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All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Preliminary Results from the Joint Russian and US Field Test: Measurement of Sensorimotor and Cardiovascular Responses Immediately Following Landing of the Soyuz Spacecraft

Ongoing collaborative research efforts between NASA's Neuroscience and Cardiovascular Laboratories, and the Institute of Biomedical Problems' (IBMP) Sensory-Motor and Countermeasures Laboratories have been measuring functional sensorimotor, cardiovascular and strength responses following bed rest, dry immersion, short duration (Space Shuttle) and long duration (Mir and International Space Station) space flights. While the unloading paradigms associated with dry immersion and bed rest have do serve as acceptable flight analogs, testing of crew responses following the long duration flights does not begin until a minimum of 24 hours after landing. As a result it is not possible to estimate the nonlinear trend of the early (<24 hr) recovery process nor is it possible to accurately assess the full impact of the decrements associated with long duration flight. To overcome these limitations both the Russian and U.S. sides have implemented testing at the time of landing and before the flight crews have left the landing site. By joint agreement this research effort has been identified as the functional Field Test (FT). For practical reasons the FT has been divided into two phases: the full FT and a preliminary pilot version (PFT) of the FT that is reduced in both length and scope. The primary goal of this research is to determine functional abilities in long duration space flight crews beginning as soon after landing as possible (< 2 hr) with one to three immediate follow-up measurements on the day of landing. This goal has both sensorimotor and cardiovascular elements including an evaluation of NASA's new anti-orthostatic compression garment as compared with the Russian Kentavr garment. Functional sensorimotor measurements will include, but are not limited to, assessment of hand/eye coordination, ability to egress from a seated position, walk normally without falling, measurement of dynamic visual acuity, ability to discriminate different forces generated with both the hands and legs, recovery from a fall, a coordinated walk involving tandem heel-to-toe placement and determination of postural ataxia while standing. The cardiovascular portion of the investigation includes blood pressure and heart rate measurements during a timed stand test in conjunction with postural ataxia testing. In addition to the immediate post-landing collection of data for the full FT, postflight data will be acquired at a minimum of one to three more other times within the 24 hr following landing and continue until functional sensorimotor and cardiovascular responses have returned to preflight normative values. The PFT represents a single trial run comprised of jointly agreed tests from the full FT and relies heavily on IBMP's Sensory-Motor and Countermeasures Laboratories for content, and implementation. The PFT is currently scheduled for the September 2013 landing of the Soyuz spacecraft (34S). Testing will include: (1) a sit-to-stand test, (2) recovery from a fall where the crewmember begins in the prone position on the ground and then stands for 3 min while cardiovascular stability is determined and postural ataxia data are acquired, and (3) a tandem heel-to-toe walk to determine changes in the central locomotor program. Video, cardiovascular parameters (heart rate and blood pressure), data from body-worn inertial sensors and severity of postflight motion sickness will be available for analysis. It is our intent to present, at this celebratory symposium, a summary of these data obtained from two crewmembers. In summary, the level of functional deficit is expected to be most profound during the acquisition of gravity loads immediately after landing when the demands for crew intervention in response to emergency operations will be greatest. Clearly measureable performance parameters such as ability to perform a seat egress, recover from a fall or the ability to see clearly when walking, and related physiological data (orthostatic responses) are required to provide an evidence base for characterizing programmatic risks and the degree of variability among crewmembers. Overall, these early functional and related physiological measurements will allow estimation of nonlinear sensorimotor and cardiovascular recovery trends to an accuracy that has not been previously captured in over 50 years of space flight.

Reschke, M. F.↗
DOE OSTI2024

Scale translation yields insights into gas adsorption under nanoconfinement

This work describes a scale-translating simulation framework to investigate gas adsorption behavior in nanoconfined pores. The framework combines molecular simulations (MSs), equation of state (EoS), and lattice Boltzmann (LB) simulations. MSs reveal the physics of methane adsorption in nano-sized pores, where input values of fugacity coefficients are optimized based on EoS predictions. Then, an LB free-energy model, which incorporates a viral EoS, upscales intermolecular forces and estimates adsorption behavior via a proposed fluid–wall interaction model. Armed with the values of the LB interaction parameter as a function of pressure, the LB model is used to predict fluid behavior in irregular nanopores, and the results are validated against reference MS data. The LB model is then used to study adsorption behavior at a continuum scale in representative organic shale nanopores based on finely characterized Vaca Muerta shale samples. Furthermore, the results show that methane adsorption could significantly increase contained fluids by 10%–25% in pores smaller than 20 nm. However, in larger pores (40 nm to 90 nm), adsorption's impact diminishes to 2%–3%, suggesting sorption's negligible role beyond a 40 nm pore size.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS2012

Validation of Airborne FMCW Radar Measurements of Snow Thickness Over Sea Ice in Antarctica

Antarctic sea ice and its snow cover are integral components of the global climate system, yet many aspects of their vertical dimensions are poorly understood, making their representation in global climate models poor. Remote sensing is the key to monitoring the dynamic nature of sea ice and its snow cover. Reliable and accurate snow thickness data are currently a highly sought after data product. Remotely sensed snow thickness measurements can provide an indication of precipitation levels, predicted to increase with effects of climate change in the polar regions. Airborne techniques provide a means for regional-scale estimation of snow depth and distribution. Accurate regional-scale snow thickness data will also facilitate an increase in the accuracy of sea ice thickness retrieval from satellite altimeter freeboard estimates. The airborne data sets are easier to validate with in situ measurements and are better suited to validating satellite algorithms when compared with in situ techniques. This is primarily due to two factors: better chance of getting coincident in situ and airborne data sets and the tractability of comparison between an in situ data set and the airborne data set averaged over the footprint of the antennas. A 28-GHz frequency modulated continuous wave (FMCW) radar loaned by the Center for Remote Sensing of Ice Sheets to the Australian Antarctic Division is used to measure snow thickness over sea ice in East Antarctica. Provided with the radar design parameters, the expected performance parameters of the radar are summarized. The necessary conditions for unambiguous identification of the airsnow and snowice layers for the radar are presented. Roughnesses of the snow and ice surfaces are found to be dominant determinants in the effectiveness of layer identification for this radar. Finally, this paper presents the first in situ validated snow thickness estimates over sea ice in Antarctica derived from an FMCW radar on a helicopterborne platform.

sea ice↗
NASA NTRSDate not supplied

TPSAS-NF1676L-27509-DND

The information about composition of aerosols has a great importance for monitoring and understanding of climate and environment dynamics. Such information can be obtained using situ measurements or chemical transport models. However, in situ sampling has limited spatial and temporal coverage, while estimations have large uncertainties. The present work enables the monitoring of aerosol chemical species from space-borne observations, providing observationally-based results with spatial and temporal coverage. Following the ideas of Schuster et al.(2005, 2009, 2016), we retrieve chemical composition directly from satellite observations without intermediate retrieval of the refractive index (in contrast with Schuster's approach). This approach is expected to reduce the influence of modeling uncertainties, and to provide additional constraints in situations where remote sensing observations do not have enough spectral sensitivity to refractive index. One of principal difficulties is the identification of an adequate model for linking refractive index to chemical composition. Therefore, the initial effort of this work has focused on identifying an optimal physico-chemistry to refractive index conversion model. With that purpose, we first tested the retrieval approach using a simplified volume-weighting model and updated by the Maxwell Garnett mixing model. This concept was incorporated into the GRASP algorithm designed to retrieve an extended set of atmospheric parameters from remote sensing observations. Then a series of sensitivity tests using synthetic data of POLDER/PARASOL were conducted, and followed by inversion of real PARASOL observations over Africa. The sensitivity tests showed that these two models allow the retrieval to distinguish amongst the assumed chemical species. Results obtained from real PARASOL data demonstrated good agreement with the optical characteristics provided by AERONET. In addition, the obtained patterns of chemical component distribution agreed with known physical expectations. We also compared the chemical composition retrievals to GOCART model simulations and obtained good consistencies.

Lei Li↗
DOE OSTI2022

Vibrational response and temperature of shock-compressed Pt: In situ extended x-ray absorption fine structure measurements to 325 GPa

Single pulse (~100 ps duration) extended x-ray absorption fine structure (EXAFS) measurements were obtained in laser shocked Pt to examine atomic vibrational properties and to determine temperatures for shock pressures from 72-325 GPa. Pt x-ray absorption spectra were recorded while a planar shock wave was propagating through the Pt sample. The absorption spectrum corresponding to the shocked Pt was obtained by subtracting the ambient Pt contribution from the measured absorption spectrum. Fits to the shocked state EXAFS data provided Pt lattice parameters consistent with the known Pt Hugoniot and the mean squared relative displacements (MSRDs) for nearest neighbor Pt atoms. Pt temperatures in the shocked state, estimated from the MSRDs using the correlated Debye model and correlated Einstein models, were consistent with both the Hugoniot temperatures calculated by integration along the Hugoniot and with the Hugoniot temperatures from published first-principles calculations. However, the agreement between the Hugoniot temperatures from EXAFS measurements and the calculated Hugoniot temperatures is not as good above 200 GPa, likely due to anharmonic effects. Furthermore, the present results demonstrate that single-pulse synchrotron EXAFS measurements in laser-shocked solids are useful for quantitative temperature determination and for examination of vibrational properties, including anharmonicity, at extreme pressure-temperature conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Dwarf spheroidal J-factor likelihoods for generalized NFW profiles

ABSTRACT Indirect detection strategies of particle dark matter (DM) in Dwarf spheroidal satellite galaxies (dSphs) typically entail searching for annihilation signals above the astrophysical background. To robustly compare model predictions with the observed fluxes of product particles, most analyses of astrophysical data – which are generally frequentist – rely on estimating the abundance of DM by calculating the so-called J factor. This quantity is usually inferred from the kinematic properties of the stellar population of a dSph using the Jeans equation, commonly by means of Bayesian techniques that entail the presence (and additional systematic uncertainty) of prior choice. Here, extending earlier work, we develop a scheme to derive the profile likelihood for J factors of dwarf spheroidals for models with five or more free parameters. We validate our method on a publicly available simulation suite, released by the Gaia Challenge, finding satisfactory statistical properties for bias and probability coverage. We present the profile likelihood function and maximum likelihood estimates for the J-factor of 10 dSphs. As an illustration, we apply these profile likelihoods to recently published analyses of γ-ray data with the Fermi Large Area Telescope to derive new, consistent upper limits on the DM annihilation cross-section. We do this for a subset of systems, generally referred to as classical dwarfs. The implications of these findings for DM searches are discussed, together with future improvements and extensions of this technique.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1993

Description and availability of airborne Doppler radar data

An airborne, forward-looking, pulse, Doppler radar has been developed in conjunction with the joint FAA/NASA Wind Shear Program. This radar represents a first in an emerging technology. The radar was developed to assess the applicability of an airborne radar to detect low altitude hazardous wind shears for civil aviation applications. Such a radar must be capable of looking down into the ground clutter environment and extracting wind estimates from relatively low reflectivity weather targets. These weather targets often have reflectivities several orders of magnitude lower than the surrounding ground clutter. The NASA radar design incorporates numerous technological and engineering achievements in order to accomplish this task. The basic R/T unit evolved from a standard Collins 708 weather radar, which supports specific pulse widths of 1-7 microns and Pulse Repetition Frequencies (PRF) of less than 1-10 kHz. It was modified to allow for the output of the first IF signal, which fed a NASA developed receiver/detector subsystem. The NASA receiver incorporated a distributed, high-speed digital attenuator, producing a range bin to range bin automatic gain control system with 65 dB of dynamic range. Using group speed information supplied by the aircraft's navigation system, the radar signal is frequency demodulated back to base band (zero Doppler relative to stationary ground). The In-phase & Quadrature-phase (I/Q) components of the measured voltage signal are then digitized by a 12-bit A-D converter (producing an additional 36 dB of dynamic range). The raw I/Q signal for each range bin is then recorded (along with the current radar & aircraft state parameters) by a high-speed Kodak tape recorder.

Harrah, S. D.↗
NASA NTRSDate not supplied

Developing Deep Learning Models for System Remaining Useful Life Predictions: Application to Aircraft Engines

Prognostics and health management (PHM) is an important part of ensuring reliable operations of complex safety- critical systems. System-level remaining useful life (RUL) estimation is a much more complex problem than making estimations at the component level, and system-level RUL methodologies remain sparse in the literature. Model-based approaches have traditionally worked in the past for components such as capacitors, MOSFETs, batteries, or hard-drives (to name a few examples), but developing high fidelity dynamics models of cyber physical systems that can be used to study the effects of multiple degrading components in the system remains a challenging task. Some initial work on model-based System RUL predictions was demonstrated in Khorasgani, et al [1], but, to generalize the system-level prognostics problem, we have to resort to pure data driven and hybrid approaches. In this work, we propose an end-to-end data- driven framework for developing deep learning models to predict remaining useful life of cyber physical systems operating under unknown faulty conditions. The raw data is organized with a data schema that improves the model development process and down stream data analysis tasks. Due to the unknown faulty conditions, the raw sensor data is transformed into signals that expose the underlying degradation processes, which are then used for model development. Bayesian Optimization is used to tune the model parameters prior to training and validation. We show that this approach results in accurate predictions within 3 cycles to end of life (EOL). We demonstrate the effectiveness of our approach by applying it to the N-CMAPSS turbofan engine dataset recently released by NASA, which includes high fidelity degradation modeling, real world operating conditions, and a large set of fault operating modes.

Prognostics↗
DOE OSTI2020

Arctic Tipping Points Triggering Global Change (LDRD Final Report)

The Arctic is warming and feedbacks in the coupled Earth system may be driving the Arctic to tipping events that could have critical downstream impacts for the rest of the globe. In this project we have focused on analyzing sea ice variability and loss in the coupled Earth system Summer sea ice loss is happening rapidly and although the loss may be smooth and reversible, it has significant consequences for other Arctic systems as well as geopolitical and economic implications. Accurate seasonal predictions of sea ice minimum extent and long-term estimates of timing for a seasonally ice-free Arctic depend on a better understanding of the factors influencing sea ice dynamics and variation in this strongly coupled system. Under this project we have investigated the most influential factors in accurate predictions of September Arctic sea ice extent using machine learning models trained separately on observational data and on simulation data from five E3SM historical ensembles. Monthly averaged data from June, July, and August for a selection of ice, ocean, and atmosphere variables were used to train a random forest regression model. Gini importance measures were computed for each input feature with the testing data. We found that sea ice volume is most important earlier in the season (June) and sea ice extent became a more important predictor closer to September. Results from this study provide insight into how feature importance changes with forecast length and illustrates differences between observational data and simulated Earth system data. We have additionally performed a global sensitivity analysis (GSA) using a fully coupled ultra- low resolution configuration E3SM. To our knowledge, this is the first global sensitivity analysis involving the fully-coupled E3SM Earth system model. We have found that parameter variations show significant impact on the Arctic climate state and atmospheric parameters related to cloud parameterizations are the most significant. We also find significant interactions between parameters from different components of E3SM. The results of this study provide invaluable insight into the relative importance of various parameters from the sea ice, atmosphere and ocean components of the E3SM (including cross-component parameter interactions) on various Arctic-focused quantities of interest (QOIs).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Modeling Phenological Controls on Carbon Dynamics in Dryland Sagebrush Ecosystems

Dryland ecosystems play an important role in determining how precipitation anomalies affect terrestrial carbonfluxes at regional to global scales. Thus, to understand how climate change may affect the global carbon cycle,we must also be able to understand and model its effects on dryland vegetation. Dynamic Global VegetationModels (DGVMs) are an important tool for modeling ecosystem dynamics, but they often struggle to reproduceseasonal patterns of plant productivity. Because the phenological niche of many plant species is linked to bothtotal productivity and competitive interactions with other plants, errors in how process-based models representphenology hinder our ability to predict climate change impacts. This may be particularly problematic in drylandecosystems where many species have developed a complex phenology in response to seasonal variability in bothmoisture and temperature. Here, we examine how uncertainty in key parameters as well as the structure ofexisting phenology routines affect the ability of a DGVM to match seasonal patterns of leaf area index (LAI) andgross primary productivity (GPP) across a temperature and precipitation gradient. First, we optimized modelparameters using a combination of site-level eddy covariance data and remotely-sensed LAI data. Second, wemodified the model to include a semi-deciduous phenology type and added flexibility to the representation ofgrass phenology. While optimizing parameters reduced model bias, the largest gains in model performance wereassociated with the development of our new representation of phenology. This modified model was able to bettercapture seasonal patterns of both leaf area index (R2=0.75) and gross primary productivity (R2=0.84), thoughits ability to estimate total annual GPP depended on using eddy covariance data for optimization. The new modelalso resulted in a more realistic outcome of modeled competition between grass and shrubs. These findingsdemonstrate the importance of improving how DGVMs represent phenology in order to accurately forecastclimate change impacts in dryland ecosystems.

Ecosystem model Phenology Parameter optimization E↗
NASA NTRS2014

Preliminary Sensorimotor and Cardiovascular Results from the Joint Russian and U.S. Pilot Field Test with Planning for the Full Field Test Beginning with the Year Long Intenational Space Station

Ongoing collaborative research efforts between NASA's Neuroscience and Cardiovascular Laboratories, and the Institute of Biomedical Problems' (IBMP) Sensory-Motor and Countermeasures Laboratories have been measuring functional sensorimotor, cardiovascular and strength responses following bed rest, dry immersion, short duration (Space Shuttle) and long duration (Mir and International Space Station) space flights. While the unloading paradigms associated with dry immersion and bed rest does serve as acceptable flight analogs, testing of crew responses following the long duration flights previously has not been possible until a minimum of 24 hours after landing. As a result, it is not possible to estimate the nonlinear trend of the early (<24 hr) recovery process, nor is it possible to accurately assess the full impact of the decrements associated with long duration flight. To overcome these limitations, both the Russian and U.S. sides have implemented testing at landing site. By joint agreement, this research effort has been identified as the functional Field Test (FT). For practical reasons the FT has been divided into two phases: the full FT and a preliminary pilot version (PFT) of the FT that is reduced in both length and scope. The primary goal of this research is to determine functional abilities in long duration space flight crews beginning as soon after landing as possible (< 2 hr) with one to three immediate follow-up measurements on the day of landing. This goal has both sensorimotor and cardiovascular elements, including evaluations of NASA's new anti-orthostatic compression garment and the Russian Kentavr garment. Functional sensorimotor measurements will include, but are not limited to, assessment of hand/eye coordination, ability to egress from a seated position, walk normally without falling, measurement of dynamic visual acuity, ability to discriminate different forces generated with both the hands and legs, recovery from a fall, a coordinated walk involving tandem heel-to-toe placement, and determination of postural ataxia while standing. The cardiovascular portion of the investigation includes blood pressure and heart rate measurements during a timed stand test in conjunction with postural ataxia testing (quiet stance sway) as well as cardiovascular responses during other functional tasks. In addition to the immediate post-landing collection of data for the full FT, postflight data will be acquired at a minimum of one to three more other times within the 24 hr following landing and continue until functional sensorimotor and cardiovascular responses have returned to preflight normative values. The PFT represents a single trial run comprised of jointly agreed upon subset of tests from the full FT and relies heavily on IBMP's Sensory-Motor and Countermeasures Laboratories for content and implementation. The PFT was first conducted following the September 2013 landing of the Soyuz spacecraft (34S) and again following the landing of Soyuz 35S in November. Testing included: (1) a sit-tostand test, (2) recovery from a fall where the crewmember began in the prone position on the ground and then stood for 3 min while cardiovascular stability was determined and postural ataxia data were acquired, and (3) a tandem heel-to-toe walk test to determine changes in the central locomotor program. Video, cardiovascular parameters (heart rate and blood pressure), data from body-worn inertial sensors and severity of postflight motion sickness were collected for analysis. In summary, the level of functional deficit is expected to be most profound during the acquisition of gravity loads immediately after landing when the demands for crew intervention in response to emergency operations will be greatest. Clearly measureable performance parameters such as ability to perform a seat egress, recover from a fall or the ability to see clearly when walking, and related physiological data (orthostatic responses) are required to provide an evidence base for characterizing programmatic risks and the degree of variability among crewmembers for exploration missions where the crew will be unassisted after landing. Overall, these early functional and related physiological measurements will allow estimation of nonlinear sensorimotor and cardiovascular recovery trends to an accuracy that has not been previously captured in over 50 years of space flight.

Reschke, M. F.↗
DOE OSTI2025

The hierarchical growth of bright central galaxies and intracluster light as traced by the magnitude gap

Using a sample of 2800 galaxy clusters identified in the Dark Energy Survey across the redshift range 0.20 < z < 0.60, we characterize the hierarchical assembly of bright central galaxies (BCGs) and the surrounding intracluster light (ICL). To quantify hierarchical formation we use the stellar mass–halo mass (SMHM) relation, comparing the halo mass, estimated via the mass–richness relation, to the stellar mass within the BCG + ICL system. Moreover, we incorporate the magnitude gap (M14), the difference in brightness between the BCG (measured within 30 kpc) and fourth brightest cluster member galaxy within 0.5 $R_{200,c}$, as a third parameter in this linear relation. The inclusion of M14, which traces BCG hierarchical growth, increases the slope and decreases the intrinsic scatter, highlighting that it is a latent variable within the BCG + ICL SMHM relation. Moreover, the correlation with M14 decreases at large radii. However, the stellar light within the BCG + ICL transition region (30 –80 kpc) most strongly correlates with halo mass and has a statistically significant correlation with M14. Since the transition region and M14 are independent measurements, the transition region may grow due to the BCG’s hierarchical formation. Additionally, as M14 and ICL result from hierarchical growth, we use a stacked sample and find that clusters with large M14 values are characterized by larger ICL and BCG + ICL fractions, which illustrates that the merger processes that build the BCG stellar mass also grow the ICL. Furthermore, this may suggest that M14 combined with the ICL fraction can identify dynamically relaxed clusters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

KCl-UCl 3 molten salts investigated by Ab Initio Molecular Dynamics (AIMD) simulations

Ab Initio Molecular Dynamics (AIMD) simulations are performed on molten KCl-UCl3 salt mixtures to determine energies, heat capacities, and densities. The density-dependent energy correction (DFT-dDsC), Grimme et al.'s DFT-D3, and Langreth & Lundqvist (vdW-cx) models are used for dispersion forces and combined with the Perdew-Burke-Ernzerhof (PBE) exchange-correlation potential with a Hubbard U parameter for the 5f electrons of uranium. After validating predictions for the end-member systems to literature data, KCl-UCl 3 mixtures are studied at select temperatures. Densities and energies both deviate from ideal solution behavior, with the maximum deviation occurring around 36% UCl 3 for mixing energies and slightly lower (29% UCl3) for densities. Compared to the NaCl-UCl 3 system, which was previously investigated using the same simulation methodologies, the KCl-UCl 3 density and mixing energy deviations from ideal solution behavior are larger by almost a factor of two. No deviation from ideal solution behavior for heat capacity was observed. The AIMD predictions for mixing energies and densities agree qualitatively with experimental data, though the spread in data obtained from the various dispersion force models utilized, measurements, and empirical estimates makes strong conclusions difficult. The dependence of thermodynamic and thermophysical properties on composition is correlated with the local chemistry of the solution phase, in particular, the tendency of UCl 3 to form network structures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

An extended trajectory-mechanics approach for calculating two-phase flow paths

A technique originating in quantum dynamics is used to derive a trajectory-based, semi-analytical solution for two-phase flow. The partial differential equation governing the evolution of the aqueous phase is equivalent to a family of ordinary differential equations defined along a path through the porous medium. The trajectories may be found by solving the differential equations directly or by post-processing the output of a numerical solution to the full set of governing equations. The trajectories, which differ from conventional streamlines, are found to bend downward in response to gravitational forces. The curvature is more pronounced as the dip of the porous layer containing the flow increases. Subtle changes in the relative permeability curve can lead to significant variations in the trajectories. The ordinary differential equation for the trajectory provides an expression for the travel time along the path. The expression produces a semi-analytical approximation to the model parameter sensitivities, the partial derivatives of the travel times with respect to changes in the permeability model. The semi-analytical trajectory-based sensitivities generally agree with those computed using a numerical reservoir simulator and a perturbation approach. The sensitivities are useful in tomographic imaging algorithms designed to estimate the spatial variation in permeability within a porous medium using multiphase observations.

58 GEOSCIENCES↗
DOE OSTI2019

An Empirical Assessment of the MODIS Land Cover Dynamics and TIMESAT Land Surface Phenology Algorithms

Observations of vegetation phenology at regional-to-global scales provide important information regarding seasonal variation in the fluxes of energy, carbon, and water between the biosphere and the atmosphere. Numerous algorithms have been developed to estimate phenological transition dates using time series of remotely sensed spectral vegetation indices. A key challenge, however, is that different algorithms provide inconsistent results. This study provides a comprehensive comparison of start of season (SOS) and end of season (EOS) phenological transition dates estimated from 500 m MODIS data based on two widely used sources of such data: the TIMESAT program and the MODIS Global Land Cover Dynamics (MLCD) product. Specifically, we evaluate the impact of land cover class, criteria used to identify SOS and EOS, and fitting algorithm (local versus global) on the transition dates estimated from time series of MODIS enhanced vegetation index (EVI). Satellite-derived transition dates from each source are compared against each other and against SOS and EOS dates estimated from PhenoCams distributed across the Northeastern United States and Canada. Our results show that TIMESAT and MLCD SOS transition dates are generally highly correlated (r = 0.51-0.97), except in Central Canada where correlation coefficients are as low as 0.25. Relative to SOS, EOS comparison shows lower agreement and higher magnitude of deviations. SOS and EOS dates are impacted by noise arising from snow and cloud contamination, and there is low agreement among results from TIMESAT, the MLCD product, and PhenoCams in vegetation types with low seasonal EVI amplitude or with irregular EVI time series. In deciduous forests, SOS dates from the MLCD product and TIMESAT agree closely with SOS dates from PhenoCams, with correlations as high as 0.76. Overall, our results suggest that TIMESAT is well-suited for local-to-regional scale studies because of its ability to tune algorithm parameters, which makes it more flexible than the MLCD product. At large spatial scales, where local tuning is not feasible, the MLCD product provides a readily available data set based on a globally consistent approach that provides SOS and EOS dates that are comparable to results from TIMESAT.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Geophysical Signatures of Crack Network Coalescence in Rocks at Multiple Length Scales

The main goal of the research project was to identify the geophysical signatures of fracture growth in natural rocks by utilizing novel geophysical techniques. The research objectives were to (a) investigate the potential for geophysical methods to determine when cracks initiate, the types and locations of propagated cracks, and the coalescence of networks of cracks in natural rocks at multiple scales, (b) determine how damage at the microscale evolved into damage at the macroscale and then link the microscopic and macroscopic observations, (c) quantify crack coalescence in rocks under realistic stress conditions using coupled mechanical-geophysical-optical visualization, and (d) identify the precursors in geophysical signals to crack coalescence. The following research thrusts were explored to achieve the research objectives: (1) uniaxial compression testing of rock specimens with and without a set of pre‐existing flaws and (2) triaxial compression testing of natural rock specimens. These thrusts allowed for exploring fracturing in rocks under realistic in situ environments and at multiple scales. This project provided educational opportunities for nine graduate and undergraduate students and resulted in 27 peer-reviewed publications. This first research thrust focused on investigating the micromechanics of fractures in rocks through uniaxial compression testing combined with advanced geophysical and imaging techniques, specifically acoustic emission (AE) monitoring, ultrasonic imaging, and 2-dimensional Digital Image Correlation (2D-DIC). By examining damage processes under time-independent and time-dependent loading conditions, insights into damage localization, crack initiation, and fracturing mechanisms were gained. It was observed that the AE signals and the strain-based measurements directly reflect the state of damage in the rock specimen and could be used to identify the cracking levels, such as the crack initiation (CI) and crack damage (CD), and the mode of deformation. A novel calibration apparatus was developed to enhance the accuracy of AE sensors, allowing for the estimation of key parameters such as magnitude, source dimension, stress drop, and radiated seismic energy associated with the fractures. The findings highlighted significant variations in the temporal evolution of AE source parameters during the primary, secondary, and tertiary stages of creep, identifying tensile cracking as the primary deformation mode. The second research thrust focused on enhancing the understanding of fracturing processes in natural rocks through triaxial compression testing, real-time AE monitoring, and ultrasonic monitoring. We investigated the impact of various factors such as fracture propagation regimes, injection parameters, rock types, and pre-existing conditions on the hydraulic fracture (HF) behavior using scaled true-triaxially loaded specimens of Barre granite and Lyons sandstone. Custom sensor housing facilitated concurrent active and passive monitoring to analyze hydro-mechanical responses and microseismicity associated with different HF scenarios. A coupled investigation of passive microseismicity and active signal attributes permitted a detailed comprehension of the various HF processes (aseismic deformation, fracture initiation and propagation, fluid permeation, and leak-off) and their dependence on the specific rock type. The findings of this research demonstrated the effectiveness of AE monitoring techniques in providing valuable insights into the impact of various factors on the behavior and dynamics of HF processes. The advancements in monitoring techniques, offering a more thorough and precise approach, represent a significant step towards optimizing HF practices and ensuring sustainable resource extraction.

58 GEOSCIENCES↗
DOE OSTI2020

Modeling sediment diagenesis processes on riverbed to better quantify aquatic carbon fluxes and stocks in a small watershed of the Mid-Atlantic region

Background: Despite the widely recognized importance of aquatic processes for bridging gaps in the global carbon cycle, there is still a lack of understanding of the role of riverbed processes for carbon flows and stocks in aquatic environments. Here, we added a sediment diagenesis and sediment carbon (C) resuspension module into the SWAT-C model and tested it for simulating both particulate organic C (POC) and dissolved organic C (DOC) fluxes using 4 years of monthly observations (2014–2017) in the Tuckahoe watershed (TW) in the U.S. Mid-Atlantic region. Results: Sensitivity analyses show that parameters that regulate POC deposition in river networks are more sensitive than those that determine C resuspension from sediments. Further analyses indicate that allochthonous contributions to POC and DOC are about 36.6 and 46 kgC ha –1 year –1 , respectively, while autochthonous contributions are less than 0.72 kgC ha –1 year –1 for both POC and DOC (less than 2% of allochthonous sources). The net deposition of POC on the riverbed (i.e., 11.4 kgC ha –1 year –1 ) retained ca. 31% of terrestrial inputs of POC. In addition, average annual buried C was 0.34 kgC ha –1 year –1 , accounting for only 1% of terrestrial POC inputs or 3% of net POC deposition. The results indicate that about 79% of deposited organic C was converted to inorganic C (CH 4 and CO 2 ) in the sediment and eventually released into the overlying water column. Conclusion: This study serves as an exploratory study on estimation of C fluxes from terrestrial to aquatic environments at the watershed scale. We demonstrated capabilities of the SWAT-C model to simulate C cycling from uplands to riverine ecosystems and estimated C sinks and sources in aquatic environments. Overall, the results highlight the importance of including carbon cycle dynamics within the riverbed in order to accurately estimate aquatic carbon fluxes and stocks. The new capabilities of SWAT-C are expected to serve as a useful tool to account for those processes in watershed C balance assessment.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2018

Simulated Encounters of the Parker Solar Probe with a Coronal-Hole Jet

Solar coronal jets are small, transient, collimated ejections most easily observed in coronal holes (CHs). The upcoming Parker Solar Probe (PSP) mission provides the first opportunity to encounter CH jets in situ near the Sun and examine their internal structure and dynamics. Using projected mission orbital parameters, we have simulated PSP encounters with a fully three-dimensional magnetohydrodynamic (MHD) model of a CH jet. We find that three internal jet regions, featuring different wave modes and levels of compressibility, have distinct identifying signatures detectable by PSP. The leading Alfvén wave front and its immediate wake are characterized by transAlfvénic plasma flows with mild density enhancements. This front exhibits characteristics of a fast switch-on MHD shock, whose arrival is signaled by the sudden onset of large-amplitude transverse velocity and magnetic-field oscillations highly correlated in space and time. The trailing portion is characterized by supersonic but subAlfvénicout flows of dense plasma with uncorrelated velocity and magnetic-field oscillations. This compressible region contains most of the jet's mass. The volume between the immediate wake and dense jet, the remote wake,mixes and transitions the characteristics of the two other regions. In addition to probing each region separately, we also simulate a corotational PSP-jet encounter. In this scenario, the simulated spacecraft hovers over the jet producing CH, as may occur during the mission's corotational phases, sampling each jet region in turn. We estimate that PSP will encounter numerous CH jets over the lifetime of the mission.

Roberts, Merrill A.↗