Kunpeng 920 beside few cases. Furthermore, problem size performance portability experiments with various convolution shapes shows that FastConv achieves 1.2x to 1.7x speedup and 2x to 22x speedup over NNPACK and ARM NN inference engine using Winograd on Kunpeng 920 . CPU performance portability evaluation on the VGG--16 show an average speedup over NNPACK of 1.42x, 1.21x, 1.26x, 1.37x, 2.26x, and 11.02x is observed on Kunpeng 920, Snapdragon 835, 855, 888, Apple M1, and AWS Graviton2, respectively.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Hydrogen Consortium: Technical Progress on Renewable Hydrogen Production R&D

HydroGEN (https://www.h2awsm.org/) Energy Materials Network (EMN) is an U.S. Department of Energy (DOE) EERE Hydrogen and Fuel Cell Technologies Office (HFTO)-funded consortium that aims to accelerate the discovery and development of advanced water splitting materials (AWSM) for clean, low-cost hydrogen production. This is in line with the H2@Scale initiative (https://www.energy.gov/eere/fuelcells/h2-scale), with the goal to meet U.S. DOE's Hydrogen Shot production cost target of $1/kg H2 within 1 decade. Materials innovations are key to enhancing performance, durability, and cost of hydrogen generation technologies. Large scale, low cost hydrogen from diverse domestic resources can enable an economically competitive and environmentally beneficial future energy system across multiple sectors. HydroGEN is focused on low technology readiness level AWS technologies, including low- (alkaline exchanged membrane electrolysis) and high-temperature electrolysis (proton-conducting solid oxide electrolysis), photoelectrochecmical (PEC) and solar thermochemical (STCH) water splitting. This presentation will provide an overview of the HydroGEN EMN and technical highlights of a few lab-led and FOA-awarded R&D projects. HydroGEN continues to grow its community of industry, university, and national laboratories, forming a national innovation ecosystem focused on renewable hydrogen production.

clean hydrogen↗

DOE OSTI2024

HydroGEN Overview: A Consortium on Advanced Water Splitting Materials

clean hydrogen↗

DOE OSTI2021

Characterization of CST Post-Processing AP-105 Hanford Tank Waste

The primary goal of the Tank Side Cesium Removal (TSCR) system, under development by Washington River Protection Solutions, LLC (WRPS), is to remove entrained solids and 137 Cs from the Hanford tank waste supernate to expedite production of low-activity waste. Ion exchange (IX) testing of 10.9 L of waste from Hanford tank 241-AP-105 (AP-105), performed by Pacific Northwest National Laboratory, used a lead-lag-polish column format, with a bed volume of 10 mL per column, to decontaminate tank waste supernate using crystalline silicotitanate (CST) as the IX media. The AP-105 Cs IX processing test, discussed elsewhere, resulted in a shorter transition zone (i.e., steeper load curve) than those defined by wastes from tanks 241-AP-107 and 241-AW-102.1 The shorter transition zone was indicative of a matrix effect retarding Cs capacity. Therefore, aliquots of spent CST from the lead, lag, and polish columns were subjected to a digestion protocol to quantify analytes retained by the CST and extrapolate the impact on Cs capacity. The spent CST was digested using a combination of 5 M HNO 3 and H 2 O 2 with vigorous heating and stirring. Due to the radiation dose accompanying the 137 Cs on the CST columns, a secondary Cs separation by ammonium molybdophosphate embedded in polyacrylonitrile (AMP-PAN) was performed to separate the 137 Cs from the CST so the samples could be contact-handled for analysis outside of a shielded facility.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Overview of 2016 through 2018 Testing of Air-Purifying Respirator (APR) Cartridge Performance on Multiple Hanford Tank Headspaces and Exhausters

Between 2016 and 2018, 28 air purifying respirator (APR) cartridge tests were performed on headspace vapors from seven Hanford waste storage tanks (SY-102, A-101, BY-108, AX-101, BY-110, SX-101, and SX-104) and seven waste tank exhausters (AP in 2016, AP in 2018, 702-AZ, AN and AW in 2016, and AX and 702-AZ in 2017). All but two tests were conducted under static conditions absent waste-disturbing activities in the subject tanks or tank farms. The two exceptions were cartridges tested with vapors from 702-AZ in 2017 when samples were taken during waste-disturbing activities. Multipurpose APR cartridges, SCOTT 7422-SD1 and 7422-SC1, were tested on samples from each of the 14 tanks or exhausters. Out of 612 Chemicals of Potential Concern (COPCs), only ammonia, mercury, N-nitrosodimethylamine (NDMA), 2,5-dimethylfuran, 2,5-dihydrofuran, furan, and 1,3-butadiene exhibited breakthroughs with outlet concentrations that were >10% of their Occupational Exposure Limits (OEL).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Probing the Electronic and Opto-Electronic Properties of Multilayer MoS 2 Field-Effect Transistors at Low Temperatures

Transition metal dichalcogenides (TMDs)-based field-effect transistors (FETs) are being investigated vigorously for their promising applications in optoelectronics. Despite the high optical response reported in the literature, most of them are studied at room temperature. To extend the application of these materials in a photodetector, particularly at a low temperature, detailed understanding of the photo response behavior of these materials at low temperatures is crucial. Here we present a systematic investigation of temperature-dependent electronic and optoelectronic properties of few-layers MoS 2 FETs, synthesized using the mechanical exfoliation of bulk MoS 2 crystal, on the Si/SiO 2 substrate. Our MoS 2 FET show a room-temperature field-effect mobility μ FE ~40 cm 2 ·V -1 ·s -1 , which increases with decreasing temperature, stabilizing at 80 cm 2 ·V -1 ·s -1 below 100 K. The temperature-dependent (50 K < T < 300 K) photoconductivity measurements were investigated using a continuous laser source λ = 658 nm (E = 1.88 eV) over a broad range of effective illuminating laser intensity, P eff (0.02 μW < P eff < 0.6 μW). Photoconductivity measurements indicate a fractional power dependence of the steady-state photocurrent. The room-temperature photoresponsivity (R) obtained in these samples was found to be ~2 AW -1 , and it increases as a function of decreasing temperature, reaching a maximum at T = 75 K. The optoelectronic properties of MoS 2 at a low temperature give an insight into photocurrent generation mechanisms, which will help in altering/improving the performance of TMD-based devices for various applications.

2D materials↗

NASA NTRS1974

Comparison of the acoustic characteristics of large-scale models of several propulsive-lift concepts

Wind-tunnel acoustic investigations were performed to determine the acoustic characteristics and the effect of forward speed on the over-the-wing externally blown jet flap (OTW), the under-the-wing externally blown jet flap (UTW), the internally blown jet flap (IBF), and the augmentor wing (AW). The data presented represent the basic noise generated by the powered-lift system without acoustic treatment, assuming all other noise sources, such as the turbofan compressor noise, have been suppressed. Under these conditions, when scaled to a 100,000-lb aircraft, the OTW concept exhibited the lowest perceived noise levels, because of dominant low-frequency noise and wing shielding of the high-frequency noise. The AW was the loudest configuration, because of dominant high-frequency noise created by the high jet velocities and small nozzle dimensions. All four configurations emitted noise 10 to 15 PNdB higher than the noise goal of 95 PNdB at 500 ft.

Falarski, M. D.↗

NASA NTRSDate not supplied

Evaluation of Aqua MODIS and S-NPP VIIRS Thermal Emissive Bands Calibration Stability Using Dome-C

Establishing the calibration consistency between satellite measurements is an essential step in the implementation of a long-term global monitoring plan, which often leads to sensor calibration improvements. The Suomi National Polar-Orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) is a polar-orbiting Earth remote sensing instrument built with a strong Moderate Resolution Imaging Spectroradiometer (MODIS) heritage. The center wavelengths of all VIIRS thermal emissive bands (TEBs) match well with those of MODIS with the exception of VIIRS TEB M15 (10.7μm). Previous work from the MODIS Characterization Support Team (MCST) at the NASA/GSFC used specific Earth surface targets to track the long-term consistency,stability, and relative bias between the two MODIS instruments onboard the Terra and Aqua satellites. Using similar methodologies, this paper evaluates the TEB calibration consistency between the MODIS instruments and S-NPP VIIRS over Dome Concordia (Dome-C). The Dome-C site is uniformly snow-covered and the atmospheric effects are small in the surrounding area. Near-surface air temperature measurements from an Automatic Weather Station (AWS) are used as a reference to track each sensor’s calibration stability and determine the relative bias between the MODIS and VIIRS instruments. The results of this study provide a quantitative assessment of the S-NPP VIIRS TEB mission-long performance.

MODIS↗

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↗