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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Treatment of low strains and long hold times in high temperature metal fatigue by strainrange partitioning

A procedure for treating creep-fatigue for low strainranges and long hold times is outlined. A semi-experimental approach, wherein several cycles of the imposed loading is actually applied to a specimen in order to determine the stable hysteresis loop, can be very useful in the analysis. Because such tests require only a small fraction of the total failure time, they are not inherently prohibitive if experimental equipment is available. The need for accurate constitutive equations is bypassed because the material itself acts to translate the imposed loading into the responsive hysteresis loops. When strainrange partitioning has been applied in such cases very good results have been obtained.

Manson, S. S.↗
NASA NTRS2005

Verification of the Multi-Axial, Temperature and Time Dependent (MATT) Failure Criterion

An extensive test and analytical effort has been completed by the Space Shuttle's Reusable Solid Rocket Motor (KSKM) nozzle program to characterize the failure behavior of two epoxy adhesives (TIGA 321 and EA946). As part of this effort, a general failure model, the "Multi-Axial, Temperature, and Time Dependent" or MATT failure criterion was developed. In the initial development of this failure criterion, tests were conducted to provide validation of the theory under a wide range of test conditions. The purpose of this paper is to present additional verification of the MATT failure criterion, under new loading conditions for the adhesives TIGA 321 and EA946. In many cases, the loading conditions involve an extrapolation from the conditions under which the material models were originally developed. Testing was conducted using three loading conditions: multi-axial tension, torsional shear, and non-uniform tension in a bondline condition. Tests were conducted at constant and cyclic loading rates ranging over four orders of magnitude. Tests were conducted under environmental conditions of primary interest to the RSRM program. The temperature range was not extreme, but the loading ranges were extreme (varying by four orders of magnitude). It should be noted that the testing was conducted at temperatures below the glass transition temperature of the TIGA 321 adhesive. However for the EA946, the testing was conducted at temperatures that bracketed the glass transition temperature.

Richardson, David E.↗
DOE OSTI2021

The effect of electrical current on premature failures and microstructural degradation in bearing steel

Premature failures associated with microstructural degradation, i.e. white etching cracks (WECS), are becoming commonplace as applications are requiring tribological components to operate under extreme conditions. Although the specific drivers of WECs are still debated, the failures are often found in applications where cyclic loading is combined with added energy from stressors such as slip, impacts, or stray current. The aim of the current work is to elucidate effect that variable current has on premature failure. Numerous commercially available lubricants were tested, and both lubricant base oil type and additive package were found to have an effect on WEC failure time.

Bearing failure↗
DOE OSTI2020

PVAnalytics [SWR-20-33]

PVAnalytics inputs long term (multiple years) photovoltaic (PV) outdoor sensor data and completes autonomous quality assurance (QA) analysis on the data. Time series data from individual sensors such as electric meters, inverter outputs, irradiance, and temperature sensors are compared to physically expected outputs of these sensors under clear sky conditions based on the latitude, longitude, and orientation of the PV system. PVAnalytics outputs as QA pass or fail for each sensor, reasons determined for failure, time series flags identifying QA thresholds have been exceeded, flags for sunny days, the time zone found for the given sensor, sensor drift, time periods for passing data, and results of orientation checks.

Muller, Matthew↗
DOE OSTI2022

Classification of Photovoltaic Failures with Hidden Markov Modeling, an Unsupervised Statistical Approach

Failure detection methods are of significant interest for photovoltaic (PV) site operators to help reduce gaps between expected and observed energy generation. Current approaches for field-based fault detection, however, rely on multiple data inputs and can suffer from interpretability issues. In contrast, this work offers an unsupervised statistical approach that leverages hidden Markov models (HMM) to identify failures occurring at PV sites. Using performance index data from 104 sites across the United States, individual PV-HMM models are trained and evaluated for failure detection and transition probabilities. This analysis indicates that the trained PV-HMM models have the highest probability of remaining in their current state (87.1% to 93.5%), whereas the transition probability from normal to failure (6.5%) is lower than the transition from failure to normal (12.9%) states. A comparison of these patterns using both threshold levels and operations and maintenance (O&M) tickets indicate high precision rates of PV-HMMs (median = 82.4%) across all of the sites. Although additional work is needed to assess sensitivities, the PV-HMM methodology demonstrates significant potential for real-time failure detection as well as extensions into predictive maintenance capabilities for PV.

classification↗
DOE OSTI2021

Laboratory earthquake forecasting: A machine learning competition

Earthquake prediction, the long-sought holy grail of earthquake science, continues to confound Earth scientists. Could we make advances by crowdsourcing, drawing from the vast knowledge and creativity of the machine learning (ML) community? We used Google’s ML competition platform, Kaggle, to engage the worldwide ML community with a competition to develop and improve data analysis approaches on a forecasting problem that uses laboratory earthquake data. The competitors were tasked with predicting the time remaining before the next earthquake of successive laboratory quake events, based on only a small portion of the laboratory seismic data. The more than 4,500 participating teams created and shared more than 400 computer programs in openly accessible notebooks. Complementing the now well-known features of seismic data that map to fault criticality in the laboratory, the winning teams employed unexpected strategies based on rescaling failure times as a fraction of the seismic cycle and comparing input distribution of training and testing data. In addition to yielding scientific insights into fault processes in the laboratory and their relation with the evolution of the statistical properties of the associated seismic data, the competition serves as a pedagogical tool for teaching ML in geophysics. The approach may provide a model for other competitions in geosciences or other domains of study to help engage the ML community on problems of significance.

58 GEOSCIENCES↗
DOE OSTI2022

Validation of material models for puncture of 7075-T651 aluminum plate

Plate puncture simulations are challenging computational tasks that require advanced material models including high strain rate and thermal-mechanical effects on both deformation and failure, plus finite element techniques capable of representing large deformations and material failure. The focus of this work is on the material issues, which require large sets of experiments, flexible material models and challenging calibration procedures. In this study, we consider the puncture of 12.7 mm thick, 7075-T651 aluminum alloy plates by a cylindrical punch with a hemispherical nose and diameter of 12.7 mm. The plasticity and ductile failure models were isotropic with calibration data obtained from uniaxial tension tests at different temperatures and strain rates plus quasi-static notched tension tests and shear-dominated tests described here. Sixteen puncture experiments were conducted to identify the threshold penetration energy, mode of puncture and punch acceleration during impact, The punch was mounted on a 139 kg mass and dropped on the plates with different impact speeds. Since the mass was the same in all tests, the quantity of interest was the impact speed. The axis and velocity of the punch were perpendicular to the plate surface. The mean threshold punch speed was 3.05 m/s, and the mode of failure was plugging by thermal-mechanical shear banding accompanied by scabbing fragments. Application of the material models in simulations of the tests yielded accurate estimates of the threshold puncture speed and of the mode of failure. Time histories of the punch acceleration compared well between simulation and test. Remarkably, the success of the simulations occurred in spite of even the smallest element used being larger than the width of the shear bands.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Reliability modeling in a predictive maintenance context: A margin-based approach

Current system reliability methods (typically based on fault trees or reliability block diagrams) can effectively propagate reliability data from the asset to the system level in order to identify system critical points. However, employed asset reliability data are an approximated integral representation of the past industrywide operational experience, and they neglect the present asset health status (available, for example, from online monitoring data and diagnostic assessments) and forecasted health projection (when available from prognostic models). Asset health should be informed solely by that specific asset’s current and historical performance data and should not be an approximated integral representation of the past industrywide operational experience (as currently performed by system reliability models through Bayesian updating processes). Sensor data, diagnostic assessments, and prognostic assessments are in fact not considered in plant reliability models used to inform system engineers on the most critical assets. In addition, the propagation of quantitative health data from the asset to the system level is a challenge given the diverse nature and structure of health data elements (e.g., vibration spectra, temperature readings, expected failure time). Ideally, in a predictive maintenance context, system reliability models should support decision making by propagating available health information from the asset to the system level in order to provide a quantitative snapshot of system health and identify the most critical assets. Here, this paper is directly addressing these two goals by proposing a different approach for reliability modeling that relies on asset diagnostic and prognostic assessments, along with monitoring data to measure asset health. The propagation of health data from the asset to the system level is performed through fault tree models not in probability terms, but in terms of margin where margin is the “distance” between the present status and an undesired event (e.g., failure or unacceptable performance). Through a cause-effect lens, while classical reliability models target the effect associated with asset performance, a margin-based approach focuses on the cause of an undesired asset performance (i.e., its health). Hence, thinking of reliability in terms of margins implies decision-making based on causal reasoning. We will show how fault tree models can be solved using a margin language and how this process can effectively assist system engineers to identify the most critical assets.

97 - MATHEMATICS AND COMPUTING↗
NASA NTRS2002

Improved Multi-Axial, Temperature and Time Dependent (MATT) Failure Model

An extensive effort has recently been completed by the Space Shuttle's Reusable Solid Rocket Motor (RSRM) nozzle program to completely characterize the effects of multi-axial loading, temperature and time on the failure characteristics of three filled epoxy adhesives (TIGA 321, EA913NA, EA946). As part of this effort, a single general failure criterion was developed that accounted for these effects simultaneously. This model was named the Multi- Axial, Temperature, and Time Dependent or MATT failure criterion. Due to the intricate nature of the failure criterion, some parameters were required to be calculated using complex equations or numerical methods. This paper documents some simple but accurate modifications to the failure criterion to allow for calculations of failure conditions without complex equations or numerical techniques.

Richardson, D. E.↗
DOE OSTI2023

Profiling overstory survival trends following varying thinning and burning disturbance regimes in a mixed pine-hardwood forest in the US South

Prescribed burning as a silvicultural tool may be effective for achieving various management objectives, yet some practitioners have concerns about inadvertently increasing overstory tree mortality. Using extensive data from a long-term, ongoing study in northcentral Alabama, USA, that systematically applies a variety of thinning and prescribed burning disturbances on mixed pine-hardwood stands, we assess survival trends for different groups of trees. The primary research question is whether more frequent prescribed burns adversely affects overstory survival versus infrequent or no burns; secondary questions explore whether overstory survival trends differ based on thinning level, species group, or size class. Interest is in broad groups of trees, not individual tree survival or mortality; consequently, survival analysis methods are used, including nonparametric Kaplan-Meier (KM) techniques for examining single grouping factors, and parametric accelerated failure time models for analyzing simultaneous effects of multiple covariates. Leveraging relatively recent methodological advances, the statistical techniques are adjusted for interval censored data. KM survival curves showed that more frequent prescribed fires did not result in differing survival trends. Also, trees in unthinned stands had the lowest 14-year survival compared to thinned stands, oaks had the highest survival compared to pines and the others species group, and the smallest size class of overstory trees had the lowest survival. In conclusion, these results support managing transitional mixed pine-hardwoods using thinning and multiple prescribed fires to restore specific species composition and structure.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Battery asset management with cycle life prognosis

We report Battery Asset Management problem determines the minimum cost replacement schedules for each individual asset in a group of battery assets that operate in parallel. Battery cycle life varies under different operating conditions including temperature, depth of discharge (DOD), charge rate, etc., and a battery deteriorates due to usage, which cannot be handled by current asset management models. This paper presents a new battery asset management methodology where battery cycle life prognosis is integrated with parallel asset management to reduce lifecycle cost of the Battery Energy Storage Systems (BESS). For the battery failure time prognosis, a nonlinear physics-based battery capacity fade model is developed and incorporated in parallel asset management model to update battery capacity over time. Experiment results have shown that the developed battery asset management methodology can be conveniently used to facilitate BESS asset management decision making thereby decreasing asset lifecycle costs.

25 ENERGY STORAGE↗
DOE OSTI2021

The Preservation of Climate‐Driven Landslide Dams in Western Oregon

Abstract Bedrock landsliding, including the formation of landslide dams, is a predominant geomorphic process in steep landscapes. Clarifying the importance of hydrologic and seismic mechanisms for triggering deep‐seated landslides remains an ongoing effort, and formulation of geomorphic metrics that predict dam preservation is crucial for quantifying secondary landslide hazards. Here, we identify >200 landslide‐dammed lakes in western Oregon and utilize dendrochronology and enhanced 14 C dating (“wiggle matching”) of “ghost forests” to establish slope failure timing at 20 sites. Our dated landslide dataset reveals bedrock landsliding has been common since the last Cascadia Subduction Zone earthquake in January 1700 AD. Our study does not reveal landslides that date to 1700 AD. Rather, we observe temporal clustering of at least four landslides in the winter of 1889/1890 AD, coincident with a series of atmospheric rivers that generated one of the largest regionally recorded floods. We use topographic and field analyses to assess the relation between dam preservation and topographic characteristics of the impounded valleys. In contrast to previous studies, we do not observe systematic scaling between dam size and upstream drainage area, though dam stability indices for our sites correspond with “stable” dams elsewhere. Notably, we observe that dams are preferentially preserved at drainage areas of ∼1.5 to 13 km 2 and valley widths of ∼25 to 80 m, which may reflect the reduced downstream influence of debris flows and the accumulation of mature conifer trees upstream from landslide‐dammed lake outlets. We suggest that wood accumulation upstream of landslide dams tempers large stream discharges, thus inhibiting dam incision.

Struble, William T.↗
DOE OSTI2022

Failure Probability Constrained AC Optimal Power Flow

Despite cascading failures being the central cause of blackouts in power transmission systems, existing operational and planning decisions are made largely by ignoring their underlying cascade potential. This paper posits a reliability-aware AC Optimal Power Flow formulation that seeks to design a dispatch point which has a low operator-specified likelihood of triggering a cascade starting from any single component outage. By exploiting a recently developed analytical model of the probability of component failure, our Failure Probability-constrained ACOPF (FP-ACOPF) utilizes the system's expected first failure time as a smoothly tunable and interpretable signature of cascade risk. Here, we use techniques from bilevel optimization and numerical linear algebra to efficiently formulate and solve the FP-ACOPF using off-the-shelf solvers. Extensive simulations on the IEEE 118-bus case show that, when compared to the unconstrained and N-1 security-constrained ACOPF, our probability-constrained dispatch points can significantly lower the probabilities of long severe cascades and of large demand losses, while incurring only minor increases in total generation costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Testing in Support of the Development of EPP Plus SMT Design Method at ORNL (FY2021)

Experiments in support of the development of the integrated Elastic–Perfectly Plastic (EPP) plus Simplified Model Test (SMT) design methodology, referred to as the EPP+SMT method, continued in FY21. This report focuses on the methodology for developing the EPP+SMT creep-fatigue (CF) design curves at low strain ranges. The creep damage-based method and dissipated work-based method were used to evaluate the available CF data at the low strain range region. A set of failure criteria were determined, and a simple extrapolation method was developed to predict the CF life cycles at low strain ranges that are not accessible by experiments due to the extraordinarily long failure times at the low strain region (thousands to hundreds of thousands of years) and the inability of the test machine to control these small strain ranges due to the signal to noise issues. An experimental method with the concept of block-strain range CF testing was proposed to generate the information needed to extrapolate the CF design curves to low strain ranges. Based on this new testing approach, a preliminary EPP+SMT CF design curve was developed for Alloy 617 at 950°C with tension hold time of 100 s. The analysis in this report shows the potential of generating a set of EPP+SMT CF design curves with different hold times within a reasonable amount of time and testing effort. Based on such a progress, a hold time extrapolation procedure for low strain ranges will be developed in FY22 and critical testing will be carried out to complete the development of the EPP+SMT CF design curves for Alloy 617.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Extinction Dynamics of the Foot-and-Mouth Disease Virus Carrier State Under Natural Conditions

Foot-and-mouth disease (FMD) is one of the most economically important livestock diseases worldwide. Following the clinical phase of FMD, a large proportion of ruminants remain persistently infected for extended periods. Although extinction of this carrier state occurs continuously at the animal and population levels, studies vary widely in their estimates of the duration of persistent infection. There is a need for robust statistical models to capture the dynamics of persistent infection for the sake of guiding FMD control and trade policies. The goal of the current study was to develop and assess statistical models to describe the extinction of FMD virus (FMDV) persistent infection using data from primary longitudinal studies of naturally infected cattle and Asian buffalo in Vietnam and India. Specifically, accelerated failure time (AFT) models and generalized linear mixed models (GLMM) were developed to predict the probability of persistent infection in seropositive animals and identified carriers at the individual animal level at sequential time points after outbreaks. The primary studies were analyzed by country and combined using an individual-participant data meta-analysis approach. The models estimated similar trends in the duration of persistent infection for the study/species groups included in the analyses, however the significance of the trends differed between the models. The overall probabilities of persistent infection were similar as predicted by the AFT and GLMM models: 6 months: 99% (AFT) /80% (GLMM), 12 months: 51% (AFT) /32% (GLMM), 18 months: 6% (AFT) /5% (GLMM), 24 months: 0.8% (AFT) /0.6% (GLMM). These models utilizing diverse and robust data sets predict higher probabilities of persistence than previously published, suggesting greater endurance of carriers subsequent to an outbreak. This study demonstrates the utility of statistical models to investigate the dynamics of persistent infection and the importance of large datasets, which can be achieved by combining data from several smaller studies in meta-analyses. Results of this study enhance current knowledge of the FMDV carrier state and may inform policy decisions regarding FMDV persistent infection.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1980

Lithium battery discharge tests

The long term discharge of a variety of lithium cells was characterized and the susceptibility of the cells to chemical variation during the slow discharge was tested. A shunt resistor was set across the terminals to monitor the voltage as a function of time. Failures were identified by premature voltage drops.

Johnson, C. J.↗
NASA NTRS1985

Exponential order statistic models of software reliability growth

Failure times of a software reliabilty growth process are modeled as order statistics of independent, nonidentically distributed exponential random variables. The Jelinsky-Moranda, Goel-Okumoto, Littlewood, Musa-Okumoto Logarithmic, and Power Law models are all special cases of Exponential Order Statistic Models, but there are many additional examples also. Various characterizations, properties and examples of this class of models are developed and presented.

Miller, D. R.↗