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At least 163 records · Page 9

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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 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↗

NASA NTRS1996

Relation of systemic and local muscle exercise capacity to skeletal muscle characteristics in men with congestive heart failure

OBJECTIVES. The present study was undertaken to further characterize changes in skeletal muscle morphology and histochemistry in congestive heart failure and to determine the relation of these changes to abnormalities of systemic and local muscle exercise capacity. BACKGROUND. Abnormalities of skeletal muscle appear to play a role in the limitation of exercise capacity in congestive heart failure, but information on the changes in muscle morphology and biochemistry and their relation to alterations in muscle function is limited. METHODS. Eighteen men with predominantly mild to moderate congestive heart failure (mean +/- SEM New York Heart Association functional class 2.6 +/- 0.2, ejection fraction 24 +/- 2%) and eight age- and gender-matched sedentary control subjects underwent measurements of peak systemic oxygen consumption (VO2) during cycle ergometry, resistance to fatigue of the quadriceps femoris muscle group and biopsy of the vastus lateralis muscle. RESULTS. Peak VO2 and resistance to fatigue were lower in the patients with heart failure than in control subjects (15.7 +/- 1.2 vs. 25.1 +/- 1.5 ml/min-kg and 63 +/- 2% vs. 85 +/- 3%, respectively, both p < 0.001). Patients had a lower proportion of slow twitch, type I fibers than did control subjects (36 +/- 3% vs. 46 +/- 5%, p = 0.048) and a higher proportion of fast twitch, type IIab fibers (18 +/- 3% vs. 7 +/- 2%, p = 0.004). Fiber cross-sectional area was smaller, and single-fiber succinate dehydrogenase activity, a mitochondrial oxidative marker, was lower in patients (both p < or = 0.034). Likewise, the ratio of average fast twitch to slow twitch fiber cross-sectional area was lower in patients (0.780 +/- 0.06 vs. 1.05 +/- 0.08, p = 0.019). Peak VO2 was strongly related to integrated succinate dehydrogenase activity in patients (r = 0.896, p = 0.001). Peak VO2, resistance to fatigue and strength also correlated significantly with several measures of fiber size, especially of fast twitch fibers, in patients. None of the skeletal muscle characteristics examined correlated with exercise capacity in control subjects. CONCLUSIONS. These results indicate that congestive heart failure is associated with changes in the characteristics of skeletal muscle and local as well as systemic exercise performance. There are fewer slow twitch fibers, smaller fast twitch fibers and lower succinate dehydrogenase activity. The latter finding suggests that mitochondrial content of muscle is reduced in heart failure and that impaired aerobic-oxidative capacity may play a role in the limitation of systemic exercise capacity.

Non-NASA Center↗

DOE OSTI2024

Brittle failure analysis and modeling of high-burnup PWR fuel cladding alloys

The aim of this research is the development of methods for predicting mechanical behavior and identification of limiting conditions to prevent brittle failure of high-burnup (HBU) pressure water reactor (PWR) fuel cladding alloys. A finite element (FE) model of the ring compression test (RCT) was created to analyze the failure behavior of zirconium-based alloys with radial hydrides during the RCT. An elastic-plastic material model describes the zirconium alloy. The stress-strain curve needed for the elastic-plastic material model was derived by inverse finite element analyses. Cohesive zone modeling is used to reproduce sudden load drops during RCT loading. Based on the failure mechanism in non-irradiated ZIRLO (R) claddings, a micro-mechanical model was developed that distinguishes between brittle failure along hydrides and ductile failure of the zirconium matrix. Two different cohesive laws representing these types of failure are present in the same cohesive interface. The key differences between these constitutive laws are the cohesive strength, the stress at which damage initiates, and the cohesive energy, which is the damage energy dissipated by the cohesive zone. Statistically generated matrix-hydride distributions were mapped onto the cohesive elements and simulations with focus on the first load drop were performed. Computational results are in good agreement with the RCT results conducted on high-burnup M5 (R) samples. It could be shown that crack initiation and propagation strongly depend on the specific configuration of hydrides and matrix material in the fracture area.

Simbruner, Kai↗

DOE OSTI2025

Failure Analysis–Informed Risk Assessment Framework for Geological Carbon Storage Using Numerical Simulation and Machine Learning

Geological carbon storage (GCS) is recognized as a critical technology for achieving large-scale reductions in anthropogenic carbon dioxide (CO 2 ) emissions. Ensuring long-term containment and safety requires robust risk assessment frameworks that account for geological uncertainty and identify potential failure scenarios. Among various indicators, the area of review (AoR) serves as a key metric for evaluating storage performance, regulatory compliance, and monitoring design, as it delineates the spatial extent impacted by pressure buildup and plume migration. However, conventional AoR-based risk assessments typically perturb parameters within narrow uncertainty bounds, potentially overlooking rare but high-impact events arising from extreme geological conditions. In this study, we present a failure analysis–informed risk assessment framework for large-scale GCS projects to improve site prescreening and monitoring design. A suite of 300 numerical simulations was generated using stochastic geological models that vary five key parameters: net-to-gross ratio, anisotropy azimuth, porosity multiplier, permeability multiplier, and vertical-to-horizontal permeability ratio. Among these, 200 realizations represent normal geological uncertainty, while 100 additional cases explore extreme yet plausible conditions for failure-case analysis. The AoR was simulated and computed from pressure and CO 2 saturation fields, where the baseline AoR boundary, representing the extent predicted under typical geological uncertainty, was defined as the union of 200 normal-range simulations, and failure was identified when extreme-range cases exceeded this baseline. Results show that incorporating broader parameter uncertainty produces significantly larger AoR extents, underscoring the potential underestimation of risk under conventional uncertainty ranges. Furthermore, spatial probability maps derived from failure-induced AoR exceedance identify regions requiring enhanced monitoring attention. Various machine learning (ML)–based classifiers were developed to predict failure occurrence from geological parameters, with the random forest model achieving the highest performance (F1-score of 0.986). Consistent findings from correlation coefficient, feature importance, and Sobol sensitivity analyses reveal that low net-to-gross ratios and permeability multipliers are the dominant risk drivers, reflecting reduced reservoir connectivity and limited pressure dissipation. Altogether, these results provide a novel framework for risk-informed site prescreening and monitoring design that explicitly considers rare but high-impact geological scenarios in GCS projects.

25 ENERGY STORAGE↗

DOE OSTI2025

Strain to failure measurements of Cr coatings with different processing

Differently processed Cr coatings on Zircaloy cladding were assessed for coating strain to failure. This report includes i) quantification of Cr coating strain to failure for several coating variants, ii) incorporation of high throughput analysis developed utilizing artificial intelligence, and iii) develop a hoop direction coating strain to failure testing approach for high temperatures that doesn’t require digital image correlation strain measurements. Room temperature strain to failure measurements indicated that heat treatment had an impact on strain to failure of the coating, with increasing heat treatment temperature increasing the average strain to failure of the Cr coating.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Failure Strain and Related Triaxiality of Aluminum 6061-T6, A36 Carbon Steel, 304 Stainless Steel, and Nitronic 60 Metals, Part I: Experimental Investigation

The objective of this study is to develop failure-limit material models for Aluminum 6061-T6, A36 Carbon Steel, 304 Stainless Steel, and Nitronic 60 metals, based on parameters of plastic equivalent strain (failure strain) and stress triaxiality. The research is conducted in two parts. This paper presents Part One of the study. In Part One, custom-designed test specimens undergo controlled uniaxial tension and compression testing at ambient temperature. These tests are performed at quasi-static speeds using Universal Testing Machines (UTMs) in accordance with ASTM E8 and ASTM E9 standards. Experimental data, specifically engineering stress–strain and force–displacement curves, are recorded from the onset of loading until specimen fracture, or in the case of compression tests, until the capacity of the testing machine is reached. In Part Two, the emphasis shifts to the calibration of Finite Element Analysis (FEA) models of the custom-designed test specimens. Plastic equivalent strain and the corresponding stress triaxiality values at failure are extracted from each test specimen for the given metal. These values are then systematically plotted onto a single graph to construct the failure-limit curve, which delineates the boundary conditions for material failure. This approach will facilitate the development of a comprehensive material property definition that correlates plastic equivalent strain with stress triaxiality at failure for Aluminum 6061-T6, A36 Carbon Steel, 304 Stainless Steel, and Nitronic 60 metals.

Harwell, Ron↗

NASA NTRS1976

Failure detection and isolation investigation for strapdown skew redundant tetrad laser gyro inertial sensor arrays

The degree to which flight-critical failures in a strapdown laser gyro tetrad sensor assembly can be isolated in short-haul aircraft after a failure occurrence has been detected by the skewed sensor failure-detection voting logic is investigated along with the degree to which a failure in the tetrad computer can be detected and isolated at the computer level, assuming a dual-redundant computer configuration. The tetrad system was mechanized with two two-axis inertial navigation channels (INCs), each containing two gyro/accelerometer axes, computer, control circuitry, and input/output circuitry. Gyro/accelerometer data is crossfed between the two INCs to enable each computer to independently perform the navigation task. Computer calculations are synchronized between the computers so that calculated quantities are identical and may be compared. Fail-safe performance (identification of the first failure) is accomplished with a probability approaching 100 percent of the time, while fail-operational performance (identification and isolation of the first failure) is achieved 93 to 96 percent of the time.

Eberlein, A. J.↗

NASA NTRS1980

Ferrographic and spectrographic analysis of oil sampled before and after failure of a jet engine

An experimental gas turbine engine was destroyed as a result of the combustion of its titanium components. Several engine oil samples (before and after the failure) were analyzed with a Ferrograph as well as plasma, atomic absorption, and emission spectrometers. The analyses indicated that a lubrication system failure was not a causative factor in the engine failure. Neither an abnormal wear mechanism, nor a high level of wear debris was detected in the oil sample from the engine just prior to the test in which the failure occurred. However, low concentrations of titanium were evident in this sample and samples taken earlier. After the failure, higher titanium concentrations were detected in oil samples taken from different engine locations. Ferrographic analysis indicated that most of the titanium was contained in spherical metallic debris after the failure.

Jones, W. R., Jr.↗