SEARCH · Search NASA

Results for “Safe Learning”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Smart CO2 Transport-Route Planning Tool: Providing Data and Insights for Accelerating Carbon Transport & Storage Deployment

Overview presentation given at the 2024 FECM / NETL Carbon Management Research Project Review Meeting on NETL's Bipartisan Infrastructure Law-funded Smart CO2 Transport-Route Planning Tool and associated geodatabase. This machine learning informed, data-driven public resource was designed to inform regulators, industry, and researchers plan and develop safe and efficient transport routes across the country.

Romeo, Lucy↗

NASA NTRS2018

Verification and Validation Challenges for Adaptive Flight Control of Complex Autonomous Systems

Autonomy of aerospace systems requires the ability for flight control systems to be able to adapt to complex uncertain dynamic environment. In spite of the five decades of research in adaptive control, the fact still remains that currently no adaptive control system has ever been deployed on any safety-critical or human-rated production systems such as passenger transport aircraft. The problem lies in the difficulty with the certification of adaptive control systems since existing certification methods cannot readily be used for nonlinear adaptive control systems. Research to address the notion of metrics for adaptive control began to appear in the recent years. These metrics, if accepted, could pave a path towards certification that would potentially lead to the adoption of adaptive control as a future control technology for safety-critical and human-rated production systems. Development of certifiable adaptive control systems represents a major challenge to overcome. Adaptive control systems with learning algorithms will never become part of the future unless it can be proven that they are highly safe and reliable. Rigorous methods for adaptive control software verification and validation must therefore be developed to ensure that adaptive control system software failures will not occur, to verify that the adaptive control system functions as required, to eliminate unintended functionality, and to demonstrate that certification requirements imposed by regulatory bodies such as the Federal Aviation Administration (FAA) can be satisfied. This presentation will discuss some of the technical issues with adaptive flight control and related V&V challenges.

Nguyen, Nhan T.↗

NASA NTRS2021

NASA Framework for the Ethical Use of Artificial Intelligence (AI)

The NASA Framework for the Ethical Use of Artificial Intelligence (AI) provides six key principles to guide NASA's use of AI. The principles are NASA's AI must be 1. Fair, 2., Explainable and transparent, 3. Accountable, 4. Secure and safe, 5. Human-centric and societally beneficial, and 6. Scientifically and technically robust. The framework describes each ethical AI principle, and then applies that principle to NASA work. The framework also includes a list of questions practitioners should use to guide their AI work. Finally, the framework focuses on concrete, practical considerations for the next five - ten years, while also beginning to lay the foundation for longer-term disruptive change as human-level (or beyond) AI is created.

Artificial Intelligence↗

NASA NTRSDate not supplied

Metal Additive Manufacturing for Rocket Engines: Successes and Failures

NASA has been developing additive manufacturing (AM) for various technical and programmatic advantages for complex rocket engine and aerospace components. This maturation has focused on various AM processes, new alloys, characterizing material properties, developing standards, producing demonstrator parts, and integrating AM hardware in liquid rocket engines through test-fail-fix cycles, as well as application and dissemination of lessons learned of the AM lifecycle. The importance of proper AM processing was made evident in the failure of a Laser Powder Bed Fusion (L-PBF) copper-alloy combustion chamber during a hot-fire test due to a degraded material quality. The hot-fire test aimed to demonstrate high duty cycle under a risk-tolerant development project, where consequences of component failure would be minimal. However, the unintentional component failure emphasized the necessity of robust material characterization and rigorous process control procedures for the safe use of AM components in critical applications. This presentation provides an overview of the development failure, a discussion on the evaluation of the failed chamber and supplemental chambers produced at the same time, a representative material samples that included intentional build witness lines, and a summary of the key results and recommendations from the evaluations. NASA continues to approach AM processes and designs with a level of risk and acceptance of failures that is appropriate for the project objectives, with the overall goal of safe implementation of AM technology and transferring AM technology into commercial space applications. This presentation with provide critical awareness to the community lessons learned on proper implementation of AM.

L-PBF↗

NASA NTRSDate not supplied

Successes and Failures of Metal Additive Manufacturing for Rocket Engines

Additive Manufacturing↗

NASA NTRS2006

NASA Crew Launch Vehicle Approach Builds on Lessons from Past and Present Missions

The United States Vision for Space Exploration, announced in January 2004, outlines the National Aeronautics and Space Administration's (NASA) strategic goals and objectives, including retiring the Space Shuttle and replacing it with a new human-rated system suitable for missions to the Moon and Mars. The Crew Exploration Vehicle (CEV) that the new Crew Launch Vehicle (CLV) lofts into space early next decade will initially ferry astronauts to the International Space Station and be capable of carrying crews back to lunar orbit and of supporting missions to Mars orbit. NASA is using its extensive experience gained from past and ongoing launch vehicle programs to maximize the CLV system design approach, with the objective of reducing total lifecycle costs through operational efficiencies. To provide in-depth data for selecting this follow-on launch vehicle, the Exploration Systems Architecture Study was conducted during the summer of 2005, following the confirmation of the new NASA Administrator. A team of aerospace subject matter experts used technical, budget, and schedule objectives to analyze a number of potential launch systems, with a focus on human rating for exploration missions. The results showed that a variant of the Space Shuttle, utilizing the reusable Solid Rocket Booster as the first stage, along with a new upper stage that uses a derivative of the RS-25 Space Shuttle Main Engine to deliver 25 metric tons to low-Earth orbit, was the best choice to reduce the risks associated with fielding a new system in a timely manner. The CLV Project, managed by the Exploration Launch Office located at NASA's Marshall Space Flight Center, is leading the design, development, testing, and operation of this new human-rated system. The CLV Project works closely with the Space Shuttle Program to transition hardware, infrastructure, and workforce assets to the new launch system . leveraging a wealth of lessons learned from Shuttle operations. The CL V is being designed to reduce costs through a number of methods, ranging from validating requirements to conducting trades studies against the concept design. Innovations such as automated processing will build on lessons learned from the Shuttle, other launch systems, Department of Defense operations experience, and subscale flight tests such as the Delta Clipper-Experimental Advanced (DCXA) vehicle operations that utilized minimal touch labor, automated cryogen ic propellant loading , and an 8-hour turnaround for a cryogenic propulsion system. For the CLV, the results of hazard analyses are contributing to an integrated vehicle health monitoring system that will troubleshoot anomalies and determine which ones can be solved without human intervention. Such advances will help streamline the mission operations process for pilots and ground controllers alike. In fiscal year 2005, NASA invested approximately $4.5 billion of its $16 bill ion budget on the Space Shuttle. The ultimate goal of the CLV Project is to deliver a safe, reliable system designed to minimize lifecycle costs so that NASA's budget can be invested in missions of scientific discovery. Lessons learned from developing the CLV will be applied to the growth path for future systems, including a heavy lift launch vehicle.

Dumbacher, Daniel L.↗

NASA NTRS2011

Human Factors Throughout the Life Cycle: Lessons Learned from the Shuttle Program

With the ending of the Space Shuttle Program, it is critical that we not forget the Human Factors lessons we have learned over the years. At every phase of the life cycle, from manufacturing, processing and integrating vehicle and payload, to launch, flight operations, mission control and landing, hundreds of teams have worked together to achieve mission success in one of the most complex, high-risk socio-technical enterprises ever designed. Just as there was great diversity in the types of operations performed at every stage, there was a myriad of human factors that could further complicate these human systems. A single mishap or close call could point to issues at the individual level (perceptual or workload limitations, training, fatigue, human error susceptibilities), the task level (design of tools, procedures and aspects of the workplace), as well as the organizational level (appropriate resources, safety policies, information access and communication channels). While we have often had to learn through human mistakes and technological failures, we have also begun to understand how to design human systems in which individuals can excel, where tasks and procedures are not only safe but efficient, and how organizations can foster a proactive approach to managing risk and supporting human enterprises. Panelists will talk about their experiences as they relate human factors to a particular phase of the shuttle life cycle. They will conclude with a framework for tying together human factors lessons-learned into system-level risk management strategies.

human factors↗

NASA NTRSDate not supplied

What Can We Learn From Resilient Pilot Behaviors? The Case of Energy Management While Flying a Star

Recently, there has been increased interest in documenting flightcrew behaviors that contribute to safe operations. Instead of only capturing errors, new efforts are attempting to understand how pilots manage complexity and variability in the operational environment to ensure a safe mission. This approach highlights pilot responses to events and conditions that fall outside typical TEM threats; e.g., revised ATC clearances. This approach presents a two-sided coin: characterize flightcrew resilience /or/ generate insights regarding complexity in the operational environment that is not adequately managed by current flight deck interface designs, procedures, and training. To capture operational complexity, we have been analyzing flight path management tied to flying an RNAV STAR. Because ATC often requests revisions—e.g., descend late—and because RNAV STARs may not align with airplane performance limits, flightcrews need to monitor, anticipate threats to RNAV STAR compliance, and devise ways to accommodate unexpected challenges. In this paper, we identify general strategies that can support response adaptation and explore methods to facilitate training these strategies.

flight operations↗

NASA NTRS2007

Flight and Integrated Testing: Blazing the Trail for the Ares Launch Vehicles

It has been 30 years since the United States last designed and built a human-rated launch vehicle. The National Aeronautics and Space Administration (NASA) has marshaled unique resources from the government and private sectors that will carry the next generation of astronauts into space safer and more efficiently than ever and send them to the Moon to develop a permanent outpost. NASA's Flight and Integrated Test Office (FITO) located at Marshall Space Flight Center and the Ares I-X Mission Management Office have primary responsibility for developing and conducting critical ground and flight tests for the Ares I and Ares V launch vehicles. These tests will draw upon Saturn and the Space Shuttle experiences, which taught the value of using sound systems engineering practices, while also applying aerospace best practices such as "test as you fly" and other lessons learned. FITO will use a variety of methods to reduce the technical, schedule, and cost risks of flying humans safely aboard a launch vehicle.

Taylor, James L.↗

NASA NTRS2007

An Exploration Perspective of Beamed Energy Propulsion

The Vision for Exploration is currently focused on flying the Space Shuttle safely to complete our Space Station obligations, retiring the Shuttle in 2010, then returning humans to the Moon and learning how to proceed to Mars and beyond. The NASA budget still includes funds for science and aeronautics but the primary focus is on human exploration. Fiscal constraints have led to pursuing exploration vehicles that use heritage hardware, particularly existing boosters and engines, with the minimum modifications necessary to satisfy mission requirements. So, pursuit of immature technologies is not currently affordable by NASA. Beamed energy is one example of an immature technology, from a human exploration perspective, that may eventually provide significant benefits for human exploration of space, but likely not in the near future. Looking to the more distant future, this paper will examine some of the criteria that must be achieved by beamed energy propulsion to eventually contribute to human exploration of the solar system. The analysis focuses on some of the implications of increasing the payload fraction of a launch vehicle, with a quick look at trans-lunar injection. As one would expect, there is potential for benefit, and there are concerns. The analysis concludes with an assessment of the Technology Readiness Level (TRL) for some beamed energy propulsion components, indicating that TRL 2 is close to being completed.

Cole, John W.↗

NASA NTRS2024

International Space Station Satellite Deployment: Jettison Policy and Best Practices for Satellite Payload Developers

The International Space Station (ISS) deploys dozens of small satellites into Low Earth Orbit (LEO) each year. This presentation and associated paper cover the ISS Jettison Policy requirements and review/approval process, as well as best practices for satellite Payload Developers who have satellites manifested for deployment from ISS. Specifically, topics will include ISS Jettison Policy requirements to limit generation of orbital debris, limit risk of collision with ISS, and limit risk of collision with ISS visiting vehicles. The paper will include details on the ISS Program jettison candidate analysis and approval process, timelines for data submittal to ISS Program, resources for small satellite developers, and design & analysis recommendations for small satellite developers to maximize their likelihood of successful deployment from ISS. New Station deploy capabilities and ways the ISS Program addresses and facilitates innovations in small satellite technology, including propulsion systems, deorbit devices, constellation development, and novel tech demos, will also be explored. The 2024 session topic that best fits this abstract is Orbital Debris, SSA & STM. The ISS Jettison Policy intends to quantify and control the risks of deploying and operating small satellites, not only to ensure the safety of the humans flying in space, but also to preserve the orbital environment for world space activities and enable the significant benefits brought by such utilization. The ISS Program is committed to working with smallsat providers to address their challenges and enable safe, accessible, innovative missions. The Policy has grown with the industry, with each deploy yielding hard-earned lessons learned that improve our process – not only for the next deploy campaign, but with applicability and adaptability for future applications in LEO and beyond.

Jettison Policy↗

NASA NTRS2019

Health Management and Prognostics for Electric Aircraft Powertrain

W and c Any air borne vehicle needs incorporating safety as key parameter of measure, and inclusion of autonomy raises the critical need for safety under autonomous operations. Management of faults and component degradation is key as complexity in autonomous operations grow over the period of time. Therefore, in addition to basic operational requirements, an autonomous electric vehicle should be able to make accurate estimates of its current system health and take the correct decisions to complete its mission successfully. Real-time safety and state-awareness tools are therefore essential for the vehicle to be able to reach its destination in a safe and successful manner. The need for safety assurance and health management capabilities is particularly relevant for aircraft electric propulsion systems, which are relatively new and with limited historical to learn. They are critical systems requiring high power density along with reliability, resilience, efficient management of weight, and operational costs. A model- based fault diagnosis and prognostics approach of complex critical systems can successfully accomplish the safety and state awareness goal for such electric propulsion systems, enabling autonomous decision making capability for safe and efficient operation. To identify critical components in the system a Qualitative Bayesian approach using FMECA is implemented. This requires the assessment of some quantities representing the state of the electric unmanned aerial systems (e-UAS), as well as look-ahead forecasts of such states during the entire flight, presented in form of safety metrics (SM). In-service data and performance data gathered from degraded components sup- ports diagnostic and prognostic methods for these systems, but this data can be difficult to obtain as weight and packaging restrictions reduce redundancy and instrumentation on-board the vehicle. Therefore, an model-based framework should be capable or operating with limited data. In addition to data scarcity, the variability of such complex critical systems re- quires the model-based framework to reason in the presence of uncertainty, such as sensor noise, and modeling imperfections. Quantification of errors and uncertainties in the measured states and quantities is therefore a fundamental step for a precise estimation of such SMs; un-modeled uncertainty may result in erroneous state assessment and un- reliable predictions of future states of e-UAVs. Typical, centralized model-based schemes suffer from inherent disadvantages such as computational complexity, single point of failure, and scalability issues, and therefore may fail in such a complex scenario. This paper presents a methodology for developing a system level diagnostics and prognostics approach using a Qualitative Bayesian FMECA approach along with a formal uncertainty management framework for an e-UAS. In this work we demonstrate the efficacy of the framework to predict effects of sub-system level degradation on vehicle operation incorporating uncertainty management to predict future behavior under different operating conditions.

Kulkarni, Chetan↗

DOE OSTI2025

Ensuring Safe, Effective, and Reliable Use of Artificial Intelligence-Based Applications for Nuclear Electricity Generation through a Systems Approach

There is a significant potential to reduce operating and maintenance cost at nuclear power plants using artificial intelligence (AI) and machine learning (ML). For instance, AI/ML has the potential to significant improve work management processes, condition reporting, and plant surveillance activities. However, the nuclear industry has been slow in adopting AI/ML due to several multifaceted barriers discussed in this paper. This work presents such multidisciplinary approach intended to 1) accelerate industry adoption of AI/ML-based applications at nuclear power plants and 2) ensure their safe, reliable, and effective use. This approach is discussed further in this work and will be used to address overarching challenges associated with AI deployment at scale to provide industry guidance that support accelerated adoption of AI/ML technologies throughout the industry.

99 - GENERAL AND MISCELLANEOUS↗

NASA NTRS1990

Growing the Space Station's electrical power plant

For over a decade NASA LeRC has been defining, demonstrating, and evaluating power electronic components and multi-kilowatt, multiply redundant, electrical power systems as part of OAST charter. Whether one considers aircraft (commercial transport/military), Space Station Freedom, growth station, launch vehicles, or the new Human Exploration Initiative, the conclusions remain the same: high frequency AC power distribution and control is superior to all other approaches for achieving a fast, smart, safe, versatile, and growable electrical power system that will meet a wide range of mission options. To meet the cost and operability goals of future aerospace missions that require significantly higher electrical power and longer durations, we must learn to integrate multiple technologies in ways that enhance overall system synergisms. The way NASA is doing business in space electric power is challenged and some approaches for evolving large space vehicles and platforms in well constructed steps to provide safe, ground testable, growable, smart systems that provide simple, replicative logic structures, which enable hardware and software verification, validation, and implementation are proposed. Viewgraphs are included.

Sundberg, Gale R.↗

DOE OSTI2024

Predicting the heat release variability of Li-ion cells under thermal runaway with few or no calorimetry data

Accurate measurement of the variability of thermal runaway behavior of lithium-ion cells is critical for designing safe battery systems. However, experimentally determining such variability is challenging, expensive, and time-consuming. Here, we utilize a transfer learning approach to accurately estimate the variability of heat output during thermal runaway using only ejected mass measurements and cell metadata, leveraging 139 calorimetry measurements on commercial lithium-ion cells available from the open-access Battery Failure Databank. We show that the distribution of heat output, including outliers, can be predicted accurately and with high confidence for new cell types using just 0 to 5 calorimetry measurements by leveraging behaviors learned from the Battery Failure Databank. Fractional heat ejection from the positive vent, cell body, and negative vent are also accurately predicted. We demonstrate that by using low cost and fast measurements, we can predict the variability in thermal behaviors of cells, thus accelerating critical safety characterization efforts.

25 ENERGY STORAGE↗

NASA NTRS1991

Applications of fuzzy logic to control and decision making

Long range space missions will require high operational efficiency as well as autonomy to enhance the effectivity of performance. Fuzzy logic technology has been shown to be powerful and robust in interpreting imprecise measurements and generating appropriate control decisions for many space operations. Several applications are underway, studying the fuzzy logic approach to solving control and decision making problems. Fuzzy logic algorithms for relative motion and attitude control have been developed and demonstrated for proximity operations. Based on this experience, motion control algorithms that include obstacle avoidance were developed for a Mars Rover prototype for maneuvering during the sample collection process. A concept of an intelligent sensor system that can identify objects and track them continuously and learn from its environment is under development to support traffic management and proximity operations around the Space Station Freedom. For safe and reliable operation of Lunar/Mars based crew quarters, high speed controllers with ability to combine imprecise measurements from several sensors is required. A fuzzy logic approach that uses high speed fuzzy hardware chips is being studied.

Lea, Robert N.↗

DOE OSTI2024

Development of algorithms for augmenting and replacing conventional process control using reinforcement learning

Here, this work seeks to allow for the online operation and training of model-free reinforcement learning (RL) agents but limit the risk to system equipment and personnel. The parallel implementation of RL alongside more conventional process control (CPC) allows for the RL algorithm to learn from CPC. The past performance of both methods are assessed on a continuous basis allowing for a transition from CPC to RL and, if needed, transitioning back to CPC from RL. This allows for the RL algorithm to slowly and safely assume control of the process without significant degradation in control performance. It is shown that the RL can derive a near optimal policy even when coupled with a suboptimal CPC. It is also demonstrated that the coupled RL-CPC algorithm learns at a faster rate than traditional RL methods of exploration while the algorithm’s performance does not deteriorate below CPC, even when exposed to an unknown operating condition.

30 DIRECT ENERGY CONVERSION↗

NASA NTRS2020

MER Opportunity dust-storm recovery operations and implications for future Mars surface missions

In June 2018, NASA’s Mars Exploration Rover Opportunity became engulfed in the most intense global dust storm observed in its 14-year mission and in Mars’ recorded history. Sapped of life-giving solar energy, Opportunity fell silent to ground operators on June 11, in what would be its final call home. Over the course of the next eight months, the MER team employed numerous recovery efforts and radiated over one thousand commands to wake the silent rover. Although unsuccessful, MER’s dust-storm recovery team changed the paradigm of dust-storm operations from Opportunity’s survival of a previous global dust storm in 2007. In this paper, the authors offer a glimpse into MER’s recovery efforts and lessons learned from Opportunity dust-storm operations for future solar-powered Mars surface missions. In the first section, the authors discuss the indicators of the approaching dust storm and the actions the team employed to reduce Opportunity’s power consumption and preserve available battery charge prior to loss of contact. The second section discusses the team’s recovery efforts until Opportunity’s declared End-of-Mission, the steps the team took to re-establish contact with Opportunity, the assumptions made during each step of the recovery process, and the commanding actions employed. Finally, the authors discuss the operational impacts of global dust storms on the safe and successful operation of solar-powered spacecraft on the Martian surface, and offer design recommendations for future solar-powered missions from the lessons learned during Opportunity’s 14-year mission and experience through two global dust storms.

Nelson, Robert W.↗