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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Polar stratospheric clouds inferred from satellite data

Anomalously high radiances from the ozone channel of the Limb Infrared Monitor of the Stratosphere (LIMS) sounding instrument have been observed in the Northern Hemisphere winter lower stratosphere. Such events, thought to be due to polar stratospheric clouds (PSCs), are examined further by computing relative humidities using Stratospheric Sounding Unit temperatures and water vapor measurements from the LIMS Map Archive Tape analyses. Regions identified as PSCs are found to correspond closely to regions of high humidity. While instances of saturation were found, the average humidity at the centers of 39 PSCs was calculated to be 58 percent. Possible reasons for this apparent discrepancy are discussed. Applying a similar approach to the Southern Hemisphere, in 1979, virtually no PSCs are found in the vortex after September 10 at 20 km. This result has important implications for a number of proposed explanations for the Antarctic ozone hole.

Austin, J.↗
NASA NTRS1989

Implications of the giant planets for the formation and evolution of planetary systems

The giant planet region in the solar system appears to be bounded inside by the limit of water condensation, suggesting that the most abundant astrophysical condensate plays an important role in giant planet formation. Indeed, Jupiter and Saturn exhibit evidence for rock and/or ice cores or central concentrations that probably accumulated first, acting as nuclei for subsequent gas accumulation. This is a 'planetary' accumulation process, distinct from the stellar formation process, even though most of Jupiter has a similar composition to the primordial sun. Uranus and Neptune appear to exhibit evidence of an important role for giant impacts in their structure and evolution. No simple picture emerges for the temperature structure of the solar nebula from observations alone. However, it seems likely that Jupiter is the key to the planetary system, and a similar planet could be expected for other systems. The data and inferences from these data are summarized for the entire known solar system beyond the asteroid belt.

Stevenson, David J.↗
NASA NTRS1992

Constraints on the thermal evolution of Venus inferred from Magellan data

The impact craters with diameters from 1.5 to 280 km compiled from Magellan observations indicate that the crater population on Venus has a completely spatially random distribution and the size/density distribution of craters with diameters greater than or equal to 35 km is consistent with a 'production' population with an age of 500 plus or minus 250 m.y. The similarity in size distribution from area to area indicates that the crater distribution is independent of crater size. Also, the forms of the modified craters are virtually identical to those of the pristine craters. These observations imply that Venus reset its cratering record by global resurfacing 500 m.y. ago, and resurfacing declined relatively fast. The fact that less than 40 percent of all craters have been modified and that the few volcanically embayed craters are located on localized tectonic regions indicate that only minor and localized volcanism and tectonism have occurred since the latest vigorous resurfacing event approximately 500 m.y. ago and the interior of Venus has been solid and possibly colder than Earth's. This is because the high-temperature lithosphere of Venus would facilitate upward ascending of mantle plumes and result in extensive volcanism if the venusian upper mantle were as hot as or hotter than Earth's. Therefore, the present surface morphology of Venus may provide useful constraints on the pattern of that vigorous convection, and possibly on the thermal state of the venusian mantle. We examine this possibility through numerical calculations of three-dimensional thermal convection models in a spherical shell with temperature- and pressure-dependent Newtonian viscosity, temperature-dependent thermal diffusivity, pressure-dependent thermal expansion coefficient, and time-dependent internal heat production rate solar magnitude.

Arkani-Hamed, Jafar↗
NASA NTRS1993

Constraints on the thermal evolution of Venus inferred from Magellan data

One interpretation of the Magellan data suggests that the cratering record on Venus was erased by a global resurfacing event, or events, the latest ending about 500 m.y. ago. In this global-resurfacing model the resurfacing was followed by minor volcanism and tectonism that has been concentrated primarily in the equatorial highland regions characterized by extensive fracture belts and rifts. A thermal evolution model of Venus that can explain these observations is one in which a deformable lithosphere, capable of being incorporated in mantle circulations, provides an almost stress-free condition at the surface. Mantle convection with an almost stress-free boundary at the surface cools the interior more efficiently. Rapid cooling decreases the Rayleigh number of mantle convection below a transition value required for oscillatory convection, and the vigor of convection diminishes as the mantle changes to a quasi-steady circulation after about 500 m.y. ago.

Arkani-Hamed, J.↗
NASA NTRS2002

Use of Satellite Data Assimilation to Infer Land Surface Thermal Inertia

There are two important but observationally uncertain parameters in the grid averaged surface energy budgets of mesoscale models - surface moisture availability and thermal heat capacity. A technique has been successfully developed for assimilating Geostationary Operational Environmental Satellite (GOES) skin temperature tendencies during the mid-morning time frame to improve specification of surface moisture. In a new application of the technique, the use of satellite skin temperature tendencies in early evening is explored to improve specification of the surface thermal heat capacity. Together, these two satellite assimilation constraints have been shown to significantly improve the characterization of the surface energy budget of a mesoscale model on fine spatial scales. The GOES assimilation without the adjusted heat capacity was run operationally during the International H2O Project on a 12-km grid. This paper presents the results obtained when using both the moisture availability and heat capacity retrievals in concert. Preliminary results indicate that retrieved moisture availability alone improved the verification statistics of 2-meter temperature and dew point forecasts. Results from the 1.5 month long study period using the bulk heat capacity will be presented at the meeting.

Lapenta, William↗
NASA NTRS2001

Horizontal Temperature Variability in the Stratosphere: Global Variations Inferred from CRISTA Data

In two separate orbital campaigns (November, 1994 and August, 1997), the Cryogenic Infrared Spectrometers and Telescopes for the Atmosphere (CRISTA) instrument acquired global stratospheric data of high accuracy and high spatial resolution. The standard limb-scanned CRISTA measurements resolved atmospheric spatial structures with vertical dimensions greater than or equal to 1.5 - 2 km and horizontal dimensions is greater than or equal to 100 - 200 km. A fluctuation analysis of horizontal temperature distributions derived from these data is presented. This method is somewhat complementary to conventional power-spectral analysis techniques.

FLUCTUATION ANALYSIS↗
NASA NTRS2016

Expected Geochemical and Mineralogical Properties of Meteorites from Mercury: Inferences from Messenger Data

Meteorites from the Moon, Mars, and many types of asteroid bodies have been identified among our global inventory of meteorites, however samples of Mercury and Venus have not been identified. The absence of mercurian and venusian meteorites could be attributed to an inability to recognize them in our collections due to a paucity of geochemical information for Venus and Mercury. In the case of mercurian meteorites, this possibility is further supported by dynamical calculations that suggest mercurian meteorites should be present on Earth at a factor of 2-3 less than meteorites from Mars [1]. In the present study, we focus on the putative mineralogy of mercurian meteorites using data obtained from the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft, which has provided us with our first quantitative constraints on the geochemistry of planet Mercury. We have used the MESSENGER data to compile a list of mineralogical and geochemical characteristics that a meteorite from Mercury is likely to exhibit.

McCubbin, F. M.↗
NASA NTRS2024

A Low Density Ocean Inside Titan Inferred From Cassini Data

The Cassini mission has provided measurements of the gravity of several moons of Saturn, as well as an estimate of the tidal response, expressed as the degree 2 Love number k 2 , of its largest moon, Titan. The first estimates of Titan’s Love number were larger than pre-Cassini expectations. Interior modeling suggested it may be explained with a dense ocean, but interpretation remained unclear. We have analyzed Cassini tracking data to determine Titan’s gravity field and its Love number. Our gravity results are consistent with earlier studies, but we find a lower Love number for Titan of k 2 =0.375±0.06. This lower value follows from an elaborate investigation of the tidal effects. We show that a dense ocean is not implied by the obtained Love number; instead, a water or ammonia ocean is more likely. A lower density ocean can increase the likeliness of contact between the silicate core and ocean, which can leach minerals into the ocean and could promote its habitability.

Sander Goossens↗
NASA NTRS2016

A Quantum Annealing Computer Team Addresses Climate Change Predictability

The near confluence of the successful launch of the Orbiting Carbon Observatory2 on July 2, 2014 and the acceptance on August 20, 2015 by Google, NASA Ames Research Center and USRA of a 1152 qubit D-Wave 2X Quantum Annealing Computer (QAC), offered an exceptional opportunity to explore the potential of this technology to address the scientific prediction of global annual carbon uptake by land surface processes. At UMBC,we have collected and processed 20 months of global Level 2 light CO2 data as well as fluorescence data. In addition we have collected ARM data at 2sites in the US and Ameriflux data at more than 20 stations. J. Dorband has developed and implemented a multi-hidden layer Boltzmann Machine (BM) algorithm on the QAC. Employing the BM, we are calculating CO2 fluxes by training collocated OCO-2 level 2 CO2 data with ARM ground station tower data to infer to infer measured CO2 flux data. We generate CO2 fluxes with a regression analysis using these BM derived weights on the level 2 CO2 data for three Ameriflux sites distinct from the ARM stations. P. Gentine has negotiated for the access of K34 Ameriflux data in the Amazon and is applying a neural net to infer the CO2 fluxes. N. Talik validated the accuracy of the BM performance on the QAC against a restricted BM implementation on the IBM Softlayer Cloud with the Nvidia co-processors utilizing the same data sets. G. Nearing and K. Harrison have extended the GSFC LIS model with the NCAR Noah photosynthetic parameterization and have run a 10 year global prediction of the net ecosystem exchange. C. Pellisier is preparing a BM implementation of the Kalman filter data assimilation of CO2 fluxes. At UMBC, R. Prouty is conducting OSSE experiments with the LISNoah model on the IBM iDataPlex to simulate the impact of CO2 fluxes to improve the prediction of global annual carbon uptake. J. LeMoigne and D. Simpson have developed a neural net image registration system that will be used for MODIS ENVI and will be converted to a BM algorithm implementation on the QAC. The first integer adder has been implemented on the D-Wave 2X by A. Shehab that will perform HAAR wavelets for image compression of MODIS scenes. Finally, based on the next generations of QACs, we are preparing a 5-year performance road map on the scalability of the current QAC algorithms.

Science Data Processing↗
DOE OSTI2025

Data-driven high-dimensional statistical inference with generative models

Crucial to many measurements at the LHC is the use of correlated multi-dimensional information to distinguish rare processes from large backgrounds, which is complicated by the poor modeling of many of the crucial backgrounds in Monte Carlo simulations. In this work, we introduce HI-SIGMA, a method to perform unbinned high-dimensional statistical inference with data-driven background distributions. In contradistinction to many applications of Simulation Based Inference in High Energy Physics, HI-SIGMA relies on generative ML models, rather than classifiers, to learn the signal and background distributions in the high-dimensional space. These ML models allow for interpretable inference while also incorporating model errors and other sources of systematic uncertainties. We showcase this methodology on a simplified version of a di-Higgs measurement in the bbγγ final state, where the di-photon resonance allows for background interpolation from sidebands into the signal region. We demonstrate that HI-SIGMA provides improved sensitivity as compared to standard classifier-based methods, and that systematic uncertainties can be straightforwardly incorporated by extending methods which have been used for histogram based analyses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1994

Measurement of aerodynamic roughness using radar backscatter over vegetated surfaces

The importance of the measurement of wind fields is discussed. Wind regime data can be used to infer the amount and type of wind induced (aerolian) transport of sand and dust, or to establish global circulation models, for example on other planets. Since local measurements are costly and often impossible, it is desired to infer such data from remotely sensed information. A potential mechanism for remotely inferring the wind regime by using synthetic aperture radar data to describe the roughness of the surface is described. A project to estimate the practicality of using such a mechanism is described. An experiment that extends the mechanism to vegetated sites, where the goal is to measure potential for erosion, is reported.

Wall, S. D.↗
DOE OSTI2025

Solving high-dimensional inverse problems using amortized likelihood-free inference with noisy and incomplete data

Here, we present a likelihood-free probabilistic inversion method based on normalizing flows for high-dimensional inverse problems. The proposed method is composed of two complementary networks: a summary network for data compression and an inference network for parameter estimation. The summary network encodes raw observations into a fixed-size vector of summary features, while the inference network generates samples of the approximate posterior distribution of the model parameters based on these summary features. The posterior samples are produced in a deep generative fashion by sampling from a latent Gaussian distribution and passing these samples through an invertible transformation. We construct this invertible transformation by sequentially alternating conditional invertible neural network and conditional neural spline flow layers. The summary and inference networks are trained simultaneously. We apply the proposed method to an inversion problem in groundwater hydrology to estimate the posterior distribution of the log-conductivity field conditioned on spatially sparse time-series observations of the system’s hydraulic head responses. The conductivity field is represented with 706 degrees of freedom in the considered problem. Comparison with the likelihood-based iterative ensemble smoother PEST-IES method demonstrates that the proposed method accurately estimates the parameter posterior distribution and the observations’ predictive posterior distribution at a fraction of the inference time of PEST-IES.

conditional invertible neural network↗
NASA NTRS1987

Use of topographic and climatological models in a geographical data base to improve Landsat MSS classification for Olympic National Park

An unsupervised computer classification of vegetation/landcover of Olympic National Park and surrounding environs was initially carried out using four bands of Landsat MSS data. The primary objective of the project was to derive a level of landcover classifications useful for park management applications while maintaining an acceptably high level of classification accuracy. Initially, nine generalized vegetation/landcover classes were derived. Overall classification accuracy was 91.7 percent. In an attempt to refine the level of classification, a geographic information system (GIS) approach was employed. Topographic data and watershed boundaries (inferred precipitation/temperature) data were registered with the Landsat MSS data. The resultant boolean operations yielded 21 vegetation/landcover classes while maintaining the same level of classification accuracy. The final classification provided much better identification and location of the major forest types within the park at the same high level of accuracy, and these met the project objective. This classification could now become inputs into a GIS system to help provide answers to park management coupled with other ancillary data programs such as fire management.

Cibula, William G.↗
NASA NTRS1983

Ionospheric and Birkeland current distributions inferred from the MAGSAT magnetometer data

Ionospheric and field-aligned sheet current density distributions are presently inferred by means of MAGSAT vector magnetometer data, together with an accurate magnetic field model. By comparing Hall current densities inferred from the MAGSAT data and those inferred from simultaneously recorded ground based data acquired by the Scandinavian magnetometer array, it is determined that the former have previously been underestimated due to high damping of magnetic variations with high spatial wave numbers between the ionosphere and the MAGSAT orbit. Among important results of this study is noted the fact that the Birkeland and electrojet current systems are colocated. The analyses have shown a tendency for triangular rather than constant electrojet current distributions as a function of latitude, consistent with the statistical, uniform regions 1 and 2 Birkeland current patterns.

Zanetti, L. J.↗
NASA NTRS1974

Lunar velocity structure and compositional and thermal inferences

Seismic data from Apollo Passive Seismic Network stations are analyzed to determine the velocity structure in the lunar crust and mantle. Since the publication of earlier results additional data has become available from the S-IVB impacts of the Apollo 16 and 17 missions and the LM ascent stage impact of the Apollo 17 mission. Data from these artificial impacts now cover a distance range of 9 to 1700 km. Travel times, amplitudes, and theoretical seismograms are used to derive a velocity structure for the outer 150 km of the moon. Preliminary results are given from the analysis of the complete set of seismograms.

Toksoz, M. N.↗
NASA NTRS1981

A new method for inferring carbon monoxide concentrations from gas filter radiometer data

A method for inferring carbon monoxide concentrations from gas filter radiometer data is presented. The technique can closely approximate the results of more costly line-by-line radiative transfer calculations over a wide range of altitudes, ground temperatures, and carbon monoxide concentrations. The technique can also be used over a larger range of conditions than those used for the regression analysis. Because the influence of the carbon monoxide mixing ratio requires only addition, multiplication and a minimum of logic, the method can be implemented on very small computers or microprocessors.

Wallio, H. A.↗
DOE OSTI2026

Goal-oriented real-time Bayesian inference for linear autonomous dynamical systems with application to digital twins for tsunami early warning

We present a goal-oriented framework for constructing digital twins with the following properties: (1) they employ discretizations of high-fidelity partial differential equation (PDE) models governed by autonomous dynamical systems, leading to large-scale forward problems; (2) they solve a linear inverse problem to assimilate observational data to infer uncertain model components followed by a forward prediction of the evolving dynamics; and (3) the entire end-to-end, data-to-inference-to-prediction computation is carried out without approximation and in real time through a Bayesian framework that rigorously accounts for uncertainties. Several challenges must be overcome to realize this framework, including the large scale of the forward problem, the high dimensionality of the parameter space, and for a class of problems including those we target, the slow decay of the singular values of the parameter-to-observable map. Here we introduce a methodology to overcome these challenges by exploiting the autonomous structure of the forward model to decompose the solution of the inverse problem into a one-time-only offline phase in which the PDE model is solved a limited number of times (equal to the number of sensors), and an online phase that maps well onto GPUs and computes the parameter inference and prediction of quantities of interest in real time, given observational data. Our ultimate goal is to apply this framework to construct digital twins for subduction zones, including Cascadia, to provide early warning for tsunamis generated by megathrust earthquakes. To this end, we demonstrate how our methodology can be used to employ seafloor pressure observations, along with the coupled acoustic–gravity wave equations, to infer the earthquake-induced spatiotemporal seafloor motion (discretized with $\mathscr{O}$ (10 9 ) parameters) and forward predict the tsunami propagation. We present results of an end-to-end inference, prediction, and uncertainty quantification for a representative test problem with $\mathscr{O}$ (10 8 ) inversion parameters for which goal-oriented Bayesian inference is accomplished exactly and in real time, that is, in a matter of seconds.

97 MATHEMATICS AND COMPUTING↗