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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Updates to the n+ 63,65 Cu Angular Distributions [Slides]

The performance of the benchmark suite is very sensitive to changes in the angular distribution data. The quasi-differential measurements performed by Blain et al at RPI provide a valuable constraint. Furthermore, ENDF/B-VIII.0 disagrees with their measurements consistently at 300 keV (the transition between RRR and high energy). The next step is to conservatively adjust the Legendre coefficients near 300 keV, validating performance against both critical benchmarks and the RPI quasi-differential measurements.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2010

Sub-10-Micron and Respirable Particles in Lunar Soils

Based on published lunar soil grain size distribution data, we estimate that 1-3% of the mass of typical mature lunar soils is comprised of grains less than 2.5 micrometers in diameter. These particles are in the respirable range (small enough to be inhaled). Estimates are used because the early methods of obtaining grain size distributions did not give reliable results below about 10 micrometers. Grain size analyses of Apollo 11 soil 10084 by a laser diffraction technique shows that this soil contains roughly 2% by volume in the respirable grain size, in agreement with our prior estimate.

Cooper, Bonnie L.↗
DOE OSTI2023

The persistence and conversion of coastal foredune and swale vegetation community distributions 63 years later

Vegetation shifts can directly alter habitat dynamics and indirectly impact habitat stability relative to disturbance response. Barrier island dune habitats exhibit spatiotemporally dynamic topography that is affected by vegetation. However, vegetation distribution data can be rare and vegetation persistence is largely unknown such that species turnover over in communities can occur unnoticed. This is true despite concerns and documented cases of woody encroachment related to climate change in these ecogeomorphic habitats where physical stability to resist storm erosion varies with vegetation distribution and density. In 1956 and 1957, the vegetation of Island Beach State Park, NJ, was mapped as a permanent record for subsequent ecological study. In June 2020, we remapped the vegetation of 5.4 of 17 km north to south, seaward of the thicket community boundary. We maintained the same classification system as the historic record, physically mapping vegetation patches via GPS. We quantified changes in thicket, heather, and grass community distribution between the two time periods. Habitat persistence and conversion varied in the 63 years. Heath communities saw 80%–97% habitat loss in conversion to woody thicket. Conversely, thicket community distribution drastically increased, replacing heath where it was previously prevalent. This represents the first known documented instances of woody encroachment for Morella pensylvanica. When they did not expand, thicket communities receded landward or underwent turnover to an invasive species. Woody species of interest for dune stabilization occupied areas of similar habitat characteristics. Dune vegetation distribution persistence from 1957 to 2020 was relatively consistent and stable with the exception of heath habitat conversion. Barrier island stability is directly related to vegetation stability such that understanding where community shifts might occur over time can aid in managing and modeling efforts surrounding these dynamic ecogeomorphic habitats.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

Modeling and simulation of the data communication network at the ASRM Facility

This paper describes the modeling and simulation of the communication network for the NASA Advanced Solid Rocket Motor (ASRM) facility under construction at Yellow Creek near Luka, Mississippi. Manufacturing, testing, and operations at the ASRM site will be performed in different buildings scattered over an 1800 acre site. These buildings are interconnected through a local area network (LAN), which will contain one logical Fiber Distributed Data Interface (FDDI) ring acting as a backbone for the whole complex. The network contains approximately 700 multi-vendor workstations, 22 multi-vendor workcells, and 3 VAX clusters interconnected via Ethernet and FDDI. The different devices produce appreciably different traffic patterns, each pattern will be highly variable, and some patterns will be very bursty. Most traffic is between the VAX clusters and the other devices. Comdisco's Block Oriented Network Simulator (BONeS) has been used for network simulation. The two primary evaluation parameters used to judge the expected network performance are throughput and delay.

Nirgudkar, R. P.↗
NASA NTRS1990

Modeling of the Space Station Freedom data management system

The data management system (DMS) is the information and communications system onboard Space Station Freedom. Extensive modeling of the DMS is being conducted throughout NASA to aid in the design and development of this vital system. Activities to model the DMS network infrastructure are described, focusing on modeling of the fiber distributed data interface (FDDI) token-ring protocol and experimental testbedding of networking aspects of the DMS.

Johnson, Marjory J.↗
DOE OSTI2025

FEDERATED LEARNING ON STOCHASTIC NEURAL NETWORKS

Federated learning is a machine learning paradigm that leverages edge computing on client devices to optimize models while maintaining user privacy by ensuring that local data remain on the device. However, since all data are collected by clients, federated learning is susceptible to latent noise in local datasets. Factors such as limited measurement capabilities or human errors may introduce inaccuracies in client data. To address this challenge, we propose the use of a stochastic neural network as the local model within the federated learning framework. Stochastic neural networks not only facilitate the estimation of the true underlying states of the data but also enable the quantification of latent noise. We refer to our federated learning approach, which incorporates stochastic neural networks as local models, as federated stochastic neural networks. In this work we will present numerical experiments demonstrating the performance and effectiveness of our method, particularly in handling nonindependent and identically distributed data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Preventing Failures By Dataset Shift Detection in Safety-Critical Graph Applications

Dataset shift refers to the problem where the input data distribution may change over time (e.g., between training and test stages). Since this can be a critical bottleneck in several safety-critical applications such as healthcare, drug-discovery, etc., dataset shift detection has become an important research issue in machine learning. Though several existing efforts have focused on image/video data, applications with graph-structured data have not received sufficient attention. Therefore, in this paper, we investigate the problem of detecting shifts in graph structured data through the lens of statistical hypothesis testing. Specifically, we propose a practical two-sample test based approach for shift detection in large-scale graph structured data. Our approach is very flexible in that it is suitable for both undirected and directed graphs, and eliminates the need for equal sample sizes. Using empirical studies, we demonstrate the effectiveness of the proposed test in detecting dataset shifts. We also corroborate these findings using real-world datasets, characterized by directed graphs and a large number of nodes.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

Design, modeling, and analysis of multi-channel demultiplexer/demodulator

Traditionally, satellites have performed the function of a simple repeater. Newer data distribution satellite architectures, however, require demodulation of many frequency division multiplexed uplink channels by a single demultiplexer/demodulator unit, baseband processing and routing of individual voice/data circuits, and remodulation into time division multiplexed (TDM) downlink carriers. The TRW MCDD (Multichannel Demultiplexer/Multirate Demodulator) operates on a 37.4 MHz composite input signal. Individual channel data rates are either 64 Kbps or 2.048 Mbps. The wideband demultiplexer divides the input signal into 1.44 MHz segments containing either a single 2.048 Mbps channel or thirty two 64 Kbps channels. In the latter case, the narrowband demultiplexer further divides the single 1.44 MHz wideband channel into thirty two 45 KHz narrowband channels. With this approach the time domain Fast Fourier Transformation (FFT) channelizer processing capacity is matched well to the bandwidth and number of channels to be demultiplexed. By using a multirate demodulator fewer demodulators are required while achieving greater flexibility. Each demodulator can process a wideband channel or thirty two narrowband channels. Either all wideband channels, a mixture of wideband and narrowband channels, or all narrowband channels can be demodulated. The multirate demodulator approach also has lower nonrecurring costs since only one design and development effort is needed. TRW has developed a proof of concept (POC) model which fully demonstrates the signal processing fuctions of MCDD. It is capable of processing either three 2.048 Mbps channels or two 2.048 Mbps channels and thirty two 64 Kbps channels. An overview of important MCDD system engineering issues is presented as well as discussion on some of the Block Oriented System Simulation analyses performed for design verification and selection of operational parameters of the POC model. Systems engineering analysis of the POC model confirmed that the MCDD concepts are not only achievable but also balance the joint goals of minimizing on-board complexity and cost of ground equipment, while retaining the flexibility needed to meet a wide range of system requirements.

Lee, David D.↗
NASA NTRS2001

Flight Demonstration of X-33 Vehicle Health Management System Components on the F/A-18 Systems Research Aircraft

The X-33 reusable launch vehicle demonstrator has identified the need to implement a vehicle health monitoring system that can acquire data that monitors system health and performance. Sanders, a Lockheed Martin Company, has designed and developed a COTS-based open architecture system that implements a number of technologies that have not been previously used in a flight environment. NASA Dryden Flight Research Center and Sanders teamed to demonstrate that the distributed remote health nodes, fiber optic distributed strain sensor, and fiber distributed data interface communications components of the X-33 vehicle health management (VHM) system could be successfully integrated and flown on a NASA F-18 aircraft. This paper briefly describes components of X-33 VHM architecture flown at Dryden and summarizes the integration and flight demonstration of these X-33 VHM components. Finally, it presents early results from the integration and flight efforts.

Schweikhard, Keith A.↗
NASA NTRS1989

Large-scale advanced propeller blade pressure distributions: Prediction and data

Two Euler analyses techniques, finite difference and finite volume, were employed to predict the blade surface pressure distributions of a large scale advanced propeller. The predicted pressure distributions were compared with wind tunnel data. Both techniques produced blade pressure distributions that are in fairly good agreement with the data over the range of test Mach numbers of 0.2 to 0.78. However, the numerical simulations fail to predict correctly the measured pressure distributions for the low Mach number, high power case. The data indicate the presence of a leading edge vortex for this case. A discussion of the compressibility effects is also presented.

Nallasamy, M.↗
DOE OSTI2025

Establishing Pb-203 production from electrodeposited Tl targets at Brookhaven National Laboratory

Background: Promising developments in Pb-212 radiopharmaceutical therapies have increased demand for Pb-203 diagnostic agents. Building on previous work from various isotope production facilities, this study optimized Pb-203 production from electrodeposited Tl targets at Brookhaven National Laboratory (BNL). The additional supply of Pb-203 may help meet growing preclinical and clinical demands. Results: Two Tl targets were irradiated at the Brookhaven Linac Isotope Producer facility with 30 ± 1 MeV protons, measured using previously published cross section data. Distribution coefficients for Pb Resin in acetate media were investigated for both Na + and K + cations, where potassium acetate was ~ 4 times more effective at stripping Pb from the Pb Resin. The Tl electrodeposition was optimized to deposit 350 mg of Tl (~ 60 mg/cm 2 ) on Au backing in under 6 h. The proposed separation process was completed in < 1.5 h and achieved > 98% and 92 ± 3% recovery of Tl and Pb, respectively, with an overall Tl-Pb separation factor of 6 × 10 5 . The experimentally measured half-life of Pb-203 was 52.4 ± 0.7 h, agreeing with 51.93 ± 0.02 h reported by the National Nuclear Data Center. The radioisotopic purity of the Pb fraction at 24 h post end of bombardment (EOB) from a 24 h irradiation was 66% Pb-203, 28% Pb-201, and 6% Pb-200. Following chemical separation, the Pb-203 produced in this work (21 MBq Pb-203 EOB) achieved apparent molar activities of 10 ± 5 and 0.9 ± 0.5 GBq/µmol for [ 203 Pb]Pb-DOTAM and [ 203 Pb]Pb-DO3A, respectively, decay corrected to EOB. Data derived from this work suggests BNL can produce > 10’s GBq Pb-203 with > 99% radiochemical and radioisotopic purity from Tl-205 for worldwide distribution. Conclusions: The production and separation of Pb-203 from natural Tl target material was successfully demonstrated at BNL. Existing methods were adapted and optimized for the facilities at BNL. Results from this work will guide future large-scale Pb-203 production opportunities at BNL for clinical applications.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
NASA NTRS2016

Unlocking the Full Potential of Earth Observation During the 2015 Texas Flood Disaster

Intense rainfall during late April and early May 2015 in Texas and Oklahoma led to widespread and sustained flooding in several river basins. Texas state agencies relevant to emergency response were activated when severe weather then ensued for 6 weeks from 8 May until 19 June following Tropical Storm Bill. An international team of scientists and flood response experts assembled and collaborated with decision-making authorities for user-driven high-resolution satellite acquisitions over the most critical areas; while experimental automated flood mapping techniques provided daily ongoing monitoring. This allowed mapping of flood inundation from an unprecedented number of spaceborne and airborne images. In fact, a total of 27,174 images have been ingested to the USGS Hazards Data Distribution System (HDDS) Explorer, except for the SAR images used. Based on the Texas flood use case, we describe the success of this effort as well as the limitations in fulfilling the needs of the decision-makers, and reflect upon these. In order to unlock the full potential for Earth observation data in flood disaster response, we suggest in a call for action(i) stronger collaboration from the onset between agencies, product developers, and decision-makers;(ii) quantification of uncertainties when combining data from different sources in order to augment information content; (iii) include a default role for the end-user in satellite acquisition planning; and(iv) proactive assimilation of methodologies and tools into the mandated agencies.

Texas↗
NASA NTRS1992

Reduction of Marine Magnetic Data for Modeling the Main Field of the Earth

The marine data set archived at the National Geophysical Data Center (NGDC) consists of shipborne surveys conducted by various institutes worldwide. This data set spans four decades (1953, 1958, 1960-1987), and contains almost 13 million total intensity observations. These are often less than 1 km apart. These typically measure seafloor spreading anomalies with amplitudes of several hundred nanotesla (nT) which, since they originate in the crust, interfere with main field modeling. The source for these short wavelength features are confined within the magnetic crust (i.e., sources above the Curie isotherm). The main field, on the other hand, is of much longer wavelengths and originates within the earth's core. It is desirable to extract the long wavelength information from the marine data set for use in modeling the main field. This can be accomplished by averaging the data along the track. In addition, those data which are measured during periods of magnetic disturbance can be identified and eliminated. Thus, it should be possible to create a data set which has worldwide data distribution, spans several decades, is not contaminated with short wavelengths of the crustal field or with magnetic storm noise, and which is limited enough in size to be manageable for the main field modeling. The along track filtering described above has proved to be an effective means of condensing large numbers of shipborne magnetic data into a manageable and meaningful data set for main field modeling. Its simplicity and ability to adequately handle varying spatial and sampling constraints has outweighed consideration of more sophisticated approaches. This filtering technique also provides the benefits of smoothing out short wavelength crustal anomalies, discarding data recorded during magnetically noisy periods, and assigning reasonable error estimates to be used in the least square modeling. A useful data set now exists which spans 1953-1987.

Baldwin, R. T.↗
DOE OSTI2022

Learning Coagulation Processes With Combinatorial Neural Networks

Abstract Simulating the evolution of a coagulating aerosol or cloud of droplets in a key problem in atmospheric science. We present a proof of concept for modeling coagulation processes using a novel combinatorial neural network (CombNN) architecture. Using two types of data from a high‐detail particle‐resolved aerosol simulation, we show that CombNN models outperform standard neural networks and are competitive in accuracy with traditional state‐of‐the‐art sectional models. These CombNN models could have application in learning coarse‐grained coagulation models for multi‐species aerosols and for learning coagulation models from observed size‐distribution data.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1998

Flight Demonstration of X-33 Vehicle Health Management System Components on the F/A-18 Systems Research Aircraft

The X-33 reusable launch vehicle demonstrator has identified the need to implement a vehicle health monitoring system that can acquire data that monitors system health and performance. Sanders, a Lockheed Martin Company, has designed and developed a commercial off-the-shelf (COTS)-based open architecture system that implements a number of technologies that have not been previously used in a flight environment. NASA Dryden Flight Research Center and Sanders teamed to demonstrate that the distributed remote health nodes, fiber optic distributed strain sensor, and fiber distributed data interface communications components of the X-33 vehicle health management (VHM) system could be successfully integrated and flown on a NASA F-18 aircraft. This paper briefly describes components of X-33 VHM architecture flown at Dryden and summarizes the integration and flight demonstration of these X-33 VHM components. Finally, it presents early results from the integration and flight efforts.

Schweikhard, Keith A.↗
NASA NTRS2014

High Performance EVA Glove Collaboration: Glove Injury Data Mining Effort

Human hands play a significant role during extravehicular activity (EVA) missions and Neutral Buoyancy Lab (NBL) training events, as they are needed for translating and performing tasks in the weightless environment. It is because of this high frequency usage that hand- and arm-related injuries and discomfort are known to occur during training in the NBL and while conducting EVAs. Hand-related injuries and discomforts have been occurring to crewmembers since the days of Apollo. While there have been numerous engineering changes to the glove design, hand-related issues still persist. The primary objectives of this study are therefore to: 1) document all known EVA glove-related injuries and the circumstances of these incidents, 2) determine likely risk factors, and 3) recommend ergonomic mitigations or design strategies that can be implemented in the current and future glove designs. METHODS: The investigator team conducted an initial set of literature reviews, data mining of Lifetime Surveillance of Astronaut Health (LSAH) databases, and data distribution analyses to understand the ergonomic issues related to glove-related injuries and discomforts. The investigation focused on the injuries and discomforts of U.S. crewmembers who had worn pressurized suits and experienced glove-related incidents during the 1980 to 2010 time frame, either during training or on-orbit EVA. In addition to data mining of the LSAH database, the other objective of the study was to find complimentary sources of information such as training experience, EVA experience, suit-related sizing data, and hand-arm anthropometric data to be tied to the injury data from LSAH. RESULTS: Past studies indicated that the hand was the most frequently injured part of the body during both EVA and NBL training. This study effort thus focused primarily on crew training data in the NBL between 2002 and 2010. Of the 87 recorded training incidents, 19 occurred to women and 68 to men. While crew ages ranged from thirties to fifties, the age category most affected was in the forties range. Incident rate calculations (incidents per 100 training runs) revealed that the 2002, 2003, and 2004 time periods registered the highest reported incident rate levels (3.4, 6.1, and 4.1 respectively) when compared to the following years (all ≤ 1.0). In addition to general hand-arm discomfort being the highest reported result from training, specific types of hand injuries or symptoms included erythema, fingernail delamination, abrasions, muscle soreness/fatigue, paresthesia, bruising, blanching, and edema. Specific body locations most affected by hand injuries included the metacarpophalangeal joints, fingernails, finger crotches, fingers in general, interphalangeal joints, and fingertips. Causes of injuries reported in the LSAH data were primarily attributed to the forces that the gloved hands were exposed to due to hand intensive tasks and/or poor glove sizing. DISCUSSION: Although the age data indicate that most injuries are reported by male crewmembers in their forties, that is also the dominant gender and age range of most EVA crew therefore it is not an unexpected finding. Age and gender analysis will continue as more details on the uninjured population is accrued. While there is a reasonable mechanism to link training quantity to injury, the results were inconsistent and point to the need for a consistent method of suit-related injury screening and documentation. For instance, the high-incident rate levels for the years 2002 to 2004 could be attributed to a comprehensive medical review of crewmembers post-NBL EVA training that occurred from July 19, 2002 to January 16, 2004. Furthermore, there could have been increased awareness from an investigation at the NBL. These investigations may have temporarily increased the fidelity of reported injuries and discomforts during these dates as compared to surrounding years, when injury signs and symptom were no longer actively being investigated but rather voluntarily reported. Data mining for possible mechanistic factors continues and includes more detailed training timelines, hand anthropometry, and suit sizing information. The limited published data looking at hand-arm anthropometry correlated hand-anthropometry metrics with injuries stemming from glove design and operation. Future work will include further evaluation of body sizing and fit in relation to hand injury incidents.

Reid, C. R.↗
NASA NTRS2017

Collaborative, Rapid Mapping of Water Extents During Hurricane Harvey Using Optical and Radar Satellite Sensors

On August 25, 2017, Hurricane Harvey made landfall between Port Aransas and Port O'Connor, Texas, bringing with it unprecedented amounts of rainfall and record flooding. In times of natural disasters of this nature, emergency responders require timely and accurate information about the hazard in order to assess and plan for disaster response. Due to the extreme flooding impacts associated with Hurricane Harvey, delineations of water extent were crucial to inform resource deployment. Through the USGS's Hazards Data Distribution System, government and commercial vendors were able to acquire and distribute various satellite imagery to analysts to create value-added products that can be used by these emergency responders. Rapid-response water extent maps were created through a collaborative multi-organization and multi-sensor approach. One team of researchers created Synthetic Aperture Radar (SAR) water extent maps using modified Copernicus Sentinel data (2017), processed by ESA. This group used backscatter images, pre-processed by the Alaska Satellite Facility's Hybrid Pluggable Processing Pipeline (HyP3), to identify and apply a threshold to identify water in the image. Quality control was conducted by manually examining the image and correcting for potential errors. Another group of researchers and graduate student volunteers derived water masks from high resolution DigitalGlobe and SPOT images. Through a system of standardized image processing, quality control measures, and communication channels the team provided timely and fairly accurate water extent maps to support a larger NASA Disasters Program response. The optical imagery was processed through a combination of various band thresholds and by using Normalized Difference Water Index (NDWI), Modified Normalized Water Index (MNDWI), Normalized Difference Vegetation Index (NDVI), and cloud masking. Several aspects of the pre-processing and image access were run on internal servers to expedite the provision of images to analysts who could focus on manipulating thresholds and quality control checks for maximum accuracy within the time constraints. The combined results of the radar- and optical-derived value-added products through the coordination of multiple organizations provided timely information for emergency response and recovery efforts.

SERVIR↗
DOE OSTI2025

Scale-up Unlearnable Examples Learning with High-performance Computing

Recent advancements in AI models, like ChatGPT, are structured to retain user interactions, which could inadvertently include sensitive healthcare data. In the healthcare field, particularly when radiologists use AI-driven diagnostic tools hosted on online platforms, there is a risk that medical imaging data may be repurposed for future AI training without explicit consent, spotlighting critical privacy and intellectual property concerns around healthcare data usage. Addressing these privacy challenges, a novel approach known as Unlearnable Examples (UEs) has been introduced, aiming to make data unlearnable to deep learning models. A prominent method within this area, called Unlearnable Clustering (UC), has shown improved UE performance with larger batch sizes but was previously limited by computational resources (e.g., a single workstation). To push the boundaries of UE performance with theoretically unlimited resources, we scaled up UC learning across various datasets using Distributed Data Parallel (DDP) training on the Summit supercomputer. Our goal was to examine UE efficacy at high-performance computing (HPC) levels to prevent unauthorized learning and enhance data security, particularly exploring the impact of batch size on UE’s unlearnability. Utilizing the robust computational capabilities of the Summit, extensive experiments were conducted on diverse datasets such as Pets, MedMNist, Flowers, and Flowers102. Our findings reveal that both overly large and overly small batch sizes can lead to performance instability and affect accuracy. However, the relationship between batch size and unlearnability varied across datasets, highlighting the necessity for tailored batch size strategies to achieve optimal data protection. The use of Summit’s high-performance GPUs, along with the efficiency of the DDP framework, facilitated rapid updates of model parameters and consistent training across nodes. Our results underscore the critical role of selecting appropriate batch sizes based on the specific characteristics of each dataset to prevent learning and ensure data security in deep learning applications. The source code is publicly available at https: // github. com/ hrlblab/ UE_ HPC .

Zhu, Yanfan [Vanderbilt University, Nashville, TN,↗