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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 NTRS2007

Advanced Image Processing for NASA Applications

The future of space exploration will involve cooperating fleets of spacecraft or sensor webs geared towards coordinated and optimal observation of Earth Science phenomena. The main advantage of such systems is to utilize multiple viewing angles as well as multiple spatial and spectral resolutions of sensors carried on multiple spacecraft but acting collaboratively as a single system. Within this framework, our research focuses on all areas related to sensing in collaborative environments, which means systems utilizing intracommunicating spatially distributed sensor pods or crafts being deployed to monitor or explore different environments. This talk will describe the general concept of sensing in collaborative environments, will give a brief overview of several technologies developed at NASA Goddard Space Flight Center in this area, and then will concentrate on specific image processing research related to that domain, specifically image registration and image fusion.

LeMoign, Jacqueline↗

NASA NTRSDate not supplied

Contamination, Transportation or Transmutation in LENR Material Analyses

LENR experiments using various loading and triggering mechanisms rely on a variety of elemental and isotopic assays to determine LENR effects. These assays include optical microscopy, Scanning Electron Microscopy with Energy Dispersive X-Ray Analysis (SEM/EDX), X-Ray Photoelectron Spectroscopy (XPS) and Transmission Electron Microscopy (TEM). All of these methods observe the surface of a material. By dissolving or vaporizing the sample, Inductively Coupled Plasma Optical Element Spectroscopy (ICP-OES) can determine elemental composition (ppb) or with mass spectroscopy, isotopes (ICP/MS). One can use a focused ion beam (FIB) to cut open a sample and observe the “cut” with either SEM/EDX, or Time-of-Flight Secondary Ion Mass Spectroscopy (TOF-SIMS). High Purity Gamma Ray Spectroscopy (HPGe) and alpha/ beta Liquid Scintillator spectroscopy can be used. We’ve employed these assay methods in our NASA GRC research under both the Advanced Energy Conversion and Lattice Confinement Fusion Projects. However, there are limitations associated with each of these methods ranging from handling contamination, instrumental limitations including sensitivity and field of view, and sample preparation.

Low Energy Nuclear Reactions↗

NASA NTRS2006

Real-time Enhancement, Registration, and Fusion for a Multi-Sensor Enhanced Vision System

Over the last few years NASA Langley Research Center (LaRC) has been developing an Enhanced Vision System (EVS) to aid pilots while flying in poor visibility conditions. The EVS captures imagery using two infrared video cameras. The cameras are placed in an enclosure that is mounted and flown forward-looking underneath the NASA LaRC ARIES 757 aircraft. The data streams from the cameras are processed in real-time and displayed on monitors on-board the aircraft. With proper processing the camera system can provide better-than- human-observed imagery particularly during poor visibility conditions. However, to obtain this goal requires several different stages of processing including enhancement, registration, and fusion, and specialized processing hardware for real-time performance. We are using a real-time implementation of the Retinex algorithm for image enhancement, affine transformations for registration, and weighted sums to perform fusion. All of the algorithms are executed on a single TI DM642 digital signal processor (DSP) clocked at 720 MHz. The image processing components were added to the EVS system, tested, and demonstrated during flight tests in August and September of 2005. In this paper we briefly discuss the EVS image processing hardware and algorithms. We then discuss implementation issues and show examples of the results obtained during flight tests. Keywords: enhanced vision system, image enhancement, retinex, digital signal processing, sensor fusion

Hines, Glenn D.↗

NASA NTRSDate not supplied

NASA Armstrong Flight Research Center Dynamics and Controls (530)

AFRC Controls and Dynamics Branch - Research Areas: - Traditional GN&C - Classical and advanced control algorithms - Risk based approaches for safety critical applications - Integration of novel sensors and sensor fusion (FOSS, LIDAR, etc.) - Trajectory optimization and control - Flight/System Dynamics - Equations of Motion and integrated modeling of vehicles and vehicle systems - Unique and novel vehicle dynamics - Methods for extracting relevant vehicle dynamic information from flight data - Human and vehicle interfaces and interactions - Handling Qualities and Pilot-in-the-loop oscillations (PIO) predictions and design metrics - Ride quality research - Autonomy - Novel algorithms, sensors, and sensor fusion - Bounding risk for testing automated systems - Pilot/Operator interactions - Engineering Support and Airworthiness Assessments - Aircraft modifications and experimental configurations

Chris Miller↗

NASA NTRS1993

Advanced data visualization and sensor fusion: Conversion of techniques from medical imaging to Earth science

Hughes Aircraft Company and the University of Chicago propose to transfer existing medical imaging registration algorithms to the area of multi-sensor data fusion. The University of Chicago's algorithms have been successfully demonstrated to provide pixel by pixel comparison capability for medical sensors with different characteristics. The research will attempt to fuse GOES (Geostationary Operational Environmental Satellite), AVHRR (Advanced Very High Resolution Radiometer), and SSM/I (Special Sensor Microwave Imager) sensor data which will benefit a wide range of researchers. The algorithms will utilize data visualization and algorithm development tools created by Hughes in its EOSDIS (Earth Observation SystemData/Information System) prototyping. This will maximize the work on the fusion algorithms since support software (e.g. input/output routines) will already exist. The research will produce a portable software library with documentation for use by other researchers.

Savage, Richard C.↗

NASA NTRS1983

Theory of Compound Liquid Drops

Dynamic behavior is analyzed for drop within drop within infinite fluid. Report gives theoretical basis for understanding behavior of compound drops. Aids in planning and interpreting experiments in laboratory, spacecraft, and research aircraft. Provides insight into fabrication of target pellets for nuclear fusion.

Saffren, M. M.↗

NASA NTRS1993

Development and calibration of UV/VUV radiometric sources

A program exists at NIST to calibrate radiometric sources for the spectral range from 118-350 nm. These include deuterium lamps, hollow-cathode lamps, RF-excited dimer lamps, and wall-stabilized argon arcs. Sources have been calibrated for and used by researchers in solar physics, astrophysics, atmospheric physics (ozone measurements), magnetically controlled fusion, and photobiology. The argon arcs were developed in our laboratory, and provide intense sources of both radiance and irradiance. Calibrations are performed relative to two primary sources, a wall-stabilized hydrogen arc and a 12,000 K black-body line arc, both developed in our laboratory. Also we recently have begun periodic calibrations on the NIST storage ring, SURF II, to insure consistency between our respective radiometric bases. Various sources have been calibrated for space' applications, including several which are flyable. Also, some development and testing of radiometers for semiconductor lithography were recently carried out with an intense argon arc source.

Bridges, J. M.↗

NASA NTRS1996

APS Conference on Understanding the Biological Clock: From Genetics to Physiology

The Conference was designed to take advantage of the fusion of two intellectually dominant but heretofore separate lines of clock research, vertebrate physiology and invertebrate and microbial genetics. The APS Conference attracted 251 scientists, 68 of whom were students. In addition to the excellent speaker program organized by Dunlap and Loros, the attendees also submitted 93 volunteer abstracts that were programmed in poster sessions. Thirty-four percent of the submitted abstracts were first authorized by a female student or scientist.

Frank, Martin↗

NASA NTRS2007

Muon Catalyzed Fusion

Muon catalyzed fusion is a process in which a negatively charged muon combines with two nuclei of isotopes of hydrogen, e.g, a proton and a deuteron or a deuteron and a triton, to form a muonic molecular ion in which the binding is so tight that nuclear fusion occurs. The muon is normally released after fusion has taken place and so can catalyze further fusions. As the muon has a mean lifetime of 2.2 microseconds, this is the maximum period over which a muon can participate in this process. This article gives an outline of the history of muon catalyzed fusion from 1947, when it was first realised that such a process might occur, to the present day. It includes a description of the contribution that Drachrnan has made to the theory of muon catalyzed fusion and the influence this has had on the author's research.

Armour, Edward A.G.↗

NASA NTRSDate not supplied

Bridging the Last Mile with Open-Source Advancements: Empowering Communities through Fusion of Aerosol Optical Depth (AOD) Products from Multi-Satellite Sensors

Aerosol Optical Depth (AOD) is a crucial parameter for understanding atmospheric aerosol distribution and their impact on climate and air quality. With the growing number of Earth observation satellites, there is an abundance of AOD products derived from various sensors onboard both geostationary and low-orbit satellites. The availability of multiple datasets provides an opportunity to harness the strengths of each sensor and create comprehensive and accurate AOD datasets for climate and air quality studies at different temporal and spatial scales. Our NASA aerosol MEaSURES project has made significant strides in recent years by undertaking the ambitious task of developing an open-source package tailored for fusing AOD products from different sources. The package is based on OOP (Object-Oriented Programming) design and is implemented in Python modules. Generic interfaces enable easy inclusion of large and heterogeneous data. The package may be utilized to produce harmonized AOD datasets with enhanced spatial and temporal coverage. The latest version of the package is able to process and integrate the dark-target AOD data from six different sensors: AHI Himawari-8, ABI GOES-West, ABI GOES-East, MODIS AQUA, MODIS TERRA, and VIIRS SNPP. Rigorous validation and intercomparison studies have been performed to assess the accuracy and reliability of the fused AOD product against ground-based measurements and reference datasets. The open-source nature of the developed package ensures transparency, reproducibility, and community engagement. The research community and stakeholders can access, contribute to, and further improve the fusion methodology, making it adaptable to other studies, or expanding it to include new satellite data as they become available. In this poster presentation, we will introduce the accomplishments and challenges faced during the development of the open-source package for AOD data fusion, and demonstrate the advantages of combining AOD products from the six aforementioned satellite sensors. The presentation aims to foster discussions, collaborations, and future directions in integrating Earth observation and remote sensing data, which may contribute to a better understanding of atmospheric aerosols and their impacts on our environment.

Zhaohui Zhang↗

NASA NTRS2021

Low and High Temperature Non-Thermonuclear Fusion Approaches to Energy Production

We are responding to the RFI points A1, A2 and A3. We appreciate the need for a high density, high power, environmentally-benign and carbon-neutral power system. Although fusion has been considered for over 70 years, the nearly intractable means of maintaining a hydrogen plasma at temperatures exceeding the center of the Sun increasingly delays not only commercialization but even the scientific breakeven point. As a recent JASON report notes, the world-wide energy grid is moving towards decentralization which is counter to the large tokamak fusion de-vices necessary given their underdense plasmas. NASA has spent several years understanding and developing Lattice Confinement Fusion as an alternative to thermonuclear fusion by exploring many means of loading and triggering fusion reactions in deuterated metal lattices. Triggering has run the gamut from bremsstrahlung-initiated photo-neutrons to the role of electron screening in assisting these reactions. Electron screening may be responsible for both nuclear effects in deuterium pumped metals as well as fast neutrons observed from electrolytically driven cathodes. Electron screened fusion rate enhancement has been observed by others, including the Lawrence Berkeley National Laboratory. NASA’s need for deep space power drove this research with a goal of a ten-year lifetime for a multi-kWe power system. Previous NASA studies have explored the use of fusion systems for nuclear thermal propulsion for manned spaceflight to the outer planets. Despite these designated uses, small-scale terrestrial power applications as well as medical isotope production are possible once scaling is achieved. ARPA-E can contribute to the Nation’s Green Energy mandates by funding research in this field that builds on condensed matter nuclear science findings by the US Navy and NASA.

L. P. Forsley↗

NASA NTRSDate not supplied

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↗

NASA NTRS1999

Propulsion Research and Technology: Overview

Propulsion is unique in being the main delimiter on how far and how fast one can travel in space. It is the lack of truly economical high-performance propulsion systems that continues to limit and restrict the extent of human endeavors in space. Therefore the goal of propulsion research is to conceive and investigate new, revolutionary propulsion concepts. This presentation reviews the development of new propulsion concepts. Some of these concepts are: (1) Rocket-based Combined Cycle (RBCC) propulsion, (2) Alternative combined Cycle engines suc2 as the methanol ramjet , and the liquid air cycle engines, (3) Laser propulsion, (4) Maglifter, (5) pulse detonation engines, (6) solar thermal propulsion, (7) multipurpose hydrogen test bed (MHTB) and other low-G cryogenic fluids, (8) Electric propulsion, (9) nuclear propulsion, (10) Fusion Propulsion, and (11) Antimatter technology. The efforts of the NASA centers in this research is also spotlighted.

Cole, John↗

NASA NTRS2002

Stereo transparency and the disparity gradient limit

Several studies (Vision Research 15 (1975) 583; Perception 9 (1980) 671) have shown that binocular fusion is limited by the disparity gradient (disparity/distance) separating image points, rather than by their absolute disparity values. Points separated by a gradient >1 appear diplopic. These results are sometimes interpreted as a constraint on human stereo matching, rather than a constraint on fusion. Here we have used psychophysical measurements on stereo transparency to show that human stereo matching is not constrained by a gradient of 1. We created transparent surfaces composed of many pairs of dots, in which each member of a pair was assigned a disparity equal and opposite to the disparity of the other member. For example, each pair could be composed of one dot with a crossed disparity of 6' and the other with uncrossed disparity of 6', vertically separated by a parametrically varied distance. When the vertical separation between the paired dots was small, the disparity gradient for each pair was very steep. Nevertheless, these opponent-disparity dot pairs produced a striking appearance of two transparent surfaces for disparity gradients ranging between 0.5 and 3. The apparent depth separating the two transparent planes was correctly matched to an equivalent disparity defined by two opaque surfaces. A test target presented between the two transparent planes was easily detected, indicating robust segregation of the disparities associated with the paired dots into two transparent surfaces with few mismatches in the target plane. Our simulations using the Tsai-Victor model show that the response profiles produced by scaled disparity-energy mechanisms can account for many of our results on the transparency generated by steep gradients.

NASA Discipline Space Human Factors↗

NASA NTRS2006

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.↗

NASA NTRS2018

Three-Dimensional Printing GRCop-42

GRCop-42 (Cu-4 at.% Cr-2 at.% Nb) is a copper (Cu)-chromium (Cr)-niobium (Nb) alloy that NASA developed for use in rocket propulsion components that required high thermal conductivity, excellent creep resistance, low-cycle fatigue life, and strength at elevated temperatures, such as combustion chamber liners and fuel injector face plates. Using powder bed fusion (PBF) 3D printing, NASA Marshall Space Flight Center (MSFC) and NASA Glenn Research Center (GRC) successfully printed near-fully-dense GRCop-42 components that may equal to or exceed their traditionally manufactured predecessors. This Technical Memorandum serves to summarize the process that was developed to achieve 3D printable near-fully-dense and functional GRCop-42.

Cooper, K. G.↗

NASA NTRSDate not supplied

In-Situ Alloying of GRCop-42 via Additive Manufacturing: Precipitate Analysis

GRCop-42, a Cu-4at% Cr-2at% Nb alloy, was designed as a high temperature, high strength, high heat flux material for rocket engine combustion chamber liners by NASA Glenn Research Center. In situ alloying of GRCop-42 (ISGRCop-42) using powder bed fusion (PBF) additive manufacturing (AM) takes elemental powders of Cu, Cr, and Nb to be introduced into the PBF environment and develop the GRCop alloy while simultaneously building an AM component. Elemental powders were milled together prior to printing in an effort to facilitate the alloying process. Success of the in situ alloying process may provide lower cost, faster lead times, alloying optimization, and more design freedom in the development of regeneratively-cooled rocket propulsion systems. Evaluation of the ISGRCop-42 was conducted using a phase extraction procedure to isolate the Cr2Nb precipitates from the pure Cu matrix. The isolated precipitates were then examined using x-ray powder diffraction (XRD), scanning electron microscopy (SEM), and energy dispersion spectroscopy (EDS). It was found that ISGRCop-42 successfully and repeatedly formed Cr2Nb at a yield as high as 89% of potential Cr2Nb. Further, it was identified that the preparation of the powder was the most influential factor in alloying success, and the second most influential factor was the laser power.

In Situ alloying↗

NASA NTRSDate not supplied

Towards A Flexible Data Fusion Tool Incorporating Model, Satellite, Regulatory Monitor and Low-Cost Sensor Data for Air Quality Estimation and Forecasting

Air quality managers, researchers, and concerned community scientists around the world have a variety of sources for air quality information, ranging from traditional regulatory monitoring networks and atmospheric chemistry models to remote sensing data products and low-cost sensor networks. However, the ability to incorporate data from these disparate sources and synthesize a comprehensive overview of the local air quality situation remains a considerable barrier for many end-users. This presentation will outline a tool, currently in development, which will address this need using a flexible data fusion approach. The tool will make use of air quality forecast model outputs (primarily from the NASA GEOS-CF composition forecast modeling system), satellite remote sensing data (from instruments including MODIS, VIIRS, TROPOMI, plus TEMPO for the US when available), and in-situ data from official regulatory and/or low-cost networks where these are available. The ability to incorporate data from low-cost sensor networks will be a key feature of the tool; it will make use of other available data sources to calibrate the low-cost sensor data on a regional scale, then use these calibrated low-cost sensor data for localized updating to resolve finer-scale air quality patterns. Development of this tool is taking place with the help of national and international partners and end-user groups, coordinated through the US EPA and the United Nations Environment Programme (UNEP). The tool is being developed on the Google Earth Engine cloud computing platform to facilitate integration of diverse data sources and free access by a broad community of end-users. Stewardship of the tool will be passed to US EPA and UNEP to support future activities with end-users in the US and around the world, and the tool itself will remain freely accessible. We hope that this tool will lower the barrier to entry for various user groups worldwide, including community scientists, who struggle to integrate disparate data sources to gain insight into their local air quality situations. This presentation will cover the early stages of the development of the tool, including the underlying methods and some pilot case studies in integrating low-cost sensor data.

global models↗