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At least 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Characterizing the 2016 Perseid Meteor Shower Outburst

The Perseid meteor shower has been observed for millennia and is known for its visually spectacular meteors and occasional outbursts. Normal activity displays Zenithal Hourly Rates (ZHRs) of approximately100. The Perseids were expected to outburst in 2016, primarily due to particles released during the 1862 and 1479 revolutions of parent Comet Swift-Tuttle. NASA's Meteoroid Environment Office predicted the timing, strength and duration of the outburst for spacecraft risk using the MSFC Meteoroid Stream Model [1]. A double peak was predicted, with an outburst displaying a ZHR of 210 +/- 50 at 00:30 UTC Aug 12 (139.5deg Solar Longitude), and a traditional peak ~12 hours later with rates still heightened from the outburst [2]. Video, visual, and radar observations taken worldwide by various entities were used to characterize the shower and compare to predictions.

Blaauw, R. C.↗
NASA NTRS2017

Characterizing the 2016 Perseid Meteor Shower Outburst

The Perseid meteor shower has been observed for millennia and known for its visually spectacular meteors and occasional outbursts. The Perseids were expected to outburst in 2016, primarily due to particles released during the 1862 and 1479 revolutions of Comet Swift-Tuttle. NASA's Meteoroid Environment Office predicted the timing, strength and duration of the outburst for spacecraft risk using the MSFC Meteoroid Stream Model. A double peak was predicted, with an outburst displaying a ZHR of 210 +/- 50 at 00:30 UTC Aug 12, and a traditional peak approximately 12 hours later with rates still heightened from the outburst. Video, visual, and radar observations taken worldwide by various entities were used to characterize the shower and compare to predictions.

Blaauw, R. C.↗
NASA NTRS2019

LTF/Fluid and Cryogenic Systems Branch

Functions of the Branch: Cross-Cutting Fluids Engineering; Research and Technology Development of Cryogenic Fluid Management (CFM) Systems; Component and System level; Design, Development Test and Evaluation (DDT&E) for Fluid, CFM, Propellant and Gaseous Systems; Fluid Component Specification and Selection; Code Compliance of Pressurized Systems; Fluid/Cryogenic System Performance Analysis and Trade Studies; Hazards Analysis and Risk Assessment of Fluidic Systems; Fluids Modeling and Simulation Capabilities

Fluid↗
NASA NTRS2019

The Space Debris Sensor Experiment

The Space Debris Sensor (SDS) is a NASA Class 1E technology demonstration external payload aboard the International Space Station (ISS). With approximately one square meter of detection area, the SDS is attached to the European Space Agency Columbus module facing the ISS velocity vector with minimal obstruction from ISS hardware. The SDS is the first flight demonstration of the Debris Resistive/Acoustic Grid Orbital NASA-Navy Sensor (DRAGONS) technology developed and matured over 10 years by the NASA Orbital Debris Program Office (ODPO), in concert with the DRAGONS consortium, to provide information on the sub-millimeter scale orbital debris environment. The SDS demonstrated the capacity to read 4 resistive grids at 1 Hz, 40 acoustic sensors at 500 kHz, and record and downlink impact data to the ground. Observable and derived data from the SDS could provide information to models that are critical to understanding risks the small debris environment poses to spacecraft in low Earth orbit. The technology demonstrated by the SDS is a major step forward in monitoring and characterizing the space debris environment. This paper will address the technical performance of the SDS during its operational lifetime and its realization of technical and scientific goals. The SDS was intended to operate for 3 years; however, the payload incurred multiple anomalies during its operational life. Subsequently termed “Anomaly #1,” the first was the symptomatic loss of low data rate 1553 channel command and telemetry. The second, Anomaly #2, was loss of all low- and medium-data rate (Ethernet) telemetry. Anomaly #2 proved to be unrecoverable, leading to loss of the payload after approximately 26 days on-board the ISS. Therefore, this paper also addresses the anomalies that occurred during operation of the SDS, their attribution, and their resolution. Lessons learned are described when relevant to anomaly identification, attribution, and resolution.

Anz-Meador, P.↗
NASA NTRS2020

Occupant Response Analysis of a Full-Scale Crash Test of a Fokker F28 Fellowship Aircraft

In this report, the capability of component fuselage testing and finite element models (FEMs) to predict occupant injury risk when applied to full-scale aircraft crash testing was evaluated. Component level and full-scale crash tests of a Fokker-F28 aircraft were performed in conjunction with representative FEM simulations. Lumbar spine injury risk, calculated through Anthropomorphic Test Device (ATD) outputs measured in the full-scale test, was compared with predictions made by component level testing and simulations. A quantitative assessment of FEM prediction accuracy was made using the International Organization for Standardization (ISO) Technical Report (TR) 16250 curve comparison methodology. Lumbar load injury risk measured in the full-scale test configuration was found to be significantly higher than in the component tests performed. The FEM provided a closer prediction of occupant injury risk than component testing but exhibited limitations in the multi-axis load environment. This work will help inform the application of component testing and FEM simulation when used to evaluate aircraft crashworthiness.

Jacob B Putnam↗
NASA NTRSDate not supplied

Inception of a Spaceflight-specific Mouse to Human Expression Profiling Translation Model

Rodents are foundational model organisms often utilized due to their seemingly analogous morphologies and biological responses to humans. However, recent studies have demonstrated that murine model data are limited in their applicability, particularly in inflammatory disease. In space studies, accurately predicting human response from mouse data is critical due to extreme limiting factors in both rodent and human spaceflight research. With successful prediction, spaceflight ailments can be predicted and prevented while respecting the constraints of the spaceflight industry and minimizing danger to humans. To do so, novel methodologies must be developed that predict human response from murine data after considering biological differences between rodents and humans in spaceflight. After considering terrestrial models, we determined that a spaceflight-based expression profiting translation tool should be created to accurately capture predictions of human gene expression in spaceflight from mouse data. To prepare to build this model, we organized known human spaceflight risks, chose analog human diseases as training data categories, then identified existing RNASeq disease datasets from GEO as potential training data. In addition, we classified existing Genelab mouse differential gene expression datasets for use as experimental data.

Translation↗
DOE OSTI2020

Understanding and Explicitly Measuring Linguistic and Stylistic Properties of Deception via Generation and Translation

Massive digital disinformation is one of the main risks of modern society. Hundreds of models and linguistic analyses have been done to compare and contrast misleading and credible content online. However, most models do not remove the confounding factor of a topic or narrative when training, so the resulting models learn a clear topical separation for misleading versus credible content. We study the feasibility of using two strategies to disentangle the topic bias from the models to understand and explicitly measure linguistic and stylistic properties of content from misleading versus credible content. First, we develop conditional generative models to create news content that is characteristic of different credibility levels. We perform multi-dimensional evaluation of model performance on mimicking both the style and linguistic differences that distinguish news of different credibility using machine translation metrics and classification models. We show that even though generative models are able to imitate both the style and language of the original content, additional conditioning on both the news category and the topic leads to reduced performance. In a second approach, we perform deception style ``transfer" by translating deceptive content into the style of credible content and vice versa. Extending earlier studies, we demonstrate that, when conditioned on a topic, deceptive content is shorter, less readable, more biased, and more subjective than credible content, and transferring the style from deceptive to credible content is more challenging than the opposite direction.

Saldanha, Emily G.↗
NASA NTRS2008

Evaluations of Risks from the Lunar and Mars Radiation Environments

Protecting astronauts from the space radiation environments requires accurate projections of radiation in future space missions. Characterization of the ionizing radiation environment is challenging because the interplanetary plasma and radiation fields are modulated by solar disturbances and the radiation doses received by astronauts in interplanetary space are likewise influenced. The galactic cosmic radiation (GCR) flux for the next solar cycle was estimated as a function of interplanetary deceleration potential, which has been derived from GCR flux and Climax neutron monitor rate measurements over the last 4 decades. For the chaotic nature of solar particle event (SPE) occurrence, the mean frequency of SPE at any given proton fluence threshold during a defined mission duration was obtained from a Poisson process model using proton fluence measurements of SPEs during the past 5 solar cycles (19-23). Analytic energy spectra of 34 historically large SPEs were constructed over broad energy ranges extending to GeV. Using an integrated space radiation model (which includes the transport codes HZETRN [1] and BRYNTRN [2], and the quantum nuclear interaction model QMSFRG[3]), the propagation and interaction properties of the energetic nucleons through various media were predicted. Risk assessment from GCR and SPE was evaluated at the specific organs inside a typical spacecraft using CAM [4] model. The representative risk level at each event size and their standard deviation were obtained from the analysis of 34 SPEs. Risks from different event sizes and their frequency of occurrences in a specified mission period were evaluated for the concern of acute health effects especially during extra-vehicular activities (EVA). The results will be useful for the development of an integrated strategy of optimizing radiation protection on the lunar and Mars missions. Keywords: Space Radiation Environments; Galactic Cosmic Radiation; Solar Particle Event; Radiation Risk; Risk Analysis; Radiation Protection.

Kim, Myung-Hee↗
DOE OSTI2023

Survey of U.S. Research Reactor Auxiliary Facilities Used for Material Testing and Basic Neutron Science

A catalogue of and attributes of the Materials Irradiation and Testing facilities (MIF) and the Basic Neutron Science facilities (BSF) of auxiliary (AUX) facilities of research reactors are compiled. The survey of these facilities is drawn from the set of U.S. university and DOE research reactor facilities and should be considered as a reference point when comparing commonalities in international AUX facilities. The size and shielding capabilities of the facilities, the typical characterization equipment used, and the neutron flux and irradiation capabilities of the facilities are listed. Short descriptions of experimental activities and current practices are detailed for MIFs and BSFs. The attributes are important in consideration of the reconfiguration of the facilities for purposes other than stated mission, i.e., for proliferation of weapons-usable nuclear material (WUNM). An evaluation of the capacity for production rate of WUNM from neutron beams-on-targets or a sample that has been placed in an irradiation position for a period is provided. Further evaluation of reconfiguration of these MIF and BSF are recommended to refine the proliferation risks. Specifically, MIF hot cells and potential configurations, additional modeling of facility throughput and development of methods for determining levels of concern for MIF and BSF have all been identified as steps for refinement of determination of the risks associated with these facilities. Future work will focus on: 1. A model of projected throughput for different MIF and BSF configurations that will be used to provide a window of potential operational misuse for a facility and better understand the capability of production and the rate of processing for WUNM in these facilities. 2. A misuse study for various configurations of MIF hot cell layouts detailing capacity, specifications, shielding constraints for MIF operations, identification of a maximum shielding thickness, and reasonable need associated with each activity performed in a MIF. 3. Development of a rule of thumb rating system utilizing data gathered from previous reports to show levels of concern at a given power level, flux, and experiment set.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2019

Using Deep Learning to Automate Inference of Meteoroid Pre-Entry Properties

Properly assessing the asteroid threat depends on the knowledge of asteroid pre-entry parameters, such as size, velocity, mass, density, and strength. Although a vast number of possible bodies to study exist, such characterization of asteroid populations is currently limited by substantial costs associated with space rendezvous missions and rare meteorite findings. As asteroids fragment, ablate, and decelerate in the atmosphere, they emit light detectable by ground-based and space-borne instruments. Earth’s atmosphere, thus, becomes an accessible laboratory that enables impactor risk assessments by facilitating inference of the pre-entry parameters. These asteroid pre-entry conditions are typically deduced by modeling the entry and breakup physics that best reproduce the observed light or energy deposition curve. However, this process requires extensive manual trial-and-error of uncertain modeling parameters. Automating meteor modeling and inference would improve property distributions used in risk assessments and enable population characterization as more light curves become more readily available through the presence of space assets and ground-based camera networks. We previously developed a genetic algorithm to automate meteor modeling by using the fragment-cloud model (FCM) to search for the values of the FCM input parameters (e.g., diameter) that generate energy deposition profiles that match the observed one. Now, we apply deep learning to infer asteroid diameter, velocity, and density from observed energy deposition curves. We trained and tested our neural network models with synthetic energy deposition curves modeled using the FCM rubble pile implementation. We present an application of a 1D convolutional neural network and compare its performance to other attempted regressors and machine learning techniques, such as a fully connected neural network and Random Forest regression, to demonstrate its capabilities. We validate our model weights and approach using the Chelyabinsk, Tagish Lake, Benešov, Košice, and Lost City meteors.

Tarano, Ana Maria↗
DOE OSTI2022

Time domain probabilistic seismic risk analysis using ground motion prediction equations of Fourier amplitude spectra

Modeling of Fourier amplitude spectra (FAS) of seismic motions has gained much attention in engineering seismology. In the past few years, several ground motion prediction equations (GMPEs) and inter-frequency correlation structure of FAS have been established. Due to many preferable characteristics of FAS, probabilistic seismic hazard/risk analysis is rapidly changing from ergodic, spectrum acceleration Sa(T 0 )-based approach to non-ergodic, site-specific, FAS-based approach. This paper presents time domain intrusive framework for probabilistic seismic risk analysis using GMPE of FAS. Herein, methodology for time domain stochastic ground motion modeling based on GMPEs of FAS is presented in some detail. The simulated uncertain motions are modeled as a random process and represented by polynomial chaos Karhunen-Loève expansion. The random process excitations are further propagated into the uncertain structural system using Galerkin stochastic finite element method (SFEM). Probabilistic evolution of structural response is solved, and such solution is used to develop seismic risk for any damage state. The presented framework is illustrated through seismic risk analysis of a four-story building subjected to possible earthquakes from two strike slip faults. The influences of the epistemic uncertainties in source stress drop Δσ and site attenuation κ0 on seismic risk are investigated. The need for non-ergodic seismic risk analysis with source-specific and site specific characterizations is emphasized.

58 GEOSCIENCES↗
NASA NTRS1985

Integrated risk/cost planning models for the US Air Traffic system

A prototype network planning model for the U.S. Air Traffic control system is described. The model encompasses the dual objectives of managing collision risks and transportation costs where traffic flows can be related to these objectives. The underlying structure is a network graph with nonseparable convex costs; the model is solved efficiently by capitalizing on its intrinsic characteristics. Two specialized algorithms for solving the resulting problems are described: (1) truncated Newton, and (2) simplicial decomposition. The feasibility of the approach is demonstrated using data collected from a control center in the Midwest. Computational results with different computer systems are presented, including a vector supercomputer (CRAY-XMP). The risk/cost model has two primary uses: (1) as a strategic planning tool using aggregate flight information, and (2) as an integrated operational system for forecasting congestion and monitoring (controlling) flow throughout the U.S. In the latter case, access to a supercomputer is required due to the model's enormous size.

Mulvey, J. M.↗
DOE OSTI2022

Stochastic agent-based model for predicting turbine-scale raptor movements during updraft-subsidized directional flights

Rapid expansion of wind energy development across the world has highlighted the need to better understand turbine-caused avian mortality. The risk to golden eagles (Aquila chrysaetos) is of particular concern due to their small population size and conservation status. Golden eagles subsidize their flight in part by soaring in orographic updrafts, which can place them in conflict with wind turbines utilizing the same low-altitude wind resource. Understanding the behavior of soaring raptors in varying atmospheric conditions can therefore be relevant to predicting and mitigating their risk of collision. We present a predictive movement model that simulates individual paths of golden eagles during directional flight (such as migration) that is subsidized by orographic updraft. We modeled eagles in a 50 km by 50 km study area in Wyoming containing three wind power plants with documented golden eagle collisions with turbines. The movement model is applicable to any region where ground elevation is known at turbine scale (50 m) and wind conditions are known at facility scale (3 km). For a given set of atmospheric conditions, the model simulates movements of thousands of orographic soaring eagles to produce a density map quantifying the relative probability of eagle presence. We validated the simulated tracks with GPS telemetry data showing four directional tracks made by golden eagles transiting through the area in 2019 and 2020. For each eagle track, validation was performed using the ratio of the model-simulated eagle presence likelihood with uniform eagle presence and the presence computed using directed random-walk movements. We found that the predictive performance of the model was significantly better (likelihood ratio 1) for low-altitude movements than high-altitude movements that can involve thermal-soaring. We employed the model to produce seasonal presence maps for migrating golden eagles. We found significant turbine-level variations in eagle presence between northerly and southerly migration routes through the study area. Overall, the proposed model offers a generalizable, probabilistic, and predictive tool to assist wind energy developers, ecologists, wildlife managers, and industry consultants in estimating the potential for conflict between soaring birds and wind turbines, thereby reducing the need for site-specific data on golden eagle movements.

17 WIND ENERGY↗
DOE OSTI2022

Natural Hazards Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

This article is about the state of ICON principles Goldman et al. (2021), https://doi.org/10.1029/2021EO153180 in natural hazards and a discussion on the opportunities and challenges of adopting them. Natural hazards pose risks to society, infrastructure, and the environment. Hazard interactions and their cascading phenomena in space and time can further intensify the impacts. Natural hazards’ risks are expected to increase in the future due to environmental, demographic, and socioeconomic changes. It is important to quantify and effectively communicate risks to inform the design and implementation of risk mitigation and adaptation strategies. Multihazard multisector risk management poses several nontrivial challenges, including: (a) integrated risk assessment, (b) Earth system data-model fusion, (c) uncertainty quantification and communication, and (d) crossing traditional disciplinary boundaries. Here, we review these challenges, highlight current research and operational endeavors, and underscore diverse research opportunities. We emphasize the need for integrated approaches, coordinated processes, open science, and networked efforts (ICON) for multihazard multisector risk management.

58 GEOSCIENCES↗
NASA NTRS2010

Reducing Tick-Borne Disease in Alabama: Linking Health Risk Perception with Spatial Analysis Using the NASA Earth Observing System

Lyme disease (LD) accounts for most vector-borne disease reports in the U.S., and although its existence in Alabama remains controversial, other tick-borne illnesses (TBI) such as Southern Tick-Associated Rash Illness (STARI) pose a health concern in the state. Phase One of the Marshall Space Flight Center-UAB DEVELOP study of TBI identified the presence of the chain of infection for LD (Ixodes scapularis ticks carrying Borrelia burgdorferi bacteria) and STARI (Amblyomma americanum ticks and an as-yet-unconfirmed agent) in Alabama. Both LD and STARI are associated with the development of erythema migrans rashes around an infected tick bite, and while treatable with oral antibiotics, a review of educational resources available to state residents revealed low levels of prevention information. To improve prevention, recognition, and treatment of TBI in Alabama, Phase Two builds a health communication campaign based on vector habitat mapping and risk perception assessment. NASA Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite imagery identified likely tick habitats using remotely sensed measurements of vegetation vigor (Normalized Difference Vegetation Index) and soil moisture. Likely tick habitats, identified as those containing both high vegetation density and soil moisture, included Oak Mountain State Park, Bankhead National Forest, and Talladega National Forest. To target a high-risk group -- outdoor recreation program participants at Alabama universities -- the study developed a behavior survey instrument based on existing studies of LD risk factors and theoretical constructs from the Social Ecological Model and Health Belief Model. The survey instrument was amended to include geographic variables in the assessment of TBI knowledge, attitudes, and prevention behaviors, and the vector habitat model will be expanded to incorporate additional environmental variables and in situ data. Remotely sensed environmental data combined with risk perception assessments inform an ongoing outreach campaign consisting of stakeholder meetings and educational seminars.

Hemmings, S.↗
NASA NTRS2015

Lunar COTS: An Economical and Sustainable Approach to Reaching Mars

The NASA COTS (Commercial Orbital Transportation Services) Program was a very successful program that developed and demonstrated cost-effective development and acquisition of commercial cargo transportation services to the International Space Station (ISS). The COTS acquisition strategy utilized a newer model than normally accepted in traditional procurement practices. This new model used Space Act Agreements where NASA entered into partnerships with industry to jointly share cost, development and operational risks to demonstrate new capabilities for mutual benefit. This model proved to be very beneficial to both NASA and its industry partners as NASA saved significantly in development and operational costs while industry partners successfully expanded their market share of the global launch transportation business. The authors, who contributed to the development of the COTS model, would like to extend this model to a lunar commercial services program that will push development of technologies and capabilities that will serve a Mars architecture and lead to an economical and sustainable pathway to transporting humans to Mars. Over the past few decades, several architectures for the Moon and Mars have been proposed and studied but ultimately halted or not even started due to the projected costs significantly exceeding NASA's budgets. Therefore a new strategy is needed that will fit within NASA's projected budgets and takes advantage of the US commercial industry along with its creative and entrepreneurial attributes. The authors propose a new COTS-like program to enter into partnerships with industry to demonstrate cost-effective, cis-lunar commercial services, such as lunar transportation, lunar ISRU operations, and cis-lunar propellant depots that can enable an economical and sustainable Mars architecture. Similar to the original COTS program, the goals of the proposed program, being notionally referred to as Lunar Commercial Orbital Transfer Services (LCOTS) program will be to: 1) reduce development and operational costs by sharing costs with industry; 2) create new markets in cis-lunar space to further reduce operational costs; and 3) enable NASA to develop an affordable and economical exploration Mars architecture. The paper will describe a plan for a proposed LCOTS program, its potential impact to an eventual Mars architecture and its many benefits to NASA, commercial space industry and the US economy.

Lunar ISRU↗
NASA NTRS2016

Lunar COTS: Using the Moon's Resources to Enable An Economical and Sustainable Pathway to Mars and Beyond

To support NASAs goal of sending humans to Mars, a new plan was constructed to develop and demonstrate cislunar capabilities and services in partnership with commercial industry using the well-proven Commercial Orbital Transportation Services (COTS) Program acquisition model. The NASA COTS Program was a very successful program that developed and demonstrated cost-effective commercial cargo transportation services to the International Space Station (ISS). As a result of NASAs COTS program, two new launch vehicles and spacecraft were developed and have been successfully performing cargo transportation missions to the ISS since 2012. The COTS acquisition strategy utilized a new model than normally accepted in traditional procurement practices. This new model used Space Act Agreements where NASA entered into partnerships with industry to jointly share cost, development and operational risks to demonstrate new capabilities for mutual benefit. This model proved to be very beneficial to both NASA and its industry partners as NASA saved significantly in development and operational costs, as much as tenfold, while industry partners successfully expanded their market share of the global launch transportation business for significant economic benefit. Using the COTS acquisition model as a basis, a new plan, notionally referred to as Lunar Commercial Orbital Transfer Services (or Lunar COTS), has been developed to determine the potential benefits and challenges of a new Lunar COTS plan[1]. The proposed plan includes low-cost, commercial-enabled missions to prospect for resources, determine the economic viability of extracting those resources and assess the value proposition of using these resources in future exploration architectures such as Mars. These missions would be accomplished in partnership with industry to meet these exploration goals but will also have the capability to carry payloads to meet science goals as well.

Zuniga, Allison↗