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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRSDate not supplied

Statistical learning framework for safety and failure analysis of a DNN-based autonomous aircraft system

Deep Neural Networks (DNNs) and Machine Learning technology is increasingly used for safety-critical applications in the Aerospace domain. To ensure safe operations, the DNN and the system must undergo rigorous verification and validation, including advanced statistical analyses. Performance and safety of the DNN and system behavior must not only be analyzed for the nominal case, but under numerous off-nominal and failure cases. In this paper we will describe how our statistical learning framework SYSAI can efficiently perform such analyses using the tool’s unique combination of advanced learning modeling and statistical analysis techniques. SYSAI can effectively explore the high-dimensional state and failure space of the system under test; geometrical shape detection of safety regions and boundaries support explainability of the results to the designer. In this paper, we report experiments and results obtained with a vision-based DNN control system (ACT) that is capable of autonomously steering an aircraft down a runway.

Yuning He↗
NASA NTRS2024

Presound: UAV Diagnostic System Enabled by Vibration-Based Machine Learning

A low-weight, inexpensive small unmanned aerial system (sUAS) that takes off, performs a mission, lands, and safely stows and recharges itself has myriad future applications ranging from agricultural imaging to last-mile package delivery. Likewise, Urban Air Mobility (UAM) systems will enable people to take air taxis from point to point in cities, rapidly moving commuters long distances without concern for road traffic and congestion. Fully electric aviation systems will be cleaner and quieter than ground transport. Cities could eliminate cars and buses, and convert roads to higher capacity bike and pedestrian throughways. Yet, for sUAS as well as UAM, system reliability and assurance is a limiting factor to deploying affordable autonomous flight systems. For this bright future of aviation to be realized, aircraft must be able to autonomously and accurately self-diagnose health issues both before takeoff and during flight. The GreenSight PreSound system is designed to identify defects on aircraft through intelligent analysis of vibration. It accomplishes this by measuring structural vibrations induced by the vehicle’s own propellers, and analyzing that data using a machine learning model that determines whether a defect is present. The PreSound system is designed to require no human oversight, and to operate across a wide array of vehicles through re-training of the model for each target aircraft. PreSound has been developed and seen limited early success using data collected from the GreenSight Dreamer sUAS, a 5lb quadrotor vehicle designed for aerial imaging applications. The final detection model, trained on data with props spinning at 50% throttle, achieves excellent performance with over 99% average accuracy in detecting blade damage using a single FFT vector input. It demonstrates the ability to generalize to new types of blade damage, correctly classifying a different type of blade damage with 98% accuracy. Full test pulses were classified with 100% accuracy, and in live testing, all sets of data during blade movement were classified accurately with over 95% confidence. When trained on in-flight data, the same model achieves an average accuracy of 85% in distinguishing between undamaged and blade-damaged states in flight. The authors believe that these accuracies show significant potential of this approach to expand unmanned flight safety, with significant potential benefits in accelerating Advanced Aerial Mobility (AAM) and UAM aviation applications.

UAS↗
NASA NTRS2022

Multi-Mission Terrain Classifier for Safe Rover Navigation and Automated Science

We previously presented Soil Property and Object Classification (SPOC), a machine learning-based terrain classifier for Mars rovers, for automatically segmenting rover images by its surface type such as sand and bedrock. This paper presents a number of practical improvements to pave the way for potential future onboard deployment. First, we achieved 97.0% overall pixel accuracy, evaluated against the classification generated by human experts on images from Mars Science Laboratory (MSL) missions. The substantial increase in accuracy was primarily enabled by the sheer volume of data used for training; we created a new large-scale dataset of Martian terrain labels, namely AI4Mars, which contains more than 400k labels contributed by citizen scientists for 50k images taken by the Mars Exploration Rovers (MER) and Mars Science Laboratory (MSL) rover. Second, we demonstrated that SPOC can quickly adapt to a new mission landed on a previously unseen site. Specifically, we pretrained a model with MER and MSL data from the AI4Mars dataset and then adapted to the Mars 2020 Rover (M2020) by feeding a small volume of data between Sol 0 and 157; the adapted model was tested on Sol 200-203 and resulted in 84.2% overall pixel accuracy and 93.4% reliability (recall) for detecting sand, the most concerning class for rover’s traversability. Third, we found that pretraining can substantially mitigate the decline of accuracy over time. We showed that the performance of a SPOC model pretrained with the ImageNet dataset and then trained by MSL images only up to Sol 390 remains comparable to a model trained by images up to Sol 1689 on the test data after Sol 1689. Fourth, we reimplemented SPOC with a light-weight convolutional neural network (CNN), MobileNetV2, which typically runs within tens of milliseconds (ms) on mobile processors such as Qualcomm’s Snapdragon. Finally, we released the AI4Mars dataset to the public to encourage open innovation.

Ono, Masahiro↗
NASA NTRSDate not supplied

OSIRIS-REx Earth Return & Entry: Navigation Operations & Lessons Learned

The Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx) spacecraft successfully returned to Earth on September24, 2024, safely delivering its Sample Return Capsule (SRC) to the Utah Test and Training Range (UTTR). This paper describes the navigation operations that occurred between the departure from Bennu and the return of the SRC. An overview is given of the Flight Dynamics System (FDS) that includes tracking, orbit determination (OD), maneuver planning, and interfaces with entry, descent, and landing. Operational details on the SRC release criteria and conjunction assessment considerations are also provided. Lessons learned are presented that may help future sample return or interplanetary entry missions.

Kenneth M. Getzandanner↗
NASA NTRS1992

Flight Testing

It is considered by the Flight Mechanics Panel of AGARD as vitally important that the NATO flight test community meet regularly so that new techniques for flight test, instrumentation and data analysis and lessons learned from past and on-going programs be disseminated to ensure that safe efficient cost-effective and timely testing is accomplished. There are many new systems being tested or planned for testing in the near future. These include programmable signal processor radars, integrated flight, fire and propulsion control systems, thrust vectoring, low observable technologies, multifunction pilot displays and multisensor integration. Acquisition and processing of large quantities of avionics multiplex data are challenges that must be met. There is a need for greater use of simulators and other hardware-in-the-loop ground test facilities.

Source record↗
NASA NTRS2006

Habitability and Human Factors: Lessons Learned in Long Duration Space Flight

This study documents the investigation of qualitative habitability and human factors feedback provided by scientists, engineers, and crewmembers on lessons learned from the ISS Program. A thorough review and understanding of this data is critical in charting NASA's future path in space exploration. NASA has been involved in ensuring that the needs of crewmembers to live and work safely and effectively in space have been met throughout the ISS Program. Human factors and habitability data has been collected from every U.S. crewmember that has resided on the ISS. The knowledge gained from both the developers and inhabitants of the ISS have provided a significant resource of information for NASA and will be used in future space exploration. The recurring issues have been tracked and documented; the top 5 most critical issues have been identified from this data. The top 5 identified problems were: excessive onsrbit stowage; environment; communication; procedures; and inadequate design of systems and equipment. Lessons learned from these issues will be used to aid in future improvements and developments to the space program. Full analysis of the habitability and human factors data has led to the following recommendations. It is critical for human factors to be involved early in the design of space vehicles and hardware. Human factors requirements need to be readdressed and redefined given the knowledge gained during previous ISS and long-duration space flight programs. These requirements must be integrated into vehicle and hardware technical documentation and consistently enforced. Lastly, space vehicles and hardware must be designed with primary focus on the user/operator to successfully complete missions and maintain a safe working environment. Implementation of these lessons learned will significantly improve NASA's likelihood of success in future space endeavors.

Baggerman, Susan D.↗
NASA NTRS2005

STS-114: Discovery Post Landing Press Briefing from JSC

LeRoy Cain, STS-114 Ascent/Entry Flight Director, takes a solo stand with the Press in this briefing. He noted that the successful flight and return of Discovery is another important milestone, a fresh start, and a new beginning as part of NASA's commitment to the President's vision of man's return to the Moon, Mars and beyond. From this successful test flight, NASA will have a lot of learning and hard work to do in preparation for the next flight. Weather factors, safe landing, touch down, communications, re-entry, the Columbia, were some topics covered with the News media.

Source record↗
NASA NTRS2006

International Space Station Acoustics

The International Space Station (ISS) presents a significant acoustics challenge considering all of the Modules and equipment that make it an on-orbit laboratory workshop and home with long-term crew occupation. This challenge is further complicated by the fact there are numerous and a wide variety suppliers of Station hardware, including International Partners. This paper addresses how ISS acoustics are managed to ensure a safe and habitable environment by establishing requirements, providing oversight and design support, sharing lessons learned and information, testing for hardware compliance, predicting future acoustic levels, and performing on-orbit measurement and monitoring of actual acoustic levels. ISS acoustic requirements are classified by the type of hardware involved, in three categories: Modules; payloads; and Government Furnished Equipment (GFE). Current status of overall ISS acoustics for each of these hardware categories will be discussed. In addition, the following items will be discussed: examples where NASA design support has been used to aid in obtaining compliance; difficulties encountered; and areas of concern.

Goodman, Jerry↗
NASA NTRS2024

Integration of Automated Systems Test Campaign NC-IAS

NASA’s 2022 strategic plan included the goal to catalyze economic growth and drive innovation in the aviation industry, and to address challenges in air transportation and airspace management within the National Airspace System (NAS). The Aeronautics Research Mission Directorate (ARMD) specifically was tasked with leading aviation innovation to enable safe and sustainable air transportation through revolutionary vehicle advances and efficient flight operations. As a part of meeting these objectives and advancing air mobility concepts, NASA initiated the National Campaign (NC) in the Advanced Air Mobility (AAM) Project within the Airspace Operations and Safety Program (AOSP). The NC was designed to support operational demonstrations with industry as well as the research and development needed to support NASA-led research flight demonstrations. Within NC, the Integration of Automated Systems (IAS), an NC activity, tested and evaluated flight deck automation and airspace operations management functions needed to enable Urban Air Mobility (UAM) operations. This was accomplished through a partnership with Sikorsky Aircraft (specifically Sikorsky Innovations), a Lockheed Martin company, and DARPA (Defense Advanced Research Projects Agency), by leveraging two automation-enabled helicopters equipped with unique capabilities that enabled NASA to develop and test two-ship conflict encounters to demonstrate flight path management and hazard avoidance technologies. The enabler in this testing was NASA-developed “Middleware” (MW) software (also known as Expandable Variable Autonomy Architecture, or EVAA), which among other things allowed multiple algorithms to be incorporated into one software build that was hosted on the dissimilar-type Sikorsky helicopters. The IAS test campaign period of performance was from March 2022 through October 2023 and was structured as a phased, or spiral, approach that ultimately led to the first-ever demonstration of two-ship UAM/AAM operations designed to safely choreograph specific conflict encounters and mission scenarios to test the research algorithms for strategic and tactical aircraft deconfliction. Lessons learned are included in the body of the report. Data collected will be used to inform FAA and industry standards groups on the increasingly automated systems needed for future AAM operations. The test encounters developed for these flight tests were proven to be highly predictable, repeatable, and safely exercised flight path planning and Detect and Avoid (DAA) algorithms. These same test encounters should be leveraged by future flight test campaigns to verify that operational safety is not compromised as the AAM architecture matures. Next steps include repeating similar encounters using unmanned aircraft carrying DAA sensors in the National Airspace.

AAM↗
NASA NTRS1992

Milstar's flexible-substrate solar array: Lessons learned

The Flexible Substrate Solar Array (FSSA) is an evolutionary development of the lightweight, flexible substrate design pioneered during the seventies. Many of the features of the design are related to the Solar Array Flight Experiment (SAFE), flown on STS-41D in 1984. FSSA development has created a substantial technology base for future flexible substrate solar arrays such as the array for the Space Station Freedom. Lessons learned during the development of the FSSA can and should be applied to the Freedom array and other future flexible substrate designs.

Gibb, John↗
NASA NTRS2019

UAS Service Supplier Checkout: How UTM Confirmed Readiness of Flight Tests with UAS Service Suppliers

NASA collaborated with industry partners to develop and test the small Unmanned Aircraft System (sUAS) Traffic Management (UTM) research platform, a software prototype used for developing airspace integration requirements for sUAS operations. The lessons learned from these activities will help inform the Federal Aviation Administration (FAA) on what is needed to safely manage sUAS operations. A core component of the UTM platform is the UAS Service Supplier (USS), which acts as a communications bridge to meet the regulatory and operational requirements. As the UTM partners began USS flight tests, NASA found that it was difficult to get all USSs functioning at comparable quality levels to ensure successful flight tests. Also, NASA anticipated that the FAA would encounter similar challenges when they begin to register USSs for operational use. These realizations led to the development of USS Checkout, a set of processes and tools designed to increase flight test efficiency. We learned that a good USS Checkout process is balanced for simplicity versus test coverage, and is amenable to automation. We also learned that when USS Checkout is a USS prerequisite for flight tests, flight tests were more efficient and effective.

Smith, Irene Skupniewicz↗
NASA NTRS1990

MILSTAR's flexible substrate solar array: Lessons learned, addendum

MILSTAR's Flexible Substrate Solar Array (FSSA) is an evolutionary development of the lightweight, flexible substrate design pioneered at Lockheed during the seventies. Many of the features of the design are related to the Solar Array Flight Experiment (SAFE), flown on STS-41D in 1984. FSSA development has created a substantial technology base for future flexible substrate solar arrays such as the array for the Space Station Freedom. Lessons learned during the development of the FSSA can and should be applied to the Freedom array and other future flexible substrate designs.

Gibb, John↗
NASA NTRS2011

Overview of Pre-Flight Physical Training, In-Flight Exercise Countermeasures and the Post-Flight Reconditioning Program for International Space Station Astronauts

International Space Station (ISS) astronauts receive supervised physical training pre-flight, utilize exercise countermeasures in-flight, and participate in a structured reconditioning program post-flight. Despite recent advances in exercise hardware and prescribed exercise countermeasures, ISS crewmembers are still found to have variable levels of deconditioning post-flight. This presentation provides an overview of the astronaut medical certification requirements, pre-flight physical training, in-flight exercise countermeasures, and the post-flight reconditioning program. Astronauts must meet medical certification requirements on selection, annually, and prior to ISS missions. In addition, extensive physical fitness testing and standardized medical assessments are performed on long duration crewmembers pre-flight. Limited physical fitness assessments and medical examinations are performed in-flight to develop exercise countermeasure prescriptions, ensure that the crewmembers are physically capable of performing mission tasks, and monitor astronaut health. Upon mission completion, long duration astronauts must re-adapt to the 1 G environment, and be certified as fit to return to space flight training and active duty. A structured, supervised postflight reconditioning program has been developed to prevent injuries, facilitate re-adaptation to the 1 G environment, and subsequently return astronauts to training and space flight. The NASA reconditioning program is implemented by the Astronaut Strength, Conditioning, and Rehabilitation (ASCR) team and supervised by NASA flight surgeons. This program has evolved over the past 10 years of the International Space Station (ISS) program and has been successful in ensuring that long duration astronauts safely re-adapt to the 1 g environment and return to active duty. Lessons learned from this approach to managing deconditioning can be applied to terrestrial medicine and future exploration space flight missions.

Kerstman, Eric↗
NASA NTRS2015

Replacement of HCFC-225 Solvent for Cleaning NASA Propulsion Oxygen Systems

Since the 1990's, when the Class I Ozone Depleting Substance (ODS) chlorofluorocarbon‐113 (CFC‐113) was banned, NASA's propulsion test facilities at Marshall Space Flight Center (MSFC) and Stennis Space Center (SSC) have relied upon hydrochlorofluorocarbon‐225 (HCFC‐225) to safely clean and verify the cleanliness of large scale propulsion oxygen systems. Effective January 1, 2015, the production, import, export, and new use of HCFC‐225, a Class II ODS, was prohibited by the Clean Air Act. In 2012 through 2014, leveraging resources from both NASA and the Defense Logistics Agency ‐ Aviation Hazardous Minimization and Green Products Branch, test labs at MSFC, SSC, and Johnson Space Center's White Sands Test Facility (WSTF) collaborated to seek out, test, and qualify a replacement for HCFC‐225 that is both an effective cleaner and safe for use with oxygen systems. This presentation summarizes the tests performed, results, and lessons learned. It also demonstrates the benefits of cross‐agency collaboration in a time of limited resources.

Lowrey, Nikki M.↗
NASA NTRS2016

Results of the Test Program for Replacement of AK-225G Solvent for Cleaning NASA Propulsion Oxygen Systems

Since the 1990's, when the Class I Ozone Depleting Substance chlorofluorocarbon-113 was banned, NASA's propulsion test facilities at Marshall Space Flight Center and Stennis Space Center have relied upon the solvent Asahiklin AK-225 (hydrochlorofluorocarbon-225ca/cb or HCFC-225ca/cb) and, more recently AK-225G (the single isomer form, HCFC-225cb) to safely clean and verify the cleanliness of large scale propulsion oxygen systems. Effective January 1, 2015, the production, import, export, and new use of Class II Ozone Depleting Substances, including AK-225G, was prohibited in the United States by the Clean Air Act. In 2012 through 2014, NASA test labs at MSFC, SSC, and Johnson Space Center's White Sands Test Facility collaborated to seek out, test, and qualify a solvent replacement for AK-225G that is both an effective cleaner and safe for use with oxygen systems. This paper summarizes the tests performed, results, and lessons learned.

Lowrey, Nikki M.↗
NASA NTRS2016

Results of the Test Program for Replacement of AK-225G Solvent for Cleaning NASA Propulsion Oxygen Systems

Since the 1990's, when the Class I Ozone Depleting Substance (ODS) chlorofluorocarbon-113 (CFC-113) was banned, NASA's propulsion test facilities at Marshall Space Flight Center (MSFC) and Stennis Space Center (SSC) have relied upon the solvent AsahiKlin AK-225 (hydrochlorofluorocarbon-225ca/cb or HCFC-225ca/cb) and, more recently AK-225G (the single isomer form, HCFC-225cb) to safely clean and verify the cleanliness of large scale propulsion oxygen systems. Effective January 1, 2015, the production, import, export, and new use of Class II Ozone Depleting Substances, including AK-225G, was prohibited in the United States by the Clean Air Act. In 2012 through 2014, NASA test labs at MSFC, SSC, and Johnson Space Center's White Sands Test Facility (WSTF) collaborated to seek out, test, and qualify a solvent replacement for AK-225G that is both an effective cleaner and safe for use with oxygen systems. This paper summarizes the tests performed, results, and lessons learned.

Lowrey, Nikki M.↗
NASA NTRS2016

The Soil Moisture Acttive Passive Mission: Fault Protection Performance and Lessons Learned

Fault protection as a discipline involves a collection of flight software logic and operational processes for detecting unacceptable anomalous behavior, responding prior to reaching criticality, restricting the propagation of a failure beyond a fault containment region, and recovering the vehicle back to full or degraded functionality if possible. The System Fault Protection (SFP) design for the SMAP Earth orbiter was put to the test during its 90-day vehicle commissioning activities. During this time, the SFP software autonomously protected the vehicle from multiple faults to critical hardware, and the operations team successfully returned the observatory to its science state. The SFP also performed well in the presence of anomalous behavior below true safety limits by not taking unnecessary response actions, instead allowing the operations team time to monitor the behavior. Certain aspects of the SFP design were modified during operations via both parameter updates and a full flight software update in order to better match the vehicle behavior in the flight environment. An evaluation of the SMAP SFP performance during vehicle Commissioning will be provided in this paper, as well as a set of lessons learned largely focused on visibility, SFP mutability in operations, responses to peripheral device faults, and Safe Mode recovery and design. By capturing some of the knowledge gained during SMAP Commissioning, it is intended that this paper provide guidance for making future System Fault Protection designs more robust and supportive of operations.

Clark, Jessica↗
NASA NTRS2003

Atmospheric Ionizing Radiation (AIR): Analysis, Results, and Lessons Learned From the June 1997 ER-2 Campaign

The United States initiated a program to assess the technology required for an environmentally safe and operationally efficient High Speed Civil Transport (HSCT) for entrance on the world market after the turn of the century. Due to the changing regulations on radiation exposures and the growing concerns over uncertainty in our knowledge of atmospheric radiations, the NASA High Speed Research Project Office (HSRPO) commissioned a review of "Radiation Exposure and High-Altitude Flight" by the National Council on Radiation Protection and Measurements (NCRP). On the basis of the NCRP recommendations, the HSRPO funded a flight experiment to resolve the environmental uncertainty in the atmospheric ionizing radiation levels as a step in developing an approach to minimize the radiation impact on HSCT operations. To minimize costs in this project, an international investigator approach was taken to assure coverage with instrument sensitivity across the range of particle types and energies to allow unique characterization of the diverse radiation components. The present workshop is a result of the flight measurements made at the maximum intensity of the solar cycle modulated background radiation levels during the month of June 1997.

Wilson, J. W.↗