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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Common Cause Failure Modeling

Common Cause Failures (CCFs) are a known and documented phenomenon that defeats system redundancy. CCFS are a set of dependent type of failures that can be caused by: system environments; manufacturing; transportation; storage; maintenance; and assembly, as examples. Since there are many factors that contribute to CCFs, the effects can be reduced, but they are difficult to eliminate entirely. Furthermore, failure databases sometimes fail to differentiate between independent and CCF (dependent) failure and data is limited, especially for launch vehicles. The Probabilistic Risk Assessment (PRA) of NASA's Safety and Mission Assurance Directorate at Marshall Space Flight Center (MFSC) is using generic data from the Nuclear Regulatory Commission's database of common cause failures at nuclear power plants to estimate CCF due to the lack of a more appropriate data source. There remains uncertainty in the actual magnitude of the common cause risk estimates for different systems at this stage of the design. Given the limited data about launch vehicle CCF and that launch vehicles are a highly redundant system by design, it is important to make design decisions to account for a range of values for independent and CCFs. When investigating the design of the one-out-of-two component redundant system for launch vehicles, a response surface was constructed to represent the impact of the independent failure rate versus a common cause beta factor effect on a system's failure probability. This presentation will define a CCF and review estimation calculations. It gives a summary of reduction methodologies and a review of examples of historical CCFs. Finally, it presents the response surface and discusses the results of the different CCFs on the reliability of a one-out-of-two system.

Hark, Frank↗
NASA NTRS2016

Common Cause Failure Modeling

Common Cause Failures (CCFs) are a known and documented phenomenon that defeats system redundancy. CCFS are a set of dependent type of failures that can be caused by: system environments; manufacturing; transportation; storage; maintenance; and assembly, as examples. Since there are many factors that contribute to CCFs, the effects can be reduced, but they are difficult to eliminate entirely. Furthermore, failure databases sometimes fail to differentiate between independent and CCF (dependent) failure and data is limited, especially for launch vehicles. The Probabilistic Risk Assessment (PRA) of NASA's Safety and Mission Assurance Directorate at Marshal Space Flight Center (MFSC) is using generic data from the Nuclear Regulatory Commission's database of common cause failures at nuclear power plants to estimate CCF due to the lack of a more appropriate data source. There remains uncertainty in the actual magnitude of the common cause risk estimates for different systems at this stage of the design. Given the limited data about launch vehicle CCF and that launch vehicles are a highly redundant system by design, it is important to make design decisions to account for a range of values for independent and CCFs. When investigating the design of the one-out-of-two component redundant system for launch vehicles, a response surface was constructed to represent the impact of the independent failure rate versus a common cause beta factor effect on a system's failure probability. This presentation will define a CCF and review estimation calculations. It gives a summary of reduction methodologies and a review of examples of historical CCFs. Finally, it presents the response surface and discusses the results of the different CCFs on the reliability of a one-out-of-two system.

Hark, Frank↗
NASA NTRS2011

Failure Modes in Capacitors When Tested Under a Time-Varying Stress

Steady step surge testing (SSST) is widely applied to screen out potential power-on failures in solid tantalum capacitors. The test simulates the power supply's on and off characteristics. Power-on failure has been the prevalent failure mechanism for solid tantalum capacitors for decoupling applications. On the other hand, the SSST can also be reviewed as an electrically destructive test under a time-varying stress. It consists of rapidly charging the capacitor with incremental voltage increases, through a low resistance in series, until the capacitor under test is electrically shorted. Highly accelerated life testing (HALT) is usually a time-efficient method for determining the failure mechanism in capacitors; however, a destructive test under a time-varying stress like SSST is even more effective. It normally takes days to complete a HALT test, but it only takes minutes for a time-varying stress test to produce failures. The advantage of incorporating specific time-varying stress into a statistical model is significant in providing an alternative life test method for quickly revealing the failure modes in capacitors. In this paper, a time-varying stress has been incorporated into the Weibull model to characterize the failure modes. The SSST circuit and transient conditions to correctly test the capacitors is discussed. Finally, the SSST was applied for testing polymer aluminum capacitors (PA capacitors), Ta capacitors, and multi-layer ceramic capacitors with both precious metal electrode (PME) and base-metal-electrodes (BME). It appears that testing results are directly associated to the dielectric layer breakdown in PA and Ta capacitors and are independent on the capacitor values, the way the capacitors being built, and the manufactures. The testing results also reveal that ceramic capacitors exhibit breakdown voltages more than 20 times the rated voltage, and the breakdown voltages are inverse proportional to the dielectric layer thickness. The possibility of ceramic capacitors in front-end decoupling applications to block the surge noise from a power supply is also discussed.

Liu, David (Donhang)↗
NASA NTRS2018

Synthesizing a New Launch Vehicle Failure Probability Based on Historical Flight Data

New launch vehicles have historically had significantly higher failure rates in early flights than what has been predicted using Probabilistic Risk Assessment - PRA. This is because PRAs typically model a mature vehicle where a significant portion of the early failure probability contributors have been eliminated due to testing and improvements after actual field operation. To capture a more accurate early flight failure probability estimate, this paper develops a method that estimates ascent failure probability starting with the first flight based on historical launch vehicle records. With new launch vehicles being developed, such as the Space Launch System - SLS, a PRA model must be extended to cover early flight failure probability contributions that are either not covered in the mature-vehicle PRA or are underestimated. These failure probability contributions include design errors, quality control deficiencies, installation errors, and environmental impacts. There are also failure dependencies due to systemic errors that still exist due to limited entire-system testing.

Cross, Robert B.↗
NASA NTRS2016

We Can't Count on Repairing All Failures Going to Mars

Reliability analysis often assumes that a complex system can be kept operating indefinitely with scheduled maintenance and emergency repair using a stock of spare parts, as long as the spare parts are not depleted. This assumption seems justified for well-tested, widely used, long operational systems with a multigenerational history of failure, redesign, and reliability growth. It seems doubtful that newer, relatively untried, high technology space systems can always be repaired. We cannot assume space systems will have a low rate of random failures that can all be repaired with a few identical spares. New untried systems usually have a high initial failure rate, called infant mortality, due to errors in requirements, design, parts, materials, and operations planning. These problems can cause groups of related failures called Common Cause Failures (CCFs). The practical definition of a CCF is any failure mode that cannot be cured using identical redundant systems or spare parts. Systems with CCFs may fail repeatedly for the same reason. Can a life support system be kept operating on the way to Mars using only redundant systems and spare parts? The failure history of International Space Station (ISS) life support systems suggests that CCFs are likely to occur and will probably require design changes rather than being reparable with spare parts.

Mars↗
NASA NTRS2020

A Method and Model to Predict Initial Failure Rates

It has long been well known that actual system reliability typically falls well short of early estimates. Failure rates are often ten or more times higher than anticipated. Many reasons have been given for this, but over-optimism is the fundamental cause of too-favorable reliability predictions. Most forecasts of reliability are essentially best-case scenarios, as are predictions of budget and schedule. Confident engineers assemble estimates bottom-up, including the known factors and ignoring problems that they hope won’t happen. Traditional reliability estimation is based on simply summing up the component failure rates. This ignores most actual failure causes. The way to reduce over-optimism is to use the historical system level failure rate from similar projects. Adjustments should not be made based purely on engineering judgment, but only if there is so logical quantitative justification. The traditional component-based reliability estimate is useful as a lower bound on the system failure rate. The difference between this lower bound component-based reliability and the historical system level reliability indicates how much of the total failure rate is due to system level problems rather than component failures.

Jones, Harry W.↗
NASA NTRS2020

A Method and Model to Predict Initial Failure Rates

It has long been well known that actual system reliability typically falls well short of early estimates. Failure rates are often ten or more times higher than anticipated. Many reasons have been given for this, but over-optimism is the fundamental cause of too-favorable reliability predictions. Most forecasts of reliability are essentially best-case scenarios, as are predictions of budget and schedule. Confident engineers assemble estimates bottom-up, including the known factors and ignoring problems that they hope won't happen. Traditional reliability estimation is based on simply summing up the component failure rates. This ignores most actual failure causes. The way to reduce over-optimism is to use the historical system level failure rate from similar projects. Adjustments should not be made based purely on engineering judgment, but only if there is so logical quantitative justification. The traditional component-based reliability estimate is useful as a lower bound on the system failure rate. The difference between this lower bound component-based reliability and the historical system level reliability indicates how much of the total failure rate is due to system level problems rather than component failures

Jones, Harry W.↗
NASA NTRSDate not supplied

Electrified Aircraft Propulsion Systems: Gas Turbine Control Considerations for the Mitigation of Potential Failure Modes and Hazards

This paper provides a high-level review of the potential failure modes and hazards to which electrified aircraft propulsion (EAP) systems are susceptible, along with potential gas turbine control-based strategies to assist in the mitigation of those failures. To introduce the types of failures that an EAP system may experience, a generic EAP system is considered, consisting of gas turbine engines, mechanical drives, electric machines, power electronics and distribution systems, energy storage devices, and motor driven propulsors. The functionality provided by each of these EAP subsystems is discussed, along with their potential failure modes, and possible strategies for mitigating those failures. To further illustrate the role of gas turbine controls in mitigating EAP failure modes, an example based on a simulated EAP concept aircraft proposed by NASA is given. The effects of failures are discussed, along with turbomachinery control strategies, including reversionary control modes, and control limit logic.

Donald L Simon↗
NASA NTRSDate not supplied

Adaptive Stress Testing: Using Reinforcement Learning to Find Failures in Safety-Critical Systems

Emerging applications in artificial intelligence, such as driverless cars and autonomous aircraft promise to be more efficient, cheaper to operate, and always available. However, ensuring the safety of these systems remains a major challenge to their certification and adoption. These autonomous systems are expected to routinely make safety-critical decisions where failures can have serious consequences including loss of life and property. Testing and validation techniques aim to identify and diagnose potential failures before the system is deployed. However, finding failure scenarios in autonomous systems can be very challenging due to high-dimensional and continuous state spaces, interaction with large environments over many time steps, and the rarity of failures. This talk presents Adaptive Stress Testing (AST), a simulation-based testing framework for finding the most likely path to a failure event of a safety-critical system. The key idea of AST is that stress testing can be formulated as a Partially Observable Markov Decision Process (POMDP), which enables reinforcement learning techniques to be used for finding failure events. Reinforcement learning algorithms can efficiently explore the search space and have been shown to scale to very large systems. We present applications of AST to find failures in various safety-critical systems including the aircraft collision avoidance systems, autonomous cars, and small unmanned aerial vehicles.

autonomous vehicles↗
NASA NTRS2021

Electrified Aircraft Propulsion Systems: Gas Turbine Control Considerations for the Mitigation of Potential Failure Modes and Hazards

This paper provides a high-level review of the potential failure modes and hazards to which electrified aircraft propulsion (EAP) systems are susceptible along with potential gas turbine control-based strategies to assist in the mitigation of those failures. To introduce the types of failures that an EAP system may experience, a generic EAP system is considered consisting of gas turbine engines, mechanical drives, electric machines, power electronics and distribution systems, energy storage devices, and motor driven propulsors. The functionality provided by each of these EAP subsystems is discussed along with their potential failure modes and possible strategies for mitigating those failures. To further illustrate the role of gas turbine controls in mitigating EAP failure modes, an example based on a simulated EAP concept aircraft proposed by NASA is given. The effects of failures are discussed, along with turbomachinery control strategies, including reversionary control modes, and control limit logic

Electrified Aircraft Propulsion↗
NASA NTRS2018

High Resolution Computed Tomography Inspection of Components Uncovers Root Causes of Vexing Failure Mysteries

During testing of actuators for fight programs, failures have occurred that required closure with an understanding of the root cause of the failure. For some InSight project actuators, intermittent changes of the winding resistance of the motors during temperature changes was extremely baffling. It was critical to determine the cause of the intermittent characteristic because the actuators were stock from a previous program and the company that provided the motors was no longer in business. Using an X-Ray Computed-Tomography (CT) method, the exact source of the intermittent failure was determined and completely understood – at dimensions of less than 20 microns. In another case, after the completion of an actuator’s life-test-to-failure, inspection was required to determine the source of the failure. The size of the actuator (10 mm diameter) required destructive means to get to the interior of the actuator for inspection, risking the loss of the source of the failure. Using CT imaging, the exact source of the failure was determined.

Johnson, Michael R.↗
DOE OSTI2020

Continued Discussion of Failure Mode Modeling and Overall Component Reliability: Is the Data Missing or Censored?

This paper is a continuation of a paper presented at the 13th Probabilistic Safety Assessment and Management Conference, in which a discussion of modeling failure modes of complex components was presented; see Paulos and Smith (2016). The paper demonstrated how the typical method of treating failure modes as being exponential in nature may yield optimistic predictions when estimating how improvements to components will perform in the real world. Instead of relying on textbook methods, it is more accurate to model the failure modes as a race in time; unfortunately, this does not give a closed-form solution. This work uses a simulation to solve for the model of the world, and is compared to the standard methodology of treating the failure modes as exponential random failures. The standard method is shown to have optimistic predictions, which will lead to prediction errors when failure modes were removed or “fixed.” The failure mode methodology presented in the first paper treated the data as being censored when the test stopped. In this paper, we will compare the results from treating the data as both censored and missing, and comparisons will be shown showing which method is more accurate and under what conditions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Integral Effect Test of ATLAS Facility on Multiple Failure in a Prolonged Station Blackout

Since the Fukushima accident, the design extension conditions (DECs) in a nuclear power plant (NPP) have attracted more importance with respect to nuclear reactor safety, and a consensus has been developed such that these high-risk multiple failure accidents should be revisited from the viewpoint of a reinforcement of the 'defense in depth' concept. In particular, a station blackout (SBO) is one of the most important DECs because a loss of the heat sink without an appropriate accident measure might lead to a core uncovery, core damage, and ultimately, a core meltdown under high pressure. SBO has been recognized to be one of the risk-contributing sequences when combined with additional failure of components such as a reactor coolant pump (RCP) seal leakage or a steam generator tube rupture (SGTR). The RCP seal failure could occur due to a loss of continuous cooling through the seal during SBO. The SGTR during SBO can be a potentially important risk due to the release of the fission product with bypassing the containment boundary. The objective of this study is to experimentally simulate and analyze a prolonged SBO scenario in a thermal hydraulic integral effect test facility, ATLAS. As test items in OECD-ATLAS project, two tests for the SBO condition were conducted with additional failures, that is, a RCP seal failure (A2.1 test) and a SGTR (A2.2 test). In those tests, both the effect of the additional failure on reactor safety and the natural circulation characteristics during prolonged SBO conditions could be investigated. The present test can provide physical insight into the system response during the prolonged SBO scenario combined with the multiple failure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Uncertainty quantification for competing failure mechanisms in unidirectionally reinforced carbon–carbon composites

Microstructure-informed finite element models play a key role in the carbon–carbon composite design process. Variability in manufacturing process parameters and experimental limitations introduce model parameter uncertainty. This study quantifies the effect of model parameter uncertainty on transverse tensile fracture behavior and proposes a methodology to predict the failure mode based on competing microscale damage mechanisms. Finite element simulations incorporate fiber–matrix interface debonding with cohesive zones and matrix damage with a smeared crack band approach in a unidirectional carbon–carbon composite. Results from a variance-based global sensitivity analysis identifies interfacial and matrix damage parameters as the primary source of variability in fracture behavior. Sobol’ indices indicate that matrix and cohesive zone strengths contribute 94% of the variance in the effective ultimate stress. A local analysis elucidates the relationship between these constituent strength parameters and failure mode by estimating the probability of cohesive, matrix, and mixed-mode dominated failure. Based on the results for 4000 simulations, 93% exhibit mixed-mode or interfacial dominated failure, which underscores the crucial role of fiber–matrix interface debonding in the transverse tensile failure of carbon–carbon composites. These uncertainty quantification results facilitate more efficient model calibration and provide a framework for microstructure-informed failure predictions in the face of manufacturing-induced uncertainty.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Best effort broadcast under cascading failures in interdependent critical infrastructure networks

Here, we present a novel study of reliable broadcast in interdependent networks, in which the failures in one network may cascade to another network. In particular, we focus on the interdependency between a communication network and a power grid network, where the power grid depends on the communication network for control and the communication network depends on the grid for power. In this paper, we propose a best effort broadcast algorithm to handle crash failures in the communication network that may cause cascading failures. We guarantee that all the correct nodes, which operate correctly according to the protocol and do not experience any software or hardware or network failures, eventually deliver the message if the sender is correct. We provide a centralized algorithm and a fully distributed algorithm for nodes to analyze and handle cascading failures. At the core of our work is the fully distributed algorithm which enjoys great performance and scalability. Our evaluation results show that the algorithm handles cascading failures with low overhead.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Identification of Modeling Approaches To Support Common-Cause Failure Analysis

Experience with applying current guidance and practices for common-cause failure (CCF) mitigation to digital instrumentation and control (I&C) systems has proven problematic, and the regulatory environment has been unpredictable. The impact of CCF vulnerability is to inhibit I&C modernization and, thereby, challenge the long-term sustainability of existing plants. For new plants and advanced reactor concepts, the issue of CCF vulnerability for highly integrated digital I&C systems imposes a design burden resulting in higher costs and increased complexity. The regulatory uncertainty regarding which mitigation strategies are acceptable (e.g., what diversity is needed and how much is sufficient) drives designers to adopt complicated, costly solutions devised for existing plants. The conditions that constrain the transition to digital I&C technology by the U.S. nuclear industry require crosscutting research to resolve uncertainty, demonstrate necessary characteristics, and establish an objective basis for qualification of digital technology for usage in Nuclear Power Plant (NPP) I&C applications. To fulfill this research need, Oak Ridge National Laboratory is conducting an investigation into mitigation of CCF vulnerability for nuclear-qualified applications. The outcome of this research is expected to contribute to a fundamentally sound, comprehensive technical basis for establishing the qualification of digital technology for nuclear power applications. This report documents the investigation of modeling approaches for representing failure of I&C systems. Failure models are used when there is a need to analyze how the probability of success (or failure) of a system depends on the success (or failure) of individual elements. If these failure models are extensible to represent CCF, then they can be employed to support analysis of CCF vulnerabilities and mitigation strategies. Specifically, the research findings documented in this report identify modeling approaches that can be adapted to contribute to the basis for developing systematic methods, quantifiable measures, and objective criteria for evaluating CCF vulnerabilities and mitigation strategies.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Probabilistic Failure Criterion of SiC/SiC Composites Under Multiaxial Loading

Owing to its excellent mechanical properties and stability under high temperature and neutron irradiation conditions, SiC/SiC composites have emerged as a promising material for light water reactors (LWRs) in the development of accident-tolerant fuel (ATF) systems. Structural integrity and retention of hermeticity are two crucial requirements for SiC/SiC claddings during normal operations, and both of them are closely related to the proportional limit stress (PLS) of the material. Understanding the behavior of SiC/SiC composites under multiaxial stress states and developing a probabilistic approach for evaluating the structural vulnerability are of paramount importance for reliability-based analysis and design of SiC/SiC composite claddings. So far, there has been very limited effort towards experimental and analytical investigations of probabilistic failure of SiC/SiC claddings. This critical knowledge gap motivates this research. A probabilistic failure criterion for SiC/SiC composites under multi-axial loading is developed, and this criterion is incorporated into reliability analysis of the structural integrity of SiC/SiC fuel cladding. The research consists of two parts: 1) experimental investigation of multiaxial failure behavior of SiC/SiC composites, and 2) theoretical modeling of time-dependent probabilistic failure of SiC/SiC cladding. In the experimental investigation, the PLS is determined through the examination of stress-strain response, the acoustic emission measurement, as well as the X-ray computed tomography. The theoretical framework is derived by combin- ing the finite weakest-link statistical model and the subcritical damage growth model. This theoretical model captures the time-dependent failure mechanism of the material, which has a major consequence for predicting the lifetime distribution of the cladding. Meanwhile, the model also predicts that the failure statistics of the cladding depends strongly on the cladding length. The results of the multiaxial experiments reveal the level of statistical variation of the PLS of SiC/SiC materials under different stress states. The theoretical model provides a robust analytical tool for extrapolation of small-scale laboratory test results to the behavior of full-scale claddings. These findings establish a scientific foundation for the development of reliability-based design of SiC/SiC fuel claddings, which will play an essential role in improving the structural safety and integrity of LWRs.

42 ENGINEERING↗
DOE OSTI2023

Analyzing Hardware and Software Common Cause Failures in Digital Instrumentation and Control Systems using Dual Error Propagation Method

This paper develops a methodology for quantifying software common cause failures (CCFs) in digital instrumentation and control (I&C) systems of nuclear power plants. To support the transition of analog I&C systems to digital in nuclear power plants, probabilistic risk assessment (PRA) techniques are used. The hardware components of the I&C systems have reliability databases that can be used in the PRA studies. However, the failure data for redundant software components of the systems is sparse. Failure of components constitutes a CCF, wherein two or more components or systems fail due to a single shared cause and coupling mechanism. This paper proposes a quantification approach that can simultaneously model hardware and software components, incorporate the CCFs of software systems in the models, and bridge the gap between the failure quantification of models and the development of CCF parametric databases. We demonstrate the dual error propagation method (DEPM) by developing I&C systems failure models for a representative digital reactor trip system. The DEPM models are built to simulate the control and data flows within the systems and can accommodate failure states. By expanding DEPM to software CCFs, we generated alpha factor parameter estimates for each of the modeled error propagation mechanisms.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗