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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Failure behavior of SiC/SiC composite tubes under strain rates similar to the pellet-cladding mechanical interaction phase of reactivity-initiated accidents

The mechanical response of a nuclear-grade silicon carbide fiber-reinforced silicon carbide matrix (SiC/SiC) composite was investigated under mechanical loading conditions mimicking the pellet-cladding mechanical interaction (PCMI) phase of a reactivity-initiated accident (RIA). In a RIA, cladding deformation and failure can be induced by the rapid thermal expansion of the nuclear fuel. A pulse-controlled modified-burst test was used to investigate RIA-like PCMI scenarios on SiC/SiC composite samples at pulse widths from 12 to 100 ms.The strain-driven nature of the cladding sample deformation was due to the rapid internal pressurization and subsequent expansion of a secondary tube. A digital-image correlation technique was used to measure strains from the speckle-painted outer surface of the tubes. The failure strains of samples tested at slower rates, such as RIA event durations of 52 and 100 ms, showed good agreement with the literature-reported values for similar composites tested at slow strain rates. Additionally, the failure strain showed good agreement with reference expansion-due-to-compression tests at slow strain rate. However, a decrease in the failure strain was determined for the fast-rate (12 ms) tests. This indicated that the failure strain of these composites might be influenced by the strain rate during RIA-like events. In conclusion, the failure strains observed in the tests corresponded to local energy depositions of approximately 50 cal/g UO 2 from hot zero power, with an initial condition of pellet–cladding gap closure prior to the event. In-pile transient testing of these concepts that would result in hoop strain due to PCMI in the range of 0.5–1.0% is recommended.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Predicting cell-to-cell failure propagation and limits of propagation in lithium-ion cell stacks

Thermal runaway of lithium-ion batteries is a risk that is magnified when stacks of lithium-ion cells are used for large scale energy storage. When limits of propagation can be identified so that systems can be designed to prevent large scale cascading failure even if a failure does occur, these systems will be safer. This work addresses the prediction of cell-to-cell failure propagation and the propagation limits in lithium-ion cell stacks to better understand and identify safe designs. A thermal-runaway model is presented based on recent developments in thermochemical source terms. It is noted that propagating failure is characterized by temperatures above which calorimetry data is available. Results show high temperature propagating failure predictions are too rapid unless an intra-particle diffusion limit is included, introducing a Damköhler number limiter into the rate expression. This new model form is evaluated against cell-to-cell failure propagation where the end cell of a stack is forced into thermal runaway through a nail-induced short circuit. Limits of propagation for this configuration are identified. Results show cell-to-cell propagation predictions are consistent with measurements over a range of cell states of charge and with the introduction of metal plates between cells to add system heat capacity representative of structural members. This consistency extends from scenarios where propagation occurs through scenarios where propagation is prevented.

25 ENERGY STORAGE↗
DOE OSTI2020

Deformation Precursors to Catastrophic Failure in Rocks

Forecasting the timing of catastrophic failure, such as crustal earthquakes, has been a central concern for centuries. Such forecasting requires identifying signals that evolve or accelerate in the precursory phase leading to failure, and the subset of signals that may be detected in the crust. We develop machine learning models to predict the proximity of catastrophic failure in synchrotron X-ray tomography triaxial compression experiments on rocks using characteristics of evolving fracture networks. We then examine the characteristics that most strongly influence the model results, and thus may be considered the best predictors of the proximity of macroscopic failure. Finally, the resulting suite of predictive parameters underscores the importance of dilation in the precursory phase leading to catastrophic failure. The results indicate that the evolution of the strain energy density field may provide more robust predictions of the proximity of failure than other existing metrics of rock deformation.

58 GEOSCIENCES↗
DOE OSTI2016

SU-F-R-20: Image Texture Features Correlate with Time to Local Failure in Lung SBRT Patients

Purpose: To explore possible correlation between CT image-based texture and histogram features and time-to-local-failure in early stage non-small cell lung cancer (NSCLC) patients treated with stereotactic body radiotherapy (SBRT).Methods and Materials: From an IRB-approved lung SBRT registry for patients treated between 2009–2013 we selected 48 (20 male, 28 female) patients with local failure. Median patient age was 72.3±10.3 years. Mean time to local failure was 15 ± 7.1 months. Physician-contoured gross tumor volumes (GTV) on the planning CT images were processed and 3D gray-level co-occurrence matrix (GLCM) based texture and histogram features were calculated in Matlab. Data were exported to R and a multiple linear regression model was used to examine the relationship between texture features and time-to-local-failure. Results: Multiple linear regression revealed that entropy (p=0.0233, multiple R2=0.60) from GLCM-based texture analysis and the standard deviation (p=0.0194, multiple R2=0.60) from the histogram-based features were statistically significantly correlated with the time-to-local-failure. Conclusion: Image-based texture analysis can be used to predict certain aspects of treatment outcomes of NSCLC patients treated with SBRT. We found entropy and standard deviation calculated for the GTV on the CT images displayed a statistically significant correlation with and time-to-local-failure in lung SBRT patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-H-BRC-02: Failure Mode and Effect Analysis of Liver Stereotactic Body Radiotherapy

Purpose: To identify areas of improvement in our liver stereotactic body radiation therapy (SBRT) program, using failure mode and effect analysis (FMEA). Methods: A multidisciplinary group consisting of one physician, three physicists, one dosimetrist and two therapists was formed. A process map covering 10 major stages of the liver SBRT program from the initial diagnosis to post treatment follow-up was generated. A total of 102 failure modes, together with their causes and effects, were identified. The occurrence (O), severity (S) and lack of detectability (D) were independently scored. The ranking was done using the risk probability number (RPN) defined as the product of average O, S and D numbers for each mode. The scores were normalized to remove inter-observer variability, while preserving individual ranking order. Further, a correlation analysis on the overall agreement on rank order of all failure modes resulted in positive values for successive pairs of evaluators. The failure modes with the highest RPN value were considered for further investigation. Results: The average normalized RPN values for all modes were 39 with a range of 9 to 103. The FMEA analysis resulted in the identification of the top 10 critical failures modes as: Incorrect CT-MR registration, MR scan not performed in treatment position, patient movement between CBCT acquisition and treatment, daily IGRT QA not verified, incorrect or incomplete ITV delineation, OAR contours not verified, inaccurate normal liver effective dose (Veff) calculation, failure of bolus tracking for 4D CT scan, setup instructions not followed for treatment and plan evaluation metrics missed. Conclusion: The application of FMEA to our liver SBRT program led to the identification and possible improvement of areas affecting patient safety.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Can Applications Recover from fsync Failures?

We analyze how file systems and modern data-intensive applications react to fsync failures. First, we characterize how three Linux file systems (ext4, XFS, Btrfs) behave in the presence of failures. We find commonalities across file systems (pages are always marked clean, certain block writes always lead to unavailability) as well as differences (page content and failure reporting is varied). Next, we study how five widely used applications (PostgreSQL, LMDB, LevelDB, SQLite, Redis) handle fsync failures. Our findings show that although applications use many failure-handling strategies, none are sufficient: fsync failures can cause catastrophic outcomes such as data loss and corruption. Our findings have strong implications for the design of file systems and applications that intend to provide strong durability guarantees.

Computer Science↗
DOE OSTI2017

Epidemic failure detection and consensus for extreme parallelism

Future extreme-scale high-performance computing systems will be required to work under frequent component failures. The MPI Forum s User Level Failure Mitigation proposal has introduced an operation, MPI Comm shrink, to synchronize the alive processes on the list of failed processes, so that applications can continue to execute even in the presence of failures by adopting algorithm-based fault tolerance techniques. This MPI Comm shrink operation requires a failure detection and consensus algorithm. This paper presents three novel failure detection and consensus algorithms using Gossiping. The proposed algorithms were implemented and tested using the Extreme-scale Simulator. The results show that in all algorithms the number of Gossip cycles to achieve global consensus scales logarithmically with system size. The second algorithm also shows better scalability in terms of memory and network bandwidth usage and a perfect synchronization in achieving global consensus. The third approach is a three-phase distributed failure detection and consensus algorithm and provides consistency guarantees even in very large and extreme-scale systems while at the same time being memory and bandwidth efficient.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Vitality models found useful in modeling tag-failure times in acoustic-tag survival studies

Abstract Acoustic telemetry studies often rely on the assumption that premature tag failure does not affect the validity of inferences. However, in some cases this assumption is possibly or likely invalid and it is necessary to apply a correction to estimation procedures. The question of which approaches and specific models are best suited to modeling acoustic tag failures has received little research attention. In this short communication, we present a meta-analysis of 42 acoustic tag-life studies, originally used to correct survival studies involving outmigrating juvenile salmonids in the Columbia/Snake river basin. We compare the performance of nine alternative parametric models including common failure–time/survival models and the vitality models of Li and Anderson Theor Popul Biol 76:118–131, (2009) and Demogr Res 28:341–372, (2013). The tag-life studies used acoustic tags from three different tag manufacturers, had expected lifetimes between 12 and 61 days, and had dry weights ranging from 0.22 to 1.65 g. In 57% of the cases, the vitality models of Li and Anderson Theor Popul Biol 76:118–131, (2009) and Demogr Res 28:341–372, (2013) fit the tag-failure times best. The vitality models were also the second-best choices in 17% of the cases. Together, the vitality models, log-logistic, (19%), and gamma models (14%) accounted for 90% of the models selected. Unlike more traditional failure–time models (e.g., Weibull, Gompertz, gamma, and log-logistic), the vitality models are capable of characterizing both the early onset of tag failure due to manufacturing errors and the anticipated battery life. We provide further guidance on appropriate sample sizes (50–100 tags) and procedures to be considered when applying precise tag-life corrections in release–recapture survival studies.

Skalski, John R. (ORCID:0000000270702505)↗
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 OSTI2018

Margins Associated with Loss of Assured Safety for Systems with Multiple Time-Dependent Failure Modes.

Representations for margins associated with loss of assured safety (LOAS) for weak link (WL)/strong link (SL) systems involving multiple time-dependent failure modes are developed. The following topics are described: (i) defining properties for WLs and SLs, (ii) background on cumulative distribution functions (CDFs) for link failure time, link property value at link failure, and time at which LOAS occurs, (iii) CDFs for failure time margins defined by (time at which SL system fails) – (time at which WL system fails), (iv) CDFs for SL system property values at LOAS, (v) CDFs for WL/SL property value margins defined by (property value at which SL system fails) – (property value at which WL system fails), and (vi) CDFs for SL property value margins defined by (property value of failing SL at time of SL system failure) – (property value of this SL at time of WL system failure). Included in this presentation is a demonstration of a verification strategy based on defining and approximating the indicated margin results with (i) procedures based on formal integral representations and associated quadrature approximations and (ii) procedures based on algorithms for sampling-based approximations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Investigation of Gel Polymer Electrolyte Failure Mechanism in Lithium-Sulfur Batteries

Lithium sulfur (Li-S) batteries are a promising candidate for next-generation energy storage due to their high theoretical energy density. However, well-known challenges such as polysulfide crossover, large volume changes during cycling, lithium dendrite growth, and passivation of reaction sites limit the capacity and capacity retention of Li-S batteries. One approach to address these issues is to use gel polymer electrolyte (GPE) in place of the typical liquid electrolyte. It is believed that GPE can reduce the dissolution and diffusion of the intermediate polysulfides and enhance the capacity retention in Li-S batteries, but additional research is needed. In particular, the difference in failure mechanisms between GPE and liquid electrolyte cells is not well understood, which is important knowledge for the rational design of high performance GPE cells. We have investigated the effects of gel polymer electrolyte on lithium-sulfur coin cell failure mechanisms. In particular, we used a discharge test with pauses to probe how the choice of electrolyte affected the amount of capacity recovered due to the pause. After discharging normally until failure, the cell was paused for some time, after which discharge was restarted until the second and final failure. Gel polymer electrolyte was found to have a higher percentage capacity recovery after pausing than liquid electrolyte, and that recovery improved at higher C-rates. Large percentage capacities recoveries suggest that mass transport limitations are leading to cell failure rather than cathode passivation as is frequently proposed. To help explain this behavior, we use a 1-dimension + time numerical continuum model for the Li-S full cell that includes the pausing step. The model includes the electrochemical reactions and precipitation of sulfur and intermediate polysulfide species, transport of species through the battery, and the effect of mass transport limitations on cell failure. The simulations show that variations in the bulk polysulfide diffusion coefficients can explain many of the differences between GPE and liquid electrolyte experimental results, and further confirm that mass transport limitations are a critical obstacle in improving the performance of GPE Li-S batteries.

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.↗
NASA NTRS1980

Failure analyses of composite bolted joints

The complex failure behavior exhibited by bolted joints of graphite epoxy (Hercules AS/3501) was investigated for the net tension, bearing and shearout failure modes using combined analytical and experimental techniques. Plane stress, linear elastic, finite element methods were employed to determine the two dimensional state of stress resulting from a loaded hole in a finite width, semiinfinite strip. The stresses predicted by the finite element method were verified by experiment to lend credence to the analysis. The influence of joint geometric parameters on the state of stress and resultant strength of the joint was also studied. The resulting functional relationships found to exist between bolted joint strength and the geometric parameters, were applied in the formulation of semiempirical strength models for the basic failure modes. A point stress failure criterion was successfully applied as the failure criterion for the net tension and shearout failure modes.

Wilson, D. W.↗
NASA NTRS1981

Failure of morphology of (0 deg)8 graphite/epoxy as influenced by environments and processing

Optical and scanning electron microscopy were used to investigate the failure morphology of graphite/epoxy specimens which had been tested until tensile failure. Failure morphology was studied as a function of the quality control variables of specimen preparation technique, prepreg batch, and cure condition, and also as a function of the environmental parameters of temperature and moisture content. Defective specimens were found to exhibit a low energy failure morphology. Poor specimen edge preparation and one batch of prepreg when tested at elevated temperature or moisture content also exhibited energy failure morphology. Postcuring had no effect on strength but did slightly alter failure morphology. Temperature or moisture appeared to decrease flaw sensitivity and thus increase strength; however, moisture also appeared to increase interfacial debonding between filament and matrix. When combined moisture and temperature increased interfacial debonding and made the epoxy matrix more prone to fracture.

Clements, L. L.↗