SEARCH · Search NASA

Results for “Resilience operations”

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 145 records · Page 8

All sources NASA NTRS DOE OSTI

NASA NTRSDate not supplied

SafeMAP: Safe Multi-Agent Planning framework based on Dynamic Probabilistic Risk Assessment

This paper proposes a risk-aware framework for Safe Multi-Agent Planning (SafeMAP) that unifies disparate models for multi-agent systems in a Markovian process that allows for simultaneous system health monitoring, decision making under uncertainty, and multi-agent system collaboration. As operations beyond low earth orbit mature, there is an increased need for autonomous cyber-physical systems with onboard decision making capabilities. Multi-agent cyber-physical systems in particular offer the potential of increased efficiency, resiliency, and mission capabilities for future applications such as multi-rover terrain operations, distributed satellite operations, and management of smart lunar habitats. SafeMAP utilizes physics-based models of each agent and the relevant components, probability models of the environment and component operational states, and reward models for mission-specific objectives such as scientific task completion or resource consumption. The output of SafeMAP is a set of mission plans that satisfy the mission objective under specified risk/reward constraints. A readable interpretation of each of these generated mission plans is provided as an additional output. SafeMAP has been demonstrated on a simulated case study involving a four-rover system performing surface mapping operations and science tasks. Results of this paper demonstrate SafeMAP’s ability to generate explainable mission plans that satisfy the mission objective while minimizing risk under nominal and off-nominal conditions.

Mohammad Hejase↗

NASA NTRSDate not supplied

Active Swarm Resiliency in the HelioSwarm Mission

Designed to observe plasma turbulence dynamics in solar wind over a distributed volume of space, the HelioSwarm mission comprises a primary chief spacecraft and eight smaller deputy satellites in uniquely assigned “loops” of periodic relative motion in a P/2 lunar resonant orbit. If one or more deputies fail, this multi-satellite architecture facilitates resiliency for science goals through repositioning of satellites to contingency loops. This strategy of Active Swarm Resiliency mitigates risk by modeling quantitative results ahead of time for mission operators to make informed decisions. Responsive actions meet minimum science objectives based on past and predicted system performance, an approach with applications to future missions with similar architecture and requirements.

Fault Management↗

NASA NTRSDate not supplied

Active Swarm Resiliency in the HelioSwarm Mission

Fault Management↗

NASA NTRS2002

Alternative Metrics for Evaluating the Resilence of Advanced Life Support Systems

Ensuring the safety of the crew is a key performance requirement of a life support system. However, a number of conceptual and practical difficulties arise when devising metrics to concretely measure the ability of a life support system to maintain critical functions in the presence of anticipated and unanticipated faults. Resilience is a dynamic property of a life support system that depends on the complex interactions between faults, controls and system hardware. We review some of the approaches to understanding the robustness or resilience of complex systems being developed in diverse fields such as ecology, software engineering and cell biology and discuss their applicability to regenerative life support systems. We also consider how approaches to measuring resilience vary depending on system design choices such as the definition and choice of the nominal operating regime. Finally, we explore data collection and implementation issues such as the key differences between the instantaneous or conditional and average or overall measures of resilience. Extensive simulation of a hybrid computational model of a water revitalization subsystem (WRS) with probabilistic, component-level faults provides data about off-nominal behavior of the system. The data are used to consider alternative measures of resilience as predictors of the system's ability to recover from component-level faults.

Bell, Ann Maria↗

NASA NTRSDate not supplied

Survey Development and Initial Data: Flight Context and Pilot Techniques in Everyday Flights

The aviation industry is recognizing that flight crews routinely contribute to system safety in ways that go beyond adherence to standard operating procedures (SOPs). Our research goals were to explore a) whether a survey could shed light on pilots' contributions to adaptation and resilience in everyday flights and b) relevant assessment methods. The survey focused on challenges faced by pilots in normal operations, and on the ways that pilots anticipate and monitor those challenges. We collected responses concerning revenue flights from two pilot groups; one group also provided responses concerning a simulated scenario. The results indicated that relatively few flights proceeded exactly as in the original flight plan. Pilots routinely anticipated and adapted to changing circumstances. We discuss some design and assessment challenges encountered for a survey on this topic, we provide 5 approaches to assessment, and we present example findings as illustrations. We hope assessment methods such as these will lead to useful surveys of resilience in flight.

pilot behavior↗

NASA NTRS2023

Nonrepudiation for Drone Related Data

In order for UTM to support safe multiple UAS operations within and beyond visual line of sight, data related to weather, 3D structures, other aircraft, etc. must be made available. To support safe operations data must be collected and maintained considering security and resilience.

Security↗

NASA NTRS1994

Bevel gear driver and method having torque limit selection

This invention comprises a torque drive mechanism utilizing axially translatable, mutually engageable transmission members having mating crown gears, driven and driving members with a three-element drive train being biased together by resilient means or by a fluid actuator system, the apparatus being operable to transmit a precisely controlled degree of torque to a driven member. The apparatus is applicable for use in hand tools and as a replacement for impact torque drivers, torque wrenches, motorized screw drivers, or the like, wherein the applied torque must be precisely controlled or limited. The bevel torque drive includes a drive gear which is axially displaceable and rotatable within cylindrical driver housing, a rotatable intermediate gear, and an output gear. Key rotationally secures displaceable gear with respect to input shaft but permits axial movement therebetween. A thrust bearing is preferably connected to the lower end of shaft for support to reduce play and friction between shaft and a transmission joint disc during rotation of the gear train. Coaxially mounted coiled spring is footed against displaceable gear for biasing the displaceable gear toward and into engagement with the intermediate gear for driving intermediate gear and output gear. Torque control is achieved by the use of straight or spiral beveled gears which are of configurations adapted to withdraw from mutual engagement upon the torque exceeding a predetermined limit. The novel, advantageous features of the invention include the configuration of the mating, crown gear sets and the axially translatable, slidable drive gear. The mechanism is capable of transmitting a high degree of torque within a narrow, compact transmission housing. The compact size and narrow, elongated configuration of the housing is particularly applicable for use in hand tools and in multiple torque driver mechanisms in which it is necessary to drive multiple fasteners which are located in close proximity. Prior torque drivers such as 'click-type' torque wrenches do not actually limit torque application but only provide an audible warning that the limit has been reached.

Cook, Joseph S., Jr.↗

NASA NTRS2020

Unsupervised Anomaly Detection in High-Dimensional Flight Data Using Convolutional Variational Auto-Encoder

The modern National Airspace System (NAS) is an extremely safe system and the aviation industry has experienced a steady decrease in fatalities over the years. This can be attributed to both improved flight critical systems with redundant hardware and software protections, as well as an increased focus on active monitoring and response to real time and historically identified vulnerabilities by implementing more resilient procedures and protocols. The main approach for identifying vulnerabilities in operations leverages domain expertise using knowledge about how the system should behave within the expected tolerances to known safety margins. This approach works well when the system has a well-defined operating condition. However, the operations in the NAS can be highly complex with various nuances that render it difficult to clearly pre-define all known safety vulnerabilities. With the advancement of data science and machine learning techniques, the potential to automatically identify emerging vulnerabilities in the observed operations has become more practical in recent years. The state-of-the-art anomaly detection approaches in aerospace data usually rely on supervised or semi-supervised learning. However, in many real-world problems such as flight safety, creating labels for the data requires huge amount of effort and is largely impractical. To address this challenge, we developed a Convolutional Variational Auto-Encoder (CVAE), which is an unsupervised learning approach for anomaly detection in high-dimensional heterogeneous time-series data. We validate performance of CVAE compared to the state-of-the-art supervised learning approach as well as unsupervised clustering-based approach using KMeans++ and kernel-based approach using One-Class Support Vector Machine (OC-SVM) on Yahoo!'s benchmark time series anomaly detection data. Finally, we showcase performance of CVAE on a case study of identifying anomalies in the first 60 seconds of commercial flights' take-offs using Flight Operational Quality Assurance (FOQA) data.

Memarzadeh, Milad↗

NASA NTRSDate not supplied

Unsupervised Anomaly Detection in High-Dimensional Flight Data Using Convolutional Variational Auto-Encoder

The modern National Airspace System (NAS) is an extremely safe system. The industry has experienced a steady decrease in fatalities over the years. This can be contributed to both improved flight critical systems with redundant hardware and software protections as well as an increased focus on active monitoring and response to real time and historically identified vulnerabilities by implementing more resilient procedures and protocols. The main practice for identifying vulnerabilities in operations leverages domain expertise using knowledge about how the system should behave with the expected tolerances to known safety margins. This approach works well when the system has a well-defined operating condition. However, the operations in the NAS can be highly complex with various nuances that render it difficult to clearly pre-define all known safety vulnerabilities. With the advancement of data science and machine learning techniques, the potential to automatically identify emerging vulnerabilities in the observed operations has become more practical in recent years. The state-of-the-art anomaly detection approaches in aerospace data usually rely on supervised or semi-supervised learning. However, in many real-world problems such as flight safety creating labels for the data requires huge amount of efforts and is largely expensive. As a result, in this article, we develop a Convolutional Variational Auto-Encoder (CVAE), an unsupervised learning approach for anomaly detection in high-dimensional heterogeneous time-series data. We validate performance of CVAE compared to the state-of-the-art supervised learning approach (as an upper bound) as well as an supervised clustering based on K-Means (as a lower bound) on Yahoo!'s benchmark time series anomaly detection data. Finally, we showcase performance of CVAE on a case study of identifying anomalies in the first 60 seconds of commercial flights' take-offs using Flight Operational Quality Assurance (FOQA) data.

Milad Memarzadeh↗

NASA NTRSDate not supplied

Creating Formal Characterizations of Routine Contingency Management in Commercial Aviation

The identification, modelling, and analysis of root causes of accidents and incidents dominate conventional safety management approaches. However, the effect of humans’ safety-producing behavior on the overall resilience of the system is often neglected. Additionally, emerging aviation markets are giving rise to concepts of operation, such as urban air mobility and optionally piloted air cargo operations, that are leading to a shift in locus of control between humans and automation. Without an understanding of the human contribution to safety, it is difficult to assess the effects of these novel role allocations on overall system safety. In this work, safety-producing behaviors are identified and abstracted into resilient performance strategies. Production rules that encapsulate these strategies are then generated and classified in the Soar cognitive architecture. The strategies are then applied to a remotely-operated air cargo example to demonstrate how safe learning is facilitated. The learned rules and strategies are then formally verified.

Safety Critical Systems↗

NASA NTRS2009

Fluoroester Co-Solvents for Low-Temperature Li+ Cells

Electrolytes comprising LiPF6 dissolved in alkyl carbonate/fluoroester mixtures have been found to afford improved low-temperature performance and greater high-temperature resilience in rechargeable lithium-ion electrochemical cells. These and other electrolytes comprising lithium salts dissolved mixtures of esters have been studied in continuing research directed toward extending the lower limit of operating temperatures of such cells. This research at earlier stages, and the underlying physical and chemical principles, were reported in numerous previous NASA Tech Briefs articles. The purpose of the present focus on high-temperature resilience in addition to low-temperature performance is to address issues posed by the flammability of the esters and, at temperatures near the upper end (about 55 C) of their intended operating temperature range, by their high chemical reactivity. As used here, high-temperature resilience signifies, loosely, a desired combination of low flammability of an electrolyte mixture and the ability of a cell that contains the mixture to sustain a relatively small loss of reversible charge/discharge capacity during storage in the fully charged condition at high temperature. The selection of fluoroesters for study as candidate electrolyte solvent components to increase high-temperature resilience was prompted in part by the observation that like other halogenated compounds, fluoroesters have low flammability. The fluoroesters investigated in this study include trifluoroethyl butyrate (TFEB), ethyl trifluoroacetate (ETFA), trifluoroethyl acetate (TFEA), and methyl pentafluoropropionate (MPFP). Solvent mixtures were prepared by mixing these fluoroesters with two other esters: ethylene carbonate (EC) and ethyl methyl carbonate (EMC).

Smart, Marshall↗

NASA NTRS2010

Playing a 3-Stringed Violin: Innovation via the Joint Evolution of People, Process, and Knowledge Management System

Users continuously evaluate the value and performance of their Knowledge Management Systems (KMS). As suggested by a punctuated socio-technical system process model, today's success can quickly become tomorrow's failure should the KMS fail to meet evolving needs and expectations. The more deeply a tool is embedded in the actual work process, the more vulnerable it is to emergent changes and perturbations. This paper uses the metaphor of a "3-stringed violin" to explore how differing levels of user knowledge about tools and processes can lead to system perturbations and how the active involvement of other actors can dampen the impact of perturbations, i.e., help the system survive the operational equivalent of a broken string. Recommendations suggest ways to increase system resiliency and contribute to incremental innovation.

Socio-technical systems↗

NASA NTRSDate not supplied

Exploring Methods to Collect and Analyze Data on Human Contributions to Aviation Safety: A Panel Discussion

Focusing on undesired operator behaviors is pervasive in system design and safety management cultures in aviation. This focus limits the data that are collected, the questions that are asked during data analysis, and therefore our understanding of what operators do in everyday work. Human performance represents a significant source of aviation safety data that includes both desired and undesired actions. When safety is characterized only in terms of errors and failures, the vast majority of human impacts on system safety and performance are ignored. The outcomes of safety data analyses dictate what is learned from those data, which in turn informs safety policies and safety-related decision making. When learning opportunities are systematically restricted by focusing only on rare failure events, not only do we learn less (and less often), but we can draw misleading conclusions by relying on a non-representative sample of human performance data. Changes in how we define and think about safety can highlight new opportunities for collection and analysis of safety-relevant data. Developing an integrated safety picture to better inform safety-related decision making and policies depends upon identifying, collecting, and interpreting safety-producing behaviors in addition to safety-reducing behaviors. Opportunities and challenges in collecting and analyzing the largely unexploited data on desired, safety-producing operator behaviors are discussed.

Aviation Safety↗

NASA NTRS2021

Resilient Space Habitat Design Using Safety Controls

Space habitats will involve a complex and tightly coupled combination of hardware, software, and humans, while operating in challenging environments that pose many risks, both known and unknown. It will not be possible to design habitats that are immune to failure, nor will it be possible to foresee all possible failures. Rather than aiming for designs where ―failure is not an option,‖ habitats must be resilient to disruptions. We propose an approach to resilient design for space habitats based on the concept of safety controls from system safety engineering. We model disruptions using a state-and-trigger approach, where the space habitat is in one of three distinct states at each time instance: nominal, hazardous, or accident. We use safety controls as ways of preventing a system from entering or remaining in a hazardous or accident state. We develop a safety control option space for the habitat, from which designers can select the set of safety controls that best meet resilience, performance, and other system goals. The safety control option space is likely to be large, accordingly, we design a database that links safety controls to the applicable states and triggers. We demonstrate our approach on the early design stage of a Martian space habitat.

Safety↗

NASA NTRS2021

Resilience Engineering's Potential for Advanced Air Mobility (AAM)

The national airspace (NAS) will rapidly evolve in the next ten to twenty years. Plans for Advanced Air Mobility (AAM) during that period envision highly automated airspace management systems and electrically powered vehicles. AAM concepts also anticipate limited human roles. The goal of limiting the human role is to minimize the potential for misadventures, yet how the human role is limited needs to be carefully considered in order to also preserve the potential for human successes. The field of resilience engineering (RE) focuses on how systems can change in order to seize an opportunity or withstand an unforeseen challenge. RE methods rely on the use of empirical data to optimize the ability of any system to adapt. RE studies have shown how individual and team initiatives ensure resilient system performance by creating safety through flexibility. Benefits of the RE approach include improved awareness of operational circumstances and how system elements depend on each other, and the ability to allocate limited resources and prepare for surprise. RE offers the ability to account for and incorporate the human role as an essential element in order to ensure NAS systems’ resilient performance. Data on the human contribution to safe and resilient system performance, which is termed “work as done,” are available but are not being considered as the NAS evolves. We present an approach that describes how use of RE can enable the evolving NAS to adapt, and perform, in a resilient manner.

Aviation Safety↗

NASA NTRSDate not supplied

Overview of Nasa's Watts on the Moon Challenge Phase 1

As NASA works to extend human exploration of the solar system, unprecedented capacity for electrical and thermal energy will be needed to support sustained human presence and the beginning of industrial activity on the Moon. Solar energy is abundant on the lunar surface but extended night hours (up to 350 consecutive hours) and extreme temperature change from daylight to nighttime operation creates complexity for solar power use. Analogous issues arise on Earth, where demand for additional renewable energy generation, including solar, is rising, but better power management, distribution, and energy storage solutions are needed to address intermittency and resiliency, among other issues. To accelerate the development of technologies for power distribution and energy storage that can operate in extreme lunar conditions, NASA’s Centennial Challenges Program launched the Watts on the Moon Challenge in September 2020. Submissions for Phase 1 of the challenge were due in March 2021 and winners were announced in May 2021. This paper provides an overview of the challenge, key technical requirements, outcomes from Phase 1, and an update on Phase 2 of the challenge, which is currently ongoing.

Denise P. Morris↗

NASA NTRS2005

Advanced Ceramic Wafer Seals Demonstrated at 2000 deg. F

Durable, high-temperature sliding seals are required in advanced hypersonic engines and around movable control surfaces on future vehicles. These seals must operate at temperatures of 2000 to 2500 F, limit hot gas flow, remain resilient for multiple cycles, and resist scrubbing damage against rough surfaces. Current seal designs do not meet these demanding requirements, so the NASA Glenn Research Center is developing advanced seals and preload devices to overcome these shortfalls. An advanced ceramic wafer seal design and two silicon nitride compression spring designs were evaluated in a series of compression, scrub, and flow tests.

Dunlap, Patrick H.↗

NASA NTRSDate not supplied

Technology Assessment and Modelling of Three Terminal Tandem Solar Cells for In-Space Utilization

NASA seeks a sustained human presence on the lunar surface. High-efficiency and resilient energy systems are critical to supporting habitats, scientific outposts, and lunar surface operations. Photovoltaics have long been the backbone of space power systems, transitioning from silicon solar cells to multi-junction III-V solar cells, which now dominate state-of-the-art (SOA) technology. Multi-junction cells achieve high efficiency by layering semiconductors, each absorbing a specific portion of the solar spectrum. However, efficiency gains are increasingly constrained by device physics and manufacturing complexity. Additionally, higher-order junctions pose challenges for accurate modelling and performance characterization due to difficulties in replicating the AM0 spectrum.

solar cells↗