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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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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Defensive Islanding to Enhance the Resilience of Distribution Systems Against Cyber-Induced Failures

The extensive integration of communication, computation, and control technologies into cyber-physical power systems (CPPSs) has increased the vulnerabilities of CPPSs to cyberattacks. This calls for developing solutions that assess and reduce the impacts of cyber-induced failures on CPPSs. This paper proposes a defensive islanding strategy to isolate impacted parts of the CPPS and form self-sufficient islanded grids with an objective of minimum load curtailment. The defensive islanding aims to split a power system into smaller grids to improve its resilience against a potential extreme event. A clustering approach that leverages the hierarchical spectral clustering method is utilized for the optimal defensive islanding. The proposed approach captures the fragility behavior and loading conditions of power system components due to cyber-induced failures. A graphical-based coupling framework is used to map the impacts of cyber failures into operation of power system components. The proposed method is demonstrated on a modified 33-node distribution feeder system integrated with distributed energy resources. The amount of load curtailment and radiality constraints have been used to evaluate the performance of the proposed clustering strategies. The results show the capability of the proposed algorithm to create islands considering the cyber-induced failures for enhanced resilience.

cyber-induced failures↗
DOE OSTI2019

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

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

42 ENGINEERING↗
DOE OSTI2024

Future climate doubles the risk of hydraulic failure in a wet tropical forest

Summary Future climate presents conflicting implications for forest biomass. We evaluate how plant hydraulic traits, elevated CO 2 levels, warming, and changes in precipitation affect forest primary productivity, evapotranspiration, and the risk of hydraulic failure. We used a dynamic vegetation model with plant hydrodynamics (FATES‐HYDRO) to simulate the stand‐level responses to future climate changes in a wet tropical forest in Barro Colorado Island, Panama. We calibrated the model by selecting plant trait assemblages that performed well against observations. These assemblages were run with temperature and precipitation changes for two greenhouse gas emission scenarios (2086–2100: SSP2‐45, SSP5‐85) and two CO 2 levels (contemporary, anticipated). The risk of hydraulic failure is projected to increase from a contemporary rate of 5.7% to 10.1–11.3% under future climate scenarios, and, crucially, elevated CO 2 provided only slight amelioration. By contrast, elevated CO 2 mitigated GPP reductions. We attribute a greater variation in hydraulic failure risk to trait assemblages than to either CO 2 or climate. Our results project forests with both faster growth (through productivity increases) and higher mortality rates (through increasing rates of hydraulic failure) in the neo‐tropics accompanied by certain trait plant assemblages becoming nonviable.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Quantitative Failure Analysis on Capacity Fade in Rechargeable Lithium Metal Cells

Rechargeable lithium battery (RLB) technology is transforming portable devices, vehicle electrification, and grid modernization. To make RLB durable, reliable and safe, conducting failure mode and effect analysis (FMEA) to identify failure mechanism under the operating conditions is very desirable. However, this ability is often overlooked or even lacking. The failure analysis (FA) is often conducted by laboratory testing and postmortem analysis, and the knowledge typically empirical. Here we present a quantitative approach for FMEA that can reveal how failure modes and effects reduce the capacity of a RLB. This approach is based on the state of the battery for FMEA, contrary to the conventional approach based on operating or testing conditions. The key aspect of this FMEA method is to convert the experimental results to a state-of-charge (SOC)-based analytic methodology. Such a conversion can separate the thermodynamic and kinetic attributes of capacity fade based on compositional correspondence in the electrode, so the loss and the decreased utilization of the active materials can be determined respectively.

25 ENERGY STORAGE↗
DOE OSTI2016

StingRAY Failure Mode, Effects and Criticality Analysis: WEC Risk Registers

Analysis method to systematically identify all potential failure modes and their effects on the Stingray WEC system. This analysis is incorporated early in the development cycle such that the mitigation of the identified failure modes can be achieved cost effectively and efficiently. The FMECA can begin once there is enough detail to functions and failure modes of a given system, and its interfaces with other systems. The FMECA occurs coincidently with the design process and is an iterative process which allows for design changes to overcome deficiencies in the analysis.Risk Registers for major subsystems completed according to the methodology described in "Failure Mode Effects and Criticality Analysis Risk Reduction Program Plan.pdf" document below, in compliance with the DOE Risk Management Framework developed by NREL.

16 TIDAL AND WAVE POWER↗
DOE OSTI2019

DiagSoftfailure: Automated Soft-Failure Diagnostic Tool Using Machine Learning for Network Users

Network performance problems resulting in slow data communication speed become a significant obstacle for a satisfactory user experience. Currently, there is a lack of an automated diagnostic tool that can help network users to find the complicated network problems that degrade network performance. To fill up this gap, InfoBeyond proposes DiagSoftfailure to provide an automated diagnosis tool. DiagSoftfailure is a machine learning-based approach to infer the location and root cause of network failures that result in performance degradation. As a user-focused tool, it allows a network user to request a diagnosis. DiagSoftfailure can automatically collect the raw packet traces in the network. Base on the network signature, automated classifiers trained by combining supervised and semi-supervised machine learning is used to identify both known and unknown soft-failures in the network. A report allows novice and expert users to understand network problems for troubleshooting. In this document, we describe the DiagSoftfailure diagnosis algorithms and our experiments in a live high-speed network. DiagSoftfailure achieves 96.39% accuracy for known soft-failure diagnosis and 99.82% for unknown soft-failure diagnosis, respectively. Such results demonstrate that DiagSoftfailure is a viable technology. InfoBeyond would develop it as a marketable product that can be used by universities, Labs, DOE, government agencies, organizations, enterprises, and scientific communities to improve their network diagnosis capabilities.

42 ENGINEERING↗
DOE OSTI2020

Geometric and Material Variability Influences Stress States Relevant to Coastal Permafrost Bluff Failure

Scientific knowledge and engineering tools for predicting coastal erosion are largely confined to temperate climate zones that are dominated by non-cohesive sediments. The pattern of erosion exhibited by the ice-bonded permafrost bluffs in Arctic Alaska, however, is not well-explained by these tools. Investigation of the oceanographic, thermal, and mechanical processes that are relevant to permafrost bluff failure along Arctic coastlines is needed. We conducted physics-based numerical simulations of mechanical response that focus on the impact of geometric and material variability on permafrost bluff stress states for a coastal setting in Arctic Alaska that is prone to toppling mode block failure. Our three-dimensional geomechanical boundary-value problems output static realizations of compressive and tensile stresses. We use these results to quantify variability in the loci of potential instability. We observe that niche dimension affects the location and magnitude of the simulated maximum tensile stress more strongly than the bluff height, ice wedge polygon size, ice wedge geometry, bulk density, Young's Modulus, and Poisson's Ratio. Our simulations indicate that variations in niche dimension can produce radically different potential failure areas and that even relatively shallow vertical cracks can concentrate displacement within ice-bonded permafrost bluffs. These findings suggest that stability assessment approaches, for which the geometry of the failure plane is delineated a priori, may not be ideal for coastlines similar to our study area and could hamper predictions of erosion rates and nearshore sediment/biogeochemical loading.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Photovoltaic System Health-State Architecture for Data-Driven Failure Detection

The timely detection of photovoltaic (PV) system failures is important for maintaining optimal performance and lifetime reliability. A main challenge remains the lack of a unified health-state architecture for the uninterrupted monitoring and predictive performance of PV systems. To this end, existing failure detection models are strongly dependent on the availability and quality of site-specific historic data. The scope of this work is to address these fundamental challenges by presenting a health-state architecture for advanced PV system monitoring. The proposed architecture comprises of a machine learning model for PV performance modeling and accurate failure diagnosis. The predictive model is optimally trained on low amounts of on-site data using minimal features and coupled to functional routines for data quality verification, whereas the classifier is trained under an enhanced supervised learning regime. The results demonstrated high accuracies for the implemented predictive model, exhibiting normalized root mean square errors lower than 3.40% even when trained with low data shares. The classification results provided evidence that fault conditions can be detected with a sensitivity of 83.91% for synthetic power-loss events (power reduction of 5%) and of 97.99% for field-emulated failures in the test-bench PV system. Finally, this work provides insights on how to construct an accurate PV system with predictive and classification models for the timely detection of faults and uninterrupted monitoring of PV systems, regardless of historic data availability and quality. Such guidelines and insights on the development of accurate health-state architectures for PV plants can have positive implications in operation and maintenance and monitoring strategies, thus improving the system’s performance.

photovoltaics↗
NASA NTRS1994

Ampoule failure sensor development for semiconductor crystal growth experiments

Currently there are no devices to detect an ampoule failure in semiconductor crystal growth experiments. If an ampoule fails, it will go undetected until the containing cartridge is breached due to chemical degradation. The experiment will then be terminated resulting in a failed experiment and a loss of data. The objective of this research was to develop a reliable failure sensor that would detect a specific liquid or vapor material before the metallic cartridge is degraded and the processing furnace contaminated. The sensor is a chemical fuse made from a metal with which the semiconductor material reacts more rapidly than it does with the containing cartridge. Upon ampoule failure, the sensor is exposed to the vapor or liquid semiconductor and the chemical reaction causes a resistance change in the sensor material. The sensor shows a step change in resistance on the order of megohms when exposed to mercury zinc telluride (HgZnTe), mercury cadmium telluride (HgCdTe), or gallium arsenide (GaAs). This ampoule failure sensor is being tested for possible use on the second United States Microgravity Mission (USML-2) and is the subject of a NASA patent application.

CHEMICAL FUSE↗
NASA NTRS1992

Alterations in left ventricular diastolic function in conscious dogs with pacing-induced heart failure

We investigated in conscious dogs (a) the effects of heart failure induced by chronic rapid ventricular pacing on the sequence of development of left ventricular (LV) diastolic versus systolic dysfunction and (b) whether the changes were load dependent or secondary to alterations in structure. LV systolic and diastolic dysfunction were evident within 24 h after initiation of pacing and occurred in parallel over 3 wk. LV systolic function was reduced at 3 wk, i.e., peak LV dP/dt fell by -1,327 +/- 105 mmHg/s and ejection fraction by -22 +/- 2%. LV diastolic dysfunction also progressed over 3 wk of pacing, i.e., tau increased by +14.0 +/- 2.8 ms and the myocardial stiffness constant by +6.5 +/- 1.4, whereas LV chamber stiffness did not change. These alterations were associated with increases in LV end-systolic (+28.6 +/- 5.7 g/cm2) and LV end-diastolic stresses (+40.4 +/- 5.3 g/cm2). When stresses and heart rate were matched at the same levels in the control and failure states, the increases in tau and myocardial stiffness were no longer observed, whereas LV systolic function remained depressed. There were no increases in connective tissue content in heart failure. Thus, pacing-induced heart failure in conscious dogs is characterized by major alterations in diastolic function which are reversible with normalization of increased loading condition.

NASA Discipline Cardiopulmonary↗
NASA NTRS1993

Test-to-Failure of a Two-Grid, 30-cm-dia. Ion Accelerator System

To determine the failure mechanism and erosion characteristics of an ion accelerator system due to erosion by charge-exchange ions a test was performed in which a 30-cm-diameter, 2-grid ion accelerator system was tested to failure. The erosion charcteristics observed in this test, however, imply significantly shorter accelerator grid life times than typically stated in the literature. Finally, the test suggests that structural failure is probably not the most likely first failure mechanism for the accelerator grid.

distortion↗
NASA NTRS2013

The Effect of Fiber Strength Stochastics and Local Fiber Volume Fraction on Multiscale Progressive Failure of Composites

Continuous fiber unidirectional polymer matrix composites (PMCs) can exhibit significant local variations in fiber volume fraction as a result of processing conditions that can lead to further local differences in material properties and failure behavior. In this work, the coupled effects of both local variations in fiber volume fraction and the empirically-based statistical distribution of fiber strengths on the predicted longitudinal modulus and local tensile strength of a unidirectional AS4 carbon fiber/ Hercules 3502 epoxy composite were investigated using the special purpose NASA Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC); local effective composite properties were obtained by homogenizing the material behavior over repeating units cells (RUCs). The predicted effective longitudinal modulus was relatively insensitive to small (~8%) variations in local fiber volume fraction. The composite tensile strength, however, was highly dependent on the local distribution in fiber strengths. The RUC-averaged constitutive response can be used to characterize lower length scale material behavior within a multiscale analysis framework that couples the NASA code FEAMAC and the ABAQUS finite element solver. Such an approach can be effectively used to analyze the progressive failure of PMC structures whose failure initiates at the RUC level. Consideration of the effect of local variations in constituent properties and morphologies on progressive failure of PMCs is a central aspect of the application of Integrated Computational Materials Engineering (ICME) principles for composite materials.

multiscale analysis↗
NASA NTRS2015

Reliability and Failure in NASA Missions: Blunders, Normal Accidents, High Reliability, Bad Luck

NASA emphasizes crew safety and system reliability but several unfortunate failures have occurred. The Apollo 1 fire was mistakenly unanticipated. After that tragedy, the Apollo program gave much more attention to safety. The Challenger accident revealed that NASA had neglected safety and that management underestimated the high risk of shuttle. Probabilistic Risk Assessment was adopted to provide more accurate failure probabilities for shuttle and other missions. NASA's "faster, better, cheaper" initiative and government procurement reform led to deliberately dismantling traditional reliability engineering. The Columbia tragedy and Mars mission failures followed. Failures can be attributed to blunders, normal accidents, or bad luck. Achieving high reliability is difficult but possible.

accidents↗
NASA NTRS2017

A Thermal Runaway Failure Model for Low-Voltage BME Ceramic Capacitors with Defects

Reliability of base metal electrode (BME) multilayer ceramic capacitors (MLCCs) that until recently were used mostly in commercial applications, have been improved substantially by using new materials and processes. Currently, the inception of intrinsic wear-out failures in high quality capacitors became much greater than the mission duration in most high-reliability applications. However, in capacitors with defects degradation processes might accelerate substantially and cause infant mortality failures. In this work, a physical model that relates the presence of defects to reduction of breakdown voltages and decreasing times to failure has been suggested. The effect of the defect size has been analyzed using a thermal runaway model of failures. Adequacy of highly accelerated life testing (HALT) to predict reliability at normal operating conditions and limitations of voltage acceleration are considered. The applicability of the model to BME capacitors with cracks is discussed and validated experimentally.

reliability↗
NASA NTRS2017

Failure Analysis of Heavy-Ion-Irradiated Schottky Diodes

In this paper, we use high- and low-magnification optical microscope images, thermal infrared camera images, and scanning electron microscope images to identify failure locations in heavy-ion-irradiated Schottky diodes. After failures have been identified, the parts were cross-sectioned to describe the structure of the failures and energy dispersive x-ray spectroscopy was used to characterize the materials in the failure structures.

Radiation effects↗
NASA NTRS2021

Aircraft Engine Run-to-Failure Dataset Under Real Flight Conditions for Prognostics and Diagnostics

A key enabler of intelligent maintenance systems is the ability to predict the remaining useful lifetime (RUL) of its components, i.e., prognostics. The development of data-driven prognostics models requires datasets with run-to-failure trajectories. However, large representative run-to-failure datasets are often unavailable in real applications because failures are rare in many safety-critical systems. To foster the development of prognostics methods, we develop a new realistic dataset of run-to-failure trajectories for a fleet of aircraft engines under real flight conditions. The dataset was generated with the Commercial Modular Aero-Propulsion System Simulation (CMAPSS) model developed at NASA. The damage propagation modelling used in this dataset builds on the modelling strategy from previous work and incorporates two new levels of fidelity. First, it considers real flight conditions as recorded on board of a commercial jet. Second, it extends the degradation modelling by relating the degradation process to its operation history. This dataset also provides the health respectively fault class. Therefore, besides its applicability to prognostics problems, the dataset can be used for fault diagnostics.

CMAPPS↗
NASA NTRSDate not supplied

Infant Mortality and Wear-Out Failures in Polymer and MnO2 Tantalum Capacitors

Reliability testing of modern tantalum capacitors shows the presence of both types, infant mortality (IM) and wearout (WO) failures. To assure reliable operation, the probability of IM failures should be reduced to below the specified level, and the time of WO inception should be greater than the required useful life of the parts at operation conditions. In this work, several types of MnO2 and polymer cathode tantalum capacitors have been tested at highly accelerated conditions to assess voltage acceleration factors, determine adequate burn-in conditions, and assess the useful life. A modified time dependent dielectric breakdown (TDDB) model has been suggested to explain both types of failure, and a physical mechanism of degradation that is based on migration and reactions of oxygen vacancies explains increase of the defect related, IM failures with the level of stress.

tantalum capacitors↗
NASA NTRS2022

NASA Physics of Failure (PoF) for Reliability

An item’s reliability or longevity is dependent not only on its design but also on how it is used, manufactured, tested, and the stresses it has or will experience. Stresses include operational and environmental exposures to thermal, voltage, current, age/exposure, mechanical, and radiation mechanisms. Therefore, in reliability analysis, it is important to consider the contributions of all of these factors when predicting the failure rates of components. Historically, there has been a reliance on handbook data (e.g., MIL-HDBK-217), but experience has shown that these values and distributions are not representative of actual performance (1,2). Therefore, to make more credible reliability and risk assessments for its missions, NASA must transition to estimating likelihoods of failure based on an item’s reliability/longevity factors (or the physical susceptibilities and strengths impacting the design’s performance) has or will experience, whenever possible. To facilitate this transition a “Handbook on Methodology for Physics of Failure Based Reliability Assessments” has been developed by NASA to assist in applying physics experiences or experiment physics for empirical analysis and conceptualized physics exposures or theoretical physics for deterministic analysis, to develop and aggregate realistic likelihoods of failure leading to more credible forecasts of item performance and longevity. In addition, since it is NASA’s intention that this document continues to evolve based on community lessons learned and the introduction of new assessment methodologies, NASA is encouraging and appreciates the contributions of current and future authors to maintain and enhance this handbook and its supporting case studies.

Physics of Failure↗