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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 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Validation and parameterization of a novel physics-constrained neural dynamics model applied to turbulent fluid flow

We report, in fluid physics, data-driven models to enhance or accelerate time to solution are becoming increasingly popular for many application domains, such as alternatives to turbulence closures, system surrogates, or for new physics discovery. In the context of reduced order models of high-dimensional time-dependent fluid systems, machine learning methods grant the benefit of automated learning from data, but the burden of a model lies on its reduced-order representation of both the fluid state and physical dynamics. In this work, we build a physics-constrained, data-driven reduced order model for Navier–Stokes equations to approximate spatiotemporal fluid dynamics in the canonical case of isotropic turbulence in a triply periodic box. The model design choices mimic numerical and physical constraints by, for example, implicitly enforcing the incompressibility constraint and utilizing continuous neural ordinary differential equations for tracking the evolution of the governing differential equation. We demonstrate this technique on a three-dimensional, moderate Reynolds number turbulent fluid flow. In assessing the statistical quality and characteristics of the machine-learned model through rigorous diagnostic tests, we find that our model is capable of reconstructing the dynamics of the flow over large integral timescales, favoring accuracy at the larger length scales. More significantly, comprehensive diagnostics suggest that physically interpretable model parameters, corresponding to the representations of the fluid state and dynamics, have attributable and quantifiable impact on the quality of the model predictions and computational complexity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Flat-histogram extrapolation as a useful tool in the age of big data

In this work, we review recent work by the authors to revisit the concept of extrapolating thermodynamic properties of classical systems using statistical mechanical principles. Specifically, we discuss how the combination of these principles with biased sampling techniques enables the prediction of free energy landscapes and other detailed information, such as structural properties, of the system in question. Remarkably accurate estimates of physical properties across a broad range of conditions have been achieved using this approach, greatly reducing the number of simulations needed to explore a given system's behaviour. While approximate, these extrapolations significantly amplify the amount of reasonably accurate information that can be extracted from simulations enabling a small set of them to feed data-intensive regression algorithms such as neural networks. Thus, this extrapolation methodology represents a useful tool for performing tasks such as high-throughput screening of physical properties, optimising force field parameters, exploring equilibrium phase behaviour, and enabling theory-guided data science for these systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Catalog-level blinding on the bispectrum for DESI-like galaxy surveys

We evaluate the performance of the catalog-level blind analysis technique (blinding) presented in Brieden et al. (2020) in the context of a fixed template power spectrum and bispectrum analysis. This blinding scheme, which is tailored for galaxy redshift surveys similar to the Dark Energy Spectroscopic Instrument (DESI), has two components: the so-called “AP blinding” (concerning the dilation parameters α$_{∥}$, α$_{⊥}$) and “RSD blinding” (redshift space distortions, affecting the growth rate parameter f). Through extensive testing, including checks for the RSD part in cubic boxes, the impact of AP blinding on mocks with realistic survey sky coverage, and the implementation of a full AP+RSD blinding pipeline, our analysis demonstrates the effectiveness of the technique in preserving the integrity of cosmological parameter estimation when the analysis includes the bispectrum statistic. We emphasize the critical role of sophisticated — and difficult to accidentally unblind — blinding methods in precision cosmology.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Verification of Electromagnetic Physics Models for Parallel Computing Architectures in the GeantV Project

An intensive R&D and programming effort is required to accomplish new challenges posed by future experimental high-energy particle physics (HEP) programs. The GeantV project aims to narrow the gap between the performance of the existing HEP detector simulation software and the ideal performance achievable, exploiting latest advances in computing technology. The project has developed a particle detector simulation prototype capable of transporting in parallel particles in complex geometries exploiting instruction level microparallelism (SIMD and SIMT), task-level parallelism (multithreading) and high-level parallelism (MPI), leveraging both the multi-core and the many-core opportunities. We present preliminary verification results concerning the electromagnetic (EM) physics models developed for parallel computing architectures within the GeantV project. In order to exploit the potential of vectorization and accelerators and to make the physics model effectively parallelizable, advanced sampling techniques have been implemented and tested. In this paper we introduce a set of automated statistical tests in order to verify the vectorized models by checking their consistency with the corresponding Geant4 models and to validate them against experimental data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

InClass nets: independent classifier networks for nonparametric estimation of conditional independence mixture models and unsupervised classification

Abstract Conditional independence mixture models (CIMMs) are an important class of statistical models used in many fields of science. We introduce a novel unsupervised machine learning technique called the independent classifier networks (InClass nets) technique for the nonparameteric estimation of CIMMs. InClass nets consist of multiple independent classifier neural networks (NNs), which are trained simultaneously using suitable cost functions. Leveraging the ability of NNs to handle high-dimensional data, the conditionally independent variates of the model are allowed to be individually high-dimensional, which is the main advantage of the proposed technique over existing non-machine-learning-based approaches. Two new theorems on the nonparametric identifiability of bivariate CIMMs are derived in the form of a necessary and a (different) sufficient condition for a bivariate CIMM to be identifiable. We use the InClass nets technique to perform CIMM estimation successfully for several examples. We provide a public implementation as a Python package called RainDancesVI.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Characterization of Deuterated-xylene Scintillator as a Neutron Spectrometer

We have experimentally characterized the neutron light output response functions of a deuterated-xylene scintillator for neutron energies lower than 10 MeV. We then used the response matrix to unfold the energy distribution of neutrons produced via several reactions, i.e. spontaneous fission, d(d,n)3He, 27Al(d,n)28Si, and 9Be(alpha,n)12C. Organic scintillators based on deuterated compounds show a fast response and good gamma-neutron discrimination capability, similar to proton-based scintillators. Deuterated scintillators can also effectively provide neutron spectra by unfolding measured data with the detector response matrix, without the need of time-of-flight. Deuteron recoils, produced by elastic collisions between deuterium and impinging neutrons, are preferentially forward-scattered. This non-isotropic reaction results in distinct peaks in the response functions to monoenergetic neutrons. In this work, we evaluated a custom-fabricated 7.62 cm x 7.62 cm deuterated-xylene (EJ301D) liquid scintillator. This liquid has a low volatility and higher flash point, compared to benzene-based deuterated detectors, e.g. EJ315 and NE230. We measured the EJ301D detector neutron response matrix (up to 6 MeV neutron energy) using an intense Cf252 source and the time-of-flight technique. The number of response functions obtained using our method is only limited by counting statistics and by the experimentally achievable energy resolution. Multi-channel unfolding was performed successfully for neutron spectra with different energy spectra.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

AN ESTIMATE OF SPENT NUCLEAR FUEL MECHANICAL LOADS IN THE GENERAL 30 CM PACKAGE DROP SCENARIO

The US Department of Energy Spent Fuel and Waste Science and Technology (SFWST) program is performing research to determine the mechanical loading conditions applied to spent nuclear fuel (SNF) during normal conditions of transport to inform mechanical tests of SNF and close an important knowledge gap related to the practical disposition of SNF in the US. Researchers at Pacific Northwest National Laboratory (PNNL) have completed an extensive finite element study to characterize and estimate the potential mechanical loads on SNF during a hypothetical 30 cm drop of an SNF transportation package. This modeling study is validated with test data collected by the SFWST program during a physical test campaign that included one-third scale package drop tests and full-scale single fuel assembly drop tests. The test campaign was led by Sandia National Laboratories (SNL) and included international collaboration with Equipos Nucleares S.A, S.M.E (ENSA) and Bundesanstalt für Materialforschung und -prüfung (BAM). The key contribution of the modeling study is to go beyond the limitations of the limited number of physical tests to estimate the impact response to variations in impact angle, initial gap conditions, fuel assembly design, burnup and other parameters that affect the mechanical loads. The methodology of this study included a classic parametric study to calculate the impact response of highly detailed fuel assemblies over many combinations of parameters. Models of a 17x17 pressurized water reactor fuel assembly and a generic 10x10 boiling water reactor fuel assembly were both used in this study to cover the major fuel assembly types in the US inventory. Over 2,000 impact responses were calculated. The results of the parametric study were evaluated using traditional methods and basic statistics. The results were also used to construct a damage model using multiple nonlinear regression techniques to predict the mechanical loads over the full range of all input parameters. The damage model was found to work very well for all impact angle cases where the cask came to rest on its side. It was concluded that end drop cases where the cask remained vertical (instead of tipping over onto its side) were not sufficiently characterized by the current set of parametric study cases to include in the damage model, but it was not a priority to fully investigate that range because the highest mechanical loads were observed in the broader range of side impact cases. This modeling work provides sufficient insight into the mechanical loads on SNF during a hypothetical 30 cm package drop that, when considered along with the physical test data collected by the SNL-led team, the SFSWT program can consider the knowledge gap closed.

Klymyshyn, Nicholas A.↗
DOE OSTI2022

Ensemble approximate control variate estimators: Applications to multi-fidelity importance sampling.

The recent growth in multifidelity uncertainty quantification has given rise to a large set of variance reduction techniques that leverage information from model ensembles to provide variance reduction for estimates of the statistics of a high-fidelity model. In this paper we provide two contributions: (1) we utilize an ensemble estimator to account for uncertainties in the optimal weights of approximate control variate (ACV) approaches and derive lower bounds on the number of samples required to guarantee variance reduction; and (2) we extend an existing multifidelity importance sampling (MFIS) scheme to leverage control variates. Our approach directly addresses a limitation of many multifidelity sampling strategies that require the usage of pilot samples to estimate covariances. As such we make significant progress towards both increasing the practicality of approximate control variates—for instance, by accounting for the effect of pilot samples—and using multifidelity approaches more effectively for estimating low-probability events. The numerical results indicate our hybrid MFIS-ACV estimator achieves up to 50% improvement in variance reduction over the existing state-of-the-art MFIS estimator, which had already shown an outstanding convergence rate compared to the Monte Carlo method, on several problems of computational mechanics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Framework for Modeling High-Impact, Low-Frequency Power Grid Events to Support Risk-Informed Decisions

Natural and man-made hazardous events resulting in loss of grid infrastructure assets challenge the electric power grid’s security and resilience. However, the planning and allocation of appropriate contingency resources for such events requires an understanding of their likelihood and the extent of their potential impact. Where these events are of low likelihood, a risk-informed perspective on planning can be problematic as there exists an insufficient statistical basis to directly estimate the probabilities and consequences of their occurrence. Since risk-informed decisions rely on such knowledge, a basis for modeling the risk associated with high-impact low frequency events (HILFs) is essential. Insights from such a model can inform where resources are most rationally and effectively expended. The present effort is focused on development of a HILF risk assessment framework. Such a framework is intended to provide the conceptual and overarching technical basis for the development of HILF risk models that can inform decision makers across numerous stakeholder sectors. The North American Electric Reliability Corporation (NERC) 2014 Standard TPL-001-4 considers severe events for transmission reliability planning, but does not address events of such severity that they have the potential to fail a substantial fraction of grid assets over a region, such as geomagnetic disturbances (GMD), extreme seismic events, and coordinated cyber-physical attacks. These are beyond current planning guidelines. As noted, the risks associated with such events cannot be statistically estimated based on historic experience; however, there does exist a stable of risk modeling techniques for rare events that have proven of value across a wide range of engineering application domains. There is an active and growing interest in evaluating the value of risk management techniques in the State transmission planning and emergency response communities, some of this interest in the context of grid modernization activities. The availability of a grid HILF risk model, integrated across multi-hazard domains which, when interrogated, can support transparent, defensible and effective decisions, is an attractive prospect among these communities. In this report, we document an integrated HILF risk framework intended to inform the development of risk models. These models would be based on the systematic and comprehensive (to within scope) characterization of hazards to the level of detail required for modeling risk, identification of the stressors associated with the hazards (i.e., the means of impacting grid and supporting infrastructure), characterization of the vulnerability of assets to these stressors and the probabilities of asset compromise, the grid’s dynamic response to the asset failures, and assessment of subsequent severities of consequence with respect to selected impact metrics, such as power outage duration and geographic reach. Specifically, the current framework is being developed to;1. Provide the conceptual and overarching technical paradigms for the development of risk models; 2. Identify the classes of models required to implement the framework - providing examples of existing models, and also identifying where modeling gaps exist; 3. Identify the types of data required, addressing circumstances under which data are sparse and the formal elicitation of informed judgment might be required; and 4. Identify means by which the resultant risk models might be interrogated to form the necessary basis for risk management.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Structural Studies of Amorphous Materials by Fluctuation Electron Microscopy

Fluctuation Electron Microscopy (FEM) is a technique that examines the fluctuations in electron scattering across a uniformly thin amorphous sample. The statistics of the intensity fluctuations, mean and variance, reveal any underlying medium-range order present in the structure. The goals of this project were: (1) To determine the fundamentals of the scattering physics that gives rise to the variance signal in fluctuation electron microscopy (FEM); (2) To use these discoveries to find ways to quantify FEM; (3) To apply the FEM method to interesting and technologically important families of amorphous materials, particularly those with important applications in energy-related processes. Excellent progress was made in items (1) and (2). In stage (3) we did not examine the metamict zircons, as proposed. Instead, we examined films of polycrystalline and amorphous semi-conducting diamond. Significant accomplishments are: (1) A Reverse Monte Carlo procedure was successfully implemented to invert FEM data into a structural model. This is computer-intensive, but it demonstrated that diffraction and FEM data from amorphous silicon are most consistent with a paracrystallite model. This means that there is more diamond-like topology present in amorphous silicon than is predicted by the continuous random network model. (2) There is significant displacement decoherence arising in diffraction from amorphous silicon and carbon. The samples are being bombarded by the electron beam and atoms do not stay still while being irradiated – much more than was formerly understood. The atom motions cause the destructive and constructive interferences in the diffraction pattern to fluctuate with time, and it is the time-averaged speckle that is being measured. The variance is reduced by a factor m, 4 ≤ m ≤ 1000, relative to that predicted by kinematical scattering theory. (3) Speckle intensity obeys a gamma distribution, where the mean intensity $ \overline{I}\ $ and m are the two parameters governing the shape of the gamma distribution profile. m is determined by the illumination spatial coherence, which is normally very high, and mostly by the displacement decoherence within the sample. (4) Amorphous materials are more affected by the electron beam than are crystalline materials. Different samples exhibit different disruptibility, as measured by the effective values of m that fit the data. (5) Understanding the origin of the displacement decoherence better should lead to efficient methods for computing the observed variance from amorphous materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Assessment of Potential Ergonomic Injury Risk in the Nuclear Material Processing Glovebox Environment [Capstone Project]

Gloveboxes are isolation barriers that are used within many different industries such as pharmaceuticals, electronic parts fabrication, nuclear, and biological. The research on glovebox ergonomics is currently limited with few ergonomic professionals that focusing exclusively on glovebox working environments. There is existing documentation on occupational injuries, such as musculoskeletal disorders (MSD), sustained as a direct result of working in gloveboxes. The main elements that pose ergonomic risks to glovebox workers are operational repetition, duration, force, vibration, lifting heavy (more than 15lbs with two hands) objects, and awkward postures. This paper examines a small sample of the potential causal or risk factors that lead to the ergonomic injuries. A meta-analysis utilizing a random effect model is used to examine data from several studies which focus on, dexterity and strength changes as result of glove thickness, and robotic assistive technology as a means to improve postural mechanics. With the meta-analysis technique, similar data sets from different research studies can be coalesced into a single weighted, statistically significant result for subsequent consideration. The results from the analysis show that increased glove thickness results in decreased dexterity for operators thus increasing ergonomic risk factors such as task duration. It is also shown that glove thickness decreases grip strength but a similar decrease in pinch strength is not definitively demonstrated. With decreased grip strength, operators will need to exert more force (a known ergonomic risk factor) on processing tools, etc. during operations thus increasing the risk of ergonomic injury. The use of robotic assistive technology as a means to improve operator posture (risk factor) was also examined. Although it may be intuitively assumed that human-robotic collaboration would be beneficial in reducing risk factors, the result from this study’s analysis was not statistically significant. It is inferred that with additional directed research on this topic another study/analysis could be statistically significant demonstrating the benefits of the technology.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Characteristics of the IBEX Ribbon and Their Implications for a Source Region Outside the Heliopause

This paper presents a comprehensive exploration of the Interstellar Boundary Explorer energetic neutral atom (ENA) ribbon, focusing on its spatial and temporal variations over 14 yr. Methodological advancements, including a refined map modeling procedure and a new ribbon separation technique with appropriate error propagation, enable a detailed investigation of the ribbon’s features. Utilizing statistically robust metrics, this study reveals details of the ribbon across energy and time. Key findings include energy- and time-dependent variations in flux, angular radius, ribbon profile width, and higher moments. By applying these metrics, we reveal new complexity to the evolution of the ribbon over time, highlighting the nuanced relationship between it and the solar wind. Furthermore, the study examines for the first time the ribbon as it passes through the starboard/heliotail region (Lon EC 120°–180°), revealing properties distinct from other portions of the ribbon. The analysis uncovers an anticorrelation between ribbon width and flux, which provides quantitative support for a multisource ribbon created by a combination of solar wind neutrals that generate a spatiall narrow ribbon component and heliosheath neutrals giving rise to a broad component. Finally, differences in the temporal evolution of the ENA flux at different energies provide additional support that the location of the ribbon source region is beyond the heliopause.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1972

Investigation of the performance characteristics of Doppler radar technique for aircraft collision hazard warning, phase 3

System studies, equipment simulation, hardware development and flight tests which were conducted during the development of aircraft collision hazard warning system are discussed. The system uses a cooperative, continuous wave Doppler radar principle with pseudo-random frequency modulation. The report presents a description of the system operation and deals at length with the use of pseudo-random coding techniques. In addition, the use of mathematical modeling and computer simulation to determine the alarm statistics and system saturation characteristics in terminal area traffic of variable density is discussed.

Source record↗
NASA NTRS1977

Body composition changes in monkeys during long-term exposure to high acceleration fields

Adult male pig-tailed monkeys, weighing 10-14 kg, were subjected to continuous centrifuging stress for 7 months in acceleration fields up to 2.5 g. In vivo analytical techniques were used to evaluate parameters of body composition, body-fluid distribution, and hematology. Statistically significant losses in total body mass, lean body mass, total body water, extracellular water content and interstitial water content proportional to the level of high g were demonstrated.

Pace, N.↗
NASA NTRS1979

Landsat-D thematic mapper simulation in an urban area using aircraft multispectral scanner data

A simulation of imagery from the Landsat-D thematic mapper was conducted in order to determine its usefulness for urban land-use classification. Aircraft 24-channel multispectral scanner imagery of the Los Angeles area at 7.5-m resolution was processed digitally by means of matrix averaging and image smoothing techniques to simulate the 30-m resolution of the thematic mapper. Mean and standard deviation statistics of training sites for resolutions of 7.5, 15, 30 and 60 m were used to generate final classification maps. Plots of relative standard deviation showed that for larger training sites, as the resolution decreased, the distribution range of density values also decreased, while plots of relative classification accuracies showed that as resolution decreased, classification accuracies for three levels of standard deviation increased. A point of diminishing returns was indicated, however, confirming the utility of the resolution intended for Landsat-D.

Clark, J.↗
NASA NTRS1982

Proceedings of the NASA Workshop on Surface Fitting

Surface fitting techniques and their utilization are addressed. Surface representation, approximation, and interpolation are discussed. Along with statistical estimation problems associated with surface fitting.

Guseman, L. F., Jr.↗
NASA NTRS1983

Statistical summaries of fatigue data for design purposes

Two methods are discussed for constructing a design curve on the safe side of fatigue data. Both the tolerance interval and equivalent prediction interval (EPI) concepts provide such a curve while accounting for both the distribution of the estimators in small samples and the data scatter. The EPI is also useful as a mechanism for providing necessary statistics on S-N data for a full reliability analysis which includes uncertainty in all fatigue design factors. Examples of statistical analyses of the general strain life relationship are presented. The tolerance limit and EPI techniques for defining a design curve are demonstrated. Examples usng WASPALOY B and RQC-100 data demonstrate that a reliability model could be constructed by considering the fatigue strength and fatigue ductility coefficients as two independent random variables. A technique given for establishing the fatigue strength for high cycle lives relies on an extrapolation technique and also accounts for "runners." A reliability model or design value can be specified.

Wirsching, P. H.↗
NASA NTRS1986

Thrust imbalance of solid rocket motor pairs on Space Shuttle flights

This analysis extends the investigation presented at the 17th Joint Propulsion Conference in 1981 to include fifteen sets of Space Shuttle flight data. The previous report dealt only with static test data and the first flight pair. The objective is to compare the authors' previous theoretical analysis of thrust imbalance with actual Space Shuttle performance. The theoretical prediction method, which involves a Monte Carlo technique, is reviewed briefly as are salient features of the flight instrumentation system and the statistical analysis. A scheme for smoothing flight data is discussed. The effects of changes in design parameters are discussed with special emphasis on the filament wound motor case being developed to replace the steel case. Good agreement between the predictions and the flight data is demonstrated.

Foster, W. A., Jr.↗