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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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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

The autonomous sciencecraft constellations

The Autonomous Sciencecraft Experiment (ASE) will fly onboard the Air Force TechSat 21 constellation of three spacecraft scheduled for launch in 2006. ASE uses onboard continuous planning, robust task and goal-based execution, model-based mode identification and reconfiguration, and onboard machine learning and pattern recognition to radically increase science return by enabling intelligent downlink selection and autonomous retargeting. In this paper we discuss how these AI technologies are synergistically integrated in a hybrid multi-layer control architecture to enable a virtual spacecraft science agent. Demonstration of these capabilities in a flight environment will open up tremendous new opportunities in planetary science, space physics, and earth science that would be unreachable without this technology.

Autonomous Sciencecraft Experiment ASE AI technolo↗
NASA NTRS2002

Spacecraft autonomy using onboard processing for a SAR constellation mission

The Autonomous Sciencecraft Experiment (ASE) will fly onboard the Air Force TechSat 21 constellation of three spacecraft scheduled for launch in 2006. ASE uses onboard continuous planning, robust task and goal-based execution, model-based mode identification and reconfiguration, and onboard machine learning and pattern recognition to radically increase science return by enabling intelligent downlink selection and autonomous retargeting. In this paper we discuss how these AI technologies are synergistically integrated in a hybrid multi-layer control architecture to enable a virtual spacecruft science agent. Demonstration of these capabilities in a flight environment will open up tremendous new opportunities in planetary science, space physics, and earth science that would be unreachable without this technology.

Autonomous Sciencecraft Experiment ASE virtual spa↗
NASA NTRSDate not supplied

ExMC Digital Engineering

Future missions beyond Artemis II will become increasingly complex as multiple vehicles (e.g., Gateway, Human Landing System (HLS), and Extravehicular Activity and Human Surface Mobility Program (EHP)), each having their own Program requirements and other associated documentation, which will need to be integrated into a single mission. Currently, the Human Health and Performance Directorate (HHPD)Program Support Teams mostly use documents to manage, perform, and archive their analyses. Identifying an opportunity for efficiency, ExMC demonstrated the ability to utilize MagicDraw, a Model-Based Systems Engineering (MBSE) tool, as a requirements database with traceability, dependencies, and relationships in one place. Rather than existing in documents, emails, and historical knowledge, ExMC pursued a Digital Engineering (DE) effort in coordination with HHPD by combining MBSE tools with other digital platforms to manage and develop user-defined databases and interfaces. This DE approach is aimed to simplify processes and reduce risk through the unification of requirements into a centralized digital network, improving collaboration, decision-making, and transparency compared to isolated documents and knowledge. However, manipulating data views and content in MagicDraw requires a steep learning curve not needed by all users and even the user-friendly web view comes with downsides due to the static views. To provide a more dynamic user interface, ExMC investigated the use of Microsoft Power Platform which does not require as steep of a learning curve to become proficient. This introduces analytics to the DE infrastructure, offering customizable and dynamic data dashboards. ExMC continues developing these dashboards and tailoring the DE infrastructure in alignment with HHPD workforce needs.

M Krihak↗
NASA NTRS1996

Lessons Learned From the Flight of the NASA In-Step Cryo System Experiment

The Cryo System Experiment was developed to validate in near zero-g space a 65 K cryogenic system for focal planes, optics, or other imaging instruments that require continuous cryogenic cooling. Two key cryogenic technologies, designed to improve performance of systems for scientific, commercial and defense applications in space, were successfully demonstrated on a February 1995 Shuttle mission. The two were a 2-watt 65 K long-life low- vibration Stirling cooler and a diode oxygen heat pipe thermal switch. Lessons learned are presented.

cryogenics↗
NASA NTRS2022

Multisensor Machine Learning to Retrieve High Spatiotemporal Resolution Land Surface Temperature

Climate change is making heat waves more frequent, long-lasting, and severe. While multiple satellite types provide data to monitor surface temperature, geostationary (GEO) sensors provide near-continuous, continental-scale observations which can better capture the diurnal variability of land surface temperature (LST) than intermittent observations from low-earth orbit (LEO) sensors. However, standard products from GEO satellites are available at coarsened spatial and temporal resolutions compared to the native sensor resolution. Using datasets from the NASA Earth Exchange, we leveraged co-located, co-temporal observations from LEO and GEO satellites to learn a data-driven mapping using a convolutional neural network. The resulting NASA Earth eXchange Artificial Intelligence LST (NEXAI-LST) achieved a mean absolute error of 1.73 K relative to the target LEO product and improves on both spatial and temporal resolution [2 km, 10 minute] compared to the GEO full disk standard product [10 km, hourly]. In validation against measurements from a ground-based sensor network, NEXAI-LST achieves similar or better fit than both LEO and GEO standard products, while depending none of the prior knowledge of land surface and atmospheric states required by physical-statistical models. Further, application of the model to unseen LEO and GEO satellites demonstrates robust generalization of the model across spatial region, time of day, and sensor. In support of NASA’s open-source science initiative, we make our NEXAI-LST product, model, and codes available to facilitate data exploration and further studies.

Kate Marie Duffy↗
DOE OSTI2025

deadtrees.earth — An open-access and interactive database for centimeter-scale aerial imagery to uncover global tree mortality dynamics

Excessive tree mortality is a global concern and remains poorly understood as it is a complex phenomenon. We lack global and temporally continuous coverage on tree mortality data. Ground-based observations on tree mortality, e.g., derived from national inventories, are very sparse, and may not be standardized or spatially explicit. Earth observation data, combined with supervised machine learning, offer a promising approach to map overstory tree mortality in a consistent manner over space and time. However, global-scale machine learning requires broad training data covering a wide range of environmental settings and forest types. Low altitude observation platforms (e.g., drones or airplanes) provide a cost-effective source of training data by capturing high-resolution orthophotos of overstory tree mortality events at centimeter-scale resolution. Here, we introduce deadtrees.earth, an open-access platform hosting more than two thousand centimeter-resolution orthophotos, covering more than 1,000,000 ha, of which more than 58,000 ha are manually annotated with live/dead tree classifications. This community-sourced and rigorously curated dataset can serve as a comprehensive reference dataset to uncover tree mortality patterns from local to global scales using space-based Earth observation data and machine learning models. This will provide the basis to attribute tree mortality patterns to environmental changes or project tree mortality dynamics to the future. The open nature of deadtrees.earth, together with its curation of high-quality, spatially representative, and ecologically diverse data will continuously increase our capacity to uncover and understand tree mortality dynamics.

Citizen science↗
DOE OSTI2024

Utility and Industry Perceptions of Control Room Modernization Over the Last 10 Years

Within the current United States (U.S.) nuclear power fleet, main control room modernization (CRM) is an important step towards cost savings. In recent decades, plants have been engaged in upgrades to varying degrees. This process requires a nuanced, balanced, and timely approach that ensures continued safety and long-term sustainability. In 2012 a survey was issued to individuals from the nuclear industry to learn their perspectives on a range of CRM issues. The survey targeted the benefits and challenges for utilities undertaking this process, including the main drivers and barriers to technology upgrades, regulatory compliance, and the effects these factors have on concepts of operations, strategic approaches, and staffing. In 2022, the survey was issued again to understand whether CRM perceptions had changed in the last 10 years. Our findings identify changes in industry thinking from a decade ago. Here we reveal perspective shifts that represent increased optimism and, in some instances, increased doubt regarding the opportunities and challenges inherent in CRM and implementation. We also report nuanced differences in CRM perspectives between utility and surrounding nuclear industry respondents.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

STag. II. Classification of Serendipitous Supernovae Observed by Galaxy Redshift Surveys

With the number of supernovae observed expected to drastically increase thanks to large-scale surveys like the Dark Energy Spectroscopic Instrument (DESI), it is necessary that the tools we use to classify these objects keep up with this increase. We previously created Supernova Tagging and Classification (STag) to address this problem by employing machine learning techniques alongside logistic regression in order to assign “tags” to spectra based on spectral features. STag II is a continuation of this work, which now makes use of model supernova spectra combined with real DESI spectra in order to train STag to better deal with realistic data. Furthermore, we also make use of the rlap score as a trustworthiness cut, making for a more robust and accurate supernova classifier than before.

Astrostatistics techniques↗
NASA NTRS1991

Visual and near-IR spectrophotometry of asteroids

We have been continuing our studies of the spectral properties of dark asteroids in the solar system. From these studies we expect to learn about the distribution of volatile materials, such as water in clay materials (water of hydration) and how the asteroids may relate to the comets. Our most recent work has been concentrating on simultaneous visual and near infrared photometry near Earth, main belt, and trojan asteroids. We have made observations of some unusual asteroids such as Chiron, which has recently shown cometary activity, and 944 Hidalgo, which has a comet-like orbit. We have also begun studies of the small, dark satellites of Mars and Jupiter in order to understand better how they may relate to the steroids. Could they actually be captured asteroids or comets?

Lebofsky, Larry A.↗
NASA NTRS2002

The K-8 Aeronautics Internet Textbook

Efforts were focused on web site migration, from UC (University of California) Davis to the National Business Aviation Association's (NBAA) web site. K8AIT (K-8 Aeronautics Internet Textbook), which has remained an unadvertised web site, receives almost two million hits per month. Project continuation funding with the National Business Aviation Association is being pursued. A Memorandum of Understanding (MOU) between NASA Ames LTP (Learning Technologies Project) and Cislunar has been drafted and approved by NASA's legal department. Additional web content on space flight and the Wright brothers has been added in English and Spanish.

Source record↗
NASA NTRS2000

Project Galileo: completing Europa, preparing for Io

Galileo has completed the Europa leg of the Galileo Europa Mission, and is now pumping down the apojove in each succeeding orbit in preparation for the Io phase. Including three encounters earlier in the primary mission, the total of ten close passes by Europa have provided a wealth of interesting and provocative information about this intriguing body. The results presented include new and exciting information about Europa's interactions with Jupiter's magnetosphere, its interior structure, and its tantalizing surface features, which strongly hint at a watery subsurface layer. Additional data concerning Callisto, and its own outlook for a subsurface ocean are also presented. In addition the engineering aspects of operating the spacecraft during the past year are explored, as well as a brief examination of what will be the challenges to prepare for the Io encounters. The steadily increasing radiation dosage that the spacecraft is experiencing is well beyond the original design parameters, and is contributing to a number of spacecraft problems and concerns. The ability of the flight team to analyze and solve these problems, even at the reduced staffing levels of an extended mission, is a testament to their tenacity and loyalty to the mission. The engineering data being generated by these continuing radiation-induced anomalies will prove invaluable to designers of future spacecraft to Jupiter and its satellites. The lessons learned during this arduous process are presented. c 2000 International Astronautical Federation. Published by Elsevier Science Ltd. All rights reserved.

long duration↗
NASA NTRS2006

NASA Exploration Launch Projects Overview: The Crew Launch Vehicle and the Cargo Launch Vehicle Systems

The U.S. Vision for Space Exploration (January 2004) serves as the foundation for the National Aeronautics and Space Administration's (NASA) strategic goals and objectives. As the NASA Administrator outlined during his confirmation hearing in April 2005, these include: 1) Flying the Space Shuttle as safely as possible until its retirement, not later than 2010. 2) Bringing a new Crew Exploration Vehicle (CEV) into service as soon as possible after Shuttle retirement. 3) Developing a balanced overall program of science, exploration, and aeronautics at NASA, consistent with the redirection of the human space flight program to focus on exploration. 4) Completing the International Space Station (ISS) in a manner consistent with international partner commitments and the needs of human exploration. 5) Encouraging the pursuit of appropriate partnerships with the emerging commercial space sector. 6) Establishing a lunar return program having the maximum possible utility for later missions to Mars and other destinations. In spring 2005, the Agency commissioned a team of aerospace subject matter experts to perform the Exploration Systems Architecture Study (ESAS). The ESAS team performed in-depth evaluations of a number of space transportation architectures and provided recommendations based on their findings? The ESAS analysis focused on a human-rated Crew Launch Vehicle (CLV) for astronaut transport and a heavy lift Cargo Launch Vehicle (CaLV) to carry equipment, materials, and supplies for lunar missions and, later, the first human journeys to Mars. After several months of intense study utilizing safety and reliability, technical performance, budget, and schedule figures of merit in relation to design reference missions, the ESAS design options were unveiled in summer 2005. As part of NASA's systems engineering approach, these point of departure architectures have been refined through trade studies during the ongoing design phase leading to the development phase that begins in 2008. Comprehensive reviews of engineering data and business assessments by both internal and independent reviewers serve as decision gates to ensure that systems can fully meet customer and stakeholder requirements. This paper provides the current CLV and CaLV configuration designs and gives examples of the progress being made during the first year of this significant effort. Safe, reliable, cost-effective space transportation systems are a foundational piece of America s future in space and the next step in realizing the plan for revitalizing lunar capabilities on the passageway to the human exploration of Mars. While building on legacy knowledge and heritage hardware for risk reduction, NASA will apply lessons learned from developing these new launch vehicles to the growth path for future missions. The elements for mission success and continued U.S. leadership in space have been assembled over the past year. As NASA designs and develops these two new systems over the next dozen years, visible progress, such as that reported in this paper, may sustain the national will to stay the course across political administrations and weather the inevitable trials that will be experienced during this challenging endeavor.

Snoddy, Jimmy R.↗
NASA NTRS2004

Multisensor Arrays for Greater Reliability and Accuracy

Arrays of multiple, nominally identical sensors with sensor-output-processing electronic hardware and software are being developed in order to obtain accuracy, reliability, and lifetime greater than those of single sensors. The conceptual basis of this development lies in the statistical behavior of multiple sensors and a multisensor-array (MSA) algorithm that exploits that behavior. In addition, advances in microelectromechanical systems (MEMS) and integrated circuits are exploited. A typical sensor unit according to this concept includes multiple MEMS sensors and sensor-readout circuitry fabricated together on a single chip and packaged compactly with a microprocessor that performs several functions, including execution of the MSA algorithm. In the MSA algorithm, the readings from all the sensors in an array at a given instant of time are compared and the reliability of each sensor is quantified. This comparison of readings and quantification of reliabilities involves the calculation of the ratio between every sensor reading and every other sensor reading, plus calculation of the sum of all such ratios. Then one output reading for the given instant of time is computed as a weighted average of the readings of all the sensors. In this computation, the weight for each sensor is the aforementioned value used to quantify its reliability. In an optional variant of the MSA algorithm that can be implemented easily, a running sum of the reliability value for each sensor at previous time steps as well as at the present time step is used as the weight of the sensor in calculating the weighted average at the present time step. In this variant, the weight of a sensor that continually fails gradually decreases, so that eventually, its influence over the output reading becomes minimal: In effect, the sensor system "learns" which sensors to trust and which not to trust. The MSA algorithm incorporates a criterion for deciding whether there remain enough sensor readings that approximate each other sufficiently closely to constitute a majority for the purpose of quantifying reliability. This criterion is, simply, that if there do not exist at least three sensors having weights greater than a prescribed minimum acceptable value, then the array as a whole is deemed to have failed.

Immer, Christopher↗
NASA NTRSDate not supplied

Component-Based Development of CFD Software FUN3D

FUN3D, a suite of Computational Fluid Dynamics simulation and design tools developed at the NASA Langley Research Center, has undergone continuous development since the late1980s. It contains a large portion of legacy code. Extending it with new capabilities becomes increasingly difficult. To improve the extensibility and reusability, FUN3D is moving toward component-based development. New features, such as Stabilized Finite Elements, Yoga, and Sparse Linear Algebra Toolkit, are integrated into the system as components. Some existing features such as the Node-Centered Finite Volume Solver, are also being refactored to components. The integration of these components poses new requirements on the development workflow. In this paper, we describe the Continuous Integration of FUN3D to support component-based development, and discuss the tools used, the practices followed, and lessons learned during the transition from the traditional approach.

computational fluid dynamics software↗
NASA NTRS2024

Earth Independent Medical Operations (EIMO) DATASCOPE Technical Interchange Meeting 21st August 2023: Background and Summary of Discussion

An aspiration for EIMO datascope is to realize artificial intelligence-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A vision proposed to the meeting participants was that of a “system of systems,” whereby EIMO will utilize AI-supported natural language processing and machine learning techniques to synthesize embedded reference databases and real-time data streams [input vectors] from multiple data sources to continuously and seamlessly assess crew health & performance. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will ideally have a degree of mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats.

Artificial Intelligence↗
DOE OSTI2025

A Digital Twin Framework Utilizing Machine Learning for Robust Predictive Maintenance: Enhancing Tire Health Monitoring

We introduce a novel digital twin (DT) framework for the predictive maintenance of long-term physical systems. Using monitoring tire health as an application, we show how the DT framework can be used to enhance automotive safety and efficiency, and how the technical challenges can be overcome using a three-step approach. First, to manage the data complexity over a long operation span, we employ data reduction techniques to concisely represent physical tires using historical performance and usage data. Relying on these data, for fast real-time prediction, we train a transformer-based model offline on our concise dataset to predict future tire health over time, represented as remaining casing potential (RCP). Based on our architecture, our model quantifies both epistemic and aleatoric uncertainties, providing reliable confidence intervals around predicted RCP. Second, to incorporate real-time data, we update the predictive model in the DT framework, ensuring its accuracy throughout its lifespan with the aid of hybrid modeling and the use of the discrepancy function. Third, to assist decision-making in predictive maintenance, we implement a tire state decision algorithm, which strategically determines the optimal timing for tire replacement based on RCP forecasted by our transformer model. This approach ensures that our DT accurately predicts system health, continually refines its digital representation, and supports predictive maintenance decisions. Furthermore, our framework effectively embodies a physical system, leveraging big data and machine learning (ML) for predictive maintenance, model updates, and decision-making.

advanced computing infrastructure↗
NASA NTRS2006

Food and Nutrition for the Moon Base: What we have Learned in 45 Years of Space Flight

The United States has a new human space flight mission to return to the Moon, this time to establish an outpost to continue research there and develop our ability to send humans to Mars and bring them back in good health. The Apollo missions were the first human expeditions to the Moon. Only 2 crew members landed on the lunar surface on each Apollo mission, and they spent a maximum of 72 hours there. Future trips will have at least 4 crew members, and the initial trips will include several days of surface activity. Eventually, these short (sortie) missions will extend to longer lunar surface times, on the order of weeks. Thus, the challenges of meeting the food and nutritional needs of crew members at a lunar outpost will be significantly different from those during the early Apollo missions. The U.S. has had humans in space beginning in 1961 with increasing lengths of time in space flight. Throughout these flights, the areas of particular concern for nutrition are body mass, bone health, and radiation protection. The development and refinement of the food systems over the last 30 years are discussed, as well as the plans for both the sortie and lunar. The articles briefly review what we know today about food and nutrition for space travelers and relate this knowledge to our planned human flights back to the Moon.

Lane, Helen↗
NASA NTRS1994

(abstract) The IRAS All-Sky Survey: Scientific and Technical Lessons Learned

Although the Infrared Astronomy Satellite (IRAS) was launched over 10 years ago, the IRAS legacy of catalogs, images, and data archives remains a vital source of information on the infrared sky. Over 4000 papers in the refereed literature have used IRAS data, and this number continues to grow. IRAS has touched on almost all aspects of astronomy, from the solar system and the interstellar medium to the formation of stars and the formation of galaxies. In this talk I will give a brief overview of the scientific results from IRAS. I will also discuss some of the operational and technical lessons learned by IRAS that may be of relevance to the upcoming ISO mission, and to future missions that must be defined in an era of declining budgets for space science.

costs operations ISO↗