Results for “Failure Rate” — Page 48

DOE OSTI2023

Survey of Aging and Monitoring Concerns for Cables and Splices Due to Cable Repair and Replacement

The purpose of this report is to survey aging and monitoring concerns for electrical cable splices in nuclear power plants (NPPs) in long term operation. As portions of existing electrical cable runs in nuclear are replaced over time due to localized events, the total number of splices in NPPs is expected to increase. Relative to cables, the body of knowledge regarding aging of splices and splices in combination with aging cables in nuclear service environments in long-term operations is low. A few reports have considered the aging of cable system components other than cables (Jacobus 1990; Nelson 1998; Villaran and Lofaro 2002), but the nuclear industry has two decades of operating experience since these were published to further enlighten this issue. Herein we discuss electrical cables and splices commonly found in U.S. nuclear power plants, their qualification in safety-related application, and methods for monitoring their health condition. Common environmental stresses that can give rise to cable and splice failure are discussed. The Nuclear Regulatory Commission (NRC) Licensee Event Reports (LER) database was used to identify documented issues of cable and splice failure. The trend in the resultant data over time is considered to see if failures are increasing as plants age. Observations and conclusions of this work include: 1. Cables and splices are highly reliable components. Occurrence rates for events of interest were low and nearly constant over the last 20 years. 2. Common-cause failure for evaluated cable events of interest was observed to primarily be associated with loose connections, which may manifest associated with workmanship issues, thermal cycling, and/or vibration. 3. Replacement of cables is more common than repair, leading to an increase in proportion of new generation cables in the plant over time. 4. Splices on degraded cables have been observed to be problematic. Due to aging NPP infrastructure, including electrical cables, it is expected that such issues will continue to increase. 5. Condition monitoring approaches, while shown to be fruitful for cables, have been shown to be insensitive to degradation of splice sleeves, which are critical to the continued performance of splices. Additional condition monitoring (CM) work is needed to evaluate methods which are sensitive to the degradation of splice components. 6. Extended Material Degradation Assessment (EMDA) knowledge gaps for electrical cables (Bernstein et al. 2014) have not been investigated for splices but may represent similar concerns such as for the accelerated aging process historically used in environmental qualification.

42 ENGINEERING↗

NASA NTRS2017

Relationship Between Unusual High-Temperature Fatigue Crack Growth Threshold Behavior in Superalloys and Sudden Failure Mode Transitions

An investigation of high temperature cyclic fatigue crack growth (FCG) threshold behavior of two advanced nickel disk alloys was conducted. The focus of the study was the unusual crossover effect in the near-threshold region of these type of alloys where conditions which produce higher crack growth rates in the Paris regime, produce higher resistance to crack growth in the near threshold regime. It was shown that this crossover effect is associated with a sudden change in the fatigue failure mode from a predominant transgranular mode in the Paris regime to fully intergranular mode in the threshold fatigue crack growth region. This type of a sudden change in the fracture mechanisms has not been previously reported and is surprising considering that intergranular failure is typically associated with faster crack growth rates and not the slow FCG rates of the near-threshold regime. By characterizing this behavior as a function of test temperature, environment and cyclic frequency, it was determined that both the crossover effect and the onset of intergranular failure are caused by environmentally driven mechanisms which have not as yet been fully identified. A plausible explanation for the observed behavior is proposed.

Fatigue Crack Growth Thresholds; Grain boundary ox↗

NASA NTRS2017

Relationship Between Unusual High-Temperature Fatigue Crack Growth Threshold Behavior in Superalloys and Sudden Failure Mode Transitions

An investigation of high temperature cyclic fatigue crack growth (FCG) threshold behavior of two advanced nickel disk alloys was conducted. The focus of the study was the unusual crossover effect in the near-threshold region of these type of alloys where conditions which produce higher crack growth rates in the Paris regime, produce higher resistance to crack growth in the near threshold regime. It was shown that this crossover effect is associated with a sudden change in the fatigue failure mode from a predominant transgranular mode in the Paris regime to fully intergranular mode in the threshold fatigue crack growth region. This type of a sudden change in the fracture mechanisms has not been previously reported and is surprising considering that intergranular failure is typically associated with faster crack growth rates and not the slow FCG rates of the near-threshold regime. By characterizing this behavior as a function of test temperature, environment and cyclic frequency, it was determined that both the crossover effect and the onset of intergranular failure are caused by environmentally driven mechanisms which have not as yet been fully identified. A plausible explanation for the observed behavior is proposed.

Fatigue Crack Growth Thresholds; Grain boundary ox↗

NASA NTRS1994

Increased walking variability in elderly persons with congestive heart failure

OBJECTIVES: To determine the effects of congestive heart failure on a person's ability to walk at a steady pace while ambulating at a self-determined rate. SETTING: Beth Israel Hospital, Boston, a primary and tertiary teaching hospital, and a social activity center for elderly adults living in the community. PARTICIPANTS: Eleven elderly subjects (aged 70-93 years) with well compensated congestive heart failure (NY Heart Association class I or II), seven elderly subjects (aged 70-79 years) without congestive heart failure, and 10 healthy young adult subjects (aged 20-30 years). MEASUREMENTS: Subjects walked for 8 minutes on level ground at their own selected walking rate. Footswitches were used to measure the time between steps. Step rate (steps/minute) and step rate variability were calculated for the entire walking period, for 30 seconds during the first minute of the walk, for 30 seconds during the last minute of the walk, and for the 30-second period when each subject's step rate variability was minimal. Group means and 5% and 95% confidence intervals were computed. MAIN RESULTS: All measures of walking variability were significantly increased in the elderly subjects with congestive heart failure, intermediate in the elderly controls, and lowest in the young subjects. There was no overlap between the three groups using the minimal 30-second variability (elderly CHF vs elderly controls: P < 0.001, elderly controls vs young: P < 0.001), and no overlap between elderly subjects with and without congestive heart failure when using the overall variability. For all four measures, there was no overlap in any of the confidence intervals, and all group means were significantly different (P < 0.05).

NASA Discipline Cardiopulmonary↗

NASA NTRS1980

Development of a laminate fatigue analysis

A fatigue analysis technique developed to predict damage growth in notched laminates is described. Features of the analysis include: criteria to relate matrix failure to cyclic stresses in and between plies; correlation of delamination growth with strain-release rate; and in-plane shear modulus change is related to cyclic shear stresses. A simplified finite element model is used to determine stresses in laminates that contain matrix damage. Failure criteria are integrated with the finite element model to form the fatigue analysis.

Roderick, G. L.↗

DOE OSTI2026

High-Sensitivity DNA Aptasensors for Detecting Salivary Biomarker S100A7 in Heart Failure

Early detection of heart failure (HF) is vital for improving patient outcomes, lowering hospital readmission rates, and enabling prompt treatment. We present the first high-affinity DNA aptamer for the salivary HF biomarker S100A7 and its application in highly sensitive, noninvasive diagnostic tests. Iterative truncation of the initial 82-nt aptamer (17–82) produced a 43-nt core (17–43) with a binding affinity of 27 nM, which was further enhanced to 5.5 nM through dimerization. Biochemical and mutational studies confirmed that 17–43 adopts a G-quadruplex structure, which is essential for S100A7 recognition and resistance to enzymatic degradation in human saliva. Incorporating 17–43 into sandwich aptamer-ELISA and hybrid aptamer–antibody ELISA assays allowed detection of recombinant S100A7 in human saliva with limits of detection (LOD) of 7.4 ng mL–1 (0.6 nM) and 29 pg/mL (2.2 pM), respectively-outperforming commercial immunoassays in both sensitivity and dynamic range. The hybrid assay maintained its full performance after 2.5 months of room temperature storage. Additionally, a biolayer interferometry (BLI) sensor with 17–43 quantified S100A7 in patient saliva (n = 3), achieving a LOD of 3.2 ng mL–1 (0.3 nM) with a total assay time of less than 20 min. The aptamer’s stability, high specificity, and versatility across biosensing platforms establish it as a promising tool for noninvasive heart failure diagnostics, laying the groundwork for portable aptamer-based biosensors for multiplexed monitoring of HF biomarkers.

DNA aptamer↗

DOE OSTI2026

Risk-Aware Measurement Synchronization and Recovery for DSSE With Heterogeneous Data Sources

Power distribution systems are increasingly integrating heterogeneous sensors with varying data reporting rates and types, which pose challenges to achieving observability at the desired temporal resolution of distribution system state estimation (DSSE). Multisensor failures caused by extreme events exacerbate these issues, introducing substantial uncertainties into DSSE. This article proposes a novel solution to these challenges by ensuring high-resolution system observability despite heterogeneous data sources and multisensor failures. First, a deep learning architecture combining long short-term memory (LSTM) and graph convolutional network (GCN) is employed to synchronize meters with different reporting rates, aiming to achieve system observability. A random-walk-model-based approach is introduced to generate pseudo-measurements while properly characterizing their uncertainties under multisensor failures. Finally, a disaster-risk-informed observability metric (RiOM) is defined to quantify the uncertainty associated with state estimation results. The proposed framework offers deeper insights into the system observability on the fly compared with conventional analysis. The effectiveness of the framework is demonstrated on an IEEE standard test case and a large-scale real-world distribution feeder in mid-Minnesota in the U.S.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Characterization of Interconnects

Combined-accelerated stress testing (C-AST) simultaneously combines stress factors of the natural environment (including UV radiation, temperature, humidity, electrical current, and external mechanical force) into a single test that requires fewer modules, fewer chambers, and makes it possible to discover weaknesses in new designs that are not known a-priori. C-AST reduces risk, accelerates time to market, and improves bankability by reducing costly overdesign using test levels not exceeding those seen in the natural environment. This project seeks to evaluate strengths and weaknesses of modern cell interconnect designs with combined-accelerated stress testing (C-AST) to screen multiple climates along with finite element and failure analysis to determine the potential for a 50-year life. Supporting this, we seek to develop methods of characterization to assess the degradation of interconnects, enable predictive rate models with material forensics and FEA and show C-AST's ability to find interconnect failures and benchmark it relative to other accelerated stress test methods like temperature cycling and cyclic dynamic mechanical loading. Examples of modern interconnect designs covered are Canadian Solar Hetero Technology ribbon enabling closer cell interconnections, SmartWire (eg. Meyer-Berger technology), and shingled cells with new interconnect materials.

C-AST↗

NASA NTRS1972

Demonstration of the use of ADAPT to derive predictive maintenance algorithms for the KSC central heat plant

The Avco Data Analysis and Prediction Techniques (ADAPT) were employed to determine laws capable of detecting failures in a heat plant up to three days in advance of the occurrence of the failure. The projected performance of algorithms yielded a detection probability of 90% with false alarm rates of the order of 1 per year for a sample rate of 1 per day with each detection, followed by 3 hourly samplings. This performance was verified on 173 independent test cases. The program also demonstrated diagnostic algorithms and the ability to predict the time of failure to approximately plus or minus 8 hours up to three days in advance of the failure. The ADAPT programs produce simple algorithms which have a unique possibility of a relatively low cost updating procedure. The algorithms were implemented on general purpose computers at Kennedy Space Flight Center and tested against current data.

Hunter, H. E.↗

NASA NTRS1986

Effect of adherend thickness and mixed mode loading on debond growth in adhesively bonded composite joints

Symmetric and unsymmetric double cantilever beam (DCB) specimens were tested and analyzed to assess the effect of: (1) adherend thickness, and (2) a predominantly mode I mixed mode loading on cyclic debond growth and static fracture toughness. The specimens were made of unidirectional composite (T300/5208) adherends bonded together with EC3445 structural adhesive. The thickness was 8, 16, or 24 plies. The experimental results indicated that the static fracture toughness increases and the cyclic debond growth rate decreases with increasing adherend thickness. This behavior was related to the length of the plastic zone ahead of the debond tip. For the symmetric DCB specimens, it was further found that displacement control tests resulted in higher debond growth rates than did load control tests. While the symmetric DCB tests always resulted in cohesive failures in the bondline, the unsymmetric DCB tests resulted in the debond growing into the thinner adherend and the damage progressing as delamination in that adherend. This behavior resulted in much lower fracture toughness and damage growth rates than found in the symmetric DCB tests.

Mangalgiri, P. D.↗

NASA NTRS1997

The hypertension of autonomic failure and its treatment

We studied the incidence and severity of supine hypertension in 117 patients with severe primary autonomic failure presenting to a referral center over a 9-year period. Patients were uniformly characterized by disabling orthostatic hypotension, lack of compensatory heart rate increase, abnormal autonomic function tests, and unresponsive plasma norepinephrine. Fifty-four patients had isolated autonomic impairment (pure autonomic failure). Sixty-three patients had central nervous system involvement in addition to autonomic impairment (multiple-system atrophy). Patients were studied off medications, in a metabolic ward, and on a controlled diet containing 150 mEq of sodium. Fifty-six percent of patients had supine diastolic blood pressure > or =90 mm Hg. The prevalence of hypertension was slightly greater in females (63%) than in males (52%). Potential mechanisms responsible for this hypertension were investigated. No correlation was found between blood volume and blood pressure. Similarly, plasma norepinephrine (92+/-15 pg/mL) and plasma renin activity (0.3+/-0.05 ng/mL per hour) were very low in the subset of patients with pure autonomic failure and supine hypertension (mean systolic/diastolic pressure, 177 +/- 6/108 +/- 2 mm Hg, range 167/97 to 219/121). Supine hypertension represents a challenge in the treatment of orthostatic hypotension. We found these patients to be particularly responsive to the hypotensive effects of transdermal nitroglycerin. Doses ranging from 0.025 to 0.1 mg/h decreased systolic blood pressure by 36+/-7 mm Hg and may effectively treat supine hypertension overnight, but the dose should be individualized and used with caution.

NASA Discipline Regulatory Physiology↗

NASA NTRS2006

Reconfigurable Control with Neural Network Augmentation for a Modified F-15 Aircraft

Description of the performance of a simplified dynamic inversion controller with neural network augmentation follows. Simulation studies focus on the results with and without neural network adaptation through the use of an F-15 aircraft simulator that has been modified to include canards. Simulated control law performance with a surface failure, in addition to an aerodynamic failure, is presented. The aircraft, with adaptation, attempts to minimize the inertial cross-coupling effect of the failure (a control derivative anomaly associated with a jammed control surface). The dynamic inversion controller calculates necessary surface commands to achieve desired rates. The dynamic inversion controller uses approximate short period and roll axis dynamics. The yaw axis controller is a sideslip rate command system. Methods are described to reduce the cross-coupling effect and maintain adequate tracking errors for control surface failures. The aerodynamic failure destabilizes the pitching moment due to angle of attack. The results show that control of the aircraft with the neural networks is easier (more damped) than without the neural networks. Simulation results show neural network augmentation of the controller improves performance with aerodynamic and control surface failures in terms of tracking error and cross-coupling reduction.

Burken, John J.↗

NASA NTRS2006

Adaptive Control Using Neural Network Augmentation for a Modified F-15 Aircraft

Description of the performance of a simplified dynamic inversion controller with neural network augmentation follows. Simulation studies focus on the results with and without neural network adaptation through the use of an F-15 aircraft simulator that has been modified to include canards. Simulated control law performance with a surface failure, in addition to an aerodynamic failure, is presented. The aircraft, with adaptation, attempts to minimize the inertial cross-coupling effect of the failure (a control derivative anomaly associated with a jammed control surface). The dynamic inversion controller calculates necessary surface commands to achieve desired rates. The dynamic inversion controller uses approximate short period and roll axis dynamics. The yaw axis controller is a sideslip rate command system. Methods are described to reduce the cross-coupling effect and maintain adequate tracking errors for control surface failures. The aerodynamic failure destabilizes the pitching moment due to angle of attack. The results show that control of the aircraft with the neural networks is easier (more damped) than without the neural networks. Simulation results show neural network augmentation of the controller improves performance with aerodynamic and control surface failures in terms of tracking error and cross-coupling reduction.

Burken, John J.↗

NASA NTRS2002

Four faces of baroreflex failure: hypertensive crisis, volatile hypertension, orthostatic tachycardia, and malignant vagotonia

BACKGROUND: The baroreflex normally serves to buffer blood pressure against excessive rise or fall. Baroreflex failure occurs when afferent baroreceptive nerves or their central connections become impaired. In baroreflex failure, there is loss of buffering ability, and wide excursions of pressure and heart rate occur. Such excursions may derive from endogenous factors such as stress or drowsiness, which result in quite high and quite low pressures, respectively. They may also derive from exogenous factors such as drugs or environmental influences. METHODS AND RESULTS: Impairment of the baroreflex may produce an unusually broad spectrum of clinical presentations; with acute baroreflex failure, a hypertensive crisis is the most common presentation. Over succeeding days to weeks, or in the absence of an acute event, volatile hypertension with periods of hypotension occurs and may continue for many years, usually with some attenuation of pressor surges and greater prominence of depressor valleys during long-term follow-up. With incomplete loss of baroreflex afferents, a mild syndrome of orthostatic tachycardia or orthostatic intolerance may appear. Finally, if the baroreflex failure occurs without concomitant destruction of the parasympathetic efferent vagal fibers, a resting state may lead to malignant vagotonia with severe bradycardia and hypotension and episodes of sinus arrest. CONCLUSIONS: Although baroreflex failure is not the most common cause of the above conditions, correct differentiation from other cardiovascular disorders is important, because therapy of baroreflex failure requires specific strategies, which may lead to successful control.

Review↗

NASA NTRS2007

Zero Gyro Kalman Filtering in the Presence of a Reaction Wheel Failure

Typical implementation of Kalman filters for spacecraft attitude estimation involves the use of gyros for three-axis rate measurements. When there are less than three axes of information available, the accuracy of the Kalman filter depends highly on the accuracy of the dynamics model. This is particularly significant during the transient period when a reaction wheel with a high momentum fails, is taken off-line, and spins down. This paper looks at how a reaction wheel failure can affect the zero-gyro Kalman filter performance for the Hubble Space Telescope and what steps are taken to minimize its impact.

Hur-Diaz, Sun↗

NASA NTRS2007

Zero Gyro Kalman Filtering in the presence of a Reaction Wheel Failure

Typical implementation of Kalman filters for spacecraft attitude estimation involves the use of gyros for three-axis rate measurements. When there are less than three axes of information available, the accuracy of the Kalman filter depends highly on the accuracy of the dynamics model. This is particularly significant during the transient period when a reaction wheel with a high momentum fails, is taken off-line, and spins down. This paper looks at how a reaction wheel failure can affect the zero-gyro Kalman filter performance for the Hubble Space Telescope and what steps are taken to minimize its impact.

Hur-Diaz, Sun↗

NASA NTRSDate not supplied

Machine Learning Enabled Quantitative Risk Assessment of Aerial Wildfire Response

Aerial wildfire operations are high risk and account for a large number of firefighter deaths. Increasing intensity of wildfires is driving a surge in aerial operations, while simultaneously there is growing interest in improving system safety and performance. In this work, wildfire aviation mishaps documented using the SAFECOM system are analyzed using a previously developed framework for hazard extraction and analysis of trends (HEAT). Hazards and specific failure modes are extracted from the narrative data in SAFECOM forms using natural language processing techniques. Metrics for each hazard are calculated, including frequency, rate, and severity. We examine whether these metrics change over time, and whether they are related to metadata, such as region and aircraft type. The results of the hazard analysis are presented in a risk matrix, identifying the highest and lowest risk hazards based on rate of occurrence and average severity. Results identify jumper operations hazards as high-risk, in addition to bucket drop failures, cargo let down failures, and severe weather as medium risk.

machine learning↗

NASA NTRSDate not supplied

Machine Learning Enabled Quantitative Risk Assessment of Aerial Wildfire Response

Aerial wildfire operations are high risk and account for a large number of firefighter deaths. Increasing intensity of wildfires is driving a surge in aerial operations, while simultaneously there is growing interest in improving system safety and performance. In this work, wildfire aviation mishaps documented using the SAFECOM system are analyzed using a previously developed framework for hazard extraction and analysis of trends (HEAT). Hazards and specific failure modes are extracted from the narrative data in SAFECOM forms using natural language processing techniques. Metrics for each hazard are calculated, including frequency, rate, and severity. We examine whether these metrics change over time, and whether they are related to metadata, such as region and aircraft type. The results of the hazard analysis are presented in a risk matrix, identifying the highest and lowest risk hazards based on rate of occurrence and average severity. Results identify jumper operations hazards as high-risk, in addition to bucket drop failures, cargo let down failures, and severe weather as medium risk.

machine learning↗