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122 records · Page 7

Remote Sensing of Tropical Ecosystems: Atmospheric Correction and Cloud Masking Matter

Tropical rainforests are significant contributors to the global cycles of energy, water and carbon. As a result, monitoring of the vegetation status over regions such as Amazonia has been a long standing interest of Earth scientists trying to determine the effect of climate change and anthropogenic disturbance on the tropical ecosystems and its feedback on the Earth's climate. Satellite-based remote sensing is the only practical approach for observing the vegetation dynamics of regions like the Amazon over useful spatial and temporal scales, but recent years have seen much controversy over satellite-derived vegetation states in Amazônia, with studies predicting opposite feedbacks depending on data processing technique and interpretation. Recent results suggest that some of this uncertainty could stem from a lack of quality in atmospheric correction and cloud screening. In this paper, we assess these uncertainties by comparing the current standard surface reflectance products (MYD09, MYD09GA) and derived composites (MYD09A1, MCD43A4 and MYD13A2 - Vegetation Index) from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite to results obtained from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. MAIAC uses a new cloud screening technique, and novel aerosol retrieval and atmospheric correction procedures which are based on time-series and spatial analyses. Our results show considerable improvements of MAIAC processed surface reflectance compared to MYD09/MYD13 with noise levels reduced by a factor of up to 10. Uncertainties in the current MODIS surface reflectance product were mainly due to residual cloud and aerosol contamination which affected the Normalized Difference Vegetation Index (NDVI): During the wet season, with cloud cover ranging between 90 percent and 99 percent, conventionally processed NDVI was significantly depressed due to undetected clouds. A smaller reduction in NDVI due to increased aerosol levels was observed during the dry season, with an inverse dependence of NDVI on aerosol optical thickness (AOT). NDVI observations processed with MAIAC showed highly reproducible and stable inter-annual patterns with little or no dependence on cloud cover, and no significant dependence on AOT (p less than 0.05). In addition to a better detection of cloudy pixels, MAIAC obtained about 20-80 percent more cloud free pixels, depending on season, a considerable amount for land analysis given the very high cloud cover (75-99 percent) observed at any given time in the area. We conclude that a new generation of atmospheric correction algorithms, such as MAIAC, can help to dramatically improve vegetation estimates over tropical rain forest, ultimately leading to reduced uncertainties in satellite-derived vegetation products globally.

tropical ecosystems↗

Integration of Omics into a New Comprehensive Rate Law for Competitive Terminal Electron-Accepting Processes in Reactive Transport Models: Application to N, Fe, S, and Contaminant Transformations in Stream and Wetland Sediments

Surface waters represent important sources of alternate energy and drinking water in the United States, and characterizing the biogeochemical processes that affect surface water quality is relevant to the DOE-BER mission. Sediment biogeochemical processes regulate the release of carbon (C), nutrients, and contaminants to surface waters and thus influence water quality. Sediment biogeochemical processes are dynamic and affected by the deposition and remobilization of solid material and changes in environmental conditions driven by water discharge variations. Wetlands are important natural filters of surface waters which may either trap, metabolize, or mobilize nutrients and contaminants. Despite their importance, biogeochemical processes regulating nutrient and contaminant release and C transformation in stream and wetland sediments cannot be predicted accurately by current mathematical models. These reactive transport models largely rely on detectable changes in geochemical conditions to activate metabolic processes, do not accurately account for the competition between microbial processes, and poorly constrain effects of hydrological perturbations on biogeochemical processes. In this BER-SBR exploratory project, metagenomic and geochemical signatures were combined to identify microbially-mediated redox processes in anaerobic stream and wetland sediments from the Savannah River Site (SRS, ANL SFA) and East Fork Poplar Creek (EFPC, ORNL SFA) that play important roles in C, uranium (U), and mercury (Hg) transformations. In addition, sediment incubations were conducted to examine the competition between anaerobic respiration processes Finally, new rate laws were developed for reactive transport models that rely on complementary metagenomic and geochemical signatures to identify the underlying anaerobic microbial processes in stream and wetland sediments, describe the competition between the dominant metabolic processes involved in nutrient release and U and Hg mobilization, and more accurately quantify carbon transformation and the response of microbial processes to changes in redox conditions associated with hydrological forcing. These rate laws were optimized in batch reactors with SRS wetland sediments, where iron and sulfate reduction dominate. Anaerobic carbon remineralization processes followed the expected thermodynamic sequence of microbial respiration with depth in both sediments, except that geochemical signals indicated that sulfate reduction was inactive in EFPC sediments and moderate in SRS wetland sediments. Estimates indicated that microbial iron reduction contributed to at least half of the production of reduced iron in these sediments. Incubations demonstrated that nitrate reduction, denitrification, and dissimilatory nitrate reduction to ammonium were active in the natural EFPC sediment and activated upon nitrate amendment in these nitrate-rich sediments. In turn, these processes were outcompeted by the addition of either iron oxides or sulfate as alternative terminal electron acceptors. Although geochemical products of sulfate reduction were not detected in the incubations, the abundance of sulfate reduction genes increased with depth in the sediment and was equally more pronounced in treatments amended with either iron oxides or sulfate. Simultaneously, anaerobic sulfide oxidizing bacteria coupling sulfide oxidation to DNRA (and not conventional denitrification) were apparently enriched over time, regardless of the treatments. These findings indicate that sulfate reduction is important in freshwater stream sediments and probably catalyzed by a cryptic sulfur cycle involving nitrogen species, in which the sulfur products from sulfate reduction are immediately removed by side reactions and not detectable by geochemical measurements alone. Similar experiments in SRS sediments, however, demonstrated little interaction between nitrogen and sulfur cycling microorganisms. Sulfate reduction was impacted by the addition of more thermodynamically favorable electron acceptors, suggesting either that iron-reducing microorganisms outcompeted sulfate-reducing microorganisms for organic substrate, depleting the stock of electron donor available for sulfate reduction, or that the cryptic sulfur cycle was shunted by the precipitation of FeS generated as a result of the abiotic reduction of iron oxides by dissolved sulfide. A diagnostic modeling exercise was conducted to further investigate the competition between terminal electron accepting processes. As conventional kinetic models typically do not account for cryptic cycles and used inaccurate formulations to describe competition between microbial communities, new metabolic rate laws were developed that explicitly express the electron acceptor-specific enzyme of each energetically favorable metabolic process based on gene abundance detected in the incubations. The model was tested with the sediment slurry incubation data to determine whether substrate competition could explain the decrease in sulfate reduction observed in the presence of iron oxide competitor. The model was able to reproduce geochemical concentrations really well in each treatment once the model was calibrated with the unamended control, suggesting that microbial competition was indeed driven by thermodynamic considerations. Overall, carbon remineralization processes and rates will be reproduced much more realistically with the new metabolic rate laws.

54 ENVIRONMENTAL SCIENCES↗

Software Testbed for Developing and Evaluating Integrated Autonomous Subsystems

To implement fault tolerant autonomy in future space systems, it will be necessary to integrate planning, adaptive control, and state estimation subsystems. However, integrating these subsystems is difficult, time-consuming, and error-prone. This paper describes Intelliface/ADAPT, a software testbed that helps researchers develop and test alternative strategies for integrating planning, execution, and diagnosis subsystems more quickly and easily. The testbed's architecture, graphical data displays, and implementations of the integrated subsystems support easy plug and play of alternate components to support research and development in fault-tolerant control of autonomous vehicles and operations support systems. Intelliface/ADAPT controls NASA's Advanced Diagnostics and Prognostics Testbed (ADAPT), which comprises batteries, electrical loads (fans, pumps, and lights), relays, circuit breakers, invertors, and sensors. During plan execution, an experimentor can inject faults into the ADAPT testbed by tripping circuit breakers, changing fan speed settings, and closing valves to restrict fluid flow. The diagnostic subsystem, based on NASA's Hybrid Diagnosis Engine (HyDE), detects and isolates these faults to determine the new state of the plant, ADAPT. Intelliface/ADAPT then updates its model of the ADAPT system's resources and determines whether the current plan can be executed using the reduced resources. If not, the planning subsystem generates a new plan that reschedules tasks, reconfigures ADAPT, and reassigns the use of ADAPT resources as needed to work around the fault. The resource model, planning domain model, and planning goals are expressed using NASA's Action Notation Modeling Language (ANML). Parts of the ANML model are generated automatically, and other parts are constructed by hand using the Planning Model Integrated Development Environment, a visual Eclipse-based IDE that accelerates ANML model development. Because native ANML planners are currently under development and not yet sufficiently capable, the ANML model is translated into the New Domain Definition Language (NDDL) and sent to NASA's EUROPA planning system for plan generation. The adaptive controller executes the new plan, using augmented, hierarchical finite state machines to select and sequence actions based on the state of the ADAPT system. Real-time sensor data, commands, and plans are displayed in information-dense arrays of timelines and graphs that zoom and scroll in unison. A dynamic schematic display uses color to show the real-time fault state and utilization of the system components and resources. An execution manager coordinates the activities of the other subsystems. The subsystems are integrated using the Internet Communications Engine (ICE). an object-oriented toolkit for building distributed applications.

Testbed↗

Enabling a Larger Deep Space Mission Suite: A Deep Space Network Queuing Antenna for Demand Access

The advent of deep space small spacecraft, as exemplified by the Mars Cubesat One (MarCO), Lunar Trailblazer, Janus, the Escape and Plasma Acceleration and Dynamics Explorers (EscaPADE), and the thirteen Artemis 1 missions, opens the possibility that a much larger number of deep space spacecraft may be launched over the next 10 years and beyond. While scientifically exciting, the prospect of a (much) larger mission suite raises significant challenges for the current approach to ground stations and mission operations. We have been investigating an integrated approach for ground stations and missions operations to enable new modes of operation while maintaining the capabilities of the current operational techniques. This integrated approach is built around three core capabilities: (1) A queuing antenna that enables monitoring the status of a much larger number of spacecraft, and allows spacecraft to transmit requests for telemetry with NASA’s Deep Space Network (DSN); (2) a flexible scheduling system that expands the current DSN scheduling services to enable allocating time on DSN antennas in near real-time; and (3) a cloud-based ground data system that can be spun up and down according to how tracks are assigned by the flexible scheduling system. We shall show that an 18 meter DSN queuing antenna equipped with cyrogenic receivers would enable use of the DSN Demand Access Service for small spacecraft throughout the inner Solar System, thus providing service to a large mission suite. We first discuss the architecture of the queuing antenna and its supporting systems, including, for instance, the service required to generate the schedule for the queueing antenna (which dictates how it slews to monitor multiple spacecraft in a day of operations). Next, we describe the signaling scheme used to encode a request, which is inherited from the already operational DSN Beacon Tone Service, and describe two alternative ways to detect the incoming tone at the ground station, one based on maximum likelihood estimation (MLE), and another one based on Fast-Fourier Transfer (FFT) processing. We then use these results to estimate the maximum range at which a request can be reliably detected as a function of the spacecraft and ground station communication capabilities. Finally, the last part of this part of this paper briefly describes the prototyping effort undertaken at Morehead State University (MSU) and JPL to demonstrate the viability of this new DSN demand access. In particular, we describe the suite of tests conducted using MSU’s 21 meter ground station to validate its use a queuing antenna.

Mattle, Emily↗

Signatures of Thermoreversible Associations in X-ray and Neutron Scattering from Dilute Polyzwitterion Solutions

In aqueous solutions of polyzwitterions (PZs), an interplay between dipole–dipole interactions and hydration of zwitterionic groups can lead to thermoreversible associations, which have been difficult to detect in experiments. Here, in this study, we investigated dilute aqueous solutions of poly(1-(3-sulphonatopropyl)-2-vinylpyridinium) (P2VPPS) using small-angle X-ray and neutron scattering (SAXS and SANS) to probe the structure and neutron spin-echo (NSE) spectroscopy to probe dynamics. The SAXS and SANS data show that the correlation length increases with an increase in the concentration of P2VPPS for three different molecular weights. The addition of 0.1 M NaCl to one of the solutions led to almost no dependence of the correlation length on the concentration. Such a concentration dependence of the correlation length suggests the formation of clusters driven by thermoreversible associations in the solutions. The NSE measurements show that the solutions with a larger correlation length display slower relaxation, reflecting the reduced mobility of larger clusters. These results should be considered as signatures of thermoreversible associations in the solutions of P2VPPS. To establish a quantitative link between local structure (clusters) and dynamics in dilute solutions of P2VPPS, we combined a thermoreversible gelation theory for the structure of PZ solutions (Li, S.-F.; Muthukumar, M. Theory of Thermoreversible Gelation and Anomalous Concentration Fluctuations in Polyzwitterion Solutions. J. Chem. Phys. 2024, 161, 024903) with a model for the dynamics of the clusters (generalized Zimm model), developed in this work. Using such a theoretical framework, we have predicted the distribution of clusters in the solutions probed with SANS and SAXS. With the distributions, the generalized Zimm model has been used to extract the diffusion constant of the clusters and their characteristic size from the NSE data, where the latter agrees with the values estimated from the SAXS/SANS data. These findings confirm the presence of thermoreversible associations and establish a quantitative link between local structure (clusters) and dynamics in dilute solutions of P2VPPS. Furthermore, with growing interest in technological applications, this work can provide useful insights into the structural and dynamical properties of other PZ solutions.

field theory↗

Dynamical Model for the Zodiacal Cloud and Sporadic Meteors

The solar system is dusty, and would become dustier over time as asteroids collide and comets disintegrate, except that small debris particles in interplanetary space do not last long. They can be ejected from the solar system by Jupiter, thermally destroyed near the Sun, or physically disrupted by collisions. Also, some are swept by the Earth (and other planets), producing meteors. Here we develop a dynamical model for the solar system meteoroids and use it to explain meteor radar observations. We find that the Jupiter Family Comets (JFCs) are the main source of the prominent concentrations of meteors arriving to the Earth from the helion and antihelion directions. To match the radiant and orbit distributions, as measured by the Canadian Meteor Orbit Radar (CMOR) and Advanced Meteor Orbit Radar (AMOR), our model implies that comets, and JFCs in particular, must frequently disintegrate when reaching orbits with low perihelion distance. Also, the collisional lifetimes of millimeter particles may be longer (approx. > 10(exp 5) yr at 1 AU) than postulated in the standard collisional models (approx 10(exp 4) yr at 1 AU), perhaps because these chondrule-sized meteoroids are stronger than thought before. Using observations of the Infrared Astronomical Satellite (IRAS) to calibrate the model, we find that the total cross section and mass of small meteoroids in the inner solar system are (1.7-3.5) 10(exp 11) sq km and approx. 4 10(exp 19) g, respectively, in a good agreement with previous studies. The mass input required to keep the Zodiacal Cloud (ZC) in a steady state is estimated to be approx. 10(exp 4)-10(exp 5) kg/s. The input is up to approx 10 times larger than found previously, mainly because particles released closer to the Sun have shorter collisional lifetimes, and need to be supplied at a faster rate. The total mass accreted by the Earth in particles between diameters D = 5 micron and 1 cm is found to be approx 15,000 tons/yr (factor of 2 uncertainty), which is a large share of the accretion flux measured by the Long Term Duration Facility (LDEF). Majority of JFC particles plunge into the upper atmosphere at <15 km/s speeds, should survive the atmospheric entry, and can produce micrometeorite falls. This could explain the compositional similarity of samples collected in the Antarctic ice and stratosphere, and those brought from comet Wild 2 by the Stardust spacecraft. Meteor radars such as CMOR and AMOR see only a fraction of the accretion flux (approx 1- 10% and approx 10-50%, respectively), because small particles impacting at low speeds produce ionization levels that are below these radars detection capabilities.

Nesvorny, David↗

Formation and detection of metastable formic acid in a supersonic expansion: High resolution infrared spectroscopy of the jet-cooled cis -HCOOH conformer

High-resolution direct absorption infrared spectra of metastable cis-formic acid (HCOOH) trapped in a cis-well resonance behind a 15 kcal/mol barrier are reported for the first time, with the energetically unstable conformer produced in a supersonic slit plasma expansion of trans-formic acid/H 2 mixtures. We present a detailed high-resolution rovibrational analysis for cis-formic acid species in the OH stretch (ν 1 ) fundamental, providing first precision vibrational band origin, rotational constants, and term values, which in conjunction with ab initio calculations at the couple-cluster with single, double, and perturbative triple [CCSD(T)]/ANOn (n = 0, 1, 2) level support the experimental assignments and establish critical points on the potential energy surface for internal rotor trans-to-cis isomerization. Relative intensities for a- and b-type transitions observed in the spectra permit the transition dipole moment components to be determined in the body fixed frame and prove to be in good agreement with ab initio CCSD(T) theoretical estimates but in poor agreement with simple bond-dipole predictions. As a result, the observed signal dependence on H 2 in the discharge suggests the presence of a novel H atom radical chemical mechanism for strongly endothermic “up-hill” internal rotor isomerization between trans- and cis-formic acid conformers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Application of Fault Management Theory to the Quantitative Selection of a Launch Vehicle Abort Trigger Suite

The theory of System Health Management (SHM) and of its operational subset Fault Management (FM) states that FM is implemented as a "meta" control loop, known as an FM Control Loop (FMCL). The FMCL detects that all or part of a system is now failed, or in the future will fail (that is, cannot be controlled within acceptable limits to achieve its objectives), and takes a control action (a response) to return the system to a controllable state. In terms of control theory, the effectiveness of each FMCL is estimated based on its ability to correctly estimate the system state, and on the speed of its response to the current or impending failure effects. This paper describes how this theory has been successfully applied on the National Aeronautics and Space Administration's (NASA) Space Launch System (SLS) Program to quantitatively estimate the effectiveness of proposed abort triggers so as to select the most effective suite to protect the astronauts from catastrophic failure of the SLS. The premise behind this process is to be able to quantitatively provide the value versus risk trade‐off for any given abort trigger, allowing decision makers to make more informed decisions. All current and planned crewed launch vehicles have some form of vehicle health management system integrated with an emergency launch abort system to ensure crew safety. While the design can vary, the underlying principle is the same: detect imminent catastrophic vehicle failure, initiate launch abort, and extract the crew to safety. Abort triggers are the detection mechanisms that identify that a catastrophic launch vehicle failure is occurring or is imminent and cause the initiation of a notification to the crew vehicle that the escape system must be activated. While ensuring that the abort triggers provide this function, designers must also ensure that the abort triggers do not signal that a catastrophic failure is imminent when in fact the launch vehicle can successfully achieve orbit. That is, the abort triggers must have low false negative rates to be sure that real crew‐threatening failures are detected, and also low false positive rates to ensure that the crew does not abort from non‐crew‐threatening launch vehicle behaviors. The analysis process described in this paper is a compilation of over six years of lessons learned and refinements from experiences developing abort triggers for NASA's Constellation Program (Ares I Project) and the SLS Program, as well as the simultaneous development of SHM/FM theory. The paper will describe the abort analysis concepts and process, developed in conjunction with SLS Safety and Mission Assurance (S&MA) to define a common set of mission phase, failure scenario, and Loss of Mission Environment (LOME) combinations upon which the SLS Loss of Mission (LOM) Probabilistic Risk Assessment (PRA) models are built. This abort analysis also requires strong coordination with the Multi‐Purpose Crew Vehicle (MPCV) and SLS Structures and Environments (STE) to formulate a series of abortability tables that encapsulate explosion dynamics over the ascent mission phase. The design and assessment of abort conditions and triggers to estimate their Loss of Crew (LOC) Benefits also requires in‐depth integration with other groups, including Avionics, Guidance, Navigation and Control(GN&C), the Crew Office, Mission Operations, and Ground Systems. The outputs of this analysis are a critical input to SLS S&MA's LOC PRA models. The process described here may well be the first full quantitative application of SHM/FM theory to the selection of a sensor suite for any aerospace system.

Lo, Yunnhon↗

Optimizing infrasound observations for sample return capsule re-entry: Insights from OSIRIS-REx and Hayabusa2

The atmospheric entry of meteoroids presents a rare and unpredictable phenomenon, posing challenges for systematic observation and detailed characterization. Such events are nonetheless critical for advancing understanding of acoustic wave propagation, atmospheric structure, and entry dynamics. In contrast, sample return capsules (SRCs) from space missions follow well constrained re-entry trajectories, enabling planned observations of shock wave generation and propagation under controlled conditions. This study compares two SRC atmospheric entries, Hayabusa2 in 2020 and OSIRIS-REx in 2023, to assess how different infrasound array configurations influence shock wave detection and trajectory validation. Hayabusa2’s re-entry was monitored using a distributed network of 28 portable infrasound sensors across seven arrays in Woomera, Australia, permitting three-dimensional reconstruction of the trajectory and analysis of wave characteristics. For OSIRIS-REx, a compact four-sensor array deployed near Eureka Airport provided trajectory confirmation through arrival-time differences and back-azimuth estimates. Spectral and waveform analyses revealed differences in signal properties associated with variations in entry angle and velocity. The results illustrate both the strengths and the limitations of the deployed array configurations. The dense and distributed arrays during Hayabusa2’s re-entry enabled detailed trajectory reconstruction, whereas the compact array at Eureka primarily provided confirmation of signal coherence and back-azimuth consistency. These case studies highlight that even relatively small arrays, if located close to the predicted ground track, can still capture useful information on arrival direction and timing. Such insights provide practical guidance for planning future observational campaigns of SRC returns and other controlled atmospheric entries, and may also inform approaches to opportunistic observations of meteoroid events and other atmospheric acoustic phenomena.

celestial mechanics: orbit determination↗

Application of X-Ray Pulsar Navigation: A Characterization of the Earth Orbit Trade Space

The potential for pulsars as a navigation source has been studied since their discovery in 1967. X-ray pulsar navigation (XNAV) is a celestial navigation system that uses the consistent timing nature of x-ray photons from milli-second pulsars (MSP) to perform space navigation. By comparing the detected arrival of x-ray photons to a reference database of expected pulsar lightcurve timing models, one can infer a range and range rate measurement based on light time delay. Much of the challenge of XNAV comes from the faint signal, availability, and distant nature of pulsars. This is a study of potential pulsar XNAV measurements to measure extended Kalman filter (EKF) tracking performance with a wide trade space of bounded Earth orbits, using a simulation of existing x-ray detector space hardware. An example of an x-ray detector for XNAV is the NASA Station Explorer for X-ray Timing and Navigation (SEXTANT) mission, a technology demonstration of XNAV set to perform on the International Space Station (ISS) in late 2016early 2017. XNAV hardware implementation is driven by trajectory and environmental influences which add noise to the x-ray pulse signal. In a closed Earth orbit, the radiation environment can exponentially increase the signal noise from x-ray pulsar sources, decreasing the quality and frequency of measurements. The SEXTANT mission in particular improves on the signal to noise ratio by focusing an array of 56 x-ray silicon drift detectors at one pulsar target at a time. This reduces timing glitches and other timing noise contributions from ambient x-ray sources to within a 100 nanosecond resolution. This study also considers the SEXTANT scheduling challenges inherent in a single target observation. Finally, as the navigation sources are now relatively inertial targets, XNAV measurements are also subject to periods of occultation from various celestial bodies. This study focuses on the characterization of these drivers in closed Earth orbits and is not a tuning analysis of the EKF. The study shows that the closed Earth orbit for XNAV performance is reliant on the orbit semi-major axis and eccentricity as well as orbit inclination. These parameters are the primary drivers of pulsar measurement availability and significantly influence the natural spacecraft orbit dynamics. Sensitivity to initial orbit determination error growth due to the scarcity of XNAV measurements within an orbital period require appropriate timing of initial XNAV measurements. The orbit angles of argument of perigee and right ascension of the ascending node, alongside the other orbit parameters, complete the initial cadence of XNAV measurements. The performance of initial XNAV measurements then propagates throughout the experimental period. The study provides a basis to missions who wish to consider XNAV as a potential navigation source in a closed Earth orbit design. It provides a family of orbit trajectories as well as other modeling considerations needed to effectively evaluate if XNAV is an effective navigation source for a potential mission. As an EKF is sensitive to a linearized estimated state, this study has a direct benefit of providing effective XNAV measurements to maintain spacecraft tracking, independent of other navigation sources. In the particular use case of the SEXTANT mission, it also provides a novel scheduling algorithm which addresses the need to prioritize and manage pulsar observations for effective navigation.

PULSAR↗

Application of X-Ray Pulsar Navigation: A Characterization of the Earth Orbit Trade Space

The potential for pulsars as a navigation source has been studied since their discovery in 1967. X-ray pulsar navigation (XNAV) is a celestial navigation system that uses the consistent timing nature of x-ray photons from millisecond pulsars (MSP) to perform space navigation. By comparing the detected arrival of x-ray photons to a reference database of expected pulsar light-curve timing models, one can infer a range and range rate measurement based on light time delay. Much of the challenge of XNAV comes from the faint signal, availability, and distant nature of pulsars. This is a study of potential pulsar XNAV measurements to measure extended Kalman filter (EKF) tracking performance with a wide trade space of bounded Earth orbits, using a simulation of existing x-ray detector space hardware. An example of an x-ray detector for XNAV is the NASA Station Explorer for X-ray Timing and Navigation (SEXTANT) mission, a technology demonstration of XNAV set to perform on the International Space Station (ISS) in late 2016early 2017. XNAV hardware implementation is driven by trajectory and environmental influences which add noise to the x-ray pulse signal. In a closed Earth orbit, the radiation environment can exponentially increase the signal noise from x-ray pulsar sources, decreasing the quality and frequency of measurements. The SEXTANT mission in particular improves on the signal to noise ratio by focusing an array of 56 x-ray silicon drift detectors at one pulsar target at a time. This reduces timing glitches and other timing noise contributions from ambient x-ray sources to within a 100 nanosecond resolution. This study also considers the SEXTANT scheduling challenges inherent in a single target observation. Finally, as the navigation sources are now relatively inertial targets, XNAV measurements are also subject to periods of occultation from various celestial bodies. This study focuses on the characterization of these drivers in closed Earth orbits and is not a tuning analysis of the EKF. The study shows that the closed Earth orbit for XNAV performance is reliant on the orbit semi-major axis and eccentricity as well as orbit inclination. These parameters are the primary drivers of pulsar measurement availability and significantly influence the natural spacecraft orbit dynamics. Sensitivity to initial orbit determination error growth due to the scarcity of XNAV measurements within an orbital period require appropriate timing of initial XNAV measurements. The orbit angles of argument of perigee and right ascension of the ascending node, alongside the other orbit parameters, complete the initial cadence of XNAV measurements. The performance of initial XNAV measurements then propagates throughout the experimental period. The study provides a basis to missions who wish to consider XNAV as a potential navigation source in a closed Earth orbit design. It provides a family of orbit trajectories as well as other modeling considerations needed to effectively evaluate if XNAV is an effective navigation source for a potential mission. As an EKF is sensitive to a linearized estimated state, this study has a direct benefit of providing effective XNAV measurements to maintain spacecraft tracking, independent of other navigation sources. In the particular use case of the SEXTANT mission, it also provides a novel scheduling algorithm which addresses the need to prioritize and manage pulsar observations for effective navigation.

x-ray↗

Final Report DE-FE0031785 Mohsen Ahmadian, Ph.D. Demonstration of Proof of Concept of a Multiphysics Approach for Real-Time Remote Monitoring of Dynamic Changes in Pressure and Salinity in Hydraulically Fractured Networks

Hydraulic fracturing has evolved into a multistep process with varying flow rates, carrier fluids (e.g., gel or slickwater), proppant loadings, and proppant grain sizes. As a result, primary recovery from a hydraulically fractured tight-oil reservoir is often a tiny fraction of the original oil in place, ranging between 5 and 10%. As stated in the FOA1990, “part of this problem is due to the inability of current well completion processes to effectively stimulate the entire reservoir volume in contact with the wellbore. Innovative technologies are needed that can help improve the effectiveness of reservoir completion methods, maximize stimulated reservoir volumes, and optimize recovery over the entire producing life span of a well”. We first need to enhance the current fracture diagnostic techniques to improve a well-completion design. However, detecting and delineating a subsurface hydraulic fracture is extremely difficult because the induced fracture network is only fractionally propped, and these propped fractures are generally very thin. Microseismic and tiltmeter monitoring techniques can provide information on the fracture extent but provide little or no information on the movement and final distribution of proppant or production fluids. On the other hand, electromagnetic (EM) imaging has shown the capability to monitor proppant distribution throughout the fracture area, especially in the presence of Electrically Active Proppants (EAPs). A previous EM survey of hydraulic fracturing at the Devine Fracture Pilot Site (DFPS) and subsequent EM code developments demonstrated this survey as a robust technique to remotely interrogate the extent of the EAP-filled hydraulic fracture during its propagation. The objectives of the project were threefold: (1) to capitalize on the material properties of an EAP to demonstrate remote monitoring of relative changes in pressure, pressure, and flow that are commonly encountered during production from a hydraulically fractured reservoir; (2) to evaluate EM imaging tools, to achieve Objective 1 in near real-time; and (3) to develop a multi-physics joint inversion approach to precisely predict flow patterns and physiochemical changes within an EAP-filled fracture network. This research project was built upon our previous work at the Devine Test Site managed by the Bureau of Economic Geology (BEG) at The University of Texas at Austin (UT-Austin). It also leveraged a significant investment from the Advanced Energy Consortium (AEC) to address the DOE's interest in subsurface flow, containment, and characterization by multiple signals. This three-year and three-month project succeeded in demonstrating the feasibility of a real-time dynamic fluid flow mapping technique at Technology Readiness Level 5 (TRL5) by utilizing a commercially available surface-based Controlled-Source Electromagnetic (CSEM) method (Objectives 1, 2). We demonstrated that injections into an EAP-filled fracture could be successfully coupled with real-time electric field measurements on the surface, leading to remote monitoring of dynamic changes within the EAP-filled fracture. Furthermore, the observed electric field in our study is influenced by bottomhole pressure, flow rate, and salinity, which is demonstrated by comparing these parameters with the electrical field potentials. EM simulations solely based on assumptions of fracture conductivity changes during injection did not reproduce the whole measured electric field magnitudes. Preliminary estimates showed that including Streaming Potential (SP) in our geophysical model is likely needed to reduce the simulation misfit.

02 PETROLEUM↗

Videos, photos, and AI-derived grain size data associated with “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization” under review. This data package includes five data types: 1) raw photos and videos from drone survey and walking smartphone surveys; 2) images derived from raw videos; 3) manual labeling of reference scales; 4) metadata for all images and photo resolution derived from artificial intelligence (AI) models or manual labels, 5) grain size data obtained from AI models for all photos, 6) metadata and grain size data after quality control, 7) summaries of sample efficiency for all data, and 8) computational fluid dynamics (CFD) data used to support hydro-biogeochemical (HBGC) parameter estimation. Such data is used to 1) demonstrate significant improvements in accuracy, efficiency, and quality control for grain size data collection with the help of AI models, 2) study the spatial heterogeneity of grain size and observation reproducibility based on tens of thousands of data points generated by the AI models, and 3) evaluate the impacts of grain size heterogeneity on key HBGC parameters across sediment-to-reach and hourly-to-yearly scales. In particular, the data package contains 116 folders and 179696 files. The files include 41 videos in .mov format, 64047 photos in .jpg format, 13541 video-derived photos in .png format, 12747 segmentation mask data in .tif format, 12747 segmentation data in .json format, 24771 .csv files that with metadata and grain size for each individual photo as well as water depth and velocity data from CFD and observation, 51791 .txt files of raw AI predicted labels, and 11 flight record data in .srt format. The summary for all metadata and grain size statistics information is included in “Scales_V3_NG.csv” and “Statistics_V3_NG.csv”. The summary for data that pass data quality control (QC) level 0-2 is included in “QCStatistics_V3_NG.csv”. The QC level 0 represents photos whose photo resolution is positive, excluding photos that miss reference scale. The QC level 1 means reference scale circularity uncertainty is less than 5% for smartphone images while representing photo resolution is larger than 0.44 mm/pixel for drone images. The QC level 2 means excluding photos whose grain number is less than 100, a minimum number of grains recommended by classic literature. The summary for each video’s name, length, frame rates, survey area, grain number, survey efficiency, etc. can be found in “QCSummary_V3_NG.csv”. The summary for site name, GPS coordinates, and number of images at each site can be found in “SitesSummary_V3_*.csv” files. Overall computational efficiency summary is reported in Table 4 of accompanying manuscript. Additionally, the nitrate concentration data used in this work was downloaded from an existing dataset published on ESS-DIVE (Boat-Dragged Sensor Hanford Reach.csv; Conner A. et al., 2020). We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Port of Benton, and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the data were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate data collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗