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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Stability of Kuramoto networks subject to large and small fluctuations from heterogeneous and spatially correlated noise

Oscillatory networks subjected to noise are broadly used to model physical and technological systems. Due to their nonlinear coupling, such networks typically have multiple stable and unstable states that a network might visit due to noise. In this article, we focus on the assessment of fluctuations resulting from heterogeneous and spatially correlated noise inputs on Kuramoto model networks. We evaluate the typical, small fluctuations near synchronized states and connect the network variance to the overlap between stable modes of synchronization and the input noise covariance. Going beyond small to large fluctuations, we introduce the indicator mode approximation that projects the dynamics onto a single amplitude dimension. Such an approximation allows for estimating rates of fluctuations to saddle instabilities, resulting in phase slips between connected oscillators. Statistics for both regimes are quantified in terms of effective noise amplitudes that are compared and contrasted for several noise models. In conclusion, bridging the gap between small and large fluctuations, we show that a larger network variance does not necessarily lead to higher rates of large fluctuations.

42 ENGINEERING↗
DOE OSTI2021

The PENELOPE Physics Models and Transport Mechanics. Implementation into Geant4

A translation of the PENELOPE physics subroutines to C++, designed as an extension of the GEANT4 toolkit, is presented. The Fortran code system PENELOPE performs Monte Carlo simulation of coupled electron-photon transport in arbitrary materials for a wide energy range, nominally from 50 eV up to 1 GeV. PENELOPE implements the most reliable interaction models that are currently available, limited only by the required generality of the code. In addition, the transport of electrons and positrons is simulated by means of an elaborate class II scheme in which hard interactions (involving deflection angles or energy transfers larger than pre-defined cutoffs) are simulated from the associated restricted differential cross sections. After a brief description of the interaction models adopted for photons and electrons/positrons, we describe the details of the class-II algorithm used for tracking electrons and positrons. The C++ classes are adapted to the specific code structure of GEANT4. They provide a complete description of the interactions and transport mechanics of electrons/positrons and photons in arbitrary materials, which can be activated from the G4ProcessManager to produce simulation results equivalent to those from the original PENELOPE programs. The combined code, named PENG4, benefits from the multi-threading capabilities and advanced geometry and statistical tools of GEANT4.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRSDate not supplied

Hail Storm Risk Assessment Using Space-Borne Remote Sensing Observations and Reanalyses

Much of the world is impacted by severe thunderstorms, but whether they become disasters depends upon resilience--our capacity to prepare, mitigate, respond, and recover. Hail is the costliest severe weather hazard for the insurance industry, generating ~70% of severe convective storm losses due to damage to assets such as homes, businesses, agriculture, and infrastructure. Most insurance companies do not reserve enough capital to cover catastrophes, so they acquire reinsurance. The reinsurance industry uses catastrophe models (CatModels) to statistically estimate risk to an insurer’s portfolio. Hail CatModels are developed with climatologies that define hailstorm frequency and severity. Hail-prone areas can be defined using hail reports from trained spotters, the media, and the general public. Extremely severe hail (2+ inch diameter) occurs nearly every day across the world. Weather radars can detect hail because hailstones strongly reflect microwave signals that they emit. However, hail climatologies are difficult to derive because hail covers small areas and there are neither hail reporting mechanisms (e.g. website or mobile app) nor radar networks in most places outside the US and Europe. This lack of ground truth on severe hail puts society and economies at risk. Hail is generated within storms by strong updrafts. These updrafts exhibit unique signatures in NASA and other agency satellite observations, offering new opportunities for hailstorm analysis. Geostationary (GEO) visible and infrared imagery has been collected for ~15-25 years across the world (region dependent) and methods have been developed at NASA Langley Research Center (LaRC) to detect hailstorm updrafts using GEO imagery. Climatological GEO updraft data has been used by Willis Towers Watson (WTW), a leader in catastrophe risk assessment for the insurance industry, and Karlsruhe Institute of Technology to develop CatModels over Europe and Australia. Hail can also be inferred with passive microwave imagery collected by low-Earth-orbiting sensors such as the GPM GMI, TRMM TMI, AMSR-E, AMSR-2, SSM/I, and SSMIS over the last 20+ years using methods developed at the Marshall Space Flight Center (MSFC). Hailstorms generate enhanced lightning flash rates that can be tracked using new GOES-R series GEO Lightning Mapping (GLM) imagery. Atmospheric reanalyses can be used to define favorable hailstorm environments for combination with the satellite-based storm detections. This presentation will describe a framework for developing continental to global hail climatologies and CatModels based on NASA satellite data and capabilities. This is a collaboration between LaRC and MSFC, WTW, and partners in Brazil, Argentina, and South Africa. This project seeks to mitigate hail disasters by aiding development of new satellite-based severe storm nowcasting tools by regional partners and developing climatologies to improve societal understanding of hail frequency. GEOO visible and infrared metrics of storm intensity, environmental conditions based on reanalyses, spotter hail reports and radar MESH observations are intercompared to quantify the detectability of hailstorms, and our ability to discriminate hailstorms from other severe storms. We are also maturing methods using land surface imaging satellite data (e.g. MODIS, Landsat, Sentinel 1 and 2) to identify hail damage to agriculture. Work with WTW will improve socioeconomic resilience through development of new CatModels. Southern Brazil, Uruguay, Paraguay, and Argentina feature some of the most intense thunderstorms on Earth. South America and South Africa are developing insurance markets of interest to WTW clients, and is similar to other regions routinely impacted by hail that do not have comprehensive hail reporting or radars to assess hailstorm frequency. Project datasets will be made available via online GIS-enabled tools developed at the LaRC Atmospheric Science Data Center (ASDC) which will visualize data and provide it in multiple formats for use in a wide range of open source and commercial tools.

Kristopher Michael Bedka↗
NASA NTRS1994

An analytical and experimental investigation of the response of the curved, composite frame/skin specimens

Six-foot diameter, semicircular graphite/epoxy specimens representative of generic aircraft frames were loaded quasi-statistically to determine their load response and failure mechanisms for large deflections that occur in airplanes crashes. These frame/skin specimens consisted of a cylindrical skin section co-cured with a semicircular I-frame. The skin provided the necessary lateral stiffness to keep deformations in the plane of the frame in order to realistically represent deformations as they occur in actual fuselage structures. Various frame laminate stacking sequences and geometries were evaluated by statically loading the specimen until multiple failures occurred. Two analytical methods were compared for modeling the frame/skin specimens: a two-dimensional shell finite element analysis and a one-dimensional, closed-form, curved beam solution derived using an energy method. Flange effectivities were included in the beam analysis to account for the curling phenomenon that occurs in thin flanges of curved beams. Good correlation was obtained between experimental results and the analytical predictions of the linear response of the frames prior to the initial failure. The specimens were found to be useful for evaluating composite frame designs.

Moas, Eduardo↗
NASA NTRS2005

Chemical Loss of Polar Ozone: Present Understanding and Remaining Uncertainties

Not long after the discovery of the Antarctic ozone hole, it was established that halogen compounds, supplied to the atmosphere mainly by anthropogenic activities, are the primary driver of polar ozone loss. We will briefly review the chemical mechanisms that cause polar ozone loss and the early evidence showing the key role played by anthropogenic halogens. Recently, stratospheric halogen loading has leveled off, due to adherence to the Montreal Protocol and its amendments that has essentially banned CFCs (chlorofluorocarbons) and other halocarbons. We will describe recent reports of the first stage of recovery of the Antarctic ozone hole (e.g., a statistically significant slowing of the downward trend), associated with the leveling off of stratospheric halogens. Despite this degree of understanding, we will discuss the tendency of photochemical models to underestimate the observed rate of polar ozone loss and a hypothesis that has recently been put forth that might resolve this discrepancy. Finally, we will briefly discuss chemical loss of Arctic ozone, which

climate change↗
NASA NTRS2010

The Prediction Properties of Inverse and Reverse Regression for the Simple Linear Calibration Problem

The calibration of measurement systems is a fundamental but under-studied problem within industrial statistics. The origins of this problem go back to basic chemical analysis based on NIST standards. In today's world these issues extend to mechanical, electrical, and materials engineering. Often, these new scenarios do not provide "gold standards" such as the standard weights provided by NIST. This paper considers the classic "forward regression followed by inverse regression" approach. In this approach the initial experiment treats the "standards" as the regressor and the observed values as the response to calibrate the instrument. The analyst then must invert the resulting regression model in order to use the instrument to make actual measurements in practice. This paper compares this classical approach to "reverse regression," which treats the standards as the response and the observed measurements as the regressor in the calibration experiment. Such an approach is intuitively appealing because it avoids the need for the inverse regression. However, it also violates some of the basic regression assumptions.

Parker, Peter A.↗
NASA NTRS2015

Hybrid Reynolds-Averaged/Large Eddy Simulation of a Cavity Flameholder; Assessment of Modeling Sensitivities

Steady-state and scale-resolving simulations have been performed for flow in and around a model scramjet combustor flameholder. The cases simulated corresponded to those used to examine this flowfield experimentally using particle image velocimetry. A variety of turbulence models were used for the steady-state Reynolds-averaged simulations which included both linear and non-linear eddy viscosity models. The scale-resolving simulations used a hybrid Reynolds-averaged / large eddy simulation strategy that is designed to be a large eddy simulation everywhere except in the inner portion (log layer and below) of the boundary layer. Hence, this formulation can be regarded as a wall-modeled large eddy simulation. This effort was undertaken to formally assess the performance of the hybrid Reynolds-averaged / large eddy simulation modeling approach in a flowfield of interest to the scramjet research community. The numerical errors were quantified for both the steady-state and scale-resolving simulations prior to making any claims of predictive accuracy relative to the measurements. The steady-state Reynolds-averaged results showed a high degree of variability when comparing the predictions obtained from each turbulence model, with the non-linear eddy viscosity model (an explicit algebraic stress model) providing the most accurate prediction of the measured values. The hybrid Reynolds-averaged/large eddy simulation results were carefully scrutinized to ensure that even the coarsest grid had an acceptable level of resolution for large eddy simulation, and that the time-averaged statistics were acceptably accurate. The autocorrelation and its Fourier transform were the primary tools used for this assessment. The statistics extracted from the hybrid simulation strategy proved to be more accurate than the Reynolds-averaged results obtained using the linear eddy viscosity models. However, there was no predictive improvement noted over the results obtained from the explicit Reynolds stress model. Fortunately, the numerical error assessment at most of the axial stations used to compare with measurements clearly indicated that the scale-resolving simulations were improving (i.e. approaching the measured values) as the grid was refined. Hence, unlike a Reynolds-averaged simulation, the hybrid approach provides a mechanism to the end-user for reducing model-form errors.

Baurle, R. A.↗
DOE OSTI2021

Identification of Life Models for Li-Ion Batteries Using Penalized Regression and Bilevel Optimization

Reduced-order physics-based life models are extremely useful for rapidly predicting battery state-of-health and for simulating battery lifetime in arbitrary aging conditions. However, identification of well-parameterized models is difficult. This is because, for maximum usefulness in predicting lifetime under a variety of conditions, aging test data exhibits many degradation mechanisms, which all need to be accurately modeled. However, because aging tests are time-consuming and expensive, especially for large-format batteries, a minimum of tests are conducted while probing many stress factors. Building a well-parameterized model is then very challenging: an under-parameterized model will neglect critical degradation modes, and an over-parameterized model will extrapolate poorly to new testing conditions. To complicate this matter, the functional form of the model for any individual degradation rate can be very difficult to identify. In this work, the statistical tools of penalized regression and bilevel optimization are used to help identify both the functional forms of and optimize the parameters of reduced-order life models, accelerating identification of robust models. Model robustness is demonstrated through traditional statistics methods of cross-validation and sensitivity analysis, uncertainty quantification through bootstrap resampling and Monte-Carlo simulation, and simulation of real-world use cases.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Nonlinear proper orthogonal decomposition for convection-dominated flows

Autoencoder techniques find increasingly common use in reduced order modeling as a means to create a latent space. This reduced order representation offers a modular data-driven modeling approach for nonlinear dynamical systems when integrated with a time series predictive model. In this Letter, we put forth a nonlinear proper orthogonal decomposition (POD) framework, which is an end-to-end Galerkin-free model combining autoencoders with long short-term memory networks for dynamics. By eliminating the projection error due to the truncation of Galerkin models, a key enabler of the proposed nonintrusive approach is the kinematic construction of a nonlinear mapping between the full-rank expansion of the POD coefficients and the latent space where the dynamics evolve. We test our framework for model reduction of a convection-dominated system, which is generally challenging for reduced order models. Our approach not only improves the accuracy, but also significantly reduces the computational cost of training and testing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1997

Ultrasonic wave velocity measurement in small polymeric and cortical bone specimens

A system was refined for the determination of the bulk ultrasonic wave propagation velocity in small cortical bone specimens. Longitudinal and shear wave propagations were measured using ceramic, piezoelectric 20 and 5 MHz transducers, respectively. Results of the pulse transmission technique were refined via the measurement of the system delay time. The precision and accuracy of the system were quantified using small specimens of polyoxymethylene, polystyrene-butadiene, and high-density polyethylene. These polymeric materials had known acoustic properties, similarity of propagation velocities to cortical bone, and minimal sample inhomogeneity. Dependence of longitudinal and transverse specimen dimensions upon propagation times was quantified. To confirm the consistency of longitudinal wave propagation in small cortical bone specimens (< 1.0 mm), cut-down specimens were prepared from a normal rat femur. Finally, cortical samples were prepared from each of ten normal rat femora, and Young's moduli (Eii), shear moduli (Gij), and Poisson ratios (Vij) were measured. For all specimens (bone, polyoxymethylene, polystyrene-butadiene, and high-density polyethylene), strong linear correlations (R2 > 0.997) were maintained between propagation time and distance throughout the size ranges down to less than 0.4 mm. Results for polyoxymethylene, polystyrene-butadiene, and high-density polyethylene were accurate to within 5 percent of reported literature values. Measurement repeatability (precision) improved with an increase in the wave transmission distance (propagating dimension). No statistically significant effect due to the transverse dimension was detected.

Non-NASA Center↗
NASA NTRS1978

The X-ray source Serpens X-1 - Ariel 5 observations and discussion of models for the spectrum and time variability

Experimental data from Ariel 5 on the spectral shape and time variability of Ser X-1 are presented, and possible explanations for the observations are discussed in terms of current theoretical suggestions for source emission. The observations are summarized in the form of a light curve for 3-7.6-keV photons. The data are fitted with a power law of index -2.3, which yields a hydrogen column density of (1.1 + or - 0.4) x 10 to the 22nd power atoms/sq cm. No persistent periodicity of amplitude greater than 5% of the steady flux is found, but evidence of statistically significant burst activity is obtained. Various emission mechanisms are considered for the time-averaged spectrum and the X-ray bursts. It is suggested that the inverse Compton mechanism is a likely cause for the emission from this source and that the source is radiating near the Eddington limit.

Coe, M. J.↗
DOE OSTI2025

A Standardized Analysis Process Using Digital Image Correlation to Calculate In Situ Cladding Strain from Modified Burst Tests for Fuel Performance Code Validation

Historical data collection on nuclear fuel cladding materials has focused on generating a statistically significant amount of data to assess the material and its failure behavior. Furthermore, data generated to support material model and failure criteria development were previously posttest evaluations, so a large number of tests was required to gain new understanding. A way to expedite this process is to develop techniques capable of generating large, high-fidelity data sets from a single test with lower uncertainty or quantified uncertainty. One such example of this approach is Oak Ridge National Laboratory’s use of modified burst tests (MBTs) to analyze the mechanical behavior and failure conditions of cladding during a simulated reactivity-initiated accident (RIA). Each test incorporates digital image correlation (DIC) analysis techniques that are used to assess the accumulated strain in situ, as well as eventual cladding failure. This work has been fruitful in defining strain-to-failure conditions for materials like silicon carbide (SiC) fiber–reinforced/SiC matrix composite tubes (SiC/SiC), iron-chromium-aluminum (FeCrAl) alloy tubes, and chromium-coated Zircaloy-4 tubes. However, there are numerous DIC software available, including open-source and proprietary software. The different DIC software use various algorithms to process images and calculate displacement values. Using these different software and algorithms can lead to varying results, and perhaps larger-than-expected uncertainties. In the present study, previously published MBT data encompassing a variety of test conditions were reanalyzed with two different DIC software to assess the variance in the calculated strain results. The data consisted of SiC/SiC, FeCrAl, and chromium-coated Zircaloy-4 tubes. Plots of the calculated strains during the transient revealed good agreement between the two DIC software. The average root-mean-square errors between the two software was 0.20% strain, which is slightly larger than a previously reported error value for these tests. In conclusion, this variance in results is low enough that this analysis method can be used for code validation.

Reactivity-initiated accident↗
DOE OSTI2025

Time-domain theory of transient heat conduction in the local limit

Ultrafast and nanoscale heat conduction demands a unified theoretical framework that rigorously bridges macroscopic transport equations with microscopic material properties derived from statistical physics. Existing empirical generalizations of Fourier's law often lack a solid microscopic foundation, failing to connect observed non-Fourier behavior with underlying atomic-scale mechanisms. In this work, we present a time-domain theory of transient heat conduction rooted in Zwanzig's statistical theory of irreversible processes. Central to this framework is the time-domain transport function $\overleftrightarrow{𝑍}$⁡(𝑡) defined through equilibrium time-correlation functions of heat fluxes. This function generalizes the conventional concept of steady-state thermal conductivity, governing the transition of conduction dynamics from onset second sound type wave propagation at finite speeds to diffusion-dominated behavior across broad temporal and spatial scales. Unlike phonon hydrodynamic models that rely on mesoscopic constructs such as phonon drift velocity, our approach provides a quantitative and microscopic description of intrinsic memory effects in transient heat fluxes and applies universally to bulk materials at any temperature or length scale. By integrating atomistic-scale first-principles calculations with continuum-level macroscopic equations, this framework offers a robust foundation for numerical simulations of transient temperature fields. Furthermore, it facilitates the interpretation and design of transient thermal grating experiments using nanometer-scale heat sources and ultrafast laser systems in the extreme ultraviolet and x-ray wavelength ranges, advancing our understanding of heat dissipation dynamics.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

The advanced characterization, post-irradiation examination, and materials informatics for the development of ultra high-burnup annular U-10Zr metallic fuel

U-Zr metallic fuel is a promising fuel candidate for Gen Ⅳ fast spectrum reactors. Previous experimental irradiation campaigns showed that the sodium thermal bonded U-10Zr fuel design can achieve a burnup of 10% fissions per initial heavy metal atom (FIMA). Advanced metallic fuel designs are pushing the burnup limit to 20% or even 30% FIMA. To achieve the higher burnup and eliminate the pyrophoric sodium, a prototypical annular fuel has been designed, fabricated, clad with HT-9 in the Materials and Fuels Complex, and irradiated in the Advanced Test Reactors of Idaho National Laboratory (INL) to a peak burnup of 3.3% FIMA. During irradiation, the mechanical contact between fuel and cladding acts as a thermal bond. The irradiation lasted for 132 days in the reactor. Recently, the archived fresh and irradiated fuel samples were characterized using advanced characterization capabilities in the Irradiated Materials Characterization Laboratory (IMCL) of INL. This article summarizes the results of advanced characterization and computer vision-based materials informatics to reveal the irradiation effects on U-Zr metallic fuel. Future work will focus on further implementation of advanced characterization and statistical data mining to improve the fidelity of fuel performance modeling and support U-Zr metallic fuel qualification for fast spectrum reactors.

Yao, Tiankai↗
NASA NTRS1994

Applications of squeezed states: Bogoliubov transformations and wavelets to the statistical mechanics of water and its bubbles

The squeezed states or Bogoliubov transformations and wavelets are applied to two problems in nonrelativistic statistical mechanics: the dielectric response of liquid water, epsilon(q-vector,w), and the bubble formation in water during insonnification. The wavelets are special phase-space windows which cover the domain and range of L(exp 1) intersection of L(exp 2) of classical causal, finite energy solutions. The multiresolution of discrete wavelets in phase space gives a decomposition into regions of time and scales of frequency thereby allowing the renormalization group to be applied to new systems in addition to the tired 'usual suspects' of the Ising models and lattice gasses. The Bogoliubov transformation: squeeze transformation is applied to the dipolaron collective mode in water and to the gas produced by the explosive cavitation process in bubble formation.

Defacio, Brian↗
DOE OSTI2022

Uptake of N 2 O 5 by aqueous aerosol unveiled using chemically accurate many-body potentials

The reactive uptake of N 2 O 5 to aqueous aerosol is a major loss channel for nitrogen oxides in the troposphere. Despite its importance, a quantitative picture of the uptake mechanism is missing. Here we use molecular dynamics simulations with a data-driven many-body model of coupled-cluster accuracy to quantify thermodynamics and kinetics of solvation and adsorption of N 2 O 5 in water. The free energy profile highlights that N 2 O 5 is selectively adsorbed to the liquid–vapor interface and weakly solvated. Accommodation into bulk water occurs slowly, competing with evaporation upon adsorption from gas phase. Leveraging the quantitative accuracy of the model, we parameterize and solve a reaction–diffusion equation to determine hydrolysis rates consistent with experimental observations. We find a short reaction–diffusion length, indicating that the uptake is dominated by interfacial features. The parameters deduced here, including solubility, accommodation coefficient, and hydrolysis rate, afford a foundation for which to consider the reactive loss of N 2 O 5 in more complex solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2019

North American Extreme Precipitation Events and Related Large-Scale Meteorological Patterns: a Review of Statistical Methods, Dynamics, Modeling, and Trends

This paper surveys the current state of knowledge regarding Large-Scale Meteorological Patterns (LSMPs) associated with short-duration (less than one week) extreme precipitation events over North America. In contrast to teleconnections, which are typically defined based on the characteristic spatial variations of a meteorological field or on the remote circulation response to a known forcing, LSMPs are defined relative to the occurrence of a specific phenomenon—here, extreme precipitation—and with an emphasis on the synoptic scales that have a primary influence in individual events, have medium-range weather predictability, and are well-resolved in both weather and climate models. For the LSMP relationship with extreme precipitation, we consider the previous literature with respect to definitions and data, dynamical mechanisms, model representation, and climate change trends. There is considerable uncertainty in identifying extremes based on existing observational precipitation data and some limitations in analyzing the associated LSMPs in reanalysis data. Many different definitions of “extreme” are in use, making it difficult to directly compare different studies. Dynamically, several types of meteorological systems—extratropical cyclones, tropical cyclones, mesoscale convective systems, and mesohighs—and several mechanisms—fronts, atmospheric rivers, and orographic ascent—have been shown to be important aspects of extreme precipitation LSMPs. The extreme precipitation is often realized through mesoscale processes organized, enhanced, or triggered by the LSMP. Understanding of model representation, trends, and projections for LSMPs is at an early stage, although some 4 promising analysis techniques have been identified and the LSMP perspective is useful for evaluating model dynamics.

Mathew Barlow↗
DOE OSTI2025

Federated Learning for Efficient Condition Monitoring and Anomaly Detection in Industrial Cyber-Physical Systems

Detecting and localizing anomalies in cyber-physical systems (CPS) has become increasingly challenging as systems grow in complexity, particularly due to varying sensor reliability and node failures in distributed environments. While federated learning (FL) offers a foundation for distributed model training, existing approaches lack mechanisms to handle these CPS-specific challenges. This paper presents an enhanced FL framework that introduces three key innovations: adaptive model aggregation based on sensor reliability, dynamic node selection for resource optimization, and Weibull-based checkpointing for fault tolerance. Our framework enables reliable condition monitoring while addressing the computational and reliability challenges of industrial CPS deployments. Experiments on NASA Bearing and Hydraulic System Datasets demonstrate superior performance over state-of-the-art FL methods, achieving 99.5% AUC-ROC in anomaly detection and maintaining accuracy under node failures. Statistical validation using Mann-Whitney (U) test confirms significant improvements (p < 0.05) in both detection accuracy and computational efficiency across diverse operational scenarios.1

Marfo, William [University of Texas at El Paso,Dep↗