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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Independent Orbiter Assessment (IOA): Assessment of the reaction control system, volume 1

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) are presented. The IOA effort first completed an analysis of the aft and forward Reaction Control System (RCS) hardware, and Electrical Power Distribution and Control (EPD and C), generating draft failure modes and potential critical items. To preserve independence, this analysis was accomplished without reliance upon the results contained within the NASA FMEA/CIL documentation. The IOA results were then compared to the proposed Post 51-L NASA FMEA/CIL baseline. This report documents the results of that comparison for the Orbiter RCS hardware and EPD and C systems. The IOA product for the RCS analysis consisted of 208 hardware and 2064 EPD and C failure mode worksheets that resulted in 141 hardware and 449 EPD and C potential critical items (PCIs) being identified. A comparison was made of the IOA product to the NASA FMEA/CIL baseline. After comparison and discussions with the NASA subsystem manager, 96 hardware issues, 83 of which concern CIL items or PCIs, and 280 EPD and C issues, 158 of which concern CIL items or PCIs, and 280 EPD and C issues, 158 of which concern CIL items or PCIs, remain unresolved. Volume 1 contains the subsystem description, assessment results, and some of the IOA worksheets.

Prust, Chet D.↗
DOE OSTI2020

The Corrective Maintenance Paradigm Shift at Hanford's Tank Farms - 20077

Hanford's Tank Farms facilities have been used to safely store waste for over 70 years, with the first single-shell tanks being constructed in 1943. Tank Farm facilities consist of 149 single-shell tanks, 28 double-shell tanks, an evaporator facility, and wastewater treatment facilities. Tank Farm facilities are aging, with a tremendous corrective maintenance burden on the Tank Farm contractor. The mission of Tank Farm facilities is soon changing from waste storage to waste staging for the Hanford Waste Treatment and Immobilization Plant (WTP). WTP operations will demand a significant increase in Tank Farm facility operations, in which corrective maintenance outage windows will shrink drastically. This realization has forced the Tank Farm contractor to consider a paradigm shift in Tank Farm facilities Maintenance planning, and the use of reliability Engineering tools. The Tank Farm Production Operations Engineering Cognizant System Engineering (CSE) organization has led the way in motivating this paradigm shift. This shift has been realized through the use of: 1) technical exchange with other Department of Energy (DOE) contractors to develop improvements in the CSE program, 2) a shift from the use of lagging to leading system health indicators, and 3) a Plant Health Committee to unite Engineering, Operations, and Maintenance personnel toward a productive maintenance strategy. The CSE organization has held several technical exchanges with other DOE contractors to discuss CSE concepts, and how to better maintain aging infrastructure. The technical exchange with other contractors has greatly reduced the time required to make improvements in the Tank Farm CSE program. Other DOE contractors have already faced issues surrounding aging infrastructure, and have vast experience in improving the reliability and usable life of structures and components in nuclear facilities. The past CSE program used lagging health indicators to determine the health of systems. The key lagging indicator used to determine system health was availability, which is the percentage of time that a facility was ready for operation compared to the time the facility was demanded for operation. Availability was a good indicator of health in the waste storage mission of Tank Farms, where safe storage was the most important function of the facility, and where maintenance outage windows were typically long-duration. In current and future operations, outage windows are reducing, resulting in the need for much more reliable systems. Systems that have had high availability may suddenly become inoperable due to a failed component or sub-system. In several instances, the use of availability as an indicator of system health failed to predict system/equipment failure before its occurrence. In discussions with other DOE contractors, a set of reliability tools, including leading indicators of health, has been implemented in the CSE program. This primarily involves the use of failure modes and effects analysis and the study of equipment failure to develop system monitoring plans that focus on trending data to detect oncoming equipment failure ahead of time. In addition, the use of a Plant Health Committee has added significantly to the paradigm shift from a corrective maintenance philosophy to the use of predictive and preventive maintenance. The Plant Health Committee is a chartered team consisting of Engineering, Operations, and Maintenance personnel. CSEs use this forum to present the results of their performance monitoring, including the presentation of health via leading health indicators. The most positive aspect of this committee is the communication that it creates within these critical organizations. The Operations and Maintenance organization benefit from focusing maintenance on the reliability-centered focus provided by Engineering. Engineering benefits from the operational experience of the Operations organization and from the failure data that can be provided by Maintenance personnel. The continued use of the Plant Health Committee is expected to further decrease maintenance outage times, in better support of oncoming 24/7 operations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1988

Independent Orbiter Assessment (IOA): FMEA/CIL assessment

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) are presented. Direction was given by the Orbiter and GFE Projects Office to perform the hardware analysis and assessment using the instructions and ground rules defined in NSTS 22206. The IOA analysis features a top-down approach to determine hardware failure modes, criticality, and potential critical items. To preserve independence, the anlaysis was accomplished without reliance upon the results contained within the NASA and prime contractor FMEA/CIL documentation. The assessment process compares the independently derived failure modes and criticality assignments to the proposed NASA Post 51-L FMEA/CIL documentation. When possible, assessment issues are discussed and resolved with the NASA subsystem managers. The assessment results for each subsystem are summarized. The most important Orbiter assessment finding was the previously unknown stuck autopilot push-button criticality 1/1 failure mode, having a worst case effect of loss of crew/vehicle when a microwave landing system is not active.

Saiidi, Mo J.↗
DOE OSTI2023

PacWave South SeaRAY k2 Risk Registers

The SeaRAY is a deployable power system for maritime sensors, monitoring equipment, communications, unmanned underwater vehicles, and other similar payloads. This project is to design, deliver, and test a prototype low-power WEC that lowers the total cost of ownership and provides robust, new capabilities for customers in the maritime environment. Failure Modes, Effects, and Criticality Analysis (FMECA) is conducted to systematically identify all potential failure modes and their effects on the system, and to analyze the criticality of each risk based on the likelihood of the event and the severity of the impact. Actions may then be recommended to mitigate the criticality of a risk, either by reducing the likelihood of the risk or the severity of its impact. Risk assessment is executed iteratively as an integral part of the design process. By incorporating risk assessment early in the development cycle, mitigation of risk can be achieved cost effectively. The actions recommended to mitigate risk may be subsequently executed, and as the design progresses the risk assessment is reviewed and revised. Review of the risk assessment is integrated into structured design reviews, ensuring that critical risks are comprehended and that the Project will not progress to e.g. fabrication while intolerable risks remain. The risk assessment process results in the population and maintenance of Risk Registers (RRs). Each major system (and as needed, subsystem) will have a distinct RR. This allows each system or subsystem to be assessed individually, rendering the RRs to a manageable size for review.

16 TIDAL AND WAVE POWER↗
NASA NTRS1991

Collision avoidance for CTV: Requirements and capabilities

Collision avoidance must be ensured during Cargo Transfer Vehicle (CTV) operations near the space station. The design of the Collision Avoidance Maneuver (CAM) will involve analysis of CTV failure modes during rendezvous and proximity operations as well as analysis of possible problems external to the CTV, but that would require CTV to execute a CAM. In considering the requirements and design of the CAM for the CTV, the CAM design for the Orbital Maneuvering Vehicle (OMV) is a useful reference point from which some lessons can be learned and many CTV design options can be set forth.

Nosek, Thomas↗
NASA NTRSDate not supplied

Discovery and Analysis of Rare High-Impact Failure Modes using Adversarial RL-Informed Sampling

Adaptive learning agents have tremendous potential to handle critical tasks currently performed by humans. Unfortunately, due to their complexity, it can be difficult to verify that these learning agents do not have critical failure modes. Standard verification and validation methods often do not apply directly to learning agents and Monte Carlo methods have difficulty covering even a small fraction of the state space, especially in multiagent systems or over long time horizons. To overcome this difficulty, we demonstrate an adaptive stress-testing method based on reinforcement learning of correlations that raise the probability of failure. This approach has three key properties: (1) it is able to find rare failure modes with far greater sample efficiency than Monte Carlo methods, (2) it can estimate the true probability of a failure mode despite the inherent bias in the learning method, and (3) it is capable of learning and resampling compact representations of multimodal failure spaces. These properties are important in practice as we need to find disparate failure modes while accounting for their actual relevance. This is a significant advantage over traditional adaptive stress testing methods that give abstract likelihoods of particular failure instances, but cannot estimate the probability of a broader failure mode. We test our algorithm on a simple problem from the aviation domain where an autonomous aircraft lands in gusty wind conditions. The results suggest that we can find failure modes with far fewer samples than the Monte Carlo approach and simultaneously estimate the probability of failure.

reinforcement learning↗
NASA NTRS1988

Independent Orbiter Assessment (IOA): Assessment of the orbital maneuvering subsystem, volume 2

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) are presented. The IOA effort first completed an analysis of the Orbital Maneuvering System (OMS) hardware and electrical power distribution and control (EPD and C), generating draft failure modes and potential critical items. To preserve independence, this analysis was accomplished without reliance upon the results contained within the NASA FMEA/CIL documentation. The IOA results were then compared to the proposed Post 51-L NASA FMEA/CIL baseline. This report documents the results of that comparison for the Orbiter OMS hardware and EPD and C systems. Volume 2 continues the presentation of IOA worksheets and contains the critical items list and the NASA FMEA to IOA worksheet cross reference and recommendations.

Haufler, W. A.↗
NASA NTRS1995

Detecting Hidden Failure Modes in Critical, Embedded Software

This experience report describes a method that has been used successfully to detect hidden failure modes in critical, embedded spacecraft software. The method is an adaptation of an earlier, controversial approach called failure modes and effects analysis. The adapted method was found to be well-suited to identifying latent software design weaknesses involving complex system interactions and dependencies in the two applications described here. This experience may be useful for other high-integrity software systems in which the possibility of hidden failure modes is a major concern.

detecting software failure design analysis↗
NASA NTRS1972

Spacecraft reliability/maintainability optimization.

Description of a procedure to develop a methodology to optimize man-serviced systems for reliability and maintainability. The spacecraft systems are analyzed using failure modes and effects analysis and maintenance analysis, component mean-time-between failure, duty cycle, type of redundancy, and cost information to develop parametric data on various time intervals. Included are crew time-to-repair, cost, weight, and volume effects of increasing subsystem reliability above the baseline. Results are presented for space systems using the existing data from a research and applications module. These results show the minimum cost of sustaining mission operations.

Sharmahd, J. N.↗
NASA NTRS2024

Failure-Tolerant Avionics for Crewed Space Systems Recommended Best Practices

This paper provides an overview of some of the major steps needed to mature and justify the design of an avionics system for crewed spacecraft. It is organized as a collection of artifacts or pieces of evidence that NASA needs to assess the system at design reviews, including a functional failure modes and effects analysis (FFMEA), fault containment region (FCR) definitions, the failure hypothesis, and reliability analysis. This paper is intended as a reference for designers working on NASA crewed spaceflight projects, reliability engineers responsible for avionics system assessments, and program managers wanting to understand what evidence is required at design reviews to ensure crew safety and mission success.

Avionics↗
NASA NTRSDate not supplied

Uncovering Hazards Using a Multi-Objective Optimization to Explore the Faulty State-Space

Considering resilience when designing complex engineered systems is crucial to ensure the system is safe under unexpected hazardous scenarios. Traditional risk-based approaches, such as Failure Modes and Effects Analysis (FMEA) are useful for designing the system to mitigate hazardous scenarios that can be identified by the designer, but often require experience or prior knowledge of system failures to generate. More recently, researchers have developed simulation tools that enable the designer to model large sets of hazardous scenarios (driven by both internal faults and external factors) through simulation. While these tools enable a wider scope of fault modes to be evaluated (e.g., by injecting combined set of fault modes or injecting modes at different times), the resulting assessments (like FMEA) still require knowledge of the specific modes to be evaluated. However, failure to analyze a wide variety of fault scenarios can lead to an incomplete picture of the system resilience, especially to "surprise events'' which may be difficult for the designer to identify and predict beforehand. To overcome this challenge, previous work developed a fault sampling approach for resilience simulations which would procedurally-generate a wide variety of potential faults by systematically perturbing the health states of the system. While the resulting fault modes generated covered a much larger space hazards than would be otherwise considered (and identified many unique failure trajectories which would not have otherwise been identified), it also significantly increased the computational cost of the analysis and resulted in the simulation and analysis of a large set of essentially duplicate scenarios. Additionally, as the number of dimensions in the faulty state-space increases, the full elaboration of possible modes becomes computationally infeasible, justifying the use of a more targeted search. To resolve this limitation, this work proposes the use of a multiobjective optimization algorithm to search the health state space for potential fault modes that are both (1) hazardous and (2) unique. To solve this type of problem, this work proposes the use of a cooperative co-evolutionary algorithm. To demonstrate this approach, it will be applied to a model of an autonomous rover which uses line markings to navigate, focusing on potential hazards in the drive system which could cause the rover to crash. To determine the merit of the approach, it will further be compared with the previously-presented range elaboration approach and a random mode generation approach on the basis of computational efficiency and found modes.

Resilience↗
NASA NTRS2019

Characterization and Failure Analysis of 650 V Enhancement-Mode GaN HEMT for Cryogenically-Cooled Power Electronics

In order to evaluate the feasibility of newly developed GaN devices in a cryogenically-cooled converter, this paper characterizes a 650 V enhancement-mode Gallium-Nitride high-electron-mobility transistor (GaN HEMT) at cryogenic temperatures. The characterization includes both static and dynamic behaviors. The results show that this GaN HEMT is an excellent device candidate to be applied in cryogenic-cooled applications. For example, transconductance at cryogenic temperature (93 K) is 2.5 times higher than one at room temperature (298 K), and accordingly, peak di/dt during turn-on transients at cryogenic temperature is around 2 times of that at room temperature. Moreover, the on-resistance of the channel at cryogenic temperature is only one-fifth of that at room temperature. The corresponding explanations of performance trends at cryogenic temperatures are also given from the view of semiconductor physics. In addition, several device failures were observed during the dynamic characterization of GaN HEMTs at cryogenic temperatures. The ultra-fast switching speed induced high di/dt and dv/dt at cryogenic temperatures amplifies the negative effects of parasitics inside the switching loop. Based on failure waveforms, two failure modes were classified, and detailed failure mechanisms caused by ultra-fast switching speed are given in this paper.

Static and dynamic characterization↗
NASA NTRS1964

Transor analysis

Reliability and failure modes of adaptive restoring circuit module Transor

LOGIC CIRCUIT↗
NASA NTRSDate not supplied

Discovery and Analysis of Rare High-Impact Failure Modes using Adversarial RL-Informed Sampling

Adaptive learning agents have tremendous potential to handle critical tasks currently performed by humans. Unfortunately, due to their complexity, it can be difficult to verify that these learning agents do not have critical failure modes. Standard verification and validation methods often do not apply directly to learning agents and Monte Carlo methods have difficulty covering even a small fraction of the state space, especially in multiagent systems or over long time horizons. To overcome this difficulty, we demonstrate an adaptive stress-testing method based on reinforcement learning of correlations that raise the probability of failure. This approach has three key properties: (1) it is able to find rare failure modes with far greater sample efficiency than Monte Carlo methods, (2) it can estimate the true probability of a failure mode despite the inherent bias in the learning method, and (3) it is capable of learning and resampling compact representations of multimodal failure spaces. These properties are important in practice as we need to find disparate failure modes while accounting for their actual relevance. This is a significant advantage over traditional adaptive stress testing methods that give abstract likelihoods of particular failure instances, but cannot estimate the probability of a broader failure mode. We test our algorithm on a simple problem from the aviation domain where an autonomous aircraft lands in gusty wind conditions. The results suggest that we can find failure modes with far fewer samples than the Monte Carlo approach and simultaneously estimate the probability of failure.

Validation↗
NASA NTRSDate not supplied

Discovery and Analysis of Rare High-Impact Failure Modes using Adversarial RL-Informed Sampling

Adaptive learning agents have tremendous potential to handle critical tasks currently performed by humans. Unfortunately, due to their complexity, it can be difficult to verify that these learning agents do not have critical failure modes. Standard verification and validation methods often do not apply directly to learning agents and Monte Carlo methods have difficulty covering even a small fraction of the state space, especially in multiagent systems or over long time horizons. To overcome this difficulty, we demonstrate an adaptive stress-testing method based on reinforcement learning of correlations that raise the probability of failure. This approach has three key properties: (1) it is able to find rare failure modes with far greater sample efficiency than Monte Carlo methods, (2) it can estimate the true probability of a failure mode despite the inherent bias in the learning method, and (3) it is capable of learning and resampling compact representations of multimodal failure spaces. These properties are important in practice as we need to find disparate failure modes while accounting for their actual relevance. This is a significant advantage over traditional adaptive stress testing methods that give abstract likelihoods of particular failure instances, but cannot estimate the probability of a broader failure mode. We test our algorithm on a simple problem from the aviation domain where an autonomous aircraft lands in gusty wind conditions. The results suggest that we can find failure modes with far fewer samples than the Monte Carlo approach and simultaneously estimate the probability of failure.

Validation↗
NASA NTRS1988

Independent Orbiter Assessment (IOA): Assessment of the reaction control system, volume 5

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) are presented. The IOA effort first completed an analysis of the aft and forward Reaction Control System (RCS) hardware and Electrical Power Distribution and Control (EPD and C), generating draft failure modes and potential critical items. The IOA results were then compared to the proposed Post 51-L NASA FMEA/CIL baseline. This report documents the results of that comparison for the Orbiter RCS hardware and EPD and C systems. Volume 5 contains detailed analysis and superseded analysis worksheets and the NASA FMEA to IOA worksheet cross reference and recommendations.

Prust, Chet D.↗
NASA NTRS1980

Orbiter subsystem hardware/software interaction analysis. Volume 8: Forward reaction control system

The results of the orbiter hardware/software interaction analysis for the AFT reaction control system are presented. The interaction between hardware failure modes and software are examined in order to identify associated issues and risks. All orbiter subsystems and interfacing program elements which interact with the orbiter computer flight software are analyzed. The failure modes identified in the subsystem/element failure mode and effects analysis are discussed.

Becker, D. D.↗