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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

On-Orbit Results and Lessons Learned from the ASTERIA Space Telescope Mission

The Arcsecond Space Telescope Enabling Research in Astrophysics (ASTERIA) was deployed from the International Space Station (ISS) on 20 November 2017, beginning a technology demonstration and opportunistic science mission to advance the state of the art in nanosatellite performance for astrophysical observations. The goal of ASTERIA is to achieve arcsecond-level line-of-sight pointing error and highly stable focal plane temperature control. These capabilities enable precision photometry—i.e. the careful measurement of stellar brightness over time—which in turn allows investigation of astrophysical phenomena such as transiting exoplanets. By the end of the 90-day prime mission, ASTERIA had achieved line-of-sight pointing stability of approximately 0.5 arcseconds root mean square (RMS) over 20-minute observations, pointing repeatability of 1 milliarcsecond RMS from one observation to the next, and focal plane temperature stability better than ±0.01 K over 20-minute observations. This paper presents an overview of the ASTERIA flight and ground system, summarizes the pre-delivery test campaign, and discusses the on-orbit performance obtained by the pointing and thermal control subsystems. We also describe the process for planning opportunistic science observations and present lessons learned from development and operations. Having successfully operated for over 200 days as of this writing, ASTERIA is currently in an extended mission to observe nearby bright stars for transiting exoplanets.

Seager, Sara↗
NASA NTRS1990

Hubble Space Telescope: SRM/QA observations and lessons learned

The Hubble Space Telescope (HST) Optical Systems Board of Investigation was established on July 2, 1990 to review, analyze, and evaluate the facts and circumstances regarding the manufacture, development, and testing of the HST Optical Telescope Assembly (OTA). Specifically, the board was tasked to ascertain what caused the spherical aberration and how it escaped notice until on-orbit operation. The error that caused the on-orbit spherical aberration in the primary mirror was traced to the assembly process of the Reflective Null Corrector, one of the three Null Correctors developed as special test equipment (STE) to measure and test the primary mirror. Therefore, the safety, reliability, maintainability, and quality assurance (SRM&QA) investigation covers the events and the overall product assurance environment during the manufacturing phase of the primary mirror and Null Correctors (from 1978 through 1981). The SRM&QA issues that were identified during the HST investigation are summarized. The crucial product assurance requirements (including nonconformance processing) for the HST are examined. The history of Quality Assurance (QA) practices at Perkin-Elmer (P-E) for the period under investigation are reviewed. The importance of the information management function is discussed relative to data retention/control issues. Metrology and other critical technical issues also are discussed. The SRM&QA lessons learned from the investigation are presented along with specific recommendations. Appendix A provides the MSFC SRM&QA report. Appendix B provides supplemental reference materials. Appendix C presents the findings of the independent optical consultants, Optical Research Associates (ORA). Appendix D provides further details of the fault-tree analysis portion of the investigation process.

Rodney, George A.↗
NASA NTRS1974

The effect of spurious angular accelerations on tracking in dynamic simulation

A laboratory study was conducted to investigate the effect of spurious simulator yaw motions on a pilot's control performance. A second objective was to compare the efficiency of static and dynamic simulator tracking in previously unexamined vehicle dynamics. Twelve airline pilots served as subjects in a moving-base flight simulator under congruent-motion, spurious-motion, and no-motion conditions. The results indicated a significant increase in the amount of error with increasing levels of spurious motion during the initially administered series of trials. The influence of spurious motion, however, was absent in a second series of trials. The data suggest that the pilots learned to compensate in their performance for the spurious inputs. It was also found that congruent visual and rotational cueing produced superior performance to that of tracking with visual information alone.

Beck, L. J.↗
NASA NTRS1990

Impact of a process improvement program in a production software environment: Are we any better?

For the past 15 years, Computer Sciences Corporation (CSC) has participated in a process improvement program as a member of the Software Engineering Laboratory (SEL), which is sponsored by GSFC. The benefits CSC has derived from involvement in this program are analyzed. In the environment studied, it shows that improvements were indeed achieved, as evidenced by a decrease in error rates and costs over a period in which both the size and the complexity of the developed systems increased substantially. The principles and mechanics of the process improvement program, the lessons CSC has learned, and how CSC has capitalized on these lessons are also discussed.

Heller, Gerard H.↗
NASA NTRS2004

DASL-Data and Activities for Solar Learning

DASL-Data and Activities for Solar Learning Data and Activities for Solar Learning (DASL) provides a classroom learning environment based on a twenty-five year record of solar magnetograms from the National Solar Observatory (NSO) at Kitt Peak, AZ. The data, together with image processing software for Macs or PCs, can be used to learn basic facts about the Sun and astronomy at the middle school level. At the high school level, students can study properties of the Sun's magnetic cycle with classroom exercises emphasizing data and error analysis and can participate in a new scientific study, Research in Active Solar Longitudes (RASL), in collaboration with classrooms throughout the country and scientists at NSO and NASA. We present a half-day course to train teachers in the scientific content of the project and its classroom use. We will provide a compact disc with the data and software and will demonstrate software installation and use, classroom exercises, and participation in RASL with computer projection.

Jones, Harrison P.↗
NASA NTRS2014

Rules for Optical Testing

Based on 30 years of optical testing experience, a lot of mistakes, a lot of learning and a lot of experience, I have defined seven guiding principles for optical testing - regardless of how small or how large the optical testing or metrology task: Fully Understand the Task, Develop an Error Budget, Continuous Metrology Coverage, Know where you are, Test like you fly, Independent Cross-Checks, Understand All Anomalies. These rules have been applied with great success to the inprocess optical testing and final specification compliance testing of the JWST mirrors.

Stahl, H. Philip↗
NASA NTRS2002

Human Factors Directions for Civil Aviation

Despite considerable progress in understanding human capabilities and limitations, incorporating human factors into aircraft design, operation, and certification, and the emergence of new technologies designed to reduce workload and enhance human performance in the system, most aviation accidents still involve human errors. Such errors occur as a direct or indirect result of untimely, inappropriate, or erroneous actions (or inactions) by apparently well-trained and experienced pilots, controllers, and maintainers. The field of human factors has solved many of the more tractable problems related to simple ergonomics, cockpit layout, symbology, and so on. We have learned much about the relationships between people and machines, but know less about how to form successful partnerships between humans and the information technologies that are beginning to play a central role in aviation. Significant changes envisioned in the structure of the airspace, pilots and controllers' roles and responsibilities, and air/ground technologies will require a similarly significant investment in human factors during the next few decades to ensure the effective integration of pilots, controllers, dispatchers, and maintainers into the new system. Many of the topics that will be addressed are not new because progress in crucial areas, such as eliminating human error, has been slow. A multidisciplinary approach that capitalizes upon human studies and new classes of information, computational models, intelligent analytical tools, and close collaborations with organizations that build, operate, and regulate aviation technology will ensure that the field of human factors meets the challenge.

Hart, Sandra G.↗
NASA NTRS2023

Benefits of Ka-band GaN MMIC High Power Amplifiers With Wide Bandwidth and High Spectral/Power Added Efficiencies for Cognitive Radio Platforms

A cognitive radio on a future NASA near-Earth spacecraft will be capable of sensing its environment and dynamically adapting its operating parameters to provide the desired SATCOM service to the mission. A key component that can enable this type of operation is a high-power amplifier (HPA) that resides on the radio platform. In this report, we present the RF performance characteristics of a Ka-band gallium nitride (GaN) monolithic microwave integrated circuit (MMIC) based HPA for cognitive radio platforms. These characteristics include the output power, gain, power added efficiency (PAE), RMS error vector magnitude (EVM), spectral efficiency, 3rdorder intermodulation distortion (IMD) products, spectrum, spectral regrowth, noise figure (NF), phase noise, and group delay. The data presented indicates that the HPA meets NTIA, military, and commercial spectral mask requirements. In addition, we discuss the benefits offered by the above performance characteristics toward the design and implementation of a cognitive radio platform. Furthermore, as examples, we discuss three potential use cases that apply artificial intelligence (AI) and machine learning (ML) techniques and exploit the performance characteristics discussed above to provide a knowledge-based cognitive radio platform design for SATCOM. Thus, cognitive radios with performance flexibility can enable roaming and provide seamless interoperability autonomously in the future between NASA, commercial, and other space networks owned by U.S. government agencies.

Gallium nitride↗
NASA NTRSDate not supplied

Detecting Satellite Laser Ranging Station Data and Operational Anomalies with Machine Learning Isolation Forests at NASA's CDDIS

The International Laser Ranging Service (ILRS) is currently composed of 45 active satellite laser ranging (SLR) stations with several more set to join the network over the next several years. Station changes and histories are logged to files, but not always in real time. Sometimes these details are not added until long after changes have been made to the station –on occasion, years later. This in addition to unexpected hardware errors and other system issues that are not immediately detected impact the products generated by analysts. The ILRS Central Bureau (CB) and NASA’s Crustal Dynamics Data Information System (CDDIS) have worked to provide tools for station engineers to use. This includes the creation of station plots which contain temperature and pressure information along with LAser GEOdynamic Satellite (LAGEOS) and LAser RElativity Satellite (LARES) tracking information that enable the monitoring of station performance and todetermine whether the station has undergone any changes. As next steps, the CDDIS is working to enhance these station performance monitoring tools through machine learning. Isolation forest is an unsupervised machine learning algorithm commonly applied to anomaly detection. In this poster, the CDDIS details the steps taken to track anomalies within SLR station performance using isolation forest with LAGEOS and LARES satellite data.

Benjamin P Michael↗
NASA NTRSDate not supplied

Prediction of Aircraft Estimated Time of Arrival Using A Supervised Learning Approach

We present a novel data-driven approach for prediction of the estimated time of arrival (ETA) of aircraft in the terminal area via the implementation of a Random Forest regression model. The model uses data fused from a number of sources (flight track, weather, flight plan information, etc.) and provides predictions for the remaining flight time for aircraft landing at Dallas/Fort Worth (DFW) International Airport. The predictions are made when the aircraft is at a distance of 200-miles from the airport. The results show that the model is able to predict estimated time of arrival to within ± 5 min for 90% of the flights in the test data with the mean absolute error being lower at 145 seconds. This paper covers the entire pipeline of data collection, preprocessing, setup and training of the ML model, and the results obtained for DFW.

Machine learning↗
NASA NTRS1999

NASA Space Mechanisms Handbook: Lessons Learned Documented

The need to improve space mechanism reliability is underscored by a long history of flight failures and anomalies caused by malfunctioning mechanisms on spacecraft and launch vehicles. Some examples of these failures are listed in a table. Because much experience has been gained over the years, many specialized design practices have evolved and many unsatisfactory design approaches have been identified.NASA and the NASA Lewis Research Center conducted a Lessons Learned Study (refs. 1 and 2) and wrote a handbook to document what has been learned in the past. The primary goals of the handbook were to identify desirable and undesirable design practices for space mechanisms and to reduce the number of failures caused by the repetition of past design errors. Another goal was to identify a variety of design approaches for specific applications and to provide the associated considerations and caveats for each approach in an effort to help designers choose the approach most suitable for each application. This technical summary outlines the goals and objectives of the handbook and study as well as the contents of the handbook.

Fusaro, Robert L.↗
NASA NTRS2004

MISR: protection from ourselves

Outlines lessons learned by the Instrument Operations Team of NASA/JPL Terra's Multi-angle Imaging SpectroRadiometer mission. It narrates a story of MISR: Protection from Ourselves! and describes, in detail, how the MISR instrument survived operator errors.

MISR operations↗
NASA NTRS2011

The Legacy of Space Shuttle Flight Software

The initial goals of the Space Shuttle Program required that the avionics and software systems blaze new trails in advancing avionics system technology. Many of the requirements placed on avionics and software were accomplished for the first time on this program. Examples include comprehensive digital fly-by-wire technology, use of a digital databus for flight critical functions, fail operational/fail safe requirements, complex automated redundancy management, and the use of a high-order software language for flight software development. In order to meet the operational and safety goals of the program, the Space Shuttle software had to be extremely high quality, reliable, robust, reconfigurable and maintainable. To achieve this, the software development team evolved a software process focused on continuous process improvement and defect elimination that consistently produced highly predictable and top quality results, providing software managers the confidence needed to sign each Certificate of Flight Readiness (COFR). This process, which has been appraised at Capability Maturity Model (CMM)/Capability Maturity Model Integration (CMMI) Level 5, has resulted in one of the lowest software defect rates in the industry. This paper will present an overview of the evolution of the Primary Avionics Software System (PASS) project and processes over thirty years, an argument for strong statistical control of software processes with examples, an overview of the success story for identifying and driving out errors before flight, a case study of the few significant software issues and how they were either identified before flight or slipped through the process onto a flight vehicle, and identification of the valuable lessons learned over the life of the project.

Hickey, Christopher J.↗
NASA NTRS2018

Fuzzy Modeling and Parallel Distributed Compensation for Aircraft Flight Control from Simulated Flight Data

A method is described that combines fuzzy system identification techniques with Parallel Distributed Compensation (PDC) to develop nonlinear control methods for aircraft using minimal a priori knowledge, as part of NASA’s Learn-to-Fly initiative. A fuzzy model was generated with simulated flight data, and consisted of a weighted average of multiple linear time invariant state-space cells having parameters estimated using the equation-error approach and a least-squares estimator. A compensator was designed for each subsystem using Linear Matrix Inequalities (LMI) to guarantee closed-loop stability and performance requirements. This approach is demonstrated using simulated flight data to automatically develop a fuzzy model and design control laws for a simplified longitudinal approximation of the F-16 nonlinear flight dynamics simulation. Results include a comparison of flight data with the estimated fuzzy models and simulations that illustrate the feasibility and utility of the combined fuzzy modeling and control approach.

Weinstein, Rose↗
NASA NTRSDate not supplied

Benefits of Ka-band GaN MMIC High Power Amplifiers With Wide Bandwidth and High Spectral/Power Added Efficiencies for Cognitive Radio Platforms

A cognitive radio on a future NASA near-Earth spacecraft will be capable of sensing its environment and dynamically adapting its operating parameters to provide the desired SATCOM service to the mission. A key component that can enable this type of operation is a high-power amplifier (HPA) that resides on the radio platform. In this paper, we present the RF performance characteristics of a Ka-band gallium nitride (GaN) monolithic microwave integrated circuit (MMIC) based HPA for cognitive radio platforms. These characteristics include the output power, gain, power added efficiency (PAE), RMS error vector magnitude (EVM), spectral efficiency, 3rd-order intermodulation distortion (IMD) products, spectrum, spectral regrowth, noise figure (NF), and phase noise. The data presented indicates that the HPA meets NTIA, military, and commercial spectral mask requirements. In addition, we discuss the benefits offered by the above performance characteristics toward the design and implementation of a cognitive radio platform. Furthermore, as examples, we discuss three potential use cases that apply artificial intelligence (AI) and machine learning (ML) techniques and exploit the performance characteristics discussed above to provide a knowledge-based cognitive radio platform design for SATCOM. Thus, cognitive radios with performance flexibility can enable roaming and provide seamless interoperability autonomously in the future between NASA, commercial, and other space networks owned by U.S. government agencies.

Gallium nitride↗
NASA NTRS1986

Progression-regression effects in tracking repeated patterns

Subjects used a position control system to perform compensatory tracking of a repeated input pattern. The input pattern was 20 seconds in duration and was either an arctangent function or the sum of two sine waves. Tracking error decreased with practice and increased with the addition of a concurrent memory task. The shape of the ensemble-average tracking error resembled the shape of the input velocity signal throughout these changes in performance. Regression analyses were used to parameterize these effects and compare these results with the predictions of several conceptualizations of perceptual-motor learning.

Jagacinski, R. J.↗
NASA NTRSDate not supplied

Intelligent Change Detection System: Autonomous Intelligent Machine Agent Model Development

NASA’s significant role in facilitating the harmonious integration of unmanned aircraft systems (UAS), with other aerial vehicles operating in the National Airspace System (NAS), has revealed a need for more advanced technological tools than are being utilized currently. This technology would lend itself to significantly assisting Direct-Action Aviation Personnel (DAAP) with the ingress and egress of UAS operations within the NAS. Providing research findings that would reduce technical barriers, associated with UAS-NAS integration, has been a persistent effort by both NASA and the FAA. One such research effort, pursued by NASA’s Transformative Tools and Technologies – Revolutionary Aviation Mobility (T3-RAM) project, is the development of an autonomous intelligent machine (AIM) agent that would aid DAAP functioning as implemented in remote ground control stations (RGCS). This evolution of the “human-machine” symbiosis, within the aviation environment, is necessary for many reasons. For example, there are projections of large increases to the 864,000 registered UAS and 45,000 aviation operations taking place in the NAS each day. With a data output range from 1 to 20 terabytes per flight or each aerial vehicle, which is projected to have proportional rate increase to that of registered UASs. It is evident, that due to the projected increase of UASs and their generated data, the human-agent’s data managing capabilities will be quickly overwhelmed by the enormous amounts of data emanating in the NAS. The research efforts presented in this paper puts forward results from the development, assessment, and verification of a previously conceptualized AIM-Agent that combats actionable-data (information) errors resulting from the visual perception phenomenon known as “change blindness” (CB). CB has been identified as one of the main culprits of information erroring encountered within the ground control station operator (GCSO) community.

Change Blindness↗