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Earth Science Imagery Registration

The study of global environmental changes involves the comparison, fusion, and integration of multiple types of remotely-sensed data at various temporal, radiometric, and spatial resolutions. Results of this integration may be utilized for global change analysis, as well as for the validation of new instruments or for new data analysis. Furthermore, future multiple satellite missions will include many different sensors carried on separate platforms, and the amount of remote sensing data to be combined is increasing tremendously. For all of these applications, the first required step is fast and automatic image registration, and as this need for automating registration techniques is being recognized, it becomes necessary to survey all the registration methods which may be applicable to Earth and space science problems and to evaluate their performances on a large variety of existing remote sensing data as well as on simulated data of soon-to-be-flown instruments. In this paper we present one of the first steps toward such an exhaustive quantitative evaluation. First, the different components of image registration algorithms are reviewed, and different choices for each of these components are described. Then, the results of the evaluation of the corresponding algorithms combining these components are presented o n several datasets. The algorithms are based on gray levels or wavelet features and compute rigid transformations (including scale, rotation, and shifts). Test datasets include synthetic data as well as data acquired over several EOS Land Validation Core Sites with the IKONOS and the Landsat-7 sensors.

LeMoigne, Jacqueline↗

LSKnowledge: Nexus for Transformative Scientific Discoveries and Enhanced Information Retrieval in NASA Life Sciences Portal

We stand at the brink of an extraordinary transformation in the field of AI, driven by the convergence of generative AI and semantic technologies (e.g., knowledge graphs). This fusion holds immense potential and could redefine the future of scientific exploration, particularly in the realm of life sciences research. In this context, we shed light on the pivotal roles that Large Language Models (LLMs) and semantic technologies will play in advancing research, unearthing and comprehending life sciences information through innovative approaches, and empowering researchers to extract insights from NASA's extensive Life Sciences Data Archive. Within the NASA Life Sciences Portal (NLSP), the integration of LLMs and semantic technologies unlocks several advanced capabilities. First and foremost, it equips scientists with sophisticated tools to manage the ever-expanding wealth of scientific literature and data. Furthermore, it facilitates the creation of knowledge graphs that visually represent intricate relationships among biological entities, enabling comprehensive systems-level analysis. Additionally, the fusion of generative AI (including LLMs) and semantic technology can significantly benefit NASA's life sciences research by enhancing information retrieval and hypothesis generation. These tools enhance natural language understanding, facilitating knowledge discovery within NLSP. The overarching vision is to establish a cohesive knowledge ecosystem within NLSP, harnessing the power of LLMs and semantic technologies to synthesize and cross-reference data from diverse missions, disciplines, and research domains. This holistic approach ultimately deepens our understanding of how space environments impact life sciences data. To advance this initiative, we have launched LSKnowledge, aimed at enhancing the information retrieval capabilities of NLSP. In the short term, our primary goal is to develop a robust semantic search system. This system will empower HRP (Human Research Program) researchers to navigate NLSP data repositories more efficiently and precisely, catalyzing the process of hypothesis formation and scientific breakthroughs. To achieve this, we have employed pre-trained LLMs as part of a semantic search tool that can rank and highlight the most relevant records for user queries. To assess the tool's performance, we have curated a set of approximately 200 queries from subject matter experts (SMEs) and manually ranked the top records retrieved by both the current search system and the new semantic search, using SME judgments as the gold standard for relevancy. Herein, we present the results of our comparative analysis and illustrate how these findings have informed the fine-tuning of the system for enhanced performance. In the long term, our objectives include 1) retrieving publicly available information and integrating it with NLSP data to provide more precise answers to user queries, and 2) incorporating non-textual information from the NLSP database into our approach. In conclusion, the fusion of LLMs and semantic technologies within NLSP represents a pioneering stride towards reshaping the landscape of scientific discovery. This synergy not only equips researchers with powerful tools to navigate the burgeoning sea of information but also facilitates a deeper understanding of complex biological relationships, all while accelerating hypothesis generation and knowledge discovery. Through our initiative, LSKnowledge, we are committed to continually refining and expanding these capabilities, with the aim of not only enhancing information retrieval but also integrating diverse data sources to provide more precise insights. In the grand vision, NLSP strives to become the cornerstone of a comprehensive knowledge ecosystem, unraveling the enigmatic intricacies of life sciences phenomena in the context of space environments.

Life Sciences↗

Geophysical Observations Toolkit For Evaluating Coral Health (GOTECH) Fall 2021 Final Report

The NASA Langley Research Center (LaRC) Data Science Team (DST), under the Office of the Chief Information Officer (OCIO), is investigating the capacity of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite to infer the vitality of coral reefs. This report describes the Fall 2021 period of performance for the Geophysical Observations Toolkit for Evaluating Coral Health (GOTECH) project. During this effort, two student teams at Georgia Tech developed machine-learning models to predict the vitality of coral reefs in targeted geographic regions based on backscatter data from the CALIPSO satellite. To train these models, students fused data to form a common operating picture of how coral reefs have grown and decayed worldwide. This report describes the student assignment, background, and results of the semester's research.

Machine Learning↗

Research briefing on contemporary problems in plasma science

An overview is presented of the broad perspective of all plasma science. Detailed discussions are given of scientific opportunities in various subdisciplines of plasma science. The first subdiscipline to be discussed is the area where the contemporary applications of plasma science are the most widespread, low temperature plasma science. Opportunities for new research and technology development that have emerged as byproducts of research in magnetic and inertial fusion are then highlighted. Then follows a discussion of new opportunities in ultrafast plasma science opened up by recent developments in laser and particle beam technology. Next, research that uses smaller scale facilities is discussed, first discussing non-neutral plasmas, and then the area of basic plasma experiments. Discussions of analytic theory and computational plasma physics and of space and astrophysical plasma physics are then presented.

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22 N HPGP Thruster Life Testing

In the ever-changing paradigm of efficient and capable spacecraft design, scientific missions continue pushing the envelope enabling spacecraft subsystems to deliver effective solutions to meet challenging new mission/spacecraft needs. From an in-space storable liquid chemical propulsion perspective, monopropellant hydrazine has been, and continues to be, a dependable propellant with considerable flight heritage, a variety of engine thrust classes available from multiple vendors, with repeatable and reliable performance. Additionally, the space propulsion industry has learned to successfully handle hydrazine, its regulations, the safety protocols, the personnel protective equipment, and the unique training standards–all requisite for loading spacecraft propulsion systems with toxic hypergolic hydrazine. The question now arises as to “what is next for in-space chemical propulsion?” Further, with the evolution and concrete advancements in innovative in-space green propellant technologies, capable of providing realizable benefits to scientific missions, concern over the reliability and availability of this higher performing and safer to handle class of propellants is waning. As science missions move forward with the potential flight in fusion of High Performance Green Propulsion (HPGP), NASA and its industry partners are working to address any gaps in system reliability, performance, or unique operational considerations. Propellant technology that offers both higher performance and significant reduction in personnel hazards compared to hydrazine presents an attractive propulsion subsystem design opportunity. Increased propulsion subsystem performance can result in lower spacecraft launch mass, larger scientific payloads, or extended on-orbit lifetimes. Mission trades using green propulsion technologies have been documented on multiple NASA Goddard Space Flight Center (GSFC) mission classes, examining various parameters and requirements to support mission architectures in Low Earth Orbit (LEO), High Earth Orbit (HEO), geostationary, lunar, planetary, and Quasi-halo orbit around Sun-Earth Lagrange point (L2). The results of these trade studies show promising, attainable benefits. The perceived programmatic risk of flying a newer propulsion technology has, unfortunately, not outweighed the benefits to date. To take advantage of the improved performance and mitigate programmatic risk, HPGP engines must demonstrate life testing at higher propellant throughputs than have currently been demonstrated. In an effort to proactively address the challenges with technology infusion into a risk-averse community, NASA and the Swedish National Space Agency (SNSA) outlined a collaborative Implementing Arrangement (IA) for the respective agencies to pursue increased HPGP technology maturation. This initial IA effort began in 2013, fresh off the heels of the successful PRISMA HPGP technology demonstration mission. The IA targeted objective is to reduce risk to potential future HPGP missions and fully characterize the LMP-103S propellant and associated engine performance. Over the past eight years, HPGP has flown in propulsion systems on twenty-five(25) spacecraft from seven(7) different Launch Ranges around the globe and on seven (7) different Launch Vehicles. Six(6) of these launches involved multiple loading operations for multiple spacecraft. For U.S. Range operations, nine (9) HPGP systems have been processed at Vandenberg Space Force Base(VSFB):six(6) in 2017, and three (3) in 2018. Six (6) more have been processed at Cape Canaveral Air Force Station (CCAFS)in May 2020, with three (3) systems launched in June 2020 and the remaining three (3) system were left loaded and ready until their launch in August of 2020. Three (3) more systems have been processed at Wallops Flight Facility(WFF)and launched in June 2021. In addition, these propulsion subsystems employed heritage propulsion subsystem component such as valves, filters, and pressure transducers, and have further demonstrated nominal functionality in both diaphragm and Propellant Management Device (PDM) propellant tanks. Based on these successes, HPGP technology continues to be considered for NASA Science Mission Directorate missions at GSFC. The work presented herein represents many years of development and collaborative efforts to successfully align higher performance, low toxicity hydrazine alternatives into scientific missions. NASA GSFC Propulsion Engineering, in collaboration with Bradford ECAPS, has developed mission specific thruster design and testing requirements to establish GSFC’s desired test conditions and firing sequences.In2017, the first flight-like 22N HPGP thruster Engineering Qualification Model (EQM-1)was designed and built by Bradford ECAPS to prove out the thruster design, materials, build process, and test campaign with respect to NASA GSFC critical component and mission requirements. This test program was developed to comprehensively test the thruster, the technology, and ultimately increase the 22N HPGP Technology Readiness Level(TRL). EQM-1was tested to environmental qualification levels prior to hot fire performance testing to represent the relevant end-to-end environment (launch to on-orbit operation)with required margin. This thruster demonstrated steady-state and pulse mode operational capability with propellant thruster throughput up to~53kg.At this throughput level, the EQM-1 engine began to present off-nominal performance and the test campaign was halted to allow for non-destructive testing and identify the root cause for the an omalous performance. Capitalizing on the successful elements of the EQM-1 campaign, an upgraded 22N HPGP EQM-2 has been manufactured by Bradford ECAPS to meet the complete GSFC requirements. The EQM-2 thruster’s test campaign has further demonstrated the robustness of the HPGP propulsion technology and increased the Technology Readiness Level (TRL) by undergoing a full acceptance test program, then proceeding into qualification, including environmental testing (vibration and shock to qualification levels),as well as hot-fire life testing, operating at steady-state and pulse modes with increased propellant thruster throughput to~150kg. The HPGP thruster performance testing enables effective HPGP thruster readiness evaluation to meet NASA candidate mission requirements in the future.

High↗

The Global Ecosystem Dynamics Investigation: High-Resolution Laser Ranging of the Earth’s Forests and Topography

Obtaining accurate and widespread measurements of the vertical structure of the Earth’s forests has been a longsought goal for the ecological community. Such observations are critical for accurately assessing the existing biomass of forests, and how changes in this biomass caused by human activities or variations in climate may impact atmospheric CO2 concentrations. Additionally, the three-dimensional structure of forests is a key component of habitat quality and biodiversity at local to regional scales. The Global Ecosystem Dynamics Investigation (GEDI) was launched to the International Space Station in late 2018 to provide high-quality measurements of forest vertical structure in temperate and tropical forests between 51.6 N & S latitude. The GEDI instrument is a geodetic-class laser altimeter/waveform lidar comprised of 3 lasers that produce 8 transects of structural information. Over its two-year nominal lifetime GEDI is anticipated to provide over 10 billion waveforms at a footprint resolution of 25 m. These data will be used to derive a variety of footprint and gridded products, including canopy height, canopy foliar profiles, Leaf Area Index (LAI), sub-canopy topography and biomass. Additionally, data from GEDI are used to demonstrate the efficacy of its measurements for prognostic ecosystem modeling, habit and biodiversity studies, and for fusion using radar and other remote sensing instruments. GEDI science and technology are unique: no other space-based mission has been created that is specifically optimized for retrieving vegetation vertical structure. As such, GEDI promises to advance our understanding of the importance of canopy vertical variations within an ecological paradigm based on structure, composition and function.

Dubayah, Ralph↗

Bridging Informatics and Earth Science: a Look at Gregory Leptoukh's Contributions

With the tragic passing this year of Gregory Leptoukh, the Earth and Space Sciences community lost a tireless participant in--and advocate for--science informatics. Throughout his career at NASA, Dr. Leptoukh established a theme of bridging the gulf between the informatics and science communities. Nowhere is this more evident than his leadership in the development of Giovanni (GES DISC Interactive Online Visualization ANd aNalysis Infrastructure). Giovanni is an online tool that serves to hide the often-complex technical details of data format and structure, making science data easier to explore and use by Earth scientists. To date Giovanni has been acknowledged as a contributor in 500-odd scientific articles. In recent years, Leptoukh concentrated his efforts on multi-sensor data inter-comparison, merging and fusion. This work exposed several challenges at the intersection of data and science. One of these was the ease with which a naive user might generate spurious comparisons, a potential hazard that was the genesis of the Multi-sensor Data Synergy Advisor (MDSA). The MDSA uses semantic ontologies and inference rules to organize knowledge about dataset quality and other salient characteristics in order to advise users on potential caveats for comparing or merging two datasets. Recently, Leptoukh also led the development of AeroStat, an online Giovanni instance to investigate aerosols via statistics from station and satellite comparisons and merged maps of data from more than one instrument. Aerostat offers a neural net based bias adjustment to harmonize the data by removing systematic offsets between datasets before merging. These examples exhibit Leptoukh's talent for adopting advanced computer technologies in the service of making science data more accessible to researchers. In this, he set an example that is at once both vital and challenging for the ESSI community to emulate.

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Biology-inspired Architecture for Situation Management

Situation Management is a rapidly developing science combining new techniques for data collection with advanced methods of data fusion to facilitate the process leading to correct decisions prescribing action. Current research focuses on reducing increasing amounts of diverse data to knowledge used by decision makers and on reducing time between observations, decisions and actions. No new technology is more promising for increasing the diversity and fidelity of observations than sensor networks. However, current research on sensor networks concentrates on a centralized network architecture. We believe this trend will not realize the full potential of situation management. We propose a new architecture modeled after biological ecosystems where motes are autonomous and intelligent, yet cooperate with local neighborhoods. Providing a layered approach, they sense and act independently when possible, and cooperate with neighborhoods when necessary. The combination of their local actions results in global effects. While situation management research is currently dominated by military applications, advances envisioned for industrial and business applications have similar requirements. NASA has requirements for intelligent and autonomous systems in future missions that can benefit from advances in situation management. We describe requirements for the Integrated Vehicle Health Management program where our biology-inspired architecture provides a layered approach and decisions can be made at the proper level to improve safety, reduce costs, and improve efficiency in making diagnostic and prognostic assessments of the structural integrity, aerodynamic characteristics, and operation of aircraft.

Jones, Kennie H.↗

AeroFusion: Data Fusion and Uncertainty Quantification for Entry Vehicles

AeroFusion is a NASA Langley initiative to incorporate advances in data science into the aerodynamic modeling process to improve efficiency. The effort can largely be categorized in three components: reduced-order modeling techniques, surrogate modeling techniques, and uncertainty quantification. By combining various methods from these categories, AeroFusion aims to reduce the development cost of aerodynamic models, both in terms of time and money.

Steven Snyder↗

AeroFusion: Data Fusion and Uncertainty Quantification for Entry Vehicles

AeroFusion is a NASA Langley initiative to incorporate advances in data science into the aerodynamic modeling process to improve efficiency. The effort can largely be categorized in three components: reduced-order modeling techniques, surrogate modeling techniques, and uncertainty quantification. By combining various methods from these categories, AeroFusion aims to reduce the development cost of aerodynamic models, both in terms of time and money.

Steven Snyder↗

NASA’s Goddard Space Flight Center’s Distributed Systems Missions Architecture

Space and Earth Science are being transformed by applying a distributed approach to missions, where the fusion of data from components, systems, instruments, models, and observation locations works in concert with timely responses and feedback mechanisms to multiply the knowledge obtained. Additionally, a disaggregated approach allows for a distributed cost and schedule that can be shared across multiple organizations to enable the greater mission. With the advances in reduced size, weight, and power for space-worthy components leading to the revolution in smaller spacecraft, the cost and timeliness proposition for launching multiple space assets has also greatly improved. Thus, the aerospace industry is undergoing a paradigm shift toward a proliferation of small satellites as a networked approach to meet mission objectives. This paper will describe the impetus, goal, and path to provide an openly available framework as a unifying catalyst for broad-ranging Distributed Systems Missions (DSMs) contributors.

Distributed Systems↗

NASA’s Goddard Space Flight Center’s Distributed Systems Missions Architecture

Space and Earth Science are being transformed by applying a distributed approach to missions, where the fusion of data from components, systems, instruments, models, and observation locations works in concert with timely responses and feedback mechanisms to multiply the knowledge obtained. Additionally, a disaggregated approach allows for a distributed cost and schedule that can be shared across multiple organizations to enable the greater mission. With the advances in reduced size, weight, and power for space-worthy components leading to the revolution in smaller spacecraft, the cost and timeliness proposition for launching multiple space assets has also greatly improved. Thus, the aerospace industry is undergoing a paradigm shift toward a proliferation of small satellites as a networked approach to meet mission objectives. This paper will describe the impetus, goal, and path to provide an openly available framework as a unifying catalyst for broad-ranging Distributed Systems Missions (DSMs) contributors.

Distributed Systems↗

Institute of Electrical and Electronics Engineers, Nuclear Science Symposium, 18th, and Nuclear Power Systems Symposium, 3rd, San Francisco, Calif., November 3-5, 1971, Proceedings.

Potential advantages of fusion power reactors are discussed together with the protection of the public from radioactivity produced in nuclear power reactors, and the significance of tritium releases to the environment. Other subjects considered are biomedical instrumentation, radiation damage problems, low level environmental radionuclide analysis systems, nuclear techniques in environmental research, nuclear instrumentation, and space and plasma instrumentation. Individual items are abstracted in this issue.

Source record↗

Space fusion energy conversion using a field reversed configuration reactor: A new technical approach for space propulsion and power

The fusion energy conversion design approach, the Field Reversed Configuration (FRC) - when burning deuterium and helium-3, offers a new method and concept for space transportation with high energy demanding programs, like the Manned Mars Mission and planetary science outpost missions require. FRC's will increase safety, reduce costs, and enable new missions by providing a high specific power propulsion system from a high performance fusion engine system that can be optimally designed. By using spacecraft powered by FRC's the space program can fulfill High Energy Space Missions (HESM) in a manner not otherwise possible. FRC's can potentially enable the attainment of high payload mass fractions while doing so within shorter flight times.

Schulze, Norman R.↗

Evolution of an Intelligent Information Fusion System

Consideration is given to the hardware and software needed to manage the enormous amount and complexity of data that the next generation of space-borne sensors will provide. An anthology is presented illustrating the evolution of artificial intelligence, science data processing, and management from the 1960s to the near future. Problems and limitations of technologies, data structures, data standards, and conceptual thinking are addressed. The development of an end-to-end Intelligent Information Fusion System that embodies knowledge of the user's domain-specific goals is proposed.

Campbell, William J.↗

Acoustic Levitation Containerless Processing

This research program consists of the development of acoustic containerless processing systems with applications in the areas of research in material sciences, as well as the production of new materials, solid forms with novel and unusual microstructures, fusion target spheres, and improved optical fibers. Efforts have been focused on the containerless processing at high temperatures for producing new kinds of glasses. Also, some development has occurred in the areas of containerlessly supporting liquids at room temperature, with applications in studies of fluid dynamics, potential undercooling of liquids, etc. The high temperature area holds the greatest promise for producing new kinds of glasses and ceramics, new alloys, and possibly unusual structural shapes, such as very uniform hollow glass shells for fusion target applications. High temperature acoustic levitation required for containerless processing has been demonstrated in low-g environments as well as in ground-based experiments. Future activities include continued development of the signals axis acoustic levitator.

Whymark, R. R.↗

CERES Fast Longwave And SHortwave Radiative Flux (FLASHFlux): Research to Operation

The Clouds and Earth’s Radiant Energy System (CERES) project provides satellite-based observations of how Earth’s energy flows are varying in time and space and how clouds and aerosols are affecting the Earth’s radiation budget. Nominally, CERES data products require months of validation and calibration before releasing a climate quality data. The Fast Longwave and Shortwave Radiative Flux (FLASHFlux) data product was developed as to provide key radiative flux data products within a week of observations for scientific, applied science research and educational usage. FLASHFlux achieves this by using simplified calibration process and optimized CERES data fusion production system, an operation meteorology product from Global Modeling and Assimilation Office(GMAO), and surface parameterized radiative flux models. The CERES FLASHFlux provides two data products: 1) an hourly Level 2 Single Scanner Footprint (SSF) data separately for Aqua and Terra observations, and 2) a daily Level 3 Time Interpolated and Spatially Averaged (TISA) 1ox1o gridded data that combines Aqua and Terra observations.The current operational Version 3C is being transitioned to Version4A. We compare the FLASHFlux Version4A fluxes using the specialized calibration to Version3C and to the climate quality CERES Edition4A TOA and surface fluxes over time for Terra and Aqua to determine the uncertainties of the calibration process. In addition, we also compare the impact of the fluxes by using the near real-time GMAO GEOS FP-IT instead of GMAO G5-CERES meteorology data.We also compare both SSF overpass products (for Terra and Aqua) and TISA radiative flux products to a set of surface measurement sites that are globally distributed and assess agreement.Lastly, we introduce the first CERES FF SSF data products from the CERES instrument on board NOAA-20.

P Sawaengphokhai↗