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At least 1,135 records · Page 63

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NASA NTRS2016

Distributed Visualization Project

Distributed Visualization allows anyone, anywhere to see any simulation at any time. Development focuses on algorithms, software, data formats, data systems and processes to enable sharing simulation-based information across temporal and spatial boundaries without requiring stakeholders to possess highly-specialized and very expensive display systems. It also introduces abstraction between the native and shared data, which allows teams to share results without giving away proprietary or sensitive data. The initial implementation of this capability is the Distributed Observer Network (DON) version 3.1. DON 3.1 is available for public release in the NASA Software Store (https://software.nasa.gov/software/KSC-13775) and works with version 3.0 of the Model Process Control specification (an XML Simulation Data Representation and Communication Language) to display complex graphical information and associated Meta-Data.

Tech Port↗

DOE OSTI2022

Spatiotemporal Controls on the Delivery of Dissolved Organic Matter to Streams Following a Wildfire

Warmer and drier climate has contributed to increased occurrence of large, high severity wildfires in the Pacific Northwest, drawing concerns for water quality and ecosystem recovery. While nutrient fluxes generally increase post-fire, the composition of organic matter (OM) transported to streams immediately following a fire is poorly constrained, yet can play an integral role in downstream water quality and biogeochemistry. Here, we quantified the spatiotemporal patterns of dissolved OM (DOM) chemistry for five streams burned by wildfires in Oregon, USA in 2020. We sampled over a 24-hour storm event one month after the fire, revealing variable temporal behavior in DOM dynamics. DOM chemistry was directly related with burn severity spatially. Specifically, nitrogen and aromatic character of DOM increased in streams burned at greater severity. Our results suggest a spatial overprinting of DOM dynamics immediately following fire activity and highlight a key gap in our knowledge of post-fire DOM transport to streams.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Control of low-mode drive asymmetry in an efficient long-pulse low gas-fill density Hohlraum

Laser-driven Hohlraums filled with gas at lower densities (<0.6 mg/cc) have higher efficiency compared to original ≥ 0.96 mg/cc fill because of reduced backscatter losses [Hall et al., Phys. Plasmas 24, 052706 (2017)]. However, using low-density filled Hohlraums with longer drive required for lower adiabat implosions, and hence potentially higher inertial confinement fusion gain designs, has been challenging since the Hohlraum wall blow-off is less tamped, thus altering the laser beam absorption regions and drive symmetry. A series of NIF experiments using optimized pulse shaping, beam pointing, and temporal phasing have demonstrated, through imaging of the Hohlraum and capsule dynamics, that a symmetric implosion using a 14-ns low-adiabat drive pulse {2× longer than high-density-carbon ablator designs using low gas-fill density Hohlraums [Divol et al., Phys. Plasmas 24, 056309 (2017)]} is possible in a low backscatter loss 0.45 mg/cc He-filled Hohlraum. The ingress of the Hohlraum walls was mitigated by revisiting the adiabat-shaped design [Clark et al., Phys. Plasmas 21, 112705 (2014)] that uses a low-power (1 TW) trough that delays the wall expansion. Low-mode P 2 and P 4 drive asymmetry swings caused by the drift of the laser spots were essentially zeroed out by employing temporal beam phasing between cones of beams [Turner et al., Phys. Plasmas 7, 333 (2000)]. So the results also indicate an improved coupling efficiency of ~30% compared to an earlier design using higher density filled Hohlraums and pave the way for revisiting low-adiabat, high convergence drives using CH ablators.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Synchrotron X-ray based particle image velocimetry to measure multiphase streamflow and densitometry

Synchrotron-based radiation techniques are increasingly used in the field of flow condition measurements. As a complicated multiphase flow, cavitation has been investigated in a wide variety of industrial fields, to prevent damages on spillways at large dams or intensify the bacteria eradication rate during water treatments. To control the detrimental effects of cavitating flows, the dynamics of and mechanisms affecting cavitation development shall be visualized and identified in real-time. Due to the large reflection and scattering effects of multiphase flow, standard visible-light imaging technologies cannot penetrate vapor bubbles and provide extremely limited information. In this study, the synchrotron source emitted high-flux X-ray pulses are used to capture flow motion and visualize internal structures with sufficiently high spatial and temporal resolutions. The image processing procedures on raw x-ray images are developed using 2D Fourier transform (FT) and wavelet transform (WT) to implement the contrast enhancement and de-noising. Through the edge detection algorithm, tracking either seeded particles or phase interfaces inside the opaque multiphase flow can be achieved to perform the particle image velocimetry. Further, with decomposing particle-only and particle-eliminated subplots from the X-ray phase-contrast image, the time-resolved velocity and void fraction fields are obtained simultaneously, paving a way for further flow condition analysis such as densitometry.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Raman Interferometry between Autoionizing States to Probe Ultrafast Wave-Packet Dynamics with High Spectral Resolution

Photoelectron interferometry with femtosecond and attosecond light pulses is a powerful probe of the fast electron wave-packet dynamics, albeit it has practical limitations on the energy resolution. We show that one can simultaneously obtain both high temporal and spectral resolution by stimulating Raman interferences with one light pulse and monitoring the modification of the electron yield in a separate step. Applying this spectroscopic approach to the autoionizing states of argon, we experimentally resolved its electronic composition and time evolution in exquisite detail. Theoretical calculations show remarkable agreement with the observations and shed light on the light-matter interaction parameters. Using appropriate Raman probing and delayed detection steps, this technique enables highly sensitive probing and control of electron dynamics in complex systems.

74 ATOMIC AND MOLECULAR PHYSICS↗

NASA NTRS1987

Surface temperature and albedo relationships in Senegal derived from NOAA-7 satellite data

The interaction between surface albedo and local climate in Senegal, Africa, is examined using NOAA AVHRR data collected from September 1981-October 1982. The temporal variations of albedo and surface temperature are calculated and examined. It is observed that the albedo and ground temperature are largest in the winter and spring (dry season) and smallest in the late summer and fall (wet season). From the wet to the dry seasons the albedo varied by about 3 percentage points and the ground temperature by about 13 K. A positive correlation between albedo and ground temperatures is detected; this indicates that the albedo does not control the ground temperature. Other factors that can influence ground temperatures are atmospheric turbulence, soil moisture, thermal inertia, and ground emissivity, which are all affected by the presence or absence of vegetation.

Vukovich, Fred M.↗

NASA NTRS2003

Lightning and Other Influences On Tropical Tropospheric Ozone: Empirical Studies of Covariation

Tropical and subtropical tropospheric ozone are important radiatively active species, with particularly large effects in the upper third of the troposphere. Temporal variability of O3 has proved difficult to simulate day by day in process models. Thus, individual roles of lightning, biomass burning, and other pollution in providing precursor NO(x), radicals, and chain carriers (CO, hydrocarbons) remain unquantified by simulation, and it is theoretically reasonable that individual roles are magnified by a joint synergy. We use wavelet analysis and Burg-algorithm maximum entropy spectral analyses to describe time-scales and correlation of ozone with proxies for processes controlling its concentration. Our empirical studies link time variations apparent in several datasets: the SHADOZ (Southern Hemisphere Additional Ozonesondes) network stations (Nairobi, Fiji), and auxiliary series with power to explain ozone-determining processes, with some interpretation based on the TTO (Tropical Tropospheric Ozone) product derived from TOMS (the Total Ozone Mapping Spectrometer). The auxiliary series are The OTD/LIS(Optical Transient Detector/Lightning Imaging Sensor) measurements of the lightning NO(x) source, the OLR (Outgoing Longwave Radiation)measurement of high-topped clouds, and standard meteorological variables from the United States NCEP (National Centers for Environmental Prediction) and Data Assimilation Office analyses. Concentrating on equatorial ozone, we compare the statistical evidence on the variability of tropospheric ozone. Important variations occur on approximately two-week, two-month (Madden-Julian Oscillation) and annual scales, and relations with OLR suggest controls associated with continental clouds. Hence we are now using the Lightning Imaging Sensor data set to indicate NO(x) sources. We report initial results defining relative roles of the process mentioned affecting O3 using their covariance properties.

Chatfield, Robert B.↗

NASA NTRS2007

Using Remotely-Sensed Estimates of Soil Moisture to Infer Soil Texture and Hydraulic Properties across a Semi-arid Watershed

Near-surface soil moisture is a critical component of land surface energy and water balance studies encompassing a wide range of disciplines. However, the processes of infiltration, runoff, and evapotranspiration in the vadose zone of the soil are not easy to quantify or predict because of the difficulty in accurately representing soil texture and hydraulic properties in land surface models. This study approaches the problem of parameterizing soils from a unique perspective based on components originally developed for operational estimation of soil moisture for mobility assessments. Estimates of near-surface soil moisture derived from passive (L-band) microwave remote sensing were acquired on six dates during the Monsoon '90 experiment in southeastern Arizona, and used to calibrate hydraulic properties in an offline land surface model and infer information on the soil conditions of the region. Specifically, a robust parameter estimation tool (PEST) was used to calibrate the Noah land surface model and run at very high spatial resolution across the Walnut Gulch Experimental Watershed. Errors in simulated versus observed soil moisture were minimized by adjusting the soil texture, which in turn controls the hydraulic properties through the use of pedotransfer functions. By estimating a continuous range of widely applicable soil properties such as sand, silt, and clay percentages rather than applying rigid soil texture classes, lookup tables, or large parameter sets as in previous studies, the physical accuracy and consistency of the resulting soils could then be assessed. In addition, the sensitivity of this calibration method to the number and timing of microwave retrievals is determined in relation to the temporal patterns in precipitation and soil drying. The resultant soil properties were applied to an extended time period demonstrating the improvement in simulated soil moisture over that using default or county-level soil parameters. The methodology is also applied to an independent case at Walnut Gulch using a new soil moisture product from active (C-band) radar imagery with much lower spatial and temporal resolution. Overall, results demonstrate the potential to gain physically meaningful soils information using simple parameter estimation with few but appropriately timed remote sensing retrievals.

Santanello, Joseph A.↗

NASA NTRSDate not supplied

Modeling and Impact of Solar Energetic Particles in the Heliosphere and Geospace

Understanding the radiation environment due to solar energetic particles in the heliosphere and the Earth’s magnetosphere is a challenging and practically important task. Exposure to energetic particles often leads to malfunctions and unexpected failures of electronics onboard spacecraft. The most vulnerable are exploratory missions when outside of the Earth’s magnetosphere. Geomagnetic field deflects Solar Energetic Particles (SEPs) moving through geospace though some of these particles propagate to LEO and have a high penetrating capability, thus producing significant radiation hazards for human spaceflight. Solar energetic particles also have an essential effect on the composition and dynamics of the Earth’s atmosphere. Precipitating SEPs enhance the atmospheric concentration of NOx and HOx, which play a crucial role in the ozone balance in the middle atmosphere by destroying odd oxygen through catalytic reactions. Numerical modeling of the radiation environment due to SEPs in the inner heliosphere and geospace is a multifold problem. That includes simulating 1) solar wind dynamics and the interplanetary magnetic field, 2) global modeling of the Earth’s magnetosphere, and 3) modeling transport and acceleration of SEPs in the inner heliosphere and geospace. The lecture will outline the key physical processes that control the behavior of SEPs in the heliosphere and geospace, along with the contemporary numerical methods used for their modeling. It will primarily focus on describing the SEP population in geospace across different altitudes, ranging from Low Earth Orbit (LEO) through Medium Earth Orbit (MEO) and Geostationary Orbit (GEO), up to the magnetopause, while considering the realistic geomagnetic field. Additionally, the lecture will cover how the SEP population in geospace varies in response to geomagnetic activity. This includes the temporal trapping of SEPs in geospace and the reduction of the rigidity cutoff during geomagnetic storms.

solar energetic particles↗

DOE OSTI2024

Characterizing the impact of finite matrix block size on conservative particle transport through three-dimensional fracture networks

Mass transfer of solutes between fractures and the surrounding rock matrix exerts a noticeable signature on the tail of travel time distributions. When the width of the matrix is assumed to be infinite and advective transport through the fracture is sufficiently fast, the tails of the travel time distributions exhibit a classically expected slope of ψ(t) ∝ t -3/2 . However, studies have yet to characterize how solute transfer between fractures via diffusion through finite matrix blocks influences the tail’s slope in three-dimensional fractured media. Here, in this study, we assess the impact of finite matrix block size on breakthrough curve shape at different spatio-temporal scales by con ducting particle tracking simulations in three-dimensional discrete fracture networks. We consider a variety of hydrodynamic and geostructural proper ties to determine their relative impact on the resulting travel time distributions. We observe that the impact of matrix diffusion through a finite block on travel time distributions is similar to that of an infinite matrix block when the fracture spacing is sufficiently large, matrix diffusion is relatively weak, or transport is considered at an early control plane distance. We observe that the converse of these conditions, results in deviations from the classical ψ(t) ∝ t -3/2 scaling. These results provide a first step toward developing a metric to assess when finite block size effects are expected to significantly influence transport.

58 GEOSCIENCES↗

DOE OSTI2026

Two-Dimensional Perovskite Single-Nanowire Photodetectors

High-performance microphotodetectors require materials that combine strong light–matter interaction, fast charge transport, and ambient stability. Here, we demonstrate single-nanowire devices based on the 2D perovskite (TPA3) 2 PbBr 4 , synthesized via a controlled slow-cooling self-assembly process that yields defect-minimized, anisotropic nanowires with smooth facets. These microphotodetectors exhibit ultralow dark currents (∼10 –15 A), high responsivity (up to 156 mA W –1 ), and exceptional specific detectivity (∼10 11 Jones) under near-UV (405 nm) illumination, with rise and fall times in the millisecond regime. The superior detectivity is primarily driven by the suppression of thermal noise through the material’s ultralow dark current, while the millisecond temporal response is governed by high-intensity trap-filling dynamics. The devices maintain stable operation over 4000 s of continuous on/off cycling and show remarkable ambient stability over weeks, attributed to dense crystal packing and robust organic cation layers. Furthermore, the influence of nanowire thickness on the charge collection efficiency is systematically elucidated through optical penetration depth analysis, highlighting design principles for optimizing low-dimensional perovskite photodetectors. This study introduces single 2D perovskite nanowires as a versatile platform for miniaturized, high-performance optoelectronic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1990

Lidar instruments proposed for Eos

Lidar, an acronym for light detection and ranging, represents a class of instruments that utilize lasers to send probe beams into the atmosphere or onto the surface of the Earth and detect the backscattered return in order to measure properties of the atmosphere or surface. The associated technology has matured to the point where two lidar facilities, Geodynamics Laser Ranging System (GLRS), and Laser Atmospheric Wind Sensor (LAWS) were accepted for Phase 2 studies for Eos. A third lidar facility Laser Atmospheric Sounder and Altimeter (LASA), with the lidar experiment EAGLE (Eos Atmospheric Global Lidar Experiment) was proposed for Eos. The generic lidar system has a number of components. They include controlling electronics, laser transmitters, collimating optics, a receiving telescope, spectral filters, detectors, signal chain electronics, and a data system. Lidar systems that measure atmospheric constituents or meteorological parameters record the signal versus time as the beam propagates through the atmosphere. The backscatter arises from molecular (Rayleigh) and aerosol (Mie) scattering, while attenuation arises from molecular and aerosol scattering and absorption. Lidar systems that measure distance to the Earth's surface or retroreflectors in a ranging mode record signals with high temporal resolution over a short time period. The overall characteristics and measurements objectives of the three lidar systems proposed for Eos are given.

Grant, William B.↗

NASA NTRS2014

Improving Departure Throughput by Dynamically Adjusting Inter-Arrival Spacing

LaGuardia Airport (LGA) in New York has many unique challenges that create excess taxi-out delays. The purpose of this paper is to investigate the potential benefit that could be gained by tactically adjusting the Terminal Sequencing and Spacing (TSS) schedule to precisely manage inter-arrival spacing to maximize the number of departures per arrival pair. Three strategies for dynamically adjusting arrival schedules are proposed in this paper: Delay Control, Delay and Advance, and No Slack Capacity. The benefits of these strategies were examined on actual traffic data at LGA. The results showed that by applying these strategies, a 10 to 60 increase in departures and a reduction in un-utilized departure capacity (gaps) could be achieved during the airports busiest six-hour period. Significant increases in departure throughput would improve air traffic operations by reducing departure delay time. Furthermore, the concept could be used to resolve temporal mismatches between departure capacity and demand which also cause excessive departure delays.

Yoo, Hyo-Sang↗

DOE OSTI2024

A modeling pipeline to relate municipal wastewater surveillance and regional public health data

As COVID-19 becomes endemic, public health departments require improved passive indicators, which are independent of voluntary testing data, to estimate the prevalence of COVID-19 in local communities. Quantification of SARS-CoV-2 RNA from wastewater has the potential to be a powerful passive indicator. However, connecting measured SARS-CoV-2 RNA to community prevalence is challenging. We have developed a generalized methodology to improve the predictive power of wastewater measurements and applied it to data collected from treatment plants in the Chicago area. We built and compared a set of multi-linear regression models, which incorporate pepper mild mottle virus (PMMoV) as a population biomarker, Bovine coronavirus (BCoV) as a recovery control, and wastewater system flow rate into a corrected estimate for SARS-CoV-2 RNA concentration. For our data, models with BCoV performed better than those with PMMoV, but all model estimates of prevalence significantly improved correlation compared to doing no correction. We also investigate the utility of RNA measurements in wastewater as a leading indicator of COVID-19 trends. We do this in a rolling manner for corrected wastewater data and for other prevalence indicators, and statistically compare the temporal relationship between new increases in the wastewater data and those in other prevalence indicators. We find that wastewater trends often lead other COVID-19 indicators in predicting new surges.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

A Semi‐Mechanistic Model for Partitioning Evapotranspiration Reveals Transpiration Dominates the Water Flux in Drylands

Abstract Popular evapotranspiration (ET) partitioning methods make assumptions that might not be well‐suited to dryland ecosystems, such as high sensitivity of plant water‐use efficiency (WUE) to vapor pressure deficit (VPD). Our objectives were to (a) create an ET partitioning model that can produce fine‐scale estimates of transpiration (T) in drylands, and (b) use this approach to evaluate how climate controls T and WUE across ecosystem types and timescales along a dryland aridity gradient. We developed a novel, semi‐mechanistic ET partitioning method using a Bayesian approach that constrains abiotic evaporation using process‐based models, and loosely constrains time‐varying WUE within an autoregressive framework. We used this method to estimate daily T and weekly WUE across seven dryland ecosystem types and found that T dominates ET across the aridity gradient. Then, we applied cross‐wavelet coherence analysis to evaluate the temporal coherence between focal response variables (WUE and T/ET) and environmental variables. At yearly scales, we found that WUE at less arid, higher elevation sites was primarily limited by atmospheric moisture demand, and WUE at more arid, lower elevation sites was primarily limited by moisture supply. At sub‐yearly timescales, WUE and VPD were sporadically correlated. Hence, ecosystem‐scale dryland WUE is not always sensitive to changes in VPD at short timescales, despite this being a common assumption in many ET partitioning models. This new ET partitioning method can be used in dryland ecosystems to better understand how climate influences physically and biologically driven water fluxes.

Environmental Sciences & Ecology↗

DOE OSTI2021

Spatially distributed infection increases viral load in a computational model of SARS-CoV-2 lung infection

A key question in SARS-CoV-2 infection is why viral loads and patient outcomes vary dramatically across individuals. Because spatial-temporal dynamics of viral spread and immune response are challenging to study in vivo, we developed Spatial Immune Model of Coronavirus (SIMCoV), a scalable computational model that simulates hundreds of millions of lung cells, including respiratory epithelial cells and T cells. SIMCoV replicates viral growth dynamics observed in patients and shows how spatially dispersed infections can lead to increased viral loads. The model also shows how the timing and strength of the T cell response can affect viral persistence, oscillations, and control. By incorporating spatial interactions, SIMCoV provides a parsimonious explanation for the dramatically different viral load trajectories among patients by varying only the number of initial sites of infection and the magnitude and timing of the T cell immune response. When the branching airway structure of the lung is explicitly represented, we find that virus spreads faster than in a 2D layer of epithelial cells, but much more slowly than in an undifferentiated 3D grid or in a well-mixed differential equation model. These results illustrate how realistic, spatially explicit computational models can improve understanding of within-host dynamics of SARS-CoV-2 infection.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1992

From Mars to Greenland: Charting gravity with space and airborne instruments - Fields, tides, methods, results

This symposium on space and airborne techniques for measuring gravity fields, and related theory, contains papers on gravity modeling of Mars and Venus at NASA/GSFC, an integrated laser Doppler method for measuring planetary gravity fields, observed temporal variations in the earth's gravity field from 16-year Starlette orbit analysis, high-resolution gravity models combining terrestrial and satellite data, the effect of water vapor corrections for satellite altimeter measurements of the geoid, and laboratory demonstrations of superconducting gravity and inertial sensors for space and airborne gravity measurements. Other papers are on airborne gravity measurements over the Kelvin Seamount; the accuracy of GPS-derived acceleration from moving platform tests; airborne gravimetry, altimetry, and GPS navigation errors; controlling common mode stabilization errors in airborne gravity gradiometry, GPS/INS gravity measurements in space and on a balloon, and Walsh-Fourier series expansion of the earth's gravitational potential.

Colombo, Oscar L.↗

NASA NTRS1999

Global-Scale Hydrology: Simple Characterization of Complex Simulation

Atmospheric general circulation models (AGCMS) are unique and valuable tools for the analysis of large-scale hydrology. AGCM simulations of climate provide tremendous amounts of hydrological data with a spatial and temporal coverage unmatched by observation systems. To the extent that the AGCM behaves realistically, these data can shed light on the nature of the real world's hydrological cycle. In the first part of the seminar, I will describe the hydrological cycle in a typical AGCM, with some emphasis on the validation of simulated precipitation against observations. The second part of the seminar will focus on a key goal in large-scale hydrology studies, namely the identification of simple, overarching controls on hydrological behavior hidden amidst the tremendous amounts of data produced by the highly complex AGCM parameterizations. In particular, I will show that a simple 50-year-old climatological relation (and a recent extension we made to it) successfully predicts, to first order, both the annual mean and the interannual variability of simulated evaporation and runoff fluxes. The seminar will conclude with an example of a practical application of global hydrology studies. The accurate prediction of weather statistics several months in advance would have tremendous societal benefits, and conventional wisdom today points at the use of coupled ocean-atmosphere-land models for such seasonal-to-interannual prediction. Understanding the hydrological cycle in AGCMs is critical to establishing the potential for such prediction. Our own studies show, among other things, that soil moisture retention can lead to significant precipitation predictability in many midlatitude and tropical regions.

Koster, Randal D.↗