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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2019

Earth Science Technology Office (ESTO) New Observing Strategies (NOS) and NOS-Testbed (NOS-T)

With the advancement of space hardware technologies such as smaller spacecraft, component and instrument miniaturization and high performance space processors, and with the advancement of software technologies in artificial intelligence, big data analysis and autonomous decision making, Earth Science is looking at novel ways to observe phenomena that previously could not have been studied or would have been too expensive to study with traditional missions. In particular, the New Observing Strategies (NOS) component of the NASA Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST) Program aims at leveraging these novel technologies as well as low cost and easy access to space to acquire multi-temporal or simultaneous multi-angular, multi-locations, multi-resolution and multi-spectral observations that will provide better multi-source measurements and will build a more dynamic and comprehensive picture of Earth Science phenomena that need to be studied and analyzed. For applications such as water resources management, air quality monitoring, biodiversity studies or disaster management, NOS will integrate the use of small instruments, small spacecraft, constellations of spacecraft and networks of sensors to design new missions that will provide the necessary measurements to improve future forecast and science modeling systems.Measurement acquisition will therefore be approached as a system of systems rather than on a mission basis, and a system of this complexity should not be expected to work without full integration and experimental characterization. Although most of the individual technologies enabling to link and coordinate multi-source observations are more or less mature, a few technologies need to be developed and all of them need to be integrated and tested as a system. In order for this validation to occur, the AIST Program is developing the NOS Testbed that includes 3 main goals:1.Validate novel NOS technologies, independently and as a system2.Demonstrate novel distributed operations concepts3.Socialize new Distributed Spacecraft Mission (DSM) and SensorWeb (SW) technologies and concepts to the science community by significantly retiring the risk of integrating these new technologies.The NOS Testbed will consist of multiple sensing nodes, simulated or actual, representing space, air and/or ground measurements, that are interconnected by a communications fabric (infrastructure that permits nodes to transmit and receive data between one another and interact with each other). Each node will be supported by hardware capabilities required to perform nodes monitoring and command & control, as well as intelligent "onboard" computing. The nodes will work together in a collaborative manner to demonstrate optimal science capabilities. The testbed will enable to validate technologies such as inter-node communication models, techniques and protocols; inter-node coordination; real-time data fusion and understanding; planning; sensor re-targeting; etc. Additionally, the testbed will have the capability to interact with various mission design tools, OSSEs and one or several forecast models. More details about the NOS Testbed will be presented at the confererence.

Earth Science missions; Advanced information Syste↗
NASA NTRSDate not supplied

Computational investigation on the combined effect of pore attributes on strain concentrators in metal additively manufactured materials

Metal additive manufacturing provides a pathway for creating highly optimized components. However, porosity continues to be a prevalent issue for fatigue performance despite best efforts in optimizing process parameters and postprocessing techniques. This work uses finite element analysis to conduct a parametric study to link various pore attributes (i.e., aspect ratio, orientation, and location) to strain concentration factors (SCF) under elastic/plastic deformation during uniaxial loading. Keyhole and lack-of-fusion pores are idealized by prolate and oblate ellipsoids, respectively. Each simulation of the parametric study assumes a single isolated pore in a Ti-6Al-4V material, modeled with J2-plasticity. A reduced-order model is developed to relate pore attributes to SCF, and then used to quantify the variability in SCF for a given experimentally characterized probability distribution of pore attributes. This reduced-order model can be used in a production environment to provide a first-order evaluation to rapidly screen sub-optimally performing components.

Additive Manufacturing↗
NASA NTRS1975

The detection of tightly closed flaws by nondestructive testing (NDT) methods

Liquid penetrant, ultrasonic, eddy current and X-radiographic techniques were optimized and applied to the evaluation of 2219-T87 aluminum alloy test specimens in integrally stiffened panel, and weld panel configurations. Fatigue cracks in integrally stiffened panels, lack-of-fusion in weld panels, and fatigue cracks in weld panels were the flaw types used for evaluation. A 2319 aluminum alloy weld filler rod was used for all welding to produce the test specimens. Forty seven integrally stiffened panels containing a total of 146 fatigue cracks, ninety three lack-of-penetration (LOP) specimens containing a total of 239 LOP flaws, and one-hundred seventeen welded specimens containing a total of 293 fatigue cracks were evaluated. Nondestructive test detection reliability enhancement was evaluated during separate inspection sequences in the specimens in the 'as-machined or as-welded', post etched and post proof loaded conditions. Results of the nondestructive test evaluations were compared to the actual flaw size obtained by measurement of the fracture specimens after completing all inspection sequences. Inspection data were then analyzed to provide a statistical basis for determining the flaw detection reliability.

Rummel, W. D.↗
NASA NTRSDate not supplied

Advancement of Extreme Environment Additively Manufactured Alloys for Next Generation Space Propulsion Applications

The National Aeronautics and Space Administration (NASA) has been involved in the development and maturation of metal additive manufacturing (AM) for space applications since the late 2000’s. Several efforts focused on the understanding of AM processes through material characterization and testing, standards development, component fabrication, and infusion into propulsion development and flight applications. NASA matured commonly used aerospace alloys from various alloy families (Nickel, Copper, Stainless and Steel, Aluminum, and Titanium-based) through detailed AM process and heat treatment characterization, in addition to mechanical and thermophysical testing. While these alloys are actively used in many propulsion applications, there is a need for ongoing AM optimized alloys using integrated computational materials engineering (ICME) and process development for high performance applications. The applications targeted are liquid rocket engines; advanced propulsion systems; and in-space propulsion with high heat fluxes, high pressure, and/or that use propellants that can degrade alloys (e.g., hydrogen). This paper highlights the characterization and physical properties of the more common AM alloys using laser powder bed fusion (L-PBF) and laser powder directed energy deposition (LP-DED) processes. Additionally, this paper discusses some of the ongoing novel alloy development and maturation using AM for use in these harsh environments, such as GRCop42, GRCop-84, NASA HR-1, GRX-810, and C-103. The results from these processes demonstrated that AM could enable rapid development and ongoing efforts for optimized alloys using ICME, yielding higher performances. These alloys have undergone modeling, fundamental metallurgical evaluations, heat treatment studies, detailed microstructure characterization, and mechanical testing campaigns. This, combined with direct application-specific component fabrication and hot-fire testing, enabled the increase of the Technology Readiness Level (TRL) through high duty-cycle testing. A background and overview of these novel AM-enabled alloys and AM processing developments including metallurgical and mechanical property studies is presented here. The latest advancement in the parallel component development and hot-fire testing and future developments for these alloys is also discussed.

Additive Manufacturing↗
NASA NTRSDate not supplied

Advancement of Extreme Environment Additively Manufactured Alloys for Next Generation Space Propulsion Applications

The National Aeronautics and Space Administration (NASA) has been involved in the development and maturation of metal additive manufacturing (AM) for space applications since the late 2000’s. Several efforts focused on the understanding of AM processes through material characterization and testing, standards development, component fabrication, and infusion into propulsion development and flight applications. NASA matured commonly used aerospace alloys from various alloy families (Nickel, Copper, Stainless and Steel, Aluminum, and Titanium-based) through detailed AM process and heat treatment characterization, in addition to mechanical and thermophysical testing. While these alloys are actively used in many propulsion applications, there is a need for ongoing AM optimized alloys using integrated computational materials engineering (ICME) and process development for high performance applications. The applications targeted are liquid rocket engines; advanced propulsion systems; and in-space propulsion with high heat fluxes, high pressure, and/or that use propellants that can degrade alloys (e.g., hydrogen). This paper highlights the characterization and physical properties of the more common AM alloys using laser powder bed fusion (L-PBF) and laser powder directed energy deposition (LP-DED) processes. Additionally, this paper discusses some of the ongoing novel alloy development and maturation using AM for use in these harsh environments, such as GRCop-42, GRCop-84, NASA HR-1, GRX-810, and C-103. The results from these processes demonstrated that AM could enable rapid development and ongoing efforts for optimized alloys using ICME, yielding higher performances. These alloys have undergone modeling, fundamental metallurgical evaluations, heat treatment studies, detailed microstructure characterization, and mechanical testing campaigns. This, combined with direct application-specific component fabrication and hot-fire testing, enabled the increase of the Technology Readiness Level (TRL) through high duty-cycle testing. A background and overview of these novel AM-enabled alloys and AM processing developments including metallurgical and mechanical property studies is presented here. The latest advancement in the parallel component development and hot-fire testing and future developments for these alloys is also discussed.

Additive Manufacturing↗
NASA NTRS2019

Powder Bed Fusion Additive Manufacturing of JBK-75

JBK-75 is an iron-nickel derivative alloy of A-286 that has been of interest to NASA’s propulsion community for use in fuel injectors and other components that are used in hot, corrosive environments. To enable the rapid production of these components in JBK-75, Marshall Space Flight Center has developed parameters for manufacturing fully dense JBK-75 components using powder bed fusion additive manufacturing (PBFAM). These parameters were developed in a two-step development. First, the depth of laser penetration in the powdered material was measured across a spectrum of laser powers to determine the optimal power necessary for generating the desired meltpool depth. The parameter set’s vector-to-vector spacing was then then tailored to guarantee the full densification of the desired area. The results of this development was a readily implementable parameter that produced 99.6% dense material when using a 147W power running at 600mm/s with a 85μm(32%) vector-to-vector spacing.

Jones, Z. C.↗
NASA NTRS2013

Spatial Statistical Data Fusion (SSDF)

As remote sensing for scientific purposes has transitioned from an experimental technology to an operational one, the selection of instruments has become more coordinated, so that the scientific community can exploit complementary measurements. However, tech nological and scientific heterogeneity across devices means that the statistical characteristics of the data they collect are different. The challenge addressed here is how to combine heterogeneous remote sensing data sets in a way that yields optimal statistical estimates of the underlying geophysical field, and provides rigorous uncertainty measures for those estimates. Different remote sensing data sets may have different spatial resolutions, different measurement error biases and variances, and other disparate characteristics. A state-of-the-art spatial statistical model was used to relate the true, but not directly observed, geophysical field to noisy, spatial aggregates observed by remote sensing instruments. The spatial covariances of the true field and the covariances of the true field with the observations were modeled. The observations are spatial averages of the true field values, over pixels, with different measurement noise superimposed. A kriging framework is used to infer optimal (minimum mean squared error and unbiased) estimates of the true field at point locations from pixel-level, noisy observations. A key feature of the spatial statistical model is the spatial mixed effects model that underlies it. The approach models the spatial covariance function of the underlying field using linear combinations of basis functions of fixed size. Approaches based on kriging require the inversion of very large spatial covariance matrices, and this is usually done by making simplifying assumptions about spatial covariance structure that simply do not hold for geophysical variables. In contrast, this method does not require these assumptions, and is also computationally much faster. This method is fundamentally different than other approaches to data fusion for remote sensing data because it is inferential rather than merely descriptive. All approaches combine data in a way that minimizes some specified loss function. Most of these are more or less ad hoc criteria based on what looks good to the eye, or some criteria that relate only to the data at hand.

Braverman, Amy J.↗
NASA NTRS2019

Continuous Electrode Inertial Electrostatic Confinement Fusion

The NIAC Phase I project on Inertial Electrostatic Confinement was a continuation of early stage research that was funded by an NSTRF. The student on the project, Andrew Chap, was funded by the NSTRF from Fall 2013 through the Summer of 2017, and then was funded on the NIAC through the completion of his PhD. A significant amount of work targeting the plasma confinement physics was the focus of his NSTRF, and over the course of that effort he developed a number of analyses and computational tools that leveraged GPU parallelization. A detailed discussion of these models can be found in his dissertation, which has been included as Appendix D in this report. As a requirement for the NSTRF, Andrew's full dissertation was submitted at the end of the program.Having developed the computational tools, a substantial amount of simulation and analyses leveraging those tools were conducted during the Fall of 2017, under the auspices of the NIAC funded research. Much of this work targeted optimization of the confinement fields, investigating their structure and the possible advantages of having them be time-varying. The results of these simulations can also be found in Appendix D.One of the main results from this research is that the density of ions electrostatically confined within the system can indeed be increased by several orders of magnitude by optimizing the radial potential distribution, and by dynamically varying these fields to maintain compressed ion bunches. An electron population can also be confined within the core by a static radial cusped magnetic field,which helps to support a greater ion density within the core. The issue with the confinement mechanism is that as the ion densities are increased toward fusion-relevant levels, the electrostatic forces generated by the confined electron population become so great that the ions are no longer energetic enough to leave the device core. As their excursions into the outer channels are diminished, the mechanism that is used to maintain their non-thermal velocity distributions becomes ineffective, and eventually the ions become fully confined within the core, where they thermalize. A possible fix to the problem comes by discarding the active ion control (a main pillar of the concept)but retaining the structure of the permanent magnet confinement of the electron population. Such cusped field confinement has been the focus of other IEC approaches (e.g. Polywell), but the high transparency of the permanent magnet structure lends itself to better ion extraction and power conversion (a second pillar of the concept). The question then becomes whether any influence on the ion evolution within the core can be achieved to slow the thermalization of the ions. Such approaches have been studied in highly idealized analytic models, but face major criticisms within the literature. While this is a possible path forward, the uncertainty in the approach did not warrant committing NIAC Phase II resources to investigating the concept at this time.

Sedwick, Raymond↗
NASA NTRS2009

NASA Tech Briefs, July 2009

Topics covered include: Dual Cryogenic Capacitive Density Sensor; Hail Monitor Sensor; Miniature Six-Axis Load Sensor for Robotic Fingertip; Improved Blackbody Temperature Sensors for a Vacuum Furnace; Wrap-Around Out-the-Window Sensor Fusion System; Wide-Range Temperature Sensors with High-Level Pulse Train Output; Terminal Descent Sensor Simulation; A Robust Mechanical Sensing System for Unmanned Sea Surface Vehicles; Additive for Low-Temperature Operation of Li-(CF)n Cells; Li/CFx Cells Optimized for Low-Temperature Operation; Number Codes Readable by Magnetic-Field-Response Recorders; Determining Locations by Use of Networks of Passive Beacons; Superconducting Hot-Electron Submillimeter-Wave Detector; Large-Aperture Membrane Active Phased-Array Antennas; Optical Injection Locking of a VCSEL in an OEO; Measuring Multiple Resistances Using Single-Point Excitation; Improved-Bandwidth Transimpedance Amplifier; Inter-Symbol Guard Time for Synchronizing Optical PPM; Novel Materials Containing Single-Wall Carbon Nanotubes Wrapped in Polymer Molecules; Light-Curing Adhesive Repair Tapes; Thin-Film Solid Oxide Fuel Cells; Zinc Alloys for the Fabrication of Semiconductor Devices; Small, Lightweight, Collapsible Glove Box; Radial Halbach Magnetic Bearings; Aerial Deployment and Inflation System for Mars Helium Balloons; Steel Primer Chamber Assemblies for Dual Initiated Pyrovalves; Voice Coil Percussive Mechanism Concept for Hammer Drill; Inherently Ducted Propfans and Bi-Props; Silicon Nanowire Growth at Chosen Positions and Orientations; Detecting Airborne Mercury by Use of Gold Nanowires; Detecting Airborne Mercury by Use of Palladium Chloride; Micro Electron MicroProbe and Sample Analyzer; Nanowire Electron Scattering Spectroscopy; Electron-Spin Filters Would Offer Spin Polarization Greater than 1; Subcritical-Water Extraction of Organics from Solid Matrices; A Model for Predicting Thermoelectric Properties of Bi2Te3; Integrated Miniature Arrays of Optical Biomolecule Detectors; A Software Rejuvenation Framework for Distributed Computing; Kurtosis Approach to Solution of a Nonlinear ICA Problem; Robust Software Architecture for Robots; R4SA for Controlling Robots; Bio-Inspired Neural Model for Learning Dynamic Models; Evolutionary Computing Methods for Spectral Retrieval; Monitoring Disasters by Use of Instrumented Robotic Aircraft; Complexity for Survival of Living Systems; Using Drained Spacecraft Propellant Tanks for Habitation; Connecting Node; and Electrolytes for Low-Temperature Operation of Li-CFx Cells.

Source record↗
NASA NTRS2022

NASA System-Wide Safety Wildland Firefighting Operations Workshop Report

On March 9-11, 2022, NASA’s System-Wide Safety Wildland Firefighting Operations Workshop engaged the broader wildland firefighting management ecosystem in a safety-oriented discussion via a virtual platform. This enabled a better understanding of how NASA and community expertise can be leveraged in the safe development of current and future firefighting systems and operations. The goals of the workshop were to: (1) identify and prioritize the top safety-oriented risks, gaps in capabilities, and emerging technologies to enhance wildland firefighting for both near-term and far-term concepts, with a specific focus on aviation operations and (2) engage the stakeholder community in defining emergent safety-oriented scope, roles, responsibilities, and procedures for agents undergoing increasingly complex wildland firefighting operations in information-rich, but uncertain environments. Workshop participants were solicited from wildland firefighting stakeholders across government, industry, and academia. All levels of government were engaged, as NASA sought attendees from federal, state, local, and tribal government agencies. Industry participants from traditional wildland firefighting domains such as data visualization and equipment manufacturers were invited, and corporate attendees from novel application domains such as aerial robotics and autonomous systems were present as well. The top three findings were as follows: (1) Enhancing situation awareness is a safety priority, especially in the use of aerial assets; (2) Timely access to information along with data fusion and integrated displays will enhance safety-critical decision-making both inside and outside aviation contexts; and (3) Tailorable standards and common operating pictures in the field will enhance inter-agency cooperation in the wildland firefighting lifecycle and enable the optimal use of limited resources such as aerial assets. The workshop helped inform NASA of the relevant safety-related wildland firefighting concerns and aided the broader ecosystem in understanding the potential safety-oriented role NASA might play in this community. Increased engagement with crucial governmental stakeholders (e.g., U.S. Forest Service, CAL FIRE, etc.) along with industry partners in cutting- edge information -centric domains is a fundamental next step. Additionally, the workshop findings will help define the first of a series of operationally challenging demonstrations, held in concert with strategic ecosystem partners, known as the Safety Demonstrator Series for NASA’s System-Wide Safety project. The first demonstration is set in the wildland firefighting application domain and will: (1) examine high risk operational scenarios to reduce their overall risk via services, functions or capabilities that act as risk mitigators (or transfer that risk to automated systems better able to tolerate it) and (2) explore novel tools and technologies that will enhance safety margins by enabling non-traditional or neoteric operational paradigms.

wildland firefighting↗
NASA NTRS2019

Liftoff and Transition Database Generation for Launch Vehicles Using Data-Fusion-Based Modeling

A data fusion technique for merging multiple data sources with differing fidelity and resolution was developed to support the production of aerodynamic line load databases for the Liftoff and Transition (LOT) flight phase of the Space Launch System (SLS). The technique uses a reduced order model based on a high-fidelity line load data set from Computational Fluid Dynamics (CFD) to predict solutions for a much larger solution space. Even higher-fidelity force and moment information (from wind-tunnel tests) is then used to adjust the model. The adjustment uses constrained optimization through the method of Lagrange multipliers in order to minimize the deviation of the line load distribution from the spatially-dense CFD solution, while ensuring that the integrated force and moment values match those observed in physical wind tunnel measurements. Though the wind-tunnel data are operationally-dense (available at many flow conditions), they are spatially coarse (as only the overall forces and moments are available). Conversely, CFD for such complex configurations is expensive, and thus operationally sparse. Data fusion techniques are necessary to make the most efficient use of available information, delivering accurate results within time and resource constraints.

Wignall, T. J.↗
NASA NTRSDate not supplied

The Influence of Heat Treatments on the Microstructure and Tensile Properties of Additively Manufactured Inconel 939

This study investigated the effect of heat treatment variations on the microstructure and tensile properties of laser powder bed fused Inconel 939 manufactured via laser powder bed fusion. Three different heat treatment schedules, all of which comprise stress relief, hot isostatic pressing, solution annealing, and aging, were followed, and resulting changes in microstructure were analyzed using scanning electron microscopy. Tensile tests were conducted on specimens subjected to different heat treatments to evaluate the mechanical properties at room temperature. Microstructural results showed that solution treatment at 1190 °C for 4 h led to better removal of dendritic microstructure, while second-step aging at 850 °C resulted in monomodal distribution of precipitates. However, the second-step aging temperatures from 750 to 800 °C resulted in bi-modal distribution. The optimal heat treatment schedule, which yielded a superior combination of strength and ductility, involved solution treatment at 1190 °C for 4 h and two-step aging at 1000 °C for 6 h and 800 °C for 4 h.

Laser powder bed fusion (L-PBF)↗
NASA NTRS2024

Development of a Data Fusion Methodology for Lineload Aerodynamic Databases for a Launch Vehicle during Liftoff and Transition

The need for databases for the distributed loading on launch vehicles during the early portion of flight necessitates the use of expensive computational flows in regimes where wake effects dominate. While also being expensive, this is a regime that computational tools tend to historically have problems simulating accurately. To help tackle this problem, a method of data fusion to combine computational results to wind tunnel derived force and moment data is developed. Using this method, significant reduction in computational costs and increases in confidence of the final product is possible and has been used to generate several databases for the Space Launch System (SLS) at NASA. While the full details of database generation are not part of this work, the crucial method at its core is developed here. Two SLS geometries are used throughout the work to demonstrate the techniques. These are two of the larger geometries and represent both planned crewed missions to the Moon as well as potential cargo missions to deep space. The method uses principal component analysis (PCA) to generate a reduced ordered model (ROM) to help fill in the full parameter space. Other similar techniques are explored, but were not found to have a significant result on the predictions of the ROM. Because the full number of components are kept to generate the model, this lack of difference is expected. This method is then extended to ensure that predicted surfaces match trusted force and moment data derived from wind tunnel testing. This extension is done by setting up a constrained optimization problem in order to minimize the deviation from the surface resolved computational data while still integrating to the desired values. When generating the constrained optimization problem, a weighting factor to balance these competing needs is introduced. The work compares previously introduced weighting terms from similar work to the proposed terms and shows that the previously used terms do not have as desirable behavior in this flow regime. This method is then expanded by developing a technique to incorporate uncertainty quantification into the developed data fusion methodology. This expansion takes a two pronged approach. One examines transferring the uncertainties in the force and moment database and characterizes how those adjustments change the predicted lineloads. The second looks at model form error and looks how rebuilding the model using slightly different data changes the predictions. These two terms are then combined in order to create an uncertainty model that takes both effects into account. The limitations of the proposed methods is then discussed as well as possible techniques to address these shortcomings.

Launch Vehicles↗
NASA NTRS2004

The Vasimr Engine: Project Status and Recent Accomplishments

The development of the Variable Specific Impulse Magnetoplasma Rocket (VASIMR) was initiated in the late 1970s to address a critical requirement for fast, high-power interplanetary space transportation. While not being a fusion rocket, it nevertheless borrows heavily from that technology and takes advantage of the natural topology of open-ended magnetic systems. In addition to its high power density and high exhaust velocity, VASIMR is capable of "constant power throttling" a feature, which allows in-flight mission-optimization of thrust and specific impulse to enhance performance and reduce trip time. A NASA-led, research team, involving industry, academia and government facilities is pursuing the development of this concept in the United States. The technology can be validated, in the near term, in venues such as the International Space Station, where it can also serve as both a drag compensation device and a plasma contactor for the orbital facility. Other near-Earth applications in the commercial and scientific satellite sectors are also envisioned. This presentation covers the evolution of the VASIMR concept to its present status, as well as recent accomplishments in our understanding of the physics. Approaches and collaborative programs addressing the major technical challenges will also be presented.

ChangDiaz, Franklin R.↗
NASA NTRS2019

Differences Between OCO‐2 and GOME‐2 SIF Products From a Model‐Data Fusion Perspective

Space-borne retrievals of solar-induced chlorophyll fluorescence (SIF) over land surfaces have recently become a resource for studying and quantifying the broad scale dynamics of gross carbon uptake (gross primary productivity—GPP) across ecosystems. To prepare for the assimilation of SIF data in terrestrial biosphere models, we examine how differences between SIF products (due to differences in acquisition characteristics and processing chain) may affect the optimization of model parameters and the resultant GPP estimate. We compare recent daily mean SIF products (one from the Orbiting Carbon Observatory-2 [OCO-2] and two from the Global Ozone Monitoring Experiment–2 [GOME-2], GlobFluo [GF] and NASA-v28 [N28], missions), averaged at 0.5° × 0.5° spatial resolution and 16-day temporal resolution, at the biome level. Phase differences between these products are relatively small. A first-order correction of the difference in spectral sampling between the two instruments shows that OCO-2 and N28 are consistent in terms of magnitude and amplitude, while GF is twice as large as the others. Using a bias-blind toy data assimilation framework, we analyze how biases between SIF products, and between model and products, can be partially alleviated by optimizing the slope and intercept parameters of a linear GPP-SIF operator. As observation biases can transfer to biases in other optimized process-based parameters and to modeled carbon fluxes— thereby resulting in unidentified inaccurate parameter values—we argue that potential SIF biases should be treated cautiously in real-world experiments in order to achieve realistic and reliable future simulations.

Gross primary production↗
NASA NTRS2001

Multi-Sensor Registration of Earth Remotely Sensed Imagery

Assuming that approximate registration is given within a few pixels by a systematic correction system, we develop automatic image registration methods for multi-sensor data with the goal of achieving sub-pixel accuracy. Automatic image registration is usually defined by three steps; feature extraction, feature matching, and data resampling or fusion. Our previous work focused on image correlation methods based on the use of different features. In this paper, we study different feature matching techniques and present five algorithms where the features are either original gray levels or wavelet-like features, and the feature matching is based on gradient descent optimization, statistical robust matching, and mutual information. These algorithms are tested and compared on several multi-sensor datasets covering one of the EOS Core Sites, the Konza Prairie in Kansas, from four different sensors: IKONOS (4m), Landsat-7/ETM+ (30m), MODIS (500m), and SeaWIFS (1000m).

LeMoigne, Jacqueline↗
NASA NTRSDate not supplied

Some Aeronautical Communications Experiments

Classically there has existed an asymmetry between the computing and communicating sides of aerospace systems. Over the past few decades, this asymmetry has shifted to favoring communication link technologies, meaning that advancements in available central processing units (CPUs), storage devices, and internal data buses have stagnated. Indeed, the increased emphasis placed on refining subsystem performance such as with antenna bandwidth in phased arrays, amplifier power efficiency, software defined radio (SDR) flexibility and encoding for data compression and error correction has given rise to successful debuts of multi-gigabit-per-second data return from long space-link distances. These accomplishments are easily quantifiable through link budgets and illustrate what is possible, but also reveal the deficiencies in overall communications capabilities. In particular, the ever-accelerating presence of aerospace vehicles gives rise to newer and larger classes of challenges to address the needs of 21st century systems. Furthermore remote sensing and imaging capabilities have far outpaced our ability to transmit their products to the ground, so we are increasingly dependent on pre-processing and downselection to contend with the communications bottleneck. No longer may we depend upon the constrained logistics in delivering end-to-end data delivery through manual reconfigurations, static event scheduling and execution on a per-vehicle basis, for these methods do not scale and therefore must give way to dynamic, networked approaches with an overall systems view in mind. Emerging mission requirements exhibit a trend toward multiple smaller-scale vehicles working together to perform dissimilar observations. Such operations necessitate sensor fusion across a constellation, and where data processing may be distributed throughout a fairly disconnected network whose topology changes over time in non-deterministic manners. Individual communications link performance is still very relevant to deploying an effective communications system, but now must be embedded within a greater architecture of capability to optimally utilize the bandwidth available from each link to generate an ultimate end-to-end quality of service. The deleterious effects of timing uncertainty across the arrangement presents a challenge to measurement synchronization and delivery, so a successful deployed system needs to be tolerant to the delays inherent in time-of-light between elements and digital processing latencies existing at each node. In this presentation we share the flight test results from a high performance Gbps laser communications terminal evaluated with a suite of store and forward capabilities called High-rate Delay Tolerant Networking (HDTN). The communications payload is operated over Lake Erie across a range of configurations including several convergence layers, and is evaluated to determine recovery time after link disruptions, information loss, efficiency and speed. The effectiveness of utilizing a flying laboratory to increase the Technology Readiness Level (TRL) of an integrated system in relevant environments is discussed, as well as the value of conducting aeronautics experiments to retire risk for technology infusion into space missions. Upcoming flight campaigns will be presented, including opportunities to demonstrate secure command and control, data intensive hyperspectral imaging, quantum link characterization, 4k High Definition (HD) video streaming and internetworked space-ground-aero relay operations. These experiments will pave the way for future missions which will depend upon interoperability across disparate government and privately owned networks, involve contention with uncertain and dynamic timing, and require agility to autonomously configure optimal parameters across networks of ever-increasing size and complexity to ensure data delivery. https://www1.grc.nasa.gov/space/scan/acs/tech-studies/dtn/

Daniel Raible↗
NASA NTRSDate not supplied

Enabling Interoperability in Earth System Digital Twins (ESDT): Integrating Observations, Models, and AI for Actionable Insights Through NASA'S Intelligent Systems Technology Program

NASA’s Intelligent Systems Technology Program (IST) is driving a paradigm shift in Earth science through the development of Earth System Digital Twins (ESDT). These integrated information systems create a dynamic "digital replica" of the Earth by harmonizing continuous, multi-source observations with high-fidelity models and state-of-the-art artificial intelligence (AI) that enable “What now?”, “What next?”, and “What if?” scenario building. These scenarios are reflected in NASA IST’s series of ESDTs, from the Coastal Zone Digital Twin that integrates complex data on the current state of the Chesapeake Bay to the Terrestrial Environmental Rapid-Replication and Assimilation Hydrometeorological (TerraHydro) AI-based ESDT that forecasts water movement across Earth’s surface, to the Agriculture Land Information System (AgLIS) which can be used to assess optimal planting dates and crop yield estimates. By bridging the gap between vast data archives and actionable insights, these projects enable a system-of-systems approach to understanding complex, interacting Earth processes. This poster will highlight recent innovations and future directions from NASA’s ESDT initiatives: Continuous Data Assimilation & Multi-Source Fusion. A core requirement of the ESDT work is the transition from static models to dynamic "living" replicas. This involves creating frameworks for the continual assimilation of near-real-time data from uncoordinated, heterogeneous sources, including satellite observations and airborne assets, and ground-based Internet of Things (IoT) sensors. These systems link design, operational status, and environmental data, ensuring the digital twin accurately reflects the current state of the physical Earth system. High-Fidelity Hybrid Modeling & Computational Acceleration to enable interactive "what-if" explorations, programs are moving beyond traditional, slow physical solvers by developing fast surrogate machine learning models and Deep Generative Models (DGMs). These hybrid approaches use neural networks to emulate complex physics, such as cloud feedback or ocean dynamics, at a fraction of the original computing cost, often leveraging advanced hardware like Graphics Processing Units (GPUs) to achieve the necessary scale. Federated Ecosystems & Interoperable Frameworks rather than building isolated tools, NASA IST is moving toward federated ESDTs and reusable analytic collaborative frameworks. This theme focuses on interoperability standards and common ontologies that allow specialized digital twins to interact and share data. This system-of-systems architecture supports multi-discipline investigations, such as analyzing how upstream watershed changes impact downstream urban flooding or how wildfire emissions affect regional air quality. By leveraging these advancements, ESDTs empower researchers and decision-makers to conduct real-time analysis and run complex hypothetical scenarios, ultimately improving our understanding of Earth’s evolving systems and informing critical real-world applications.

Earth System↗