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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 NTRS1991

NASA/Ames Research Center's science and applications aircraft program

NASA-Ames Research Center operates a fleet of seven Science and Applications Aircraft, namely the C-141/Kuiper Airborne Observatory (KAO), DC-8, C-130, Lear Jet, and three ER-2s. These aircraft are used to satisfy two major objectives, each of equal importance. The first is to acquire remote and in-situ scientific data in astronomy, astrophysics, earth sciences, ocean processes, atmospheric physics, meteorology, materials processing and life sciences. The second major objective is to expedite the development of sensors and their attendant algorithms for ultimate use in space and to simulate from an aircraft, the data to be acquired from spaceborne sensors. NASA-Ames Science and Applications Aircraft are recognized as national and international facilities. They have performed and will continue to perform, operational missions from bases in the United States and worldwide. Historically, twice as many investigators have requested flight time than could be accommodated. This situation remains true today and is expected to increase in the years ahead. A major advantage of the existing fleet of aircraft is their ability to cover a large expanse of the earth's ecosystem from the surface to the lower stratosphere over large distances and time aloft. Their large payload capability allows a number of scientists to use multi-investigator sensor suites to permit simultaneous and complementary data gathering. In-flight changes to the sensors or data systems have greatly reduced the time required to optimize the development of new instruments. It is doubtful that spaceborne systems will ever totally replace the need for airborne science aircraft. The operations philosophy and capabilities exist at NASA-Ames Research Center.

Hall, G. Warren↗
NASA NTRS1991

NASA's advanced space transportation system launch vehicles

Some insight is provided into the advanced transportation planning and systems that will evolve to support long term mission requirements. The general requirements include: launch and lift capacity to low earth orbit (LEO); space based transfer systems for orbital operations between LEO and geosynchronous equatorial orbit (GEO), the Moon, and Mars; and Transfer vehicle systems for long duration deep space probes. These mission requirements are incorporated in the NASA Civil Needs Data Base. To accomplish these mission goals, adequate lift capacity to LEO must be available: to support science and application missions; to provide for construction of the Space Station Freedom; and to support resupply of personnel and supplies for its operations. Growth in lift capacity must be time phased to support an expanding mission model that includes Freedom Station, the Mission to Planet Earth, and an expanded robotic planetary program. The near term increase in cargo lift capacity associated with development of the Shuttle-C is addressed. The joint DOD/NASA Advanced Launch System studies are focused on a longer term new cargo capability that will significantly reduce costs of placing payloads in space.

Branscome, Darrell R.↗
NASA NTRS1993

The Telecommunications and Data Acquisition Report

This quarterly publication provides archival reports on developments in programs managed by JPL's Office of Telecommunications and Data Acquisition (TDA). In space communications, radio navigation, radio science, and ground-based radio and radar astronomy, it reports on activities of the Deep Space Network (DSN) in planning, supporting research and technology, implementation, and operations. Also included are standards activity at JPL for space data and information systems and reimbursable DSN work performed for other space agencies through NASA. The preceding work is all performed for NASA's Office of Space Communications (OSC). The TDA Office also performs work funded by another NASA program office through and with the cooperation of OSC. This is the Orbital Debris Radar Program with tile Office of Space Systems Development. The TDA Office is directly involved in several tasks that directly support the Office of Space Science (OSS), with OSC funding DSN operational support. In radio science, The TDA Progress Report describes the spacecraft radio science program conducted using tile DSN. For the High-Resolution Microwave Survey (HRMS), the report covers implementation and operations for searching the microwave spectrum. In solar system radar, it reports on the uses of the Goldstone Solar System Radar for scientific exploration of the planets, their rings and satellites, asteroids, and comets. In radio astronomy, the areas off support include spectroscopy, very long baseline interferometry, and astrometry.

Edward C Posner↗
DOE OSTI2025

Toward Drilling the Perfect Geothermal Well: An International Research Coordination Network for Geothermal Drilling Optimization Supported by Deep Machine Learning and Cloud Based Data Aggregation

The EDGE project, supported by the U.S. Department of Energy Geothermal Technologies Office under award DE-EE0008793, established a data-driven framework for improving the efficiency, cost-effectiveness, and reliability of geothermal well drilling. The project focused on developing scalable data infrastructure, advanced machine learning and probabilistic models, and integrated analytics tools to support continuous drilling optimization. A central objective was to reduce geothermal drilling costs by up to seventy percent while minimizing the risk of well failure through predictive diagnostics and adaptive planning. Over the project period, a comprehensive data repository was designed and deployed, incorporating records from over one hundred geothermal wells across varied geological settings. This repository supported both structured and unstructured data and adhered to FAIR data principles, enabling provenance tracking, quality control, and standardized metadata. The project introduced automated ingestion pipelines and a cloud-hosted platform that facilitated access to raw, processed, and derived datasets. This infrastructure served as the foundation for model development and analysis. Machine learning workflows were developed to predict key drilling metrics including rate of penetration, non-productive time, and total drilling costs. Self-organizing maps and dimensionality reduction methods were used to uncover operational patterns and outliers, while supervised learning algorithms such as random forests and deep neural networks were applied to forecast performance outcomes. The models were validated on heterogeneous datasets from both U.S. and Icelandic fields, demonstrating variable but significant predictive accuracy. The results indicated that finer temporal resolution, inclusion of lithological data, and consistency in operational annotations could substantially improve model performance. The project also implemented process mining techniques to reconstruct state-transition models from drilling event logs. These models enabled the identification of deviations from optimal workflows and provided insights into recurring failure modes. Analysis of non-productive time highlighted the impact of equipment failures, geological challenges, and human factors, offering opportunities for targeted mitigation strategies. The EDGE Dashboard was developed as a web-based expert system integrating data visualization, model outputs, and user-driven queries. It provided an accessible interface for operators to explore historical data, evaluate predicted outcomes, and compare drilling scenarios. Initial feedback from project partners suggested that the dashboard could serve as a foundation for more advanced advisory and optimization tools. Overall, the EDGE project demonstrated the feasibility and value of applying modern data science techniques to geothermal drilling. It delivered a set of interoperable tools and models that can support more efficient, lower-risk well development. The findings point toward a viable path for transitioning from advisory analytics to semi-autonomous drilling systems, contingent on continued collaboration, expanded datasets, and field validation. The project results have immediate relevance for drilling operations, data management practices, and future geothermal R&D efforts aimed at achieving reliable, cost-competitive geothermal energy at scale.

15 GEOTHERMAL ENERGY↗
NASA NTRS2016

Collaborations and Partnerships in NASA’s Earth Science Data Systems

NASA has been collecting Earth observation data from spaceborne instruments since 1960. Today, there are tens of satellites orbiting the Earth and collecting frequent global observations for the benefit of mankind. Collaboration between NASA and organizations in the US and other countries has been extremely important in maintaining the Earth observation capabilities as well as collecting, organizing and managing the data. These collaborations have occurred in the form of: 1. NASA’s developing and launching spacecraft and instruments for operation by other agencies; 2. Instruments from collaborating organizations being flown on NASA satellites; and 3. Instruments from NASA being flown on satellites from collaborating organizations. In addition, there are collaborations such as joint science teams, data exchanges, and participation in international organizations to promote interoperability of various data systems. The purpose of this paper is to describe some of the Earth science data-related collaborative efforts in which NASA participates, and highlight a few results relevant to Earth system science research obtained through such collaborations.

Ramapriyan, Hampapuram K.↗
NASA NTRS1977

A scientific operations plan for the large space telescope

The paper describes an LST ground system which is compatible with the operational requirements of the LST. The goal of the approach is to minimize the cost of post launch operations without seriously compromising the quality and total throughput of LST science. Attention is given to cost constraints and guidelines, the telemetry operations processing systems (TELOPS), the image processing facility, ground system planning and data flow, and scientific interfaces.

West, D. K.↗
NASA NTRS1984

ERB master archival tape specification no. T 134081 ERB MAT, revision 1

The Earth radiation budget (ERB)MAT tapes are generated by the ERB MATGEN software using the IBM 3081 computer system operated by the Science and Applications Computer Center at Goddard Space Flight Center. All MAT's are 9-track and MAT data are in ascending time order. The gross tape format for NIMBUS year-1 and year-2 MAT's is different from the format of MAT's starting with year-3. The MATs from the first two years are to contain one day's worth of data while all other MATs are to contain multiple day's worth of data stacked onto the tapes.

Source record↗
NASA NTRS1986

An expert system prototype for aiding in the development of software functional requirements for NASA Goddard's command management system: A case study and lessons learned

At NASA Goddard, the role of the command management system (CMS) is to transform general requests for spacecraft opeerations into detailed operational plans to be uplinked to the spacecraft. The CMS is part of the NASA Data System which entails the downlink of science and engineering data from NASA near-earth satellites to the user, and the uplink of command and control data to the spacecraft. Presently, it takes one to three years, with meetings once or twice a week, to determine functional requirements for CMS software design. As an alternative approach to the present technique of developing CMS software functional requirements, an expert system prototype was developed to aid in this function. Specifically, the knowledge base was formulated through interactions with domain experts, and was then linked to an existing expert system application generator called 'Knowledge Engineering System (Version 1.3).' Knowledge base development focused on four major steps: (1) develop the problem-oriented attribute hierachy; (2) determine the knowledge management approach; (3) encode the knowledge base; and (4) validate, test, certify, and evaluate the knowledge base and the expert system prototype as a whole. Backcasting was accomplished for validating and testing the expert system prototype. Knowledge refinement, evaluation, and implementation procedures of the expert system prototype were then transacted.

Liebowitz, Jay↗
NASA NTRS1997

Feasibility of NASA TT&C via Commercial Satellite Services

This report presents the results of a study to identify impact and driving requirements by implementing commercial satellite communications service into traditional National Aeronautics and Space Administration (NASA) space-ground communications. The NASA communication system is used to relay spacecraft and instrument commands, telemetry and science data. NASA's goal is to lower the cost of operation and increase the flexibility of spacecraft operations. Use of a commercial network offers the opportunity to contact a spacecraft on a nearly "on-demand" basis with ordinary phone calls to enable real time interaction with science events.

Mitchell, Carl W.↗
NASA NTRS2022

Ideas on the NASA Senior Review and Mission Extension Process

Extended mission budgets fund a significant part of our community, particularly young scientists who in a relatively short time are exposed to a broad range of experiences and opportunities available in space science and other STEM fields. In particular, mission-funded science offers a relatively stable funding stream that enables meaningful mentoring efforts and interactions, including apprenticeships ranging from project management, to mission operations, to data processing and analysis, to hardware and software development, to STEM-related education and outreach. It moreover provides professional contacts that fuel diversity in mission leadership and in the science and technical workforce at-large. Last but not least, it sustains the scientific productivity of NASA’s missions, which constitute major national investments meriting their full exploitation. Budgets cuts, however, are exercising pressure on the science and operations of the extended mission fleet despite being only a small portion of the overall Division budget. The history of Heliophysics has demonstrated that maintaining the operation of missions beyond their prime phase invariably leads to a much deeper knowledge of the original mission science goals, together with new applications often not foreseen during their original design. Their operation as part of the Heliophysics System Observatory (HSO)---a coordinated, 1eliophysics, multipoint observing system of the heliosphere, is a prime example. Some of the first activities undertaken by the Parker Solar Probe and Solar Orbiter missions required recreating the larger context of their new observations by using the diversity of HSO mission capabilities. The marginal cost of maintaining this valuable, working science resource, in the form of both continuing high quality data access and expertise, is small compared to the cost of the original missions or of new missions to achieve similar objectives, making the operation of extended missions, the best “science per dollar” investment in Heliophysics. We argue that reducing both extended mission operations and science budgets will have a ripple effect across the community, including reducing employment and training opportunities for young scientists, to lowering the quality/impact of the Heliophysics Systems Observatory. Instead, we suggest that the proposal process for mission extension should be re-examined. We offer several ideas for reducing costs of extended missions toward maintaining science output and streamlining the management process.

A. Vourlidas↗
NASA NTRS2020

Overview and Initial Results of SAND-E: Semi-Autonomous Navigation for Detrital Environments

Unmanned aerial systems (UAS) and automated terrain analysis for science and navigation are new technologies for planetary exploration. The Mars Helicopter will fly with the Mars2020 rover, the Dragonfly quadcopter will explore Titan, and Soil Properties and Object Classification (SPOC) software will be used for path planning and navigation on the Mars2020 rover. Using an Argo J5 rover instrumented with stereo cameras and Autonomous Soil Assessment System (ASAS) software, and an off the shelf quadcopter, SAND-E tested the use of automated terrain analysis and UAS data for science operations in a Mars-analog environment in Iceland during July of 2019. Scientifically, we sought to determine changes in the physical and chemical properties of sediments along a glacial-fluvial-aeolian transport pathway. Operationally, we tested rover mission-like scenarios that included UAS images and classified terrain images. Here, we present the initial results for both the operations and science elements of the study. Site Selection: A goal of SAND-E is examine sorting and alteration of sediments in fluvial and aeolian environments in both mineral-dominated and glass-dominated basaltic settings. During the first year of the project we focused on a mineral-dominated environment. Selection of the location was based on prior publications that indicated our selected region had a greater abundance of crystalline sediments than other areas fluvial-aeolian settings in Iceland. Other criteria included the presence of both fluvial and aeolian landforms along a transport pathway such that the sediments in transport could be linked to their source rocks. We chose the Skjaldbreidauhraun glacial outwash plain, which sits at the base of Thórisjökull glacier. The site is 30 km north of Thingvellir National Park and ~2 hours from Reykjavik. The outwash plain is fed by two small catchments that drain from the base of the glacier and cut through hyaloclastite and shield volcano bedrock. The drainage progresses from steep alluvial fans near the glacier into a low-sloping fluvial braidplain that becomes confined by the Skjaldbreidur shield volcano and creates a shallow canyon cut into lava bedrock. The fluvial system was a typical braided alluvial environment composed pebble- and cobble-bedded longitudinal bars and sandy channel beds. The river remained active and fluctuated in response to diurnal runoff cycles near the glacier before disappearing into the sandy substrate downstream. The high concentration of suspended sediment in the river was evident by the cloudy water and the silt and clay-sized sediments that draped the channel beds after abandonment and created playas in the lowest sloping areas of the catchment. The entire fluvial system was affected by the winds generated by frontal systems and katabatic flows descending the glacier. This resulted in the formation of aeolian lag deposits and a wind-deflation plain where the fluvial system was not active. Wind ripples and drifts formed in abandoned fluvial channels from aeolian reworking of the sand-sized fluvial sediments. The silt- and clay-sized sediments found in fluvial channels, bar tops, and playas generated dust plumes during high wind events. Our operation sought to capture the variability in this system by sampling from the range of fluvial and aeolian features 6.3 km (proximal), 11.3 km (medial), and 14.4 km (distal) along the river from its origin at the base of glacier.

Ewing, R. C.↗
NASA NTRS2004

Science Data Processing for the Advanced Microwave Scanning Radiometer: Earth Observing System

The National Aeronautics and Space Administration established the framework for the Science Investigator-led Processing Systems (SIPS) to enable the Earth science data products to be produced by personnel directly associated with the instrument science team and knowledgeable of the science algorithms. One of the first instantiations implemented for NASA was the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) SIPS. The AMSR-E SIPS is a decentralized, geographically distributed ground data processing system composed of two primary components located in California and Alabama. Initial science data processing is conducted at Remote Sensing Systems (RSS) in Santa Rosa, California. RSS ingests antenna temperature orbit data sets from JAXA and converts them to calibrated, resampled, geolocated brightness temperatures. The brightness temperatures are sent to the Global Hydrology and Climate Center in Huntsville, Alabama, which generates the geophysical science data products (e.g., water vapor, sea surface temperature, sea ice extent, etc.) suitable for climate research and applications usage. These science products are subsequently sent to the National Snow and Ice Data Center Distributed Active Archive Center in Boulder, Colorado for archival and dissemination to the at-large science community. This paper describes the organization, coordination, and production techniques employed by the AMSR-E SIPS in implementing, automating and operating the distributed data processing system.

Goodman, H. Michael↗
NASA NTRSDate not supplied

Astrobee Operations on the Iss: Gui’S Impact on the Operators’ Cognitive Load

The Astrobee free-flying robots have completed their fifth successful year of operations housed in the Japanese Experimental Module (JEM) on the International Space Station (ISS). In this paper, we introduce two Graphical User Interfaces (GUI) used to operate and monitor in real-time the Astrobee free-flying robots onboard the ISS and report on the impact these GUIs have in the operator’s cognitive load. A review of the state-of-the-art GUI design for remotely teleoperated scenarios with minimal time delay is presented and the study’s conclusion used to determine the elements and recommendations to create an interface that minimizes its impact on the overall performance of an operator during an activity at the ISS. The Ground Data System (GDS) is one of the two GUIs in the study: it contains several tabs, each of which displays a different set of controls for specific tasks e.g. Overview, Run Plan, Teleoperate, Guest Science; some also display video and a three-dimensional (3D) representation of the ISS and robot based on the Astrobee’s telemetry. Most tabs enable a single operator-robot connection, however some of its tabs are capable to monitor and control up to three Astrobees simultaneously. The GDS Helper is a text-based user interface created to facilitate commanding and monitoring of an Astrobee robot directly from an SSH session. In full interactive mode it displays a maximum of 5 sections: general commanding, feedback/ack, telemetry, guest science commanding, and data, all in one view. In batch mode, it enables complex command scripting while retaining some interactive capabilities. A comparative analysis between these GUIs is carried out at an analogous ISS environment at the NASA Ames Research Center’s Granite Lab and its results presented. While GDS is able to provide an operator with control and situational awareness via its video and 3D displays, its several tabs may introduce an overwhelming amount of information confusing and delaying the operator especially during time-sensitive maneuvers where the operator may need to switch back and forth between them. GDS helper in the other hand does not provide video or 3D displays thus not allowing an operator to attain situational awareness, however it provides the operator with a design displaying commonly used data in a single window, enabling the operator to understand the state of the robot at a glance and control it through a commands entered via keyboard instead of a combination of mouse clicks and keyboard input. The results of the experiments measure the cognitive load across several operators maneuvering Astrobee to accomplish tasks ranging from fully manual to supervised activities. A GUI combining a single window displaying data along video and a 3D display is expected to reduce the operator’s cognitive load.

Astrobee↗
NASA NTRS1982

NASA-ESA Spacelab systems and programs; Proceedings of the Seminar, Washington, DC, April 23, 24, 1981

Topics discussed include the development status of the Space Shuttle and Spacelab, with attention to Spacelab subsystem performance capabilities and Shuttle-Spacelab flight operations; Spacelab data management and software for science applications, ESA and Space Shuttle pointing systems, and the Space Shuttle's Office of Space and Terrestrial Applications (OSTA)-1 payload. Also covered are the lessons learned from the first Spacelab mission, the pallet-only mode verification flight of the second Spacelab mission, the objectives of the Spacelab mission D1, its role in the German space program, and its implementation, the impact of Spacelab on space-based life sciences research, the high resolution, large area modular reflector array X-ray telescope to be used by Spacelab, and Space Shuttle contamination effects on UV coronagraphic observations.

Moore, J. W.↗
NASA NTRS1999

Computing with Beowulf

Parallel computers built out of mass-market parts are cost-effectively performing data processing and simulation tasks. The Supercomputing (now known as "SC") series of conferences celebrated its 10th anniversary last November. While vendors have come and gone, the dominant paradigm for tackling big problems still is a shared-resource, commercial supercomputer. Growing numbers of users needing a cheaper or dedicated-access alternative are building their own supercomputers out of mass-market parts. Such machines are generally called Beowulf-class systems after the 11th century epic. This modern-day Beowulf story began in 1994 at NASA's Goddard Space Flight Center. A laboratory for the Earth and space sciences, computing managers there threw down a gauntlet to develop a $50,000 gigaFLOPS workstation for processing satellite data sets. Soon, Thomas Sterling and Don Becker were working on the Beowulf concept at the University Space Research Association (USRA)-run Center of Excellence in Space Data and Information Sciences (CESDIS). Beowulf clusters mix three primary ingredients: commodity personal computers or workstations, low-cost Ethernet networks, and the open-source Linux operating system. One of the larger Beowulfs is Goddard's Highly-parallel Integrated Virtual Environment, or HIVE for short.

Cohen, Jarrett↗
NASA NTRS2011

Performance of the GLAS Space Lidar Receiver Through Its Seven-Year Space Mission

NASA s Ice, Cloud, and land Elevation Satellite (ICESat) mission [1,2] carrying the Geoscience Laser Altimeter System (GLAS) Instrument, was launched on January 12, 2003. The three lasers on ICESat have made a total of 1.98 billion laser shot measurements of the Earth s surface and atmosphere during its 17 science data collection campaigns over its seven year operating lifetime. ICESat completed its science mission after the last laser stopped operating in October 2009. The spacecraft was de-orbited on August 30, 2010. The GLAS instrument carried 3 diode-pumped Q-switched Nd:YAG lasers, which emitted 6-nsec wide pulses at 1064 and 532 nm at a 40-Hz rate. There are three lidar receiver channels, a 1064 nm surface altimetry channel, a 1064 nm cloud backscattering lidar channel, and a 532 nm cloud and aerosol backscattering lidar channel. The altimetry and cloud backscatter channels used Si avalanche photodiode (APD) operated in analog mode as in the Mars Global Surveyor s Mars Orbital Laser Altimeter [3,4]. GLAS also utilized a number of new technologies and techniques for space lidar, including passively Q-switched diode-pumped Nd:YAG lasers, a 1-m diameter telescope, a temperature tuned etalon optical bandpass filter, Si APD single photon counting detectors, 1 Gsample/sec waveform digitizers, ultra stable clock oscillators, and digital signal processing and detection algorithms [5]. A global position system (GPS) receiver was used to provide the spacecraft position and epoch times. The ICESat mission provided a unique opportunity to monitor the lidar component performance in the space environment over a multi-year time period. We performed a number of engineering tests periodically to monitor the lidar receiver performance, including receiver sensitivity, timing precision, detector dark noise, etc. A series of engineering tests were also performed after the end of the science mission to evaluate the performance of the spare detector, oscillator, waveform digitizer, and GPS receiver. An experiment was conducted which pointed GLAS to Venus to test the receiver sensitivity to star light and to verify GLAS bore sight with respect to the spacecraft coordinate system. These tests provided unique data to assess the degradation and the rate of change of these key lidar components due to space radiation and aging. They also helped to validate new techniques to operate and calibrate future space lidars.

Sun, Xiaoli↗
NASA NTRS2021

SNPP VIIRS Day Night Band: Ten Years of On-Orbit Calibration and Performance

Aboard the polar-orbiting SNPP satellite, the VIIRS instrument has been in operation since launch in October 2011. It is a visible and infrared radiometer with a unique panchromatic channel capability designated as a day-night band (DNB). This channel covers wavelengths from 0.5 to 0.9 µm and is designed with a near-constant spatial resolution for Earth observations 24 h a day. The DNB operates at 3 gain stages (low, middle, and high) to cover a large dynamic range. An onboard solar diffuser (SD) is used for calibration in the low gain stage, and to enable the derivation of gain ratios between the different stages. In this paper, we present the SNPP VIIRS DNB calibration performed by the NASA VIIRS characterization support team (VCST). The DNB calibration algorithms are described to generate the calibration coefficient look up tables (LUTs) for the latest NASA Level 1B Collection 2 products. We provide an evaluation of DNB on-orbit calibration performance. This activity supports the NASA Earth science community by delivering consistent VIIRS sensor data products via the Land Science Investigator-led Processing Systems, including the SD degradation applied for DNB calibrations in detector gain and gain ratio trending. The DNB stray light contamination and its correction are highlighted. Performance validations are presented using comparisons to the calibration methods employed by NOAA’s operational Interface Data Processing Segment. Further work on stray light corrections is also discussed.

VIIRS↗