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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 397 records · Page 22

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NASA NTRS2013

Cohesive Modeling of Transverse Cracking in Laminates with a Single Layer of Elements per Ply

This study aims to bridge the gap between classical understanding of transverse cracking in cross-ply laminates and recent computational methods for the modeling of progressive laminate failure. Specifically, the study investigates under what conditions a finite element model with cohesive X-FEM cracks can reproduce the in situ effect for the ply strength. It is shown that it is possible to do so with a single element across the thickness of the ply, provided that the interface stiffness is properly selected. The optimal value for this interface stiffness is derived with an analytical shear lag model. It is also shown that, when the appropriate statistical variation of properties has been applied, models with a single element through the thickness of a ply can predict the density of transverse matrix cracks

VanDerMeer, Frans P.↗

NASA NTRS2018

Magnetic Helicity Condensation and the Solar Cycle

Solar filaments exhibit a global chirality pattern where dextral/sinistral filaments, corresponding to negative/ positive magnetic helicity, are dominant in the northern/southern hemisphere. This pattern is opposite to the sign of magnetic helicity injected by differential rotation along east–west oriented polarity inversion lines, posing a major conundrum for solar physics. A resolution of this problem is offered by the magnetic helicity-condensation model of Antiochos. To investigate the global consequences of helicity condensation for the hemispheric chirality pattern, we apply a temporally and spatially averaged statistical approximation of helicity condensation. Realistic magnetic field configurations in both the rising and declining phases of the solar cycle are simulated. For the helicity-condensation process, we assume convective cells consisting of positive/negative vorticities in the northern/southern hemisphere that inject negative/positive helicity. The magnitude of the vorticity is varied as a free parameter, corresponding to different rates of helicity injection. To reproduce the observed percentages of dominant and minority filament chiralities, we find that a vorticity of magnitude 2.5 x 10(exp −6)/s is required. This rate, however, is insufficient to produce the observed unimodal profile of chirality with latitude. To achieve this, a vorticity of at least 5 x 10(exp −6)/s is needed. Our results place a lower limit on the small-scale helicity injection required to dominate differential rotation and reproduce the observed hemispheric pattern. Future studies should aim to establish whether the helicity injection rate due to convective flows and/or flux emergence across all latitudes of the Sun is consistent with our results.

Mackay, Duncan H.↗

DOE OSTI2020

Assessing Current and Future Infrastructure Hazards

Project Objective Execute intelligent analytics via an advanced analytical framework, to assess the current state of offshore infrastructure, evaluate infrastructure life, and identify technologies to reduce infrastructure hazards, costs, and extend infrastructure life. Approach & Results thus Far• Build comprehensive dataset• Perform data-driven analytics to evaluate infrastructure integrity 1. Remaining lifespan 2. Likelihood of future risk• Apply data-driven advanced spatial, statistical, and Machine Learning (ML) models to quantify existing infrastructure integrity• Release data and models through a smart, online platform hosted by Energy Data eXchange (EDX)

Romeo, Lucy F.↗

DOE OSTI2023

Examining Light-Induced Degradation with Combined-Accelerated Stress Testing

While further understanding is sought, the results suggest that a module can show no degradation in performance through a qualification test light soak, (IEC 61215: 2021 MQT 19.1 requirement of 10 kW minimum on one side). Yet, such cells may degrade significantly by LID under conditions within the statistical extremes of the natural environment applied in combined-accelerated stress testing (CAST).

combined-accelerated stress testing↗

DOE OSTI2025

Entropy-based feature selection for capturing impacts in Earth system models with abrupt forcing

This paper presents the development of a new entropy-based feature selection method for identifying and quantifying impacts. Here, impacts are defined as statistically significant differences in spatio-temporal fields when comparing datasets with and without an external forcing in an Earth system model. Temporal feature selection is performed by first computing the cross-fuzzy entropy to quantify similarity of patterns between two datasets and then applying changepoint detection to identify regions of statistically constant entropy. The method is used to capture temperate north surface cooling from a 9-member simulation ensemble of the Mt. Pinatubo volcanic eruption, which injected 10 Tg of SO 2 into the stratosphere. The results estimate a mean difference decrease in near surface air temperature of -0.560 K with a 99% confidence interval between -0.864 K and -0.257 K between April and November of 1992, one year following the eruption. A sensitivity analysis with decreasing SO 2 injection revealed that the impact is statistically significant at 5 Tg but not at 3 Tg. Using identified features, a dependency graph model based on a 9-day lag had significantly fewer nodes than a graph based on monthly means. Furthermore, this demonstrates our method’s ability to perform dimension reduction while still uncovering source-to-impact pathways.

Changepoint detection↗

DOE OSTI2024

Complete Development of Critical Capabilities for TRISO Fission Product Source Term Calculations and Quantify Mechanisms for Pd Penetration of SiC

Overall fission product (FP) release will be an important consideration for the licensing and deployment of advanced reactors utilizing tristructural isotropic (TRISO) fuels. This work focuses on enhancing and applying the BISON models needed to predict FP transport within TRISO particles and particle failure probability, both of which factor directly into release predictions. Specifically, this report details (1) the development of the models needed to predict palladium (Pd) conservation at the engineering scale and the application of those models to characterize Pd fluxes for input into a mechanistic multiscale model for Pd penetration; (2) the refinement of sorption mass transfer models and the development of models for trapping in porous layers, which were applied and compared to particle scans from AGR-2 to provide proof of concept for a method of particle-scale validation that may reduce uncertainties compared to compact-scale validation using data from integral effects tests; (3) the development of a failure-statistics-informed, mesh-independent methodology for applying smeared cracking, enabling further study of the localized multiphysics behaviors associated with cascading particle failure mechanisms; and (4) the preliminary characterization of those coupled multiphysics particle failure behaviors using smeared, nonretentive diffusivities to provide a baseline for future study and to guide ongoing engineering applications.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Comparative Assessment of Data-driven Process Models in Health Information Technology

Process mining for conformance analysis consists of comparing a reference process model against a data-driven process model generated via log files from information technology systems. However, in the absence of a complete reference process model, we found no suggested approaches in the literature to address the need for evaluating process conformance among different healthcare facilities to assess standardization of care. Our goal is to find similarities and dissimilarities in data-driven process models among US Veterans Health Administration (VHA) facilities that can be indicative of patient safety issues. Our hypothesis was that the analysis would not produce statistically significant differences in outcome. We present a unique implementation of conformance analysis in process mining that consists of combining process mining, process mapping and statistical metrics. We illustrate our approach by applying it to the analysis of two clinical radiology order process models generated from healthcare data provided by two similar facilities in the VHA. The comparative assessment showed that about 70% of the orders completed successfully and 30% were not completed due to policy and duplications. Our analysis found a good statistical correlation between both facilities, as the Spearman’s correlation coefficient between facilities for the frequency of cases per total hours was 0.87879, for the frequency of cases by state transition was 0.79702 and for the throughput time per state transition was 0.63582. Additional statistical analyses using the Mann-Whitney U test and the root mean square error both produced values that were not significant. The foregoing approach validated our hypothesis by demonstrating a good statistical correlation of data describing the flow of clinical radiology orders absent a credible reference model. Finding good agreement between both facilities was important in confirming that the clinical orders flow in a similar manner, suggesting standardization of care.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1993

Anomaly detection of turbopump vibration in Space Shuttle Main Engine using statistics and neural networks

The statistical and neural networks methods have been applied to investigate the feasibility in detecting anomalies in turbopump vibration of SSME. The anomalies are detected based on the amplitude of peaks of fundamental and harmonic frequencies in the power spectral density. These data are reduced to the proper format from sensor data measured by strain gauges and accelerometers. Both methods are feasible to detect the vibration anomalies. The statistical method requires sufficient data points to establish a reasonable statistical distribution data bank. This method is applicable for on-line operation. The neural networks method also needs to have enough data basis to train the neural networks. The testing procedure can be utilized at any time so long as the characteristics of components remain unchanged.

Lo, C. F.↗

NASA NTRS1985

Magnetic Field-Vector Measurements in Quiescent Prominences via the Hanle Effect: Analysis of Prominences Observed at Pic-Du-Midi and at Sacramento Peak

The Hanle effect method for magnetic field vector diagnostics has now provided results on the magnetic field strength and direction in quiescent prominences, from linear polarization measurements in the He I E sub 3 line, performed at the Pic-du-Midi and at Sacramento Peak. However, there is an inescapable ambiguity in the field vector determination: each polarization measurement provides two field vector solutions symmetrical with respect to the line-of-sight. A statistical analysis capable of solving this ambiguity was applied to the large sample of prominences observed at the Pic-du-Midi (Leroy, et al., 1984); the same method of analysis applied to the prominences observed at Sacramento Peak (Athay, et al., 1983) provides results in agreement on the most probable magnetic structure of prominences; these results are detailed. The statistical results were confirmed on favorable individual cases: for 15 prominences observed at Pic-du-Midi, the two-field vectors are pointing on the same side of the prominence, and the alpha angles are large enough with respect to the measurements and interpretation inaccuracies, so that the field polarity is derived without any ambiguity.

Bommier, V.↗

DOE OSTI2025

Expanded method for the determination of burnup in nuclear fuels using multiple neodymium isotopes

Established methods for the determination of burnup in nuclear fuels commonly rely on the measurement of 148Nd in the spent fuel in concert with known fission product yields to determine the atom percent of fissions in the fuel. This isotope of neodymium is used for various reasons, including chemical and radioactive stability, ease of measurement, and low rates of formation and destruction due to neutron flux apart from fission. However, careful calculation of effective cumulative fission yields and correction factors for (n,γ) capture reactions allows for additional stable and long-lived isotopes of neodymium to be used to provide additional independent measurements of burnup, reducing statistical uncertainty. This method was developed and successfully applied to measure the burnup of compacts from the Advanced Gas Reactor (AGR) Fuel Development and Qualification Program. The mean burnup measured using 143Nd, 145Nd, 146Nd, 148Nd, and 150Nd was statistically observed to be the same as that measured using 148Nd alone, but the statistical uncertainty in the measurement was reduced by a factor of 2, providing a tighter confidence interval in the final results.

Helmreich, Grant [ORNL] (ORCID:0000000330464394)↗

NASA NTRS1986

Numerical study of sink-flow boundary layers

Direct numerical simulations of sink-flow boundary layers, with acceleration parameters K between 1.5 x 10 to the -6th and 3.0 x 10 to the -6th, are presented. The three-dimensional, time-dependent Navier-Stokes equations are solved numerically, using a spectral method, with about one million degrees of freedom. The flow is assumed to be statistically steady, and self-similar. A multiple-scale approximation and periodic conditions are applied to the fluctuations. The turbulence is studied using instantaneous and statistical results. Good agreement with the experiments of Jones and Launder (1972) is observed. The two effects of the favorable pressure gradient are to extend the logarithmic layer, and to alter the energy balance of the turbulence near the edge of the boundary layer. At low Reynolds number the logarithmic layer is shortened and slightly displaced, but wall-layer streaks are present even at the lowest values of R(theta) for which turbulence can be sustained. Large quiescent patches appear in the flow. Relaminarization occurs at K = 3.0 x 10 to the -6th, corresponding to a Reynolds number R(theta) of about 330.

Spalart, Philippe R.↗

NASA NTRS1986

Numerical simulation of boundary layers. Part 3: Turbulence and relaminarization in sink flows

Direct numerical simulations of sink-flow boundary layers, with acceleration parameters K between 1.5 and 3.0 x 10 to the -6 power, are presented. The three-dimensional, time-dependent Navier-Stokes equations are solved numerically using a spectral method, with about 10 to the -6 degrees of freedom. The flow is assumed to be statistically steady, and self-similar. A multiple-scale approximation and periodic conditions are applied to the fluctuations. The turbulence is studied using instantaneous and statistical results. Good agreement with the experiments of Jones and Launder is observed. Two effects of the favorable pressure gradient are to extend the logarithmic layer, and to alter the energy balance of the turbulence near the edge of the boundary layer. At very low Reynolds number the logarithmic layer is shortened and slightly displaced, but wall-layer streaks are present even at the lowest values of the Reynolds number for which turbulence can be sustained. Large quiescent patches appear in the flow. Relaminarization occurs at K = 3.0 x 10 to the -6 power, corresponding to a Reynolds number, based on momentum thickness, of about 330.

Spalart, Philippe R.↗

NASA NTRS1982

A failure model for sealed nickel-cadmium batteries

A model has been developed to describe failure in electrochemical batteries. The model is based on the concept of the existence and subsequent growth of flaws which ultimately lead to battery failure. This model provides, in a natural way, for the statistical variability of lifetime data. The model as applied to the Crane data indicates that when the effects of temperature and depth of discharge are taken into account, the observed variability in lifetime data is due almost entirely to statistical variability inherent in the battery itself.

Fedors, R. F.↗

DOE OSTI2022

Deep Learning for Subgrid‐Scale Turbulence Modeling in Large‐Eddy Simulations of the Convective Atmospheric Boundary Layer

Abstract In large‐eddy simulations, subgrid‐scale (SGS) processes are parameterized as a function of filtered grid‐scale variables. First‐order, algebraic SGS models are based on the eddy‐viscosity assumption, which does not always hold for turbulence. Here we apply supervised deep neural networks (DNNs) to learn SGS stresses from a set of neighboring coarse‐grained velocity from direct numerical simulations of the convective boundary layer at friction Reynolds numbers Re τ up to 1243 without invoking the eddy‐viscosity assumption. The DNN model was found to produce higher correlation between SGS stresses compared to the Smagorinsky model and the Smagorinsky‐Bardina mixed model in the surface and mixed layers and can be applied to different grid resolutions and various stability conditions ranging from near neutral to very unstable. The DNN model can capture key statistics of turbulence in a posteriori (online) tests when applied to large‐eddy simulations of the atmospheric boundary layer.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Non-Intrusive Appliance Identification with Appliance-Specific Networks

The problem of noninstrusive load monitoring (NILM) is usually formulated as a single-channel blind source separation task, whose successful solution enable fast and convenient load identification and energy disaggregation. When applied at test time, NILM algorithms aim to identify the operating characteristics of individual appliances from an aggregate power measurement of the entire house. Recent advances in deep learning gave rise to many methods that mostly focus on learning a direct mapping from aggregate measurement to individual appliance power. However, these methods are not only computationally expensive, but they often suffer from overfitting and do not generalize very well. In this article, we propose a novel NILM method that leverages advances in statistical learning that have not been properly applied in this domain before. The proposed method consists of three stages: first, a Bayesian nonparametric learning-based approach for appliance state extraction; second, synthetic minority oversampling technique for data augmentation and mitigating the heavy imbalance in switching events; and third, appliance-specific lightweight long short-term memory networks for status classification for each appliance. Here, we adopt a “differential” input (the difference before and after the switching event) to reduce the complexity of network training and make the proposed method robust to multiappliance switching events. Experiments are conducted to demonstrate the effectiveness of the proposed method, achieving superior performance when compared to recent methods. An ablation study is conducted to demonstrate the effectiveness of each module of our method. Finally, we investigate the quality of generated synthetic samples.

42 ENGINEERING↗

NASA NTRS1991

Evaluation of some scale effects in the response and failure of composite beams

The feasibility of using scale model testing for predicting full-scale behavior of composite beams loaded in tension and flexure was investigated. Classical laws of similitude were applied to fabricate and test replica model beams to identify scaling effects in the load response, strength, and mode of failure. Experiments were conducted using graphite-epoxy composite beams having different laminate stacking sequences and a range of scaled sizes. Results indicated that the elastic response of scaled composite beams was independent of specimen size. However, a significant scale effect in strength was observed. In addition, a transition in failure mode was observed among scaled beams of certain laminate stacking sequences. Weibull statistical and fracture mechanics based models were applied to predict the strength scale effect since standard failure criteria cannot account for the influence of absolute specimen size in failure.

Jackson, Karen E.↗

DOE OSTI2022

A coupled vacancy diffusion-dislocation dynamics model for the climb-glide motion of jogged screw dislocations

Here, we develop a novel model to study the climb/glide motion of jogged screw dislocations within the discrete dislocation dynamics (DDD) framework. We present results for the dependence of the climb velocity on the applied stress and on the jog size and distribution statistics. We show that the model predictions are consistent with experimental data in both γ-TiAl and Zircaloy-4. The ranges of the applied stress and jog spacing that determine the dominance of one of three dislocation mechanisms are identified. These are the jog dragging, dipole dragging, and dipole bypass mechanisms, respectively. The overall dislocation motion in the jog dragging regime is composed of glide of screw segments and climb of jogs, controlling the plastic strain and the creep rate, respectively. Based on current simulations and on a detailed examination of the predicted jog heights compared to experiments, we advance the hypothesis that a combination of jog dragging and dipole bypass mechanisms is necessary to reproduce the high creep rate observed in some experiments.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Optimal Frequency-domain Analysis for Spacecraft Time Series: Introducing the Missing-data Multitaper Power Spectrum Estimator

While the Lomb–Scargle periodogram is foundational to astronomy, it has a significant shortcoming: the variance in the estimated power spectrum does not decrease as more data are acquired. Statisticians have a 60 yr history of developing variance-suppressing power spectrum estimators, but most are not used in astronomy because they are formulated for time series with uniform observing cadence and without seasonal or daily gaps. Here we demonstrate how to apply the missing-data multitaper power spectrum estimator to spacecraft data with uniform time intervals between observations but missing data during thruster fires or momentum dumps. The F-test for harmonic components may be applied to multitaper power spectrum estimates to identify statistically significant oscillations that would not rise above a white noise–based false alarm probability. Multitapering improves the dynamic range of the power spectrum estimate and suppresses spectral window artifacts. We show that the multitaper–F-test combination applied to Kepler observations of KIC 6102338 detects differential rotation without requiring iterative sinusoid fitting and subtraction. Significant signals reside at harmonics of both fundamental rotation frequencies and suggest an antisolar rotation profile. Next we use the missing-data multitaper power spectrum estimator to identify the oscillation modes responsible for the complex "scallop-shell" shape of the K2 light curve of EPIC 203354381. We argue that multitaper power spectrum estimators should be used for all time series with regular observing cadence.

79 ASTRONOMY AND ASTROPHYSICS↗