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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Investigation into Cloud Computing for More Robust Automated Bulk Image Geoprocessing

Geospatial resource assessments frequently require timely geospatial data processing that involves large multivariate remote sensing data sets. In particular, for disasters, response requires rapid access to large data volumes, substantial storage space and high performance processing capability. The processing and distribution of this data into usable information products requires a processing pipeline that can efficiently manage the required storage, computing utilities, and data handling requirements. In recent years, with the availability of cloud computing technology, cloud processing platforms have made available a powerful new computing infrastructure resource that can meet this need. To assess the utility of this resource, this project investigates cloud computing platforms for bulk, automated geoprocessing capabilities with respect to data handling and application development requirements. This presentation is of work being conducted by Applied Sciences Program Office at NASA-Stennis Space Center. A prototypical set of image manipulation and transformation processes that incorporate sample Unmanned Airborne System data were developed to create value-added products and tested for implementation on the "cloud". This project outlines the steps involved in creating and testing of open source software developed process code on a local prototype platform, and then transitioning this code with associated environment requirements into an analogous, but memory and processor enhanced cloud platform. A data processing cloud was used to store both standard digital camera panchromatic and multi-band image data, which were subsequently subjected to standard image processing functions such as NDVI (Normalized Difference Vegetation Index), NDMI (Normalized Difference Moisture Index), band stacking, reprojection, and other similar type data processes. Cloud infrastructure service providers were evaluated by taking these locally tested processing functions, and then applying them to a given cloud-enabled infrastructure to assesses and compare environment setup options and enabled technologies. This project reviews findings that were observed when cloud platforms were evaluated for bulk geoprocessing capabilities based on data handling and application development requirements.

Brown, Richard B.↗
NASA NTRS2005

On Automating Failure Mode Analysis and Enforcing its Integrity

This paper reports our experience on the development of a design-for-safety (DFS) workbench called Risk Assessment and Management Environment (RAME) for microelectronic avionics systems. Our objective is to transform DFS practice from an ad-hoc, inefficient, error-prone approach to a stringent engineering process such that DFS can keep up with the rapidly growing complexity of avionics systems. In particular, RAME is built upon an information infrastructure that comprises a fault model, a knowledge base, and a failure reporting/tracking system. This infrastructure permits systematic learning from prior projects and enables the automation of failure modes, effects and criticality analysis (FMECA). Among other unique features, the most important advantage of RAME is its capability of directly accepting design source code in hardware description languages (HDLs) for automated failure mode analysis, which enables RAME to be compatible and to evolve with most electronic-computer-aided-design systems. Through an initial experimental evaluation of the RAME prototype, we show that our approach to FMECA automation improves failure mode analysis turn-around-time, completeness, and accuracy.

design for safety↗
NASA NTRSDate not supplied

NASA POWER: Providing Analysis-Ready, Cloud-Optimized Data for AI /ML Training and Applications in Earth Science

As global demand for sustainable development grows, the integration of Earth Observation (EO) data into decision making frameworks has become a primary objective for the scientific community. The NASA Prediction of Worldwide Energy Resources (POWER) project serves as a bridge between NASA EO data and the specialized needs of the renewable energy, sustainable infrastructure and agroclimatology communities. In this poster presentation we will present an overview of POWER data products and services along with its use in diverse research to decision-making workflows. By providing over 40 years of high-resolution historical, hourly and daily solar and meteorological data, POWER transforms satellite observations and global model reanalysis into actionable, Analysis-Ready Dataset (ARD). Currently, the project delivers over 250 industry-friendly parameters to the users from different NASA datasets like CERES SYN1Deg, MERRA-2, and IMERG alongside downscaled CMIP6 climate model data, fulfilling over 16 million requests from 50,000 unique users monthly. To ensure data quality and traceability, these parameters are rigorously validated against the ground-based observations from the Baseline Surface Radiation Network (BSRN) and the Global Surface Summary of the Day (GSOD) – these results will be discussed in the presentation. A newly introduced web-based PaRameter Uncertainty ViEwer (PRUVE) tool will be presented that provides an online validation platform to the users that benchmarks satellite-based and assimilation data products against these surface measurements. To reduce technical barriers to data adoption, POWER data is accessible through RESTful APIs, ESRI ArcGIS Image Services, a web-based Data Access Viewer tool, allowing users to visualize, validate and apply the dataset. For efficient data delivery POWER data is cloud-optimized into Zarr datastore accessible through NASA managed Amazon S3 ensures high-performance allowing users to integrate EO directly into operational pipelines. These customized services will be presented. Use cases from application will be presented from the energy sector - such as for design of generation systems, performance monitoring of solar power plants, in infrastructure sector- optimizing building energy efficiency and thermal comfort, in agriculture – such as driving crop simulation and yield forecasting models to enable climate resilient farming. Furthermore, the shift toward machine learning (ML) in EO research that has positioned POWER as a key provider for training datasets which will be discussed. Use-cases will be presented to showcase how NASA data is enabling the development of predictive tools for climate variability and resource management. The poster will present POWER’s future plans including technology development to enhance data traceability and reproducibility and improving I/O performance to support the rapid integration of new EO products, ensuring that POWER remains a robust scalable backend for the evolving landscape of AI-driven Earth Science. Additionally, POWER is developing an AI Agent and an MCP-Server to enable industry AI-Agentic workflows.

Neha Khadka↗
NASA NTRS1987

Lunar base options in support of the permanent habitation of space

An overview of the NASA lunar base program which would establish a permanent beachhead on the moon is given. The lunar base would be used to attain science and astronomy objectives, to manufacture lunar-derived resources (particularly propellant oxygen), to support the growing space infrastructure, and to develop and test technologies that would enable near self-sufficiuency in space, limiting the amount of resources required from earth. Research concerning lunar base development, modeling and simulation are presented, including modeling engines, data bases, and subsystem transforms.

Fairchild, Kyle↗
NASA NTRS2007

The MSFC Systems Engineering Guide: An Overview and Plan

As systems and subsystems requirements become more complex in the pursuit of the exploration of space, advanced technology will demand and require an integrated approach to the design and development of safe and successful space vehicles and there products. System engineers play a vital and key role in transforming mission needs into vehicle requirements that can be verified and validated. This will result in a safe and cost effective design that will satisfy the mission schedule. A key to successful vehicle design within systems engineering is communication. Communication, through a systems engineering infrastructure, will not only ensure that customers and stakeholders are satisfied but will also assist in identifying vehicle requirements; i.e. identification, integration and management. This vehicle design will produce a system that is verifiable, traceable, and effectively satisfies cost, schedule, performance, and risk throughout the life-cycle of the product. A communication infrastructure will bring about the integration of different engineering disciplines within vehicle design. A system utilizing these aspects will enhance system engineering performance and improve upon required activities such as Development of Requirements, Requirements Management, Functional Analysis, Test, Synthesis, Trade Studies, Documentation, and Lessons Learned to produce a successful final product. This paper will describe the guiding vision, progress to date and the plan forward for development of the Marshall Space Flight Center (MSFC) Systems Engineering Guide (SEG), a virtual systems engineering handbook and archive that will describe the system engineering processes that are used by MSFC in the development of complex systems such as the Ares launch vehicle. It is the intent of this website to be a "One Stop Shop" for our systems engineers that will provide tutorial information, an overview of processes and procedures and links to assist system engineering with guidance and references, and provide an archive of systems engineering artifacts produced by the many NASA projects developed and managed by MSFC over the years.

Shelby, Jerry A.↗
NASA NTRS2001

Microwave Remote Sensing and the Cold Land Processes Field Experiment

The Cold Land Processes Field Experiment (CLPX) has been designed to advance our understanding of the terrestrial cryosphere. Developing a more complete understanding of fluxes, storage, and transformations of water and energy in cold land areas is a critical focus of the NASA Earth Science Enterprise Research Strategy, the NASA Global Water and Energy Cycle (GWEC) Initiative, the Global Energy and Water Cycle Experiment (GEWEX), and the GEWEX Americas Prediction Project (GAPP). The movement of water and energy through cold regions in turn plays a large role in ecological activity and biogeochemical cycles. Quantitative understanding of cold land processes over large areas will require synergistic advancements in 1) understanding how cold land processes, most comprehensively understood at local or hillslope scales, extend to larger scales, 2) improved representation of cold land processes in coupled and uncoupled land-surface models, and 3) a breakthrough in large-scale observation of hydrologic properties, including snow characteristics, soil moisture, the extent of frozen soils, and the transition between frozen and thawed soil conditions. The CLPX Plan has been developed through the efforts of over 60 interested scientists that have participated in the NASA Cold Land Processes Working Group (CLPWG). This group is charged with the task of assessing, planning and implementing the required background science, technology, and application infrastructure to support successful land surface hydrology remote sensing space missions. A major product of the experiment will be a comprehensive, legacy data set that will energize many aspects of cold land processes research. The CLPX will focus on developing the quantitative understanding, models, and measurements necessary to extend our local-scale understanding of water fluxes, storage, and transformations to regional and global scales. The experiment will particularly emphasize developing a strong synergism between process-oriented understanding, land surface models and microwave remote sensing. The experimental design is a multi-sensor, multi-scale (1-ha to 160,000 km ^ {2}) approach to providing the comprehensive data set necessary to address several experiment objectives. A description focusing on the microwave remote sensing components (ground, airborne, and spaceborne) of the experiment will be presented.

Kim, Edward J.↗
NASA NTRS2018

Nasa's Launch Communications Ground Segment for the 21st Century Florida Spaceport

The National Aeronautics and Space Administration (NASA) Near Earth Network (NEN) Project is implementing a new launch communications ground segment to provide services for the next generation of human and robotic space exploration systems. It will deliver unique and advanced capabilities to accelerate the transformation of Kennedy Space Center into a multi-user spaceport in cooperation with the United States Air Force (USAF). The project has leveraged commercial technologies and remote operations concepts matured in NASAs orbiting satellite ground systems to achieve dramatic lifecycle cost efficiencies as compared to the space shuttle-era ground segment. The purpose of this paper is to discuss the development history, capabilities and anticipated use cases of the NEN Launch Communications Segment (NEN LCS).The NASA Kennedy Space Center is co-located with the USAF Eastern Launch Range at Cape Canaveral, Florida. The USAF operates two launch communications ground stations, but they are not designed to transmit voice, commands or other data to the launch vehicle or astronauts. The bi-directional uplink-downlink communications responsibility for human missions has historically resided with the Goddard Space Flight Center in Greenbelt, Maryland. Several market analyses and feasibility studies investigating concepts to provide NASAs next generation launch communications services were performed during the Constellation Program prior to its cancellation in 2009, and as part of the Kennedy Space Centers follow-on efforts to transform itself into a 21st century multi-user spaceport. In 2012, the Kennedy Space Center and the USAF 45th Space Wing jointly led a study to analyze the market needs of current and future launch systems and assess the operational deficiencies of the Eastern Range infrastructure. The study team issued several recommendations, two of which ultimately became driving operational capability requirements for the NEN LCS: increased telemetry data rates of at least 20 Mbps, and S-band uplink capability. Additional capabilities identified in the requirements development process include spread spectrum modulation support, LDPC 12 and 78 error correction codes, support for IRIG-106 and CCSDS data formats, automated best source selection, and Space Link Extension (SLE) services for data distribution. The NEN LCS is comprised of two permanent ground stations, the new Kennedy Uplink Station (KUS) and refurbished Ponce de Leon (PDL) station. Both stations are remotely operated from the Global Monitor and Control Center at Wallops Flight Facility. This core architecture is extensible through host-tenant arrangements with the U.S. Air Force and deployable assets, enabling agile, tailored and robust solutions to meet the needs of civil, commercial or military customers. The NEN LCS has three use cases:1.To provide agile, tailored and robust launch communications solutions to Florida spaceport customers2.To provide orbital communications services to near-earth customers 3.To provide an experimental proving ground for Space Mobile Network concepts and technologies The NEN LCS driving mission is to support the bi-directional link with the Orion crew capsule and two 20 Mbps telemetry links from the Space Launch System core stage on Exploration Mission-1, the first integrated flight of NASAs flagship human exploration systems.

Roberts, Christopher J.↗
NASA NTRS2007

Integrating Automation into a Multi-Mission Operations Center

NASA Goddard Space Flight Center's Space Science Mission Operations (SSMO) Project is currently tackling the challenge of minimizing ground operations costs for multiple satellites that have surpassed their prime mission phase and are well into extended mission. These missions are being reengineered into a multi-mission operations center built around modern information technologies and a common ground system infrastructure. The effort began with the integration of four SMEX missions into a similar architecture that provides command and control capabilities and demonstrates fleet automation and control concepts as a pathfinder for additional mission integrations. The reengineered ground system, called the Multi-Mission Operations Center (MMOC), is now undergoing a transformation to support other SSMO missions, which include SOHO, Wind, and ACE. This paper presents the automation principles and lessons learned to date for integrating automation into an existing operations environment for multiple satellites.

Surka, Derek M.↗
NASA NTRS2020

TopiQAL: Topic-aware Question Answering using Scalable Domain-specific Supercomputers

We all have questions. About today's temperature, scores of our favorite baseball team, the Universe, and about vaccine for COVID-19. Life, physical, and natural scientists have been trying to find answers to various topics using scientific methods and experiments, while computer scientists have built language models as a tiny step towards automatically answering all of these questions across domains given a little bit of context. In this paper, we propose an architecture using state-of-the-art Natural Language Processing language models namely Topic Models and Bidirectional Encoder Representations from Transformers (BERT) that can transparently and automatically retrieve articles of relevance to questions across domains, and fetch answers to topical questions related to COVID-19 current and historical medical research literature. We demonstrate the benefits of using domain-specific supercomputers like Tensor Processing Units (TPUs), residing on cloud-based infrastructure, using which we could achieve significant gains in training and inference times, also with very minimal cost.

Penberthy, Scott↗
NASA NTRS2012

Transforming a Single-Use Spaceport to Multi-Use

The end of the Space Shuttle program brought new challenges as well as new opportunities to the John F. Kennedy Space Center. The challenge is to engineer a more flexible Spaceport to be capable of supporting manufacturing, assembly, testing, processing and launch operations for multiple spacecrafts and launch vehicle configurations. The new spaceport must support multiple commercial as well as government entities while leveraging existing infrastructure to the greatest extent possible. This paper addresses key engineering challenges during Spaceport design and development and will look at possible engineering solutions while considering reusability of legacy systems and infrastructure adaptability with emphasis on flexibility and reduction of operating cost.

Delgado, Hector N.↗
NASA NTRSDate not supplied

NASA and Advanced Air Mobility (AAM) National Campaign (NC) Tech Talk: Integrated Data Product

NASA Advanced Air Mobility (AAM) National Campaign has hosted multiple flight tests in a effort to promote public confidence and accelerate the realization of emerging aviation markets for passenger and cargo transportation in urban, suburban, rural, and regional environments. The goals and objectives for each flight test are intended to assess the performance of the vehicle’s capacity to operate safely, efficiently, and sustainably in urban areas. The Airspace Test and Infrastructure (ATI) team processes the flight data to evaluate the effectiveness of air vehicle and airspace management integration, while its analysis capabilities support the assessment of the efficacy of proposed vehicles and ground systems required to enable the vehicles’ operations. The ATI data services team creates many products from the data, first by transforming and merging the data into a single Integrated Data Product (IDP). This aligns data from many sources by time, so that, for example, the winds that impacted a flight can be aligned with its ground track and speed. A detailed IDP enables many types of statistical computation and visualizations that help researchers understand what transpired during the flight and how it can be explained. This Tech Talk will give an overview of the IDP process, including examples of the resulting products created by the data services team. It will also share an application that will allow participants to perform their own data analysis.

National Campaign, Advanced Air Mobility, Integrat↗
NASA NTRS2005

Evaluation of a Shuttle Derived Vehicle (SDV) for Cargo Transportation

In this new era of space exploration, a host of launch vehicles are being examined for possible use in transporting cargo and crew to low Earth orbit and beyond. Launch vehicles derived from the Space Shuttle Program (SSP), known as Shuttle Derived Vehicles (SDVs), are prime candidates for heavy-lift duty because of their potential to minimize non-recurring costs and because the Shuttle can leverage off proven high-performance flight systems with established ground and flight support. To determine the merits of SDVs, a detailed evaluation was performed. This evaluation included a trade study and risk assessment of options based on performance, safety reliability, cost, operations, and evolution. The purpose of this paper is to explain the approach, processes, and tools used to evaluate launch vehicles for heavy lift cargo transportation. The process included defining the trade space, characterizing the concepts, analyzing the systems, and scoring the options. The process also included a review by subject experts from NASA and industry to compare past and recent study data and assess the risks. A set of technical performance measures (TPMs) was generated based on the study requirements and constraints. Tools such as INTROS and POST were used to calculate performance, FIRST was used for prediction of reliability, and other software packages, both commercial and NASA-owned, were applied to study the trade space. By following a clear process and using the right tools a thorough assessment was performed. An SDV can be classified as either a side-mount vehicle (SMV) or an in-line vehicle OLV). An SMV is a Space Shuttle where the Orbiter is replaced by a cargo carrier. An ILV is comprised of a modified Shuttle External Tank (ET) with engines mounted to the bottom and cargo mounted atop. For both families of vehicles, Solid Rocket Boosters (SRBs) are attached to the ET. The first derivate of Shuttle is defined as the vehicle with minimum changes necessary to transform the Space Shuttle into an SDV. Deltas from the first derivate were also formulated to study more SDV options. Examples of deltas include replacing the SRBs with larger and/or more SRBs, adding an upper stage, increasing the size of the ET, changing the engines, and modifying the elements. Challenges for SDV range from tailoring infrastructure to meeting the exploration schedule. Although SDV is based on the Space Shuttle, it still includes development risk for designing and building a Cargo Carrier. There are also performance challenges in that Shuttle is not optimized for cargo-only missions, but it is a robust system built on reusability. Balancing the strengths and weaknesses of the Shuttle to meet Lunar and Mars mission objectives provides the framework for an informative trade study. SDV was carefully analyzed and the results of the study provide invaluable data for use in the new exploration initiative.

Roman, Jose M.↗
NASA NTRS1994

Fuzzy self-learning control for magnetic servo system

It is known that an effective control system is the key condition for successful implementation of high-performance magnetic servo systems. Major issues to design such control systems are nonlinearity; unmodeled dynamics, such as secondary effects for copper resistance, stray fields, and saturation; and that disturbance rejection for the load effect reacts directly on the servo system without transmission elements. One typical approach to design control systems under these conditions is a special type of nonlinear feedback called gain scheduling. It accommodates linear regulators whose parameters are changed as a function of operating conditions in a preprogrammed way. In this paper, an on-line learning fuzzy control strategy is proposed. To inherit the wealth of linear control design, the relations between linear feedback and fuzzy logic controllers have been established. The exercise of engineering axioms of linear control design is thus transformed into tuning of appropriate fuzzy parameters. Furthermore, fuzzy logic control brings the domain of candidate control laws from linear into nonlinear, and brings new prospects into design of the local controllers. On the other hand, a self-learning scheme is utilized to automatically tune the fuzzy rule base. It is based on network learning infrastructure; statistical approximation to assign credit; animal learning method to update the reinforcement map with a fast learning rate; and temporal difference predictive scheme to optimize the control laws. Different from supervised and statistical unsupervised learning schemes, the proposed method learns on-line from past experience and information from the process and forms a rule base of an FLC system from randomly assigned initial control rules.

Tarn, J. H.↗
NASA NTRSDate not supplied

Waste Materials Recycling for In-Space Manufacturing

Logistics and resupply payloads for Lunar and Martian missions are significantly more cost and schedule prohibitive compared to LEO destinations. Recycling of waste and trash materials generated throughout the duration of a mission, as well as previous missions, will be critical for enabling sustained human presence beyond Earth. Currently, no solution exists for recycling waste materials back into feedstock form beyond entry-level hobbyist equipment, which is not suitable nor practical for space applications. There is already over 500,000 lbs of trash on the moon from previous missions, which will grow exponentially over the coming decade throughout the Artemis Campaign. Waste and trash materials are precious resources that, if recovered and properly processed, can be transformed back into usable feedstock form for on-demand manufacturing capabilities. Hence, it is prudent that a recycling solution be developed and infused into future missions.

additive↗
NASA NTRS1992

Technology for libraries and information centers: A seminar in Greece, Portugal, and Turkey

Information technologies are evolving at a rapid pace in today's world. But the electronic technologies needed to transform today's libraries and information centers into electronic 'libraries without walls', where an end-user has instantaneous access to all the information needed from a desktop workstation, have not yet arrived. Even so, there are many technologies available today that can be applied in the library/information center environment to yield increased productivity. However, not all technologies are right for or successful in every environment. Mission, budget, infrastructure, client profiles, and staff skills are a few of the 'environmental' issues that must be considered when selecting and introducing new technologies into a particular information center. Key technologies used in libraries today are reviewed; it can be used as background for targeting technologies that could be successfully implemented in your own environment to further service goals. Before focusing on a selection of technologies, you must first focus on the strategic goal of your organization. The same technology is not right for every library/information center. An overview of technologies that are readily available and can be applied today is presented.

Cotter, Gladys A.↗
NASA NTRS2023

Distributed Sensing and Reasoning for Advanced Air Mobility Health Management and Mission Assurance

As envisioned, Advanced Air Mobility (AAM) and Urban Air Mobility (UAM) will introduce new vehicles and operations within the national airspace, moving people and cargo safely and efficiently at a much larger scale than today. Driven by transformative technology and revolutionary aircraft, this movement must still manage technical, regulatory, operational, and policy challenges. NASA’s work in support of AAM and UAM includes, but is not limited to tools, technologies, and architectures for distributed sensing of aircraft, data & reasoning services exchange, Human-Autonomy Teaming (HAT), contingency management, and vehicle health management. This paper builds upon these concepts and evaluates the use of distributed sensing and infrastructure assistance towards health management and mission assurance of UAM vehicles in specific operational scenarios. Through analysis of these example missions, aided by the data produced by the conceptual distributed sensing and reasoning infrastructure, we define opportunities for state estimation, diagnosis, and key decision points affecting the health state of the vehicle and the airspace volume. As a result, we define a number of measurable health state parameters providing relevant information to drive decision-making in contingency situations or feed automation tools in support of operators and managers.

Safety↗
NASA NTRSDate not supplied

Materials Informatics at NASA GRC: Machine Learning Surrogate Modeling, Data Management, and Integrated Toolsets for Establishing/Maintaining the Digital Thread

Integrated Computational Materials Engineering (ICME) has recently received widespread attention due to its promises in reducing dependence on physical testing for engineering design by relying on simulation, reducing both time and cost to market for various applications. ICME however requires validated multiscale material models, which heavily depend on available test data with full material and test pedigree, including material processing, test and measurement equipment, raw data collection, and analysis methodology and results that is findable and usable, along with integrated, efficient toolsets for effectively passing information across various length and time scales across such models. At the NASA Glenn Research Center under the Transformational Tools and Technologies Project, significant recent efforts have been directed towards establishing the required cyberinfrastructure to enable optimized ICME processes and the design of “fit-for-purpose” materials to achieve the goals outlined in the NASA Vision 2040 report. Such efforts include development of multiscale physics-based material models, which can be used to train highly efficient surrogate machine learning models, development of best practices and infrastructure for effective, traceable materials information management, and development of toolsets that integrate with physics-based codes, machine learning models, and an information management system to enable high throughput of materials data collection and analysis, establishment of digital twins and the digital thread, and automation of the ICME design process for material optimization.

Machine Learning↗
NASA NTRS2004

NASA Workshop on Technology for Human Robotic Exploration and Development of Space

Continued constrained budgets and growing interests in the industrialization and development of space requires NASA to seize every opportunity for assuring the maximum return on space infrastructure investments. This workshop provided an excellent forum for reviewing, evaluating, and updating pertinent strategic planning, identifying advanced concepts and high-risk/high-leverage research and technology requirements, developing strategies and roadmaps, and establishing approaches, methodologies, modeling, and tools for facilitating the commercial development of space and supporting diverse exploration and scientific missions. Also, the workshop addressed important topic areas including revolutionary space systems requiring investments in innovative advanced technologies; achieving transformational space operations through the insertion of new technologies; revolutionary science in space through advanced systems and new technologies enabling experiments to go anytime to any location; and, innovative and ambitious concepts and approaches essential for promoting advancements in space transportation. Details concerning the workshop process, structure, and results are contained in the ensuing report.

Mankins, J. C.↗