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At least 379 records · Page 21

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NASA NTRS2009

Biophysics Representation of the Two-Hit Model of Alzheimer's Disease for the Exploration of Late CNS Risks from Space Radiation

A concern for long-term space travel outside the Earth s magnetic field is the late effects to the central nervous system (CNS) from galactic cosmic ray (GCR) or solar particle events (SPE). Human epidemiology data is severely limited for making CNS risk estimates and it is not clear such effects occur following low LET exposures. We are developing systems biology models based on biological information on specific diseases, and experimental data for proton and heavy ion radiation. A two-hit model of Alzheimer s disease (AD) has been proposed by Zhu et al.(1), which is the framework of our model. Of importance is that over 50% of the US population over the age of 75-y have mild to severe forms of AD. Therefore we recommend that risk assessment for a potential AD risk from space radiation should focus on the projection of an earlier age of onset of AD and the prevention of this possible acceleration through countermeasures. In the two-hit model, oxidative stress and aberrant cell cycle-related abnormalities leading to amyloid-beta plaques and neurofibrillary tangles are necessary and invariant steps in AD. We have formulated a stochastic cell kinetics model of the two-hit AD model. In our model a population of neuronal cells is allowed to undergo renewal through neurogenesis and is susceptible to oxidative stress or cell cycle abnormalities with age-specific accumulation of damage. Baseline rates are fitted to AD population data for specific ages, gender, and for persons with an apolipoprotein 4 allele. We then explore how low LET or heavy ions may increase either of the two-hits or neurogenesis either through persistent oxidative stress, direct mutation, or through changes to the micro-environment, and suggest possible ways to develop accurate quantitative estimates of these processes for predicting AD risks following long-term space travel.

Cucinotta, Francis A.↗

NASA NTRS2020

Uncertainty Quantification of Global Net Methane Emissions From Terrestrial Ecosystems Using a Mechanistically Based Biogeochemistry Model

Quantification of methane (CH4) emissions from wetlands and its sinks from uplands is still fraught with large uncertainties. Here, a methane biogeochemistry model was revised, parameterized, and verified for various wetland ecosystems across the globe. The model was then extrapolated to the global scale to quantify the uncertainty induced from four different types of uncertainty sources including parameterization, wetland type distribution, wetland area distribution, and meteorological input. We found that global wetland emissions are 212 ± 62 and 212 ± 32 Tg CH4 year−1 (1Tg = 1012 g) due to uncertain parameters and wetland type distribution, respectively, during 2000–2012. Using two wetland distribution data sets and three sets of climate data, the model simulations indicated that the global wetland emissions range from 186 to 212 CH4 year−1 for the same period. The parameters were the most significant uncertainty source. After combining the global methane consumption in the range of −34 to −46 Tg CH4 year−1, we estimated that the global net land methane emissions are 149–176 Tg CH4 year−1 due to uncertain wetland distribution and meteorological input. Spatially, the northeast United States and Amazon were two hotspots of methane emission, while consumption hotspots were in the Eastern United States and eastern China. During 1950–2016, both wetland emissions and upland consumption increased during El Niño events and decreased during La Niña events. This study highlights the need for more in situ methane flux data, more accurate wetland type, and area distribution information to better constrain the model uncertainty.

wetland methane emission↗

NASA NTRS2003

Full-Scale Crash Test and Finite Element Simulation of a Composite Prototype Helicopter

A full-scale crash test of a prototype composite helicopter was performed at the Impact Dynamics Research Facility at NASA Langley Research Center in 1999 to obtain data for validation of a finite element crash simulation. The helicopter was the flight test article built by Sikorsky Aircraft during the Advanced Composite Airframe Program (ACAP). The composite helicopter was designed to meet the stringent Military Standard (MIL-STD-1290A) crashworthiness criteria and was outfitted with two crew and two troop seats and four anthropomorphic dummies. The test was performed at 38-ft/s vertical and 32.5-ft/s horizontal velocity onto a rigid surface. An existing modal-vibration model of the Sikorsky ACAP helicopter was converted into a model suitable for crash simulation. A two-stage modeling approach was implemented and an external user-defined subroutine was developed to represent the complex landing gear response. The crash simulation was executed with a nonlinear, explicit transient dynamic finite element code. Predictions of structural deformation and failure, the sequence of events, and the dynamic response of the airframe structure were generated and the numerical results were correlated with the experimental data to validate the simulation. The test results, the model development, and the test-analysis correlation are described.

Jackson, Karen E.↗

NASA NTRS1983

A study of the temporal and spectral characteristics of gamma ray bursts

Gamma-ray burst data obtained from the ISEE-3 Gamma Ray Burst Spectrometer and the Solar Maximum Mission's Hard X-ray Burst Spectrometer (HXRBS) were analyzed to yield information on burst temporal and spectral characteristics. A Monte Carlo approach was used to simulate the HXRBS response to candidate spectral models. At energies above about 100 keV, the spectra are well fit by exponential forms. At lower energies, 30 keV to 60 keV, depressions below the model continua are apparent in some bursts. The depressions are not instrumental or data-reduction artifacts. The event selection criterion of the ISEE-3 experiment is based on the time to accumulate a present number of photons rather than the photon count per unit time and is consequently independent of event duration for a given burst intensity, unlike most conventional systems. As a result, a significantly greater percentage of fast, narrow events have been detected. The ratio of count rates from two ISEE-3 detectors indicates that bursts with durations or approx. one second have much softer spectra than longer bursts.

Norris, J.↗

NASA NTRS1991

Monte Carlo analysis of dissociation and recombination behind strong shock waves in nitrogen

Computations are presented for the relaxation zone behind strong, 1D shock waves in nitrogen. The analysis is performed with the direct simulation Monte Carlo method (DSMC). The DSMC code is vectorized for efficient use on a supercomputer. The code simulates translational, rotational and vibrational energy exchange and dissociative and recombinative chemical reactions. A model is proposed for the treatment of three body-recombination collisions in the DSMC technique which usually simulates binary collision events. The model improves previous models because it can be employed with a large range of chemical-rate data, does not introduce into the flow field troublesome pairs of atoms which may recombine upon further collision (pseudoparticles) and is compatible with the vectorized code. The computational results are compared with existing experimental data. It is shown that the derivation of chemical-rate coefficients must account for the degree of vibrational nonequilibrium in the flow. A nonequilibrium-chemistry model is employed together with equilibrium-rate data to compute the flow in several different nitrogen shock waves.

Boyd, I. D.↗

NASA NTRS1992

Adaptive filtering and prediction of the Southern Oscillation index

Singular spectrum analysis (SSA), a variant of principal component analysis, is applied to a time series of the Southern Oscillation index (SOI). The analysis filters out variability unrelated to the Southern Oscillation and separates the high-frequency, 2- to 3-year variability, including the quasi-biennial oscillation, from the lower-frequency 4- to 6-year El Nino cycle. The maximum entropy method (MEM) is applied to forecasting the prefiltered SOI. Prediction based on MEM-associated autoregresive models has useful skill for 30-36 months. A 1993-1994 La Nina event is predicted based on data through February 1992.

Keppenne, Christian L.↗

NASA NTRS2016

Heavy Right-Handed Neutrino Dark Matter and PeV Neutrinos at IceCube

We discuss a simple non-supersymmetric model based on the electroweak gauge group SU(2) (sub L) times SU(2) prime times U(1) (Sub B-L) where the lightest of the right-handed neutrinos, which are part of the leptonic doublet of SU(2) prime, play the role of a long-lived unstable dark matter with mass in the multi-Peta-electronvolt range. We use a resonant s-channel annihilation to obtain the correct thermal relic density and relax the unitarity bound on dark matter mass. In this model, there exists a 3-body dark matter decay mode producing tau leptons and neutrinos, which could be the source for the Peta-electronvolt cascade events observed in the IceCube experiment. The model can be tested with more precise flavor information of the highest-energy neutrino events in future data.

Bhupal Dev, P. S.↗

NASA NTRS2019

Statistical Modeling of Quiet Sonic Boom Community Response Survey Data

The existing ban on commercial supersonic flight overland is largely due to the effects of loud and startling sonic booms on communities. NASA is planning a nationwide campaign of community response surveys using the experimental X-59 Quiet SuperSonic Technology (X-59 QueSST) aircraft to understand how communities perceive the sounds of quiet supersonic flight. The X-59 community response survey data will be presented to noise regulators, who are considering replacing the ban with a noise-based certification limit so quiet supersonic vehicles can fly over land. In this document, we use pilot community response survey data to explore and assess multiple approaches to statistically model the dose-response relationship between single-event sonic boom sound exposure and human annoyance. The models have two primary functions—estimating two types of quantities that support setting regulations and experimental design of future surveys.

Jasme Lee↗

NASA NTRSDate not supplied

Deploying a Self-Supervised Learning Based Model to Search Events Across Space and Time

Motivation - Scientific Study of natural events, phenomena, or disasters require examples which span across time and space. - Machine Learning adaptation is on the rise, but there’s a lack of labeled training datasets that could be used to train or validate the models. - Best case scenario: - There’s an event database that tracks events available through time and space. - Provides all data associated with the events. - Real life scenario: - Some events are better tracked than others. - Scientists need to spend significant time identifying and gathering examples of events from different sources.

Iksha Gurung↗

NASA NTRSDate not supplied

An Investigation Into Transecting Satellites in Future Space Traffic Management Scenarios

The number of satellites expected to populate the near-Earth space environment is set to dramatically increase in the coming decade as new large constellations are approved and deployed. Current strategies for placing new batches of these satellites on orbit often involve launching into an initial orbit, and then performing apogee raising maneuvers to reach a target altitude. Similarly, end-of-life planning for these constellation satellites can consist of de-orbit burns that lower perigee to permit disposal via re-entry. Both the raising and de-orbiting maneuvers can result in the individual satellites traveling in high-eccentricity orbits that have the potential to transect other spacecraft trajectories. While individual large constellations may be able to coexist in separate altitude and inclination bands, having thousands of satellites moving between these bands as new satellites are replaced and old ones are removed could pose additional collision risks. Similar concerns have been raised regarding the impact that large numbers of university-class CubeSats might have in terms of their overall collision risk, especially as these satellites typically do not have propulsion systems for active maneuvering. To assess the impact that transecting satellites might have to future space traffic management strategies, this study explored a variety of future realistic scenarios using a high-fidelity simulation tool. The model can simulate the orbit of tens of thousands of resident space objects (RSOs) simultaneously, to include active satellites, debris, rocket bodies, or even future hypothetical scenarios, using a realistic force model that incorporates non-spherical gravity, atmospheric drag, solar radiation pressure, and more. As the model is run forward in time, various statistics and meta-data are gathered on any predicted conjunction event, providing insight into the nature and frequency of potential collisions, e.g., what size are the two satellites, who operates the satellites, are they active or passive objects, etc. Additional customization is available in terms of how probability of collision is computed, and how the probability ellipsoids and screening volumes are determined. The simulation tool also allows for rule-based maneuvers for active satellites, e.g, given an advance conjunction “warning,” one or both of the satellites can maneuver to a safe distance. A wide range of maneuvers can be implemented using impulsive or low-thrust methods, and the latencies can also be varied, e.g., using maneuver lead times of 48 hours, 24 hours, or 12 hours. Validation of the simulation results is performed against current and historical datasets available, to include comparisons to prior conjunction data messages (CDMs), object properties (mass, volume, etc.), and two-line-element records from both public and internal sources. Using the simulation environment, an assessment on the general risks that transecting satellites might pose for hypothetical future space object environments will be presented. This will involve the simulation of approximately 50,000 new large constellation satellites, in addition to the existing catalog of approximately 20,000 known resident space objects (RSOs), over propagation periods of one month to one year. A description of the simulation methodologies, scenarios evaluated, and validation methods will also be presented, as well as a preliminary assessment of the effectiveness of several candidate maneuver strategies that have the potential to reduce collision risk between active satellites.

Brian Gunter↗

NASA NTRS2010

Near Real-Time Optimal Prediction of Adverse Events in Aviation Data

The prediction of anomalies or adverse events is a challenging task, and there are a variety of methods which can be used to address the problem. In this paper, we demonstrate how to recast the anomaly prediction problem into a form whose solution is accessible as a level-crossing prediction problem. The level-crossing prediction problem has an elegant, optimal, yet untested solution under certain technical constraints, and only when the appropriate modeling assumptions are made. As such, we will thoroughly investigate the resilience of these modeling assumptions, and show how they affect final performance. Finally, the predictive capability of this method will be assessed by quantitative means, using both validation and test data containing anomalies or adverse events from real aviation data sets that have previously been identified as operationally significant by domain experts. It will be shown that the formulation proposed yields a lower false alarm rate on average than competing methods based on similarly advanced concepts, and a higher correct detection rate than a standard method based upon exceedances that is commonly used for prediction.

Martin, Rodney Alexander↗

NASA NTRS1985

The impact of mesoscale data on the simulation of a mesoscale convective weather system

The objectives are: (1) to demonstrate the sensitivity of a numerical simulation of a mesoscale convective weather system to the initial conditions; and (2) to provide further evidence of the need for a high resolution observing system that is compatible with numerical-model initial data requirements. To this end, a series of nine numerical-model sensitivity experiments were conducted in which one or more variables from one or more observations (soundings) were omitted and/or adjusted in the model initialization. Two types of surroundings were available for manipulation in the sensitivity experiments. Specifically, for the particular event being simulated (the 1977 Johnstown flash flood), an independent mesoanalysis was available from Bosart and Sanders (1981). In his analysis, Bosart produced a fine-resolution three-dimensional array of data from which soundings that helped to define mesoscale features could be extracted. These 'nonconventional' soundings were added to the conventional sounding data routinely available for model initialization.

Fritsch, J. M.↗

NASA NTRS1987

Analysis of photopole data reduction models

An analysis of the total impulse obtained from a buried explosive charge can be calculated from displacement versus time points taken from successive film frames of high speed motion pictures of the explosive event. The indicator of that motion is a pole and baseplate (photopole), which is placed on or within the soil overburden. Here, researchers are concerned with the precision of the impulse calculation and ways to improve that precision. Also examined here is the effect of each initial condition on the curve fitting process. It is shown that the zero initial velocity criteria should not be applied due to the linear acceleration versus time character of the cubic power series. The applicability of the new method to photopole data records whose early time motions are obscured is illustrated.

Cheek, James B.↗

NASA NTRS1999

Using a Genetic Algorithm to Model Broadband Regional Waveforms for Crustal Structure in the Western United States

In this study, we analyze regional seismograms to obtain the crustal structure in the eastern Great Basin and western Colorado plateau. Adopting a for- ward-modeling approach, we develop a genetic algorithm (GA) based parameter search technique to constrain the one-dimensional crustal structure in these regions. The data are broadband three-component seismograms recorded at the 1994-95 IRIS PASSCAL Colorado Plateau to Great Basin experiment (CPGB) stations and supplemented by data from U.S. National Seismic Network (USNSN) stations in Utah and Nevada. We use the southwestern Wyoming mine collapse event (M(sub b) = 5.2) that occurred on 3 February 1995 as the seismic source. We model the regional seismograms using a four-layer crustal model with constant layer parameters. Timing of teleseismic receiver functions at CPGB stations are added as an additional constraint in the modeling. GA allows us to efficiently search the model space. A carefully chosen fitness function and a windowing scheme are added to the algorithm to prevent search stagnation. The technique is tested with synthetic data, both with and without random Gaussian noise added to it. Several separate model searches are carried out to estimate the variability of the model parameters. The average Colorado plateau crustal structure is characterized by a 40-km-thick crust with velocity increases at depths of about 10 and 25 km and a fast lower crust while the Great Basin has approximately 35- km-thick crust and a 2.9-km-thick sedimentary layer.

Bhattacharyya, Joydeep↗

NASA NTRS2017

Fluid Lensing and Applications to Remote Sensing of Aquatic Environments

The use of fluid lensing technology on UAVs is presented as a novel means for 3D imaging of aquatic ecosystems from above the water's surface at the centimeter scale. Preliminary results are presented from airborne fluid lensing campaigns conducted over the coral reefs of Ofu Island, American Samoa (2013) and the stromatolite reefs of Shark Bay, Western Australia (2014), covering a combined area of 15km2. These reef ecosystems were revealed with centimetre-scale 2D resolution, and an accompanying 3D bathymetry model was derived using fluid lensing, Structure from Motion and UAV position data. Data products were validated from in-situ survey methods including underwater calibration targets, depth measurements and millimetre-scale high-dynamic range gigapixel photogrammetry. Fluid lensing is an experimental technology that uses water transmitting wavelengths to passively image underwater objects at high-resolution by exploiting time-varying optical lensing events caused by surface waves. Fluid lensing data are captured from low-altitude, cost-effective electric UAVs to achieve multispectral imagery and bathymetry models at the centimetre scale over regional areas. As a passive system, fluid lensing is presently limited by signal-to-noise ratio and water column inherent optical properties to approximately 10 m depth over visible wavelengths in clear waters. The datasets derived from fluid lensing present the first centimetre-scale images of a reef acquired from above the ocean surface, without wave distortion. The 3D multispectral data distinguish coral, fish and invertebrates in American Samoa, and reveal previously undocumented, morphologically distinct, stromatolite structures in Shark Bay. These findings suggest fluid lensing and multirotor electric drones represent a promising advance in the remote sensing of aquatic environments at the centimetre scale, or 'reef scale' relevant to the conservation of reef ecosystems. Pending further development and validation of fluid lensing methods, these technologies present a solution for large-scale 3D surveys of shallow aquatic habitats with centimetre-scale spatial resolution and hourly temporal sampling.

Aquatic↗

NASA NTRS2007

NASA Shuttle Orbiter Reinforced Carbon Carbon (RCC) Crack Repair Arc-Jet Testing

This NASA study demonstrates the capability for testing NOAX-repaired RCC crack models in high temperature environments representative of Shuttle Orbiter during reentry. Analysis methods have provided correlation of test data with flight predictions. NOAX repair material for RCC is flown on every STS flight in the event such a repair is needed. Two final test reports are being generated on arc-jet results (both calibration model runs and repaired models runs).

Clark, ShawnDella↗

NASA NTRSDate not supplied

Impact of Canadian Wildfires on Mid Atlantic’s Region Air Quality: An Analysis Using ASDC Data

Wildfires pose a growing concern in North America due to their harmful impacts on air quality and public health, with increased wildfire activity in recent years leading to widespread smoke plumes that can transcend borders. The exposure of New York City (NYC), the most populous city in North America, to Canadian wildfire smoke highlights the substantial implications for public health and urban environments. To better understand the impact of Canadian wildfires on air quality in NYC, satellite data from the NASA Atmospheric Science Data Center (ASDC) at Langley Research Center, along with ground-based measurements and atmospheric modeling results, are analyzed. We examine concentrations of atmospheric aerosols—particularly PM2.5 particulate matter originating from Canadian wildfires—their dispersion patterns, and the duration and intensity of smoke events impacting NYC. Data from multiple satellites, such as those from the Earth Polychromatic Imaging Camera (EPIC), are synergistically used to identify regions affected by wildfires and estimate aerosol loading. Ground-based measurements, including data from air quality monitoring stations, provide localized information for validation and calibration purposes. The findings of this study contribute to our understanding of the impact of Canadian wildfires on NYC's air quality and emphasize the importance of monitoring and prediction of transboundary smoke events using data synthesized from multiple sources, such as those provided by the ASDC. This information is crucial for policymakers, public health officials, and residents in affected areas to develop effective strategies for mitigating the health risks associated with wildfire smoke and improving air quality during wildfire seasons. The utilization of ASDC data in this research highlights the critical role of atmospheric remote sensing in addressing the challenges posed by wildfires and their consequences on regional scales.

Ingrid Garcia-Solera↗

NASA NTRSDate not supplied

Analyzing the Impact of Canadian Wildfires on Air Quality in the U.S. Mid-Atlantic: with Data and Tools from NASA’s Atmospheric Sciences Data Center

Ingrid Garcia-Solera↗