Non-invasive detection of interfacial debonding and mechanical failures in high field magnets using ultrasonic wave
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Xu, Aixia↗
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Results for “failure detection”
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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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↗
Effects of adaptive task allocation on monitoring of automated systems
The effects of adaptive task allocation on monitoring for automation failure during multitask flight simulation were examined. Participants monitored an automated engine status task while simultaneously performing tracking and fuel management tasks over three 30-min sessions. Two methods of adaptive task allocation, both involving temporary return of the automated engine status task to the human operator ("human control"), were examined as a possible countermeasure to monitoring inefficiency. For the model-based adaptive group, the engine status task was allocated to all participants in the middle of the second session for 10 min, following which it was again returned to automation control. The same occurred for the performance-based adaptive group, but only if an individual participant's monitoring performance up to that point did not meet a specified criterion. For the nonadaptive control groups, the engine status task remained automated throughout the experiment. All groups had low probabilities of detection of automation failures for the first 40 min spent with automation. However, following the 10-min intervening period of human control, both adaptive groups detected significantly more automation failures during the subsequent blocks under automation control. The results show that adaptive task allocation can enhance monitoring of automated systems. Both model-based and performance-based allocation improved monitoring of automation. Implications for the design of automated systems are discussed.
Task Performance and Analysis↗
SSME Propellant Path Leak Detection
The complicated high-pressure cycle of the space shuttle main engine (SSME) propellant path provides many opportunities for external propellant path leaks while the engine is running. This mode of engine failure may be detected and analyzed with sufficient speed to save critical engine test hardware from destruction. The leaks indicate hardware failures which will damage or destroy an engine if undetected; therefore, detection of both cryogenic and hot gas leaks is the objective of this investigation. The primary objective of this phase of the investigation is the experimental validation of techniques for detecting and analyzing propellant path external leaks which have a high probability of occurring on the SSME. The selection of candidate detection methods requires a good analytic model for leak plumes which would develop from external leaks and an understanding of radiation transfer through the leak plume. One advanced propellant path leak detection technique is obtained by using state-of-the-art technology infrared (IR) thermal imaging systems combined with computer, digital image processing, and expert systems for the engine protection. The feasibility of IR leak plume detection is evaluated on subscale simulated laboratory plumes to determine sensitivity, signal to noise, and general suitability for the application.
Roger Crawford↗
Electrostatic discharge in microcircuits
The largest number of electrostatic discharge (ESD) failures have occurred in linear microcircuits employing one or more MOS capacitors. The detection of ESD failures is considered. The phenomena involved in the generation of static charge are examined and a description is provided of approaches which can be used to protect microcircuits from ESD hazards. It is pointed out that ESD failures can virtually be eliminated if the procedural guidelines of protecting static-sensitive devices are implemented and conscientiously observed.
Trigonis, A. C.↗
Gyro-based Maximum-Likelihood Thruster Fault Detection and Identification
When building smaller, less expensive spacecraft, there is a need for intelligent fault tolerance vs. increased hardware redundancy. If fault tolerance can be achieved using existing navigation sensors, cost and vehicle complexity can be reduced. A maximum likelihood-based approach to thruster fault detection and identification (FDI) for spacecraft is developed here and applied in simulation to the X-38 space vehicle. The system uses only gyro signals to detect and identify hard, abrupt, single and multiple jet on- and off-failures. Faults are detected within one second and identified within one to five accords,
Wilson, Edward↗
Developing Reliable Life Support for Mars
A human mission to Mars will require highly reliable life support systems. Mars life support systems may recycle water and oxygen using systems similar to those on the International Space Station (ISS). However, achieving sufficient reliability is less difficult for ISS than it will be for Mars. If an ISS system has a serious failure, it is possible to provide spare parts, or directly supply water or oxygen, or if necessary bring the crew back to Earth. Life support for Mars must be designed, tested, and improved as needed to achieve high demonstrated reliability. A quantitative reliability goal should be established and used to guide development t. The designers should select reliable components and minimize interface and integration problems. In theory a system can achieve the component-limited reliability, but testing often reveal unexpected failures due to design mistakes or flawed components. Testing should extend long enough to detect any unexpected failure modes and to verify the expected reliability. Iterated redesign and retest may be required to achieve the reliability goal. If the reliability is less than required, it may be improved by providing spare components or redundant systems. The number of spares required to achieve a given reliability goal depends on the component failure rate. If the failure rate is under estimated, the number of spares will be insufficient and the system may fail. If the design is likely to have undiscovered design or component problems, it is advisable to use dissimilar redundancy, even though this multiplies the design and development cost. In the ideal case, a human tended closed system operational test should be conducted to gain confidence in operations, maintenance, and repair. The difficulty in achieving high reliability in unproven complex systems may require the use of simpler, more mature, intrinsically higher reliability systems. The limitations of budget, schedule, and technology may suggest accepting lower and less certain expected reliability. A plan to develop reliable life support is needed to achieve the best possible reliability.
life support↗
Evaluation of an oil-debris monitoring device for use in helicopter transmissions
Experimental tests were performed on an OH-58A helicopter main-rotor transmission to evaluate an oil-debris monitoring device (ODMD). The tests were performed in the NASA 500-hp Helicopter Transmission Test Stand. Five endurance tests were run as part of a U.S. Navy/NASA/Army advanced lubricants program. The tests were run at 100 percent design speed, 117-percent design torque, and 121 C (250 F) oil inlet temperature. Each test lasted between 29 and 122 hr. The oils that were used conformed to MIL-L-23699 and DOD-L-85734 specifications. One test produced a massive sun-gear fatigue failure; another test produced a small spall on one sun-gear tooth; and a third test produced a catastrophic planet-bearing cage failure. The ODMD results were compared with oil spectroscopy results. The capability of the ODMD to detect transmission component failures was not demonstrated. Two of the five tests produced large amounts of debris. For these two tests, two separate ODMD sensors failed, possibly because of prolonged exposure to relatively high oil temperatures. One test produced a small amount of debris and was not detected by the ODMD or by oil spectroscopy. In general, the ODMD results matched the oil spectroscopy results. The ODMD results were extremely sensitive to oil temperature and flow rate.
Lewicki, David G.↗
Real-Time Sensor Validation System Developed
Real-time sensor validation improves process monitoring and control system dependability by ensuring data integrity through automated detection of sensor data failures. The NASA Lewis Research Center, Expert Microsystems, and Intelligent Software Associates have developed an innovative sensor validation system that can automatically detect automated sensor failures in real-time for all types of mission-critical systems. This system consists of a sensor validation network development system and a real-time kernel. The network development system provides tools that enable systems engineers to automatically generate software that can be embedded within an application. The sensor validation methodology captured by these tools can be scaled to validate any number of sensors, and permits users to specify system sensitivity. The resulting software reliably detects all types of sensor data failures.
Zakrajsek, June F.↗
FIRE: A Failure-Adaptive RL Framework for Edge Computing Migrations
In edge computing, users' service profiles are migrated between edge servers due to user mobility. Reinforcement Learning (RL) frameworks have been proposed to do so, often trained on simulated data. However, existing RL frameworks overlook occasional server failures, which although rare, impact latency-sensitive applications like AR/VR and real- time obstacle detection. These rare failures, being not adequately represented in historical training data, pose a challenge for data-driven RL algorithms. We introduce FIRE, a framework that adapts to rare events by training a RL policy in an edge computing digital twin environment. We propose FIRE-ImRE, an importance sampling-based Q-learning algorithm, which samples rare events proportionally to their impact on the value function. FIRE considers delay, migration, failure, and backup placement costs across individual and shared service profiles. We prove FIRE-ImRE's boundedness and convergence to optimality. Next, we introduce novel deep Q-learning (FIRE-ImDQL) and actor critic (FIRE-ImACRE) versions of our algorithm to enhance scalability. Here, we extend our framework to accommodate users with varying risk tolerances of rare failure events. Through trace-driven experiments, we show that FIRE reduces edge computing costs compared to vanilla RL and the greedy baseline in the event of failures.
Edge computing↗
A Survey of Logic Formalisms to Support Mishap Analysis
Mishap investigations provide important information about adverse events and near miss incidents. They are intended to help avoid any recurrence of previous failures. Over time, they can also yield statistical information about incident frequencies that helps to detect patterns of failure and can validate risk assessments. However, the increasing complexity of many safety critical systems is posing new challenges for mishap analysis. Similarly, the recognition that many failures have complex, systemic causes has helped to widen the scope of many mishap investigations. These two factors have combined to pose new challenges for the analysis of adverse events. A new generation of formal and semi-formal techniques have been proposed to help investigators address these problems. We introduce the term mishap logics to collectively describe these notations that might be applied to support the analysis of mishaps. The proponents of these notations have argued that they can be used to formally prove that certain events created the necessary and sufficient causes for a mishap to occur. These proofs can be used to reduce the bias that is often perceived to effect the interpretation of adverse events. Others have argued that one cannot use logic formalisms to prove causes in the same way that one might prove propositions or theorems. Such mechanisms cannot accurately capture the wealth of inductive, deductive and statistical forms of inference that investigators must use in their analysis of adverse events. This paper provides an overview of these mishap logics. It also identifies several additional classes of logic that might also be used to support mishap analysis.
Johnson, Chris↗
A systems engineering approach to automated failure cause diagnosis in space power systems
Automatic failure-cause diagnosis is a key element in autonomous operation of space power systems such as Space Station's. A rule-based diagnostic system has been developed for determining the cause of degraded performance. The knowledge required for such diagnosis is elicited from the system engineering process by using traditional failure analysis techniques. Symptoms, failures, causes, and detector information are represented with structured data; and diagnostic procedural knowledge is represented with rules. Detected symptoms instantiate failure modes and possible causes consistent with currently held beliefs about the likelihood of the cause. A diagnosis concludes with an explanation of the observed symptoms in terms of a chain of possible causes and subcauses.
Dolce, James L.↗
Failure Mode and Effects Analysis for a Photovoltaic Inverter
While PV panel reliability continues to increase, PV inverters become the limiting factor for PV system reliability. Consequently, it is critical to have a generic tool from a third party for PV inverter reliability assessment to help 1) utilities/PV farm operators schedule maintenance in advance, and 2) inverter developers improve the next-generation design. However, these two things cannot be accomplished without first understanding the reasons behind inverter failure. Following this idea, as the first step, it is essential to identify and investigate the most failure-prone components within a PV inverter system. After all, any system is only as reliable as the components that are contained within it. This motivates the failure mode and effects analysis (FMEA) work presented for this workshop. The FMEA is conducted as follows: first, the overview of the methodology on the development of the FMEA is presented; then, based on a top-down approach starting from the PV inverter system, critical inverter components with high failure rates are identified and summarized; afterward, a thorough FMEA study at a component-level is performed and its results, including failure modes, failure mechanisms, and critical stressors, are tabulated; finally, according to three rankings (chance of occurrence, severity of occurrence, and ease of detection prior to failure) for each failure mechanism provided by the FMEA, risk priority numbers are calculated and the failure mechanisms along with the critical stressors are ranked in terms of their potentially detrimental effect on the PV inverter.
Brown, Buck↗
AE (Acoustic Emission) for Flip-Chip CGA/FCBGA Defect Detection
C-mode scanning acoustic microscopy (C-SAM) is a nondestructive inspection technique that uses ultrasound to show the internal feature of a specimen. A very high or ultra-high-frequency ultrasound passes through a specimen to produce a visible acoustic microimage (AMI) of its inner features. As ultrasound travels into a specimen, the wave is absorbed, scattered or reflected. The response is highly sensitive to the elastic properties of the materials and is especially sensitive to air gaps. This specific characteristic makes AMI the preferred method for finding "air gaps" such as delamination, cracks, voids, and porosity. C-SAM analysis, which is a type of AMI, was widely used in the past for evaluation of plastic microelectronic circuits, especially for detecting delamination of direct die bonding. With the introduction of the flip-chip die attachment in a package; its use has been expanded to nondestructive characterization of the flip-chip solder bumps and underfill. Figure 1.1 compares visual and C-SAM inspection approaches for defect detection, especially for solder joint interconnections and hidden defects. C-SAM is specifically useful for package features like internal cracks and delamination. C-SAM not only allows for the visualization of the interior features, it has the ability to produce images on layer-by-layer basis. Visual inspection; however, is only superior to C-SAM for the exposed features including solder dewetting, microcracks, and contamination. Ideally, a combination of various inspection techniques - visual, optical and SEM microscopy, C-SAM, and X-ray - need to be performed in order to assure quality at part, package, and system levels. This reports presents evaluations performed on various advanced packages/assemblies, especially the flip-chip die version of ball grid array/column grid array (BGA/CGA) using C-SAM equipment. Both external and internal equipment was used for evaluation. The outside facility provided images of the key features that could be detected using the most advanced C-SAM equipment with a skilled operator. Investigation continued using in-house equipment with its limitations. For comparison, representative X-rays of the assemblies were also gathered to show key defect detection features of these non-destructive techniques. Key images gathered and compared are: Compared the images of 2D X-ray and C-SAM for a plastic LGA assembly showing features that could be detected by either NDE technique. For this specific case, X-ray was a clear winner. Evaluated flip-chip CGA and FCBGA assemblies with and without heat sink by C-SAM. Only the FCCGA package that had no heat sink could be fully analyzed for underfill and bump quality. Cross-sectional microscopy did not revealed peripheral delamination features detected by C-SAM. Analyzed a number of fine pitch PBGA assemblies by C-SAM. Even though the internal features of the package assemblies could be detected, C-SAM was unable to detect solder joint failure at either the package or board level. Twenty times touch ups by solder iron with 700degF tip temperature, each with about 5 second duration, did not induce defects to be detected by C-SAM images. Other techniques need to be considered to induce known defects for characterization. Given NASA's emphasis on the use of microelectronic packages and assemblies and quality assurance on workmanship defect detection, understanding key features of various inspection systems that detect defects in the early stages of package and assembly is critical to developing approaches that will minimize future failures. Additional specific, tailored non-destructive inspection approaches could enable low-risk insertion of these advanced electronic packages having hidden and fine features.
Ghaffarian, Reza↗
Health monitoring system for the SSME - Program overview
This paper considers the design of a health management system (HMS) program for enhancement of the safety of SSME operations during ground tests and space missions. The fault detection techniques based on time series, nonlinear regression, and clustering algorithms were developed and were demonstrated based on data from SSME ground test failures. The fault detection algorithms of the HMS system exhibited 100 percent detection of faults and an extremely low fault alarm rate, and were robust to sensor loss. A preliminary design of hardware architecture capable of supporting real-time operation of the HMS functions is described.
Hawman, Michael W.↗
CRYOGENIC UPPER STAGE SYSTEM SAFETY
NASA s Exploration Initiative will require development of many new systems or systems of systems. One specific example is that safe, affordable, and reliable upper stage systems to place cargo and crew in stable low earth orbit are urgently required. In this paper, we examine the failure history of previous upper stages with liquid oxygen (LOX)/liquid hydrogen (LH2) propulsion systems. Launch data from 1964 until midyear 2005 are analyzed and presented. This data analysis covers upper stage systems from the Ariane, Centaur, H-IIA, Saturn, and Atlas in addition to other vehicles. Upper stage propulsion system elements have the highest impact on reliability. This paper discusses failure occurrence in all aspects of the operational phases (Le., initial burn, coast, restarts, and trends in failure rates over time). In an effort to understand the likelihood of future failures in flight, we present timelines of engine system failures relevant to initial flight histories. Some evidence suggests that propulsion system failures as a result of design problems occur shortly after initial development of the propulsion system; whereas failures because of manufacturing or assembly processing errors may occur during any phase of the system builds process, This paper also explores the detectability of historical failures. Observations from this review are used to ascertain the potential for increased upper stage reliability given investments in integrated system health management. Based on a clear understanding of the failure and success history of previous efforts by multiple space hardware development groups, the paper will investigate potential improvements that can be realized through application of system safety principles.
Smith, R. Kenneth↗
Failure analysis of nuclear transient-tested UN tristructural isotropic fuel particles in a 3D printed SiC matrix
Fully ceramic microencapsulated fuel elements containing UN tristructural isotropic (TRISO) fuel particles within a 3D printed SiC matrix were subjected to transient testing with varying energy depositions. Detailed post-irradiation examinations were performed, including leaching in hot HNO3 and post-leaching X-ray computed tomography, to quantify the percentage of failed TRISO particles and crack propagation within the particles and surrounding fuel matrix. In parallel, detailed finite element analyses were performed for comparison with experimental findings and to better evaluate transient failure modes. The lowest transient energy deposition—which still exceeded bounding values for high-temperature gas-cooled reactor applications—resulted in no detectable TRISO particle failures or matrix cracking, which was consistent with the simulations. Simulations of the higher-energy transients for which significant TRISO particle failure was expected were generally able to reproduce the transient temperatures and matrix cracking. Thus, the TRISO particle failures were explained based on the effects of local SiC matrix thickness and porosity. Results generally confirmed the high strength of the additively manufactured SiC matrix but also affirmed the need for a modified UN TRISO architecture to prevent SiC matrix cracks from propagating through TRISO layers. This unique failure mode has not historically been considered for TRISO fuels contained in weaker graphite matrices.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Failure Mode Identification Through Clustering Analysis
Research has shown that nearly 80% of the costs and problems are created in product development and that cost and quality are essentially designed into products in the conceptual stage. Currently, failure identification procedures (such as FMEA (Failure Modes and Effects Analysis), FMECA (Failure Modes, Effects and Criticality Analysis) and FTA (Fault Tree Analysis)) and design of experiments are being used for quality control and for the detection of potential failure modes during the detail design stage or post-product launch. Though all of these methods have their own advantages, they do not give information as to what are the predominant failures that a designer should focus on while designing a product. This work uses a functional approach to identify failure modes, which hypothesizes that similarities exist between different failure modes based on the functionality of the product/component. In this paper, a statistical clustering procedure is proposed to retrieve information on the set of predominant failures that a function experiences. The various stages of the methodology are illustrated using a hypothetical design example.
Arunajadai, Srikesh G.↗