Search NASA⌕ Search

SEARCH · Search NASA

Results for “spatial prediction”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Unsteady Flowfield in a High-Pressure Turbine Modeled by TURBO

Forced response, or resonant vibrations, in turbomachinery components can cause blades to crack or fail because of the large vibratory blade stresses and subsequent high-cycle fatigue. Forced-response vibrations occur when turbomachinery blades are subjected to periodic excitation at a frequency close to their natural frequency. Rotor blades in a turbine are constantly subjected to periodic excitations when they pass through the spatially nonuniform flowfield created by upstream vanes. Accurate numerical prediction of the unsteady aerodynamics phenomena that cause forced-response vibrations can lead to an improved understanding of the problem and offer potential approaches to reduce or eliminate specific forced-response problems. The objective of the current work was to validate an unsteady aerodynamics code (named TURBO) for the modeling of the unsteady blade row interactions that can cause forced response vibrations. The three-dimensional, unsteady, multi-blade-row, Reynolds-averaged Navier-Stokes turbomachinery code named TURBO was used to model a high-pressure turbine stage for which benchmark data were recently acquired under a NASA contract by researchers at the Ohio State University. The test article was an initial design for a high-pressure turbine stage that experienced forced-response vibrations which were eliminated by increasing the axial gap. The data, acquired in a short duration or shock tunnel test facility, included unsteady blade surface pressures and vibratory strains.

Bakhle, Milind A.↗
NASA NTRS2008

Simulation of the Impact of New Aircraft and Satellite-Based Ocean Surface Wind Measurements on H*Wind Analyses

Accurate observations of surface ocean vector winds (OVW) with high spatial and temporal resolution are required for understanding and predicting tropical cyclones. As NASA's QuikSCAT and Navy's WindSat operate beyond their design life, many members of the weather and climate science communities recognize the importance of developing new observational technologies and strategies to meet the essential need for OVW information to improve hurricane intensity and location forecasts. The Hurricane Imaging Radiometer (HIRAD) is an innovative technology development which offers new and unique remotely sensed satellite observations of both extreme oceanic wind events and strong precipitation. It is based on the airborne Stepped Frequency Microwave Radiometer (SFMR), which is the only proven remote sensing technique for observing tropical cyclone (TC) ocean surface wind speeds and rain rates. The proposed HIRAD instrument advances beyond the current nadir viewing SFMR to an equivalent wide-swath SFMR imager using passive microwave synthetic thinned aperture radiometer (STAR) technology. This sensor will operate over 4-7 GHz (C-band frequencies) where the required TC remote sensing physics has been validated by both SFMR and WindSat radiometers. The instrument is described in more detail in a paper by Jones et al. presented to the Tropical Meteorology Special Symposium at this AMS Annual Meeting. Simulated HIRAD passes through a simulation of hurricane Frances are being developed to demonstrate HIRAD estimation of surface wind speed over a wide swath in the presence of heavy rain. These are currently being used in "quick" OSSEs (Observing System Simulation Experiments) with H'Wind analyses as the discriminating tool. The H'Wind analysis, a product of the Hurricane Research Division of NOAA's Atlantic , Oceanographic and Meteorological Laboratory, brings together wind measurements from a variety of observation platforms into an objective analysis of the distribution of wind speeds in a tropical cyclone. This product is designed to improve understanding of the extent and strength of the wind field, and to improve the assessment of hurricane intensity. See http://www.aoml.noaa._ov/hrd/data sub/wind.html. Observations have been simulated from both aircraft altitudes and space. The simulated flight patterns for the aircraft platform cases have been designed to duplicate the timing and flight patterns used in routine NOAA and USAF hurricane surveillance flights, and the spaceborne case simulates a TRMM orbit and altitude.

Miller, TImothy L.↗
NASA NTRS2010

Seasonal Change on Saturn from Cassini/CIRS Observations, 2004-2009

Five years of thermal infrared spectra from the Cassini Composite Infrared Spectrometer (CIRS) are analyzed to determine the response of Saturn's atmosphere to seasonal changes in insolation. Hemispheric mapping sequences at 15.0 cm-1 spectral resolution are used to retrieve the variation in the zonal mean temperatures in the stratosphere (0.5-5.0 mbar) and upper troposphere (75-800 mbar) between October 2004 (shortly after the summer solstice in the southern hemisphere) and July 2009 (shortly before the autumnal equinox). Saturn's northern mid-latitudes show signs of dramatic warming in the stratosphere (by 6-10 K) as they emerge from ring-shadow into springtime conditions, whereas southern mid-latitudes show evidence for cooling (4-6 K). The 40-K asymmetry in stratospheric temperatures between northern and southern hemispheres (at 1 mbar) slowly decreased during the timespan of the observations. Tropospheric temperatures also show temporal variations but with a smaller range, consistent with the increasing radiative time constant of the atmospheric response with increasing pressure. The tropospheric response to the insolation changes shows the largest magnitude at the locations of the broad retrograde jets. Saturn's warm south-polar stratospheric hood has cooled over the course of the mission, but remains present. Stratospheric temperatures are compared to a radiative climate model which accounts for the spatial distribution of the stratospheric coolants. The model successfully predicts the magnitude and morphology of the observed changes at most latitudes. However, the model fails at locations where strong dynamical perturbations dominate the temporal changes in the thermal field, such as the hot polar vortices and the equatorial semi-annual oscillation (Orton, G., and 27 colleagues [2008]. Nature 453, 196-198). Furthermore, observed temperatures in Saturn's ring-shadowed regions are larger than predicted by all radiative-climate models to date due to the incomplete characterization of the dynamical response to the shadow. Finally, far-infrared CIRS spectra are used to demonstrate variability of the para-hydrogen distribution over the 5-year span of the dataset, which may be related to observed changes in Saturn's tropospheric haze in the spring hemisphere.

Fletcher, Leigh N.↗
DOE OSTI2024

MORPHOLOGICAL AND RADIATION DAMAGE INFORMED THERMAL PROPERTY PREDICTION IN SCALED GEOMETRIC DOMAINS

This proposed work has the potential to rewrite the way the nuclear industry investigates new fuel and nuclear material designs. The current rubric of nuclear material design has myriad steps in the process, and while certain physics are modeled accurately, each step must be connected in order to obtain an entire description of the process. At present, neutronic, thermal, microstructural, fission product chemistry and migration, and radiation defect analysis (hereafter referred to together as “combined analysis”) are performed, albeit separately. There is no existing method which combines these physics in an attempt to understand the natural interactions between these phenomena. Consequently, the timeline for design, fabrication, experiment, validation, and licensing can take years. A disruptive approach is required to accelerate the development of new technology. This proposed undertaking creates a validated computational framework, generating a new microscopic-to-macroscopic methodology yielding thermal property predictions for nuclear fuels and materials at an engineering spatial scale.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2020

“It’s Raining Bits”: Patterns in Directional Precipitation Persistence Across the United States

The spatial and temporal ordering of precipitation occurrence impacts ecosystems, streamflow, and water availability. For example, both large-scale climate patterns and local landscapes drive weather events, and the typical speeds and directions of these events moving across a basin dictate the timing of flows at its outlet. We address the predictability of precipitation occurrence at a given location, based on the knowledge of past precipitation at surrounding locations. We identify ‘‘dominant directions of precipitation influence’’ across the continental United States based on a gridded daily dataset. Specifically, we apply information theory–based measures that characterize dominant directions and strengths of spatial and temporal precipitation dependencies. On a national average, this dominant direction agrees with the prevalent direction of weather movement from west to east across the country, but regional differences reflect topographic divides, precipitation gradients, and different climatic drivers of precipitation. Trends in these information relationships and their correlations with climate indices over the past 70 years also show seasonal and spatial divides. This study expands upon a framework of information-based predictability to answer questions about spatial connectivity in addition to temporal persistence. The methods presented here are generally useful to understand many aspects of weather and climate variability.

North America↗
NASA NTRS1994

A spectral formalism for computing three-dimensional deformations due to surface loads. 2: Present-day glacial isostatic adjustment

Using a spherically symmetric, self-gravitating, linear viscoelastic Earth model, we predict present-day three-dimensional surface deformation rates and baseline evolutions arising as a consequence of the late Pleistocene glacial cycles. In general, we use realistic models for the space-time geometry of the final late Pleistocene deglaciation event and incorporate a gravitationally self-consistent ocean meltwater redistribution. The predictions of horizontal velocity presented differ significantly, in both their amplitude and their spatial variation, from those presented in earlier analysis of others which adopted simplified models of both the late Pleistocene ice history and the Earth rheology. An important characteristic of our predicted velocity fields is that the melting of the Laurentide ice sheet over Canada is capable of contributing appreciably to the adjustment in Europe. The sensitivity of the predictions to variations in mantle rheology is investigated by considering a number of different Earth models, and by computing appropriate Frechet kernels. These calculations suggest that the sensitivity of the deformations to the Earth's rheology is significant and strongly dependent on the location of the site relative to the ancient ice sheet. The effects on the predictions of three-dimensional deformation rates of altering the ice history or adopting approximate models for the ocean meltwater redistribution have also been considered and found to be important (the former especially so). Finally, for a suite of Earth models we provide predictions of the velocity of a number of baselines in North America and Europe. We find that, in general, both radial and tangential motions contribute significantly to baseline length changes, and that these contributions are a strong function of the Earth model. We have, furthermore, found a set of Earth models which, together with the ICE-3G deglaciation chronology, produce predictions of baseline length changes that are consistent with very long baseline interferometry measurements of baselines within Europe.

Mitrovica, J. X.↗
DOE OSTI2025

Ensemble‐Based Spatially Distributed CLM5 Hydrological Parameter Estimation for the Continental United States

Abstract One of the major challenges in large‐domain hydrological modeling efforts lies in the estimation of spatially distributed hydrological parameters while simultaneously accounting for their associated uncertainties. Addressing this challenge is particularly difficult in ungauged locations. With growing societal demands for large‐scale streamflow projections to inform water resource management and long‐term planning, evaluating and constraining hydrological parameter uncertainty is increasingly vital. This study introduces a hybrid regionalization approach to enhance hydrological predictions of the Community Land Model version 5 (CLM5) across the Continental United States (CONUS), with a total of 50,629 1/8° grid cells. This hybrid method combines the strengths of two existing techniques: parameter regionalization and streamflow signature regionalization. It identifies ensemble behavioral parameters for each 1/8° grid cell across the CONUS domain, tailored to three distinct streamflow signatures focused on low flows, high flows, and annual water balance. Evaluating this hybrid method for 464 CAMELS (Catchment Attributes and Meteorology for Large‐sample Studies) basins demonstrates a significant improvement in CLM5 hydrological predictions, even in challenging arid regions. In CONUS applications, the derived spatially distributed parameter sets capture both spatial continuity and variation of parameters, highlighting their heterogeneous nature within specific regions. Overall, this hybrid regionalization approach offers a promising solution to the complex task of improving hydrological modeling over large domains for important hydrological applications.

CLM5↗
DOE OSTI2022

Large-scale homogeneity in the distribution of quasars in the Hercules-Corona Borealis Great Wall region

In light of recent debates on the existence of a gigaparsec-scale structure traced by gamma-ray bursts, namely the Hercules-Corona Borealis Great Wall (HCBGW), we revisit large-scale homogeneity in the spatial distribution of quasars. Our volume-limited sample of quasars in the redshift range 1:6 < z ≤ 2:1, which is constructed from the data release 7 of the Sloan Digital Sky Survey quasar catalogue, covers about half of the suspected HCBGW region. We analyze the sample in two complementary ways: fractal analysis of determining the average scale of homogeneity and friends- of-friends analysis of identifying specific large-scale structures. The quasar distribution on average reaches homogeneity at rh = 136 ± 38h-1 Mpc and the richness and comoving size frequencies of large (> ~ 150h-1 Mpc) quasar groups are consistent with the prediction of homogeneous distribution. These results put constraints on the spatial extent of the HCBGW but do not contradict its existence since our quasar sample does not cover the entire HCBGW region.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Machine Learning for Adaptive Model Refinement to Bridge Scales

This whitepaper is responsive to focal area (2) Predictive modeling through the use of AI techniques and AI-derived model components: the use of AI and other tools to design a prediction system comprising of a hierarchy of models (e.g., AI driven model/component/parameterization selection). Here we describe scale-aware ML models for adaptive model refinement that allow us to bridge the spatial and/or temporal scales in simulation models and observation data for capturing and predicting extreme water cycles.

58 GEOSCIENCES↗
NASA NTRS2020

A 3D Model to Predict Explicit Morphologies and Volume Fraction of Lack-of-Fusion Pores Generated in Selective Laser Melting Processes

The performance of an additively manufactured (AM) component is dependent on the distribution of process-induced defects in addition to the complex microstructure of the material, surface roughness of the component and the process-induced residual stresses. For instance, it has been well demonstrated that lack-of-fusion (LoF) pores produced in the selective laser melting (SLM) AM process can significantly limit the fatigue performance of the material. Although two-dimensional (2D) models exist to predict the 2D profiles of LoF pores, the 2D pore profiles cannot be directly inserted into a three-dimensional (3D) microstructure domain that is output from several prevailing process simulation packages. A few commercial packages that simulate the SLM process can predict LoF pores in a 3D domain, but the morphologies of LoF pores are voxelated and hence do not capture sharp corners of the pores, thereby obviating their use in fatigue crack initiation studies. In order to address the aforementioned gaps, a high-fidelity model that predicts not only the volume fraction, but also the explicit 3D morphologies and spatial distributions of LoF pores has been developed using a computer aided design-based environment. The model has been partially validated for Ti-6Al-4V alloy by comparing the predictions of the volume fraction of LoF pores predicted by the model with experimental data obtained from the literature. Absolute error in predicted volume fraction of LoF pores varied between 5.16% and 1.87% for energy density values between 13 J/mm3 and 45 J/mm3 where a significant amount (over 3% volume fraction) of LoF porosity was measured. The absolute error was within 1.87% for energy density values greater than 45 J/mm3.

Saikumar R. Yeratapally↗
NASA NTRS1993

Spatial structure, sampling design and scale in remotely-sensed imagery of a California savanna woodland

This article describes research related to sampling techniques for establishing linear relations between land surface parameters and remotely-sensed data. Predictive relations are estimated between percentage tree cover in a savanna environment and a normalized difference vegetation index (NDVI) derived from the Thematic Mapper sensor. Spatial autocorrelation in original measurements and regression residuals is examined using semi-variogram analysis at several spatial resolutions. Sampling schemes are then tested to examine the effects of autocorrelation on predictive linear models in cases of small sample sizes. Regression models between image and ground data are affected by the spatial resolution of analysis. Reducing the influence of spatial autocorrelation by enforcing minimum distances between samples may also improve empirical models which relate ground parameters to satellite data.

Mcgwire, K.↗
NASA NTRS2021

Maximum entropy modeling to identify physical drivers of shallow snowpack heterogeneity using unpiloted aerial system (UAS) lidar

Understanding the spatial variability of the snowpack is valuable for hydrologists and ecologists seeking to predict hydrological processes in a cold region. Snow distribution is a function of interactions among static variables, such as terrain, vegetation, and soil properties, and dynamic meteorological variables, such as solar radiation, wind speed and direction, and soil moisture. However, identifying the dominant physical drivers responsible for spatial patterns of the snowpack, particularly for ephemeral, shallow snowpacks, has been challenging due to the lack of the high-resolution snowpack and physical variables with high vertical accuracy as well as inherent limitations in traditional approaches. This study uses an Unpiloted Aerial System (UAS) lidar-based snow depth and static variables (1-m spatial resolution) to analyze field-scale spatial structures of snow depth and apply the Maximum Entropy (MaxEnt) model to identify primary controls over open terrain and forests at the University of New Hampshire Thompson Farm Research Observatory, New Hampshire, United States. We found that, among nine topographic and soil variables, plant functional type and terrain roughness contribute up to 80% and 76% of relative importance in the MaxEnt framework to predict locations of deeper or shallower snowpacks, respectively, across a mixed temperate forested and field landscape. Soil variables, such as organic matter and saturated hydraulic conductivity, were also important controls (up to 70% and 81%) on snow depth spatial variations for both open and forested landscapes suggesting spatial variations in soil variables under snow can control thermal transfer among soil, snowpack, and surface-atmosphere. This work contributes to improving land surface and snow models by informing parameterization of the sub-grid scale snow depths, down-scaling remotely sensed snow products, and understanding field scale snow states.

Eunsang Cho↗
DOE OSTI2025

Kinetic Modeling of Secondary Organic Aerosol in a Weather-Chemistry Model: Parameterizations, Processes, and Predictions for GOAmazon

Secondary organic aerosol (SOA) forms and evolves in the atmosphere through many pathways and processes, over diverse spatial and time scales. Hence, there is a need to represent these widely-varying kinetic processes in large-scale atmospheric models to allow for accurate predictions of the abundance, properties, and impacts of SOA. In this work, we integrated a kinetic, process-level model (simpleSOM-MOSAIC) into a weather-chemistry model (WRF-Chem) to simulate the oxidation chemistry and microphysics of atmospheric SOA. simpleSOM-MOSAIC simulates multigenerational gas-phase chemistry, autoxidation reactions, heterogeneous oxidation, oligomerization, and phase-state-influenced gas/particle partitioning of SOA. As a case study, the integrated WRF-Chem-simpleSOM-MOSAIC (WC-SSM) model was used to simulate the photochemical evolution downwind of a large city (Manaus, Brazil) in the Amazon and, in turn, study the anthropogenic and biogenic interactions in an otherwise pristine environment. Consistent with previous work, we found that OA was enhanced by up to a factor of four in the urban plume due to elevated hydroxyl radical (OH) concentrations, relative to the background, and that this OA was dominated by SOA from biogenic precursors (80%). Further, in addition to accurately simulating the OA enhancement in the urban plume, the model reproduced the magnitude of the OA oxygen-to-carbon (O:C) ratio and broadly tracked the evolution of the aerosol size distribution. Our work highlights the importance of including an integrated, kinetic representation of SOA processes in an atmospheric model

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1987

Propagation of a premixed flame in a divided-chamber combustor

The propagation of premixed ethylene-air mixtures (of 0.5, 0.525, 0.55, and 0.65 equivalence ratios) in a divided-chamber combustor was investigated. The vessel, divided by a small cylindrical prechamber, had optical access (for laser-schlieren videography) and was instrumented by a pressure transducer. For the Reynolds numbers of 1870, 2300, and 2830, the observed spatial development of the laminar flames showed that the flame position and shape could be scaled by a characteristic time, based on the burned gas flame speed and the length of the prechamber. Above a Reynolds number of 4330, this scaling breaks down the appearance of Kelvin-Helmholtz instabilities. The observed flame propagation was compared with predictions obtained with a numerical model of flame propagation. The calculated spatial and temporal development of the flame in the main combustion chamber agreed with the experimental observations only for the lowest Reynolds number (1870).

Cattolica, R. J.↗
NASA NTRS1983

A stochastic-dynamic model for the spatial structure of forecast error statistics

The present investigation is concerned with the presentation of a simplified model of the spatial structure of forecast error statistics, a comparison of the model with actual numerical weather prediction results, and the extent to which simplifying assumptions made in the model are justified. A stochastic-dynamic model is derived for the spatial structure of the global atmospheric mass-field forecast error. The model states that the relative potential vorticity of the forecast error is random. The covariance function of the model's solutions is found to be governed by a simple deterministic equation. The agreement between the stochastic model and actual mass-field forecast errors fields for 12-36 h periods validates the assumptions on which the model is derived. Within this period, the difference between the potential voriticity fields of the atmosphere and of the numerical forecasts used in the comparison is well represented by white noise.

Balgovind, R.↗
NASA NTRS1992

Surface photometry of disk galaxies at 60 and 100 microns - Radial gradients in dust temperature in optically thin disks

Surface, aperture, and grid photometry are performed at 60 and 100 microns for a sample of 28 nearby, large angular size galaxies. The spatial resolution of the data is 0.5-2.0 kpc, which allows for a coarse investigation of predicted radial gradients in physical dust temperature. A model is derived which predicts a drop of 3 K for every optical scale length, and this model agrees well with the data. In addition, for a subsample of 16 galaxies the radial profile at 60 microns is directly compared with that in the B or I band. The model predicts that optically thick disks should have scale lengths a factor of two smaller at 60 microns compared to B. In the optically thin case, the scale lengths are about equal except for the effect of the gradient in dust temperature. Virtually all of the data support the prediction of the optically thin case. Finally, 10 galaxies in the sample have sufficient angular sizes to allow for a coarse 2D spatial mapping of the 60/100 microns flux ratio. These maps clearly reveal that, when present, small amounts of hot dust dominate the emission at 60 microns and effectively mask the existence of a much larger amount of cold dust.

Bothun, Gregory D.↗
DOE OSTI2020

Imaging the energy gap modulations of the cuprate pair-density-wave state

The defining characteristic of Cooper pairs with finite center-of-mass momentum is a spatially modulating superconducting energy gap Δ(r). Recently, this concept has been generalized to the pair density wave (PDW) state predicted to exist in cuprates. Although the signature of a cuprate PDW has been detected in Cooperpair tunneling, the distinctive signature in single-electron tunneling of a periodic Δ(r) modulation has never been observed. Here, using a new approach, we discover strong Δ(r) modulations in Bi 2 Sr 2 CaCu 2 O 8+δ that have eight-unit-cell periodicity or wavevectors Q ≈ (2π/a0)(1/8, 0) and Q ≈ (2π/a0)(0, 1/8). Simultaneous imaging of the localdensity- of-states N(r, E) reveals electronic modulations with wavevectors Q and 2Q, as anticipated when the PDW coexists with superconductivity. Finally, by visualizing the topological defects in these N(r, E) density waves at 2Q, we discover them to be concentrated in areas where the PDW spatial phase changes by !, as predicted by the theory of half-vortices in a PDW state. Overall, this is a compelling demonstration, from multiple single-electron signatures, of a PDW state coexisting with superconductivity in the canonical cuprate Bi 2 Sr 2 CaCu 2 O 8+δ .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗