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At least 379 records · Page 21

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Evaluating proxies for the drivers of natural gas productivity using machine-learning models

We report the extensive development of unconventional reservoirs using horizontal drilling and multistage hydraulic fracturing has generated large volumes of reservoir characterization and production data. The analysis of this abundant data using statistical methods and advanced machine-learning (ML) techniques can provide data-driven insights into well performance. Most predictive modeling studies have focused on the impact that different well completion and stimulation strategies have on well production but have not fully exploited the available in situ rock property data to determine its role in reservoir productivity. We have used machine-learning techniques to rank rock mechanical properties, microseismic attributes, and stimulation parameters in the order of their significance for predicting natural gas production from an unconventional reservoir. The data for this study came from a hydraulically fractured well in the Marcellus Shale in Monongalia County, West Virginia. The data classes included measurements aggregated by well completion stage that included (1) gas production, (2) well-log-derived measurements including bulk density, elastic moduli, shear impedance, compressional impedance, brittleness, and gamma measurements, (3) microseismic attributes, (4) long-period long-duration (LPLD) event counts, (5) fracture counts, and (6) stimulation parameters that included the fluid injection volume and average pumping pressure. To identify observable proxies for the drivers of gas production, we evaluated five commonly used ML approaches including multivariate adaptive regression spline, Gaussian mixture model, random forest, gradient boosting, and neural network. We selected five variables including LPLD event count, seismogenic b-value, hydraulic diffusivity, cumulative moment, and fluid volume as the features most likely to impact gas productivity at the stage level in the study area. The data-driven selection of these parameters for their importance in determining gas production can help reservoir engineers design more effective hydraulic-fracture treatments in the Marcellus Shale and other similar unconventional reservoirs. Plain language summary: We use machine-learning methods and data-driven selection of reservoir parameters to rank and better understand their importance in determining gas production, which can help reservoir engineers design more effective hydraulic-fracture treatments in the Marcellus Shale and other similar unconventional reservoirs.

58 GEOSCIENCES↗

NASA NTRS2005

Photometric and Spectral Study of the Saturnian Satellites

Photometric and spectra analysis of data from the Cassini Visual and Infrared Mapping Spectrometer (VIMS) has yielded intriguing findings regarding the surface properties of several of the icy Saturnian satellites. Spectral cubes were obtained of these satellites with a wavelength distribution in the IR far more extensive than from any previous observations. Disk-integrated solar phase curves were constructed in several key IR wavelengths that are indicative of key properties of the surface of the body, such as macroscopic roughness, fluffiness (or the porosity of the surface), global albedo and scattering properties of surface particles. Polynomial fits to these phase curves indicate a linear albedo trend of the curvature of the phase functions. Rotational phase functions from Enceladus were found to exhibit a double-peaked sinusoidal curve, which shows larger amplitudes for bands corresponding to water ice and a linear amplitude-albedo trend. These functions indicate regions on the surface of the satellite of more recent geologic activity. In addition, recent images of Enceladus show tectonic features and an absence of impact craters on Southern latitudes which could be indicative of a younger surface. Investigations into the properties of these features using VIMS are underway.

Newman, Sarah F.↗

DOE OSTI2024

Machine-learning-assisted deciphering of microstructural effects on ionic transport in composite materials: A case study of Li 7 La 3 Zr 2 O 12 -LiCoO 2

The effective diffusivity of ionic species in multiphase materials is critical for the design and function of composite materials for electrochemical energy storage. In practice, effective diffusivity depends sensitively not only on the intrinsic diffusivities of constituting materials but also on their topological arrangement; nevertheless, these coupled contributions are oversimplified in most analytical models. Here, we combine atomistically informed mesoscale modeling and machine learning (ML) analysis to unravel how such features affect effective diffusivity in two-phase composites. Using the Li 7 La 3 Zr 2 O 12 -LiCoO 2 composite solid-state battery cathode as a model system, we compute effective diffusivity for 600 distinct dense polycrystalline microstructures with different topological configurations of grains, grain boundaries, and heterointerfaces. We verify that in addition to atomic-scale variabilities, microstructural feature diversity can significantly impact effective transport properties. Across the ensemble of test microstructures, this often results in bimodal distributions of effective diffusivity that encompass two qualitatively distinct operating mechanisms, which we identify via flux analysis. An ML approach reveals that the most critical determining factors for effective diffusivity are the connectivity of bulk phases and their heterointerfaces. The role of ionic mobility at the heterointerfaces is also discussed. These insights highlight the combined importance of microstructure and interface engineering in tuning the transport properties of ionic species in composite materials. In conclusion, our framework can also be extended for understanding generic microstructure-property relationships in other complex multiphase materials.

25 ENERGY STORAGE↗

DOE OSTI2022

Three-dimensional microstructural characterization of FBR MOX fuel and the contribution of microstructural features to the thermal conductivity of the fuel

Combination of microstructural characterization, property measurements, and phase field modeling is used to investigate fast breeder reactor (FBR) mixed oxide (MOX) fuel irradiated to burnup of 13.7% fissions per initial metal atom (FIMA). Here, the fuel was characterized at different radial locations, which revealed that grey phase can be present in the central region if it nucleates on five metal precipitates (FMPs). In addition, in the mid-radial region FMPs do not diffuse out of the region once formed and the size of Pd–Te precipitates is dictated by the porosity present in the region. Thermal conductivity measurements were conducted as a function of radial location and the microstructure of the fuel was correlated with the observed trend. Reconstructions of the 3D solid and gaseous fission product structures in different regions of the fuel were used to simulate the effective thermal conductivity (ETC) of the respective regions and determine which microstructural feature has the strongest impact on thermal conductivity. Based on conducted assessment, FMPs and Pd-Te precipitates improve local conductivity of central and mid-radial regions even in the presence of grey phase, but defects are primary contributor to the degradation of thermal conductivity on the periphery of the fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Polyethylene density uncertainty in the simulation of neutron detectors

Simulations with the Monte Carlo N-Particle® (MCNP®) code are frequently used to study neutron coincidence counters for international safeguards. Reducing sources of uncertainty enables more accurate simulations, which reduces the need for expensive or impossible measurements. Accurately specifying the density of polyethylene is crucial for accurate simulations. The density of polyethylene ranges from 0.88 to 0.97 g/cm 3 and high-density polyethylene (HDPE) ranges from about 0.944 to 0.965 g/cm 3 . The density of a specific detector should be measured exactly for the best simulations. Here, the density of the blue/white Active Well Coincidence Counter (AWCC) bulk polyethylene was measured to be 0.9594 +- 0.0013 g/cm 3 at 1-sigma confidence. The density was calculated from repeated measurements of the various polyethylene dimensions for volume, and weighing the polyethylene for the mass. The AWCC neutron detection efficiency was simulated for each polyethylene density. The relative range of efficiencies (3σ) was 3.4% for unspecified polyethylene, 0.9% for HDPE, and 0.3% for the measured density. The impact of modeling small features such as screws was also studied and was found to be a negligible 0.2%. Measuring polyethylene density can reduce its role in uncertainty from one of the largest to one of the smallest contributors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Stochastic multiscale modeling for quantifying statistical and model errors with application to composite materials

This paper provides a coherent and efficient computational framework for stochastic multiscale analysis of material systems in the presence of parametric uncertainties and modeling errors. Uncertainty in those model parameters that are not deduced as upscaled quantities is attributed to an uncertainty “germ”. While such parameters can appear at any scale, they are predominant at the finest analysis scale. Additional uncertainties stemming from statistical estimation, attributed to lack of data and model error, are associated with each submodel contributing to the multiscale system. Here, a robust and efficient framework based on a generalized extended polynomial chaos expansion (gEPCE) is proposed to simultaneously propagate all these uncertainties in order to provide a probabilistic representation of specific quantities of interest (QoI). We characterize the full probability distribution of the QoI and the uncertainty in the failure probability pertaining to its tails. By combining gEPCE with kernel density estimation (KDE) and directional derivatives, we construct sensitivity measures that connect these statistical metrics of QoI to the various sources of uncertainty to assess their individual and combined impacts. An illustrative problem featuring three-point bending of a composite beam is investigated to demonstrate the presented approach.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Analysis of 0.1-Hz Var Oscillations in Solar Photovoltaic Power Plants

Oscillations with very low frequency at 0.1 Hz, have been observed in voltage and var in practical solar photovoltaic (PV) systems when power exporting ramps up to a certain level. Here, this letter provides an explanation on the formation of 0.1-Hz oscillations and identifies three critical factors that lead to the oscillations: communication delay between the plant-level control and the inverter-level control, high volt/var sensitivity at a high power exporting level, and the volt-var feedback system consisting of the plant control, inverter control and the grid impact. Furthermore, a critical feature of the 0.1-Hz oscillation is also explained: why oscillations appear only in voltage and var, but not in real power.

14 SOLAR ENERGY↗

DOE OSTI2020

Collaborative investigation of the internal flow and near-nozzle flow of an eight-hole gasoline injector (Engine Combustion Network Spray G)

The internal details of fuel injectors have a profound impact on the emissions from gasoline direct injection engines. However, the impact of injector design features is not currently understood, due to the difficulty in observing and modeling internal injector flows. Gasoline direct injection flows involve moving geometry, flash boiling, and high levels of turbulent two-phase mixing. In order to better simulate these injectors, five different modeling approaches have been employed to study the engine combustion network Spray G injector. Here these simulation results have been compared to experimental measurements obtained, among other techniques, with X-ray diagnostics, allowing the predictions to be evaluated and critiqued. The ability of the models to predict mass flow rate through the injector is confirmed, but other features of the predictions vary in their accuracy. The prediction of plume width and fuel mass distribution varies widely, with volume-of-fluid tending to overly concentrate the fuel. All the simulations, however, seem to struggle with predicting fuel dispersion and by inference, jet velocity. This shortcoming of the predictions suggests a need to improve Eulerian modeling of dense fuel jets.

ECN↗

DOE OSTI2023

Integrated Multiscale Model for Design of Robust 3D Solid-state Lithium Batteries

In FY23, we successfully established the multiscale modeling framework for probing the effects of materials microstructure on cell performance of 3D solid-state batteries. The framework covers physicochemical processes co-evolving at the atomistic and microstructure scales. Our simulations revealed the mechanism of initial interfacial degradation, formation of secondary phases, and the structure-property relationship for ion transport and mechanical stability at the interface. In addition, we also established the microstructure-performance relationships by performing sensitivity tests of various microstructure features and extracting their impact on cell performance during charge-discharge cycles. We have successfully applied our multiscale, multiphysics modeling capability to common electrode and electrolyte materials that are of interests to VTO and the experimental teams within the US-Germany collaboration. The insights we obtained from these simulations provide valuable design principles to optimize materials properties for advanced 3D solid-state batteries.

25 ENERGY STORAGE↗

DOE OSTI2021

Persistent Homology Metrics Reveal Quantum Fluctuations and Reactive Atoms in Path Integral Dynamics

Nuclear quantum effects (NQEs) are known to impact a number of features associated with chemical reactivity and physicochemical properties, particularly for light atoms and at low temperatures. In the imaginary time path integral formalism, each atom is mapped onto a “ring polymer” whose spread is related to the quantum mechanical uncertainty in the particle’s position, i.e., its thermal wavelength. A number of metrics have previously been used to investigate and characterize this spread and explain effects arising from quantum delocalization, zero-point energy, and tunneling. Many of these shape metrics consider just the instantaneous structure of the ring polymers. However, given the significant interest in methods such as centroid molecular dynamics and ring polymer molecular dynamics that link the molecular dynamics of these ring polymers to real time properties, there exists significant opportunity to exploit metrics that also allow for the study of the fluctuations of the atom delocalization in time. Here we consider the ring polymer delocalization from the perspective of computational topology, specifically persistent homology, which describes the 3-dimensional arrangement of point cloud data, (i.e. atomic positions). We employ the Betti sequence probability distribution to define the ensemble of shapes adopted by the ring polymer. The Wasserstein distances of Betti sequences adjacent in time are used to characterize fluctuations in shape, where the Fourier transform and associated principal components provides added information differentiating atoms with different NQEs based on their dynamic properties. We demonstrate this methodology on two representative systems, a glassy system consisting of two atom types with dramatically different de Broglie thermal wavelengths, and ab initio molecular dynamics simulation of an aqueous 4 M HCl solution where the H-atoms are differentiated based on their participation in proton transfer reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1971

Height-depth ratios of lunar and terrestrial craters.

Quantitative analysis of Gilbert's (1893) observation regarding the surface geometry of lunar craters and terrestrial calderas. Topographic measurements were made using the ratio of exterior rim height to interior crater depth, and then extended to other types of crater. The morphometric data obtained as well as those presented elsewhere (Murray et al., 1970; Guest and Murray, 1969) verify Gilbert's contention that terrestrial calderas and most rimmed lunar craters are entirely unrelated phenomena. Auxiliary characteristics previously interpreted in terms of primary volcanic cratering on the moon are either of nonendogenic origin or are secondary endogenic features superposed on initial impact landforms (Pike, 1967).

Pike, R. J.↗

NASA NTRS1973

The velocity structure of the lunar crust.

Seismic refraction data, obtained at the Apollo 14 and 16 sites, when combined with other lunar seismic data, allow a compressional wave velocity profile of the lunar near-surface and crust to be derived. The regolith, although variable in thickness over the lunar surface, possesses surprisingly similar seismic properties. Underlying the regolith at both the Apollo 14 Fra Mauro site and the Apollo 16 Descartes site is low-velocity brecciated material or impact derived debris. Key features of the lunar seismic velocity profile are: (1) velocity increases from 100 to 300 m/sec in the upper 100 m to about 4 km/sec at 5 km depth, (2) a more gradual increase from about 4 km/sec to about 6 km/sec at 25 km depth,(3) a discontinuity at a depth of 25 km, and (4) a constant value of about 7 km/sec at depths from 25 km to about 60 km.

Kovach, R. L.↗

NASA NTRS1975

A seismic refraction technique used for subsurface investigations at Meteor Crater, Arizona

A seismic refraction technique for interpreting the subsurface shape and velocity distribution of an anomalous surface feature such as an impact crater is described. The method requires the existence of a relatively deep refracting horizon and combines data obtained from both standard shallow refraction spreads and distant offset shots by using the deep refractor as a source of initial arrivals. Results obtained from applying the technique to Meteor crater generally agree with the known structure of the crater deduced by other investigators and provide new data on an extensive fractured zone surrounding the crater. The breccia lens is computed to extend roughly 190 m below the crater floor, about 30 m less than the value deduced from early drilling data. Rocks around the crater are fractured as distant as 900 m from the rim crest and to a depth of at least 800 m beneath the crater floor.

Ackermann, H. D.↗

NASA NTRS1975

Minimum thrust levels for spinning drag-free satellites

A drag-free satellite, which contains an internal unsupported proof mass, is shielded from external forces such as solar pressure. Thrustors force the satellite to follow the proof mass and hence the satellite follows an almost purely gravitational orbit. The dominant internal disturbing force is the mass attraction of the satellite on the proof mass. Spinning the satellite reduces this force and it has been investigated what the size of the thrustors must be in this case. This size is much smaller than originally thought. Its impact on some other features is shown.

Olsder, G. J.↗

NASA NTRS1977

Geologic interpretation of new observations of the surface of Venus

New radar observations of the surface of Venus provide further evidence of a diverse and complex geologic evolution. The radar bright feature 'Beta' (24 deg N, 85 deg W) is seen to be a 700 km diameter region elevated a maximum of approximately 10 km relative to its surroundings with a 60 x 90 km wide depression at its summit. 'Beta' is interpreted to be a large volcanic construct, analogous to terrestrial and Martian shield volcanoes. Two large, quasi-circular areas of low reflectivity, examples of a class of features interpreted to be impact basins by previous investigators who were without the benefit of actual topographic information, are shown in altimetry maps to be depressions. Thus the term 'basin' can be applied, although we urge a non-genetic usage until more complete understanding of their origin is achieved through analysis of future observations.

Saunders, R. S.↗

NASA NTRS1978

SAR/LANDSAT image registration study

The author has identified the following significant results. Temporal registration of synthetic aperture radar data with LANDSAT-MSS data is both feasible (from a technical standpoint) and useful (from an information-content viewpoint). The greatest difficulty in registering aircraft SAR data to corrected LANDSAT-MSS data is control-point location. The differences in SAR and MSS data impact the selection of features that will serve as a good control points. The SAR and MSS data are unsuitable for automatic computer correlation of digital control-point data. The gray-level data can not be compared by the computer because of the different response characteristics of the MSS and SAR images.

Murphrey, S. W.↗

NASA NTRS1982

Tectonic deformation of Galileo Regio and limits to the planetary expansion of Ganymede

Galileo Regio is the largest and most prominent unit of dark, ancient, heavily cratered terrain on Ganymede. Its major tectonic feature, an arcuate system of rimmed furrows, formed very early, as nearly the entire cratering record post-dates it. Galileo Regio has undergone very little subsequent structural alteration, as opposed to the rest of the planet (i.e., replacement by grooved and smooth terrain). Its survival as an intact lithospheric unit during the era of grooved terrain formation constrains the concomitant expansion of Ganymede, if any, to be less than one percent in radius. This limit is derived from an analysis which considers Galileo Regio to be a thin, freely floating elastic spherical shell on an expanding planet. A comparison of tectonic features (both endogenic and impact produced) on Ganymede and Callisto suggests that the ultimate source that powered the creation of grooved terrain lies in the Ganymedean core.

Mckinnon, W. B.↗

NASA NTRS1985

A theory of post-stall transients in axial compression systems. II - Application

Using the theory developed in Part I, calculations have been carried out to show the evolution of the mass flow, pressure rise, and rotating-stall cell amplitude during compression system post-stall transients. In particular, it is shown that the unsteady growth or decay of the stall cell can have a significant effect on the instantaneous compressor pumping characteristic and hence on the overall system behavior. A limited parametric study is carried out to illustrate the impact of different system features on transient behavior. It is shown, for example, that the ultimate mode of system response, surge or stable rotating stall, depends not only on the B parameter, but also on the compressor length-to-radius ratio. Small values of this latter quantity tend to favor the occurrence of surge, as do large values of B. Based on the analytical and numerical results, several specific topics are suggested for future research on post-stall transients.

Greitzer, E. M.↗