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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Structure of the St. Francois Mountains and surrounding lead belt, S. E. Missouri: Inferences from thermal IR and other data sets

Heat Capacity Mapping Mission (HCMM) in the form of an apparent thermal inertia image were merged with shaded relief maps and Bouguer gravity maps. The HCMM data show that the dominant structural grain in Missouri strikes in a northwesterly direction. The strike is the same as a major basement fault or flexure identified on the basis of gravity images.

Arvidson, R. E.↗
NASA NTRS1981

Structure of the St. Francois Mountains and surrounding lead belt, S. E. Missouri: Inferences from thermal IR and other data sets

Day-IR, day-visible, and night-IR image data sets were analyzed. All three images were contrast enhanced, using a linear stretch. The night-IR image was destriped using a box-car filtering approach. Apparent thermal inertia images were generated from the data. The enhanced data and the apparent thermal inertia image were also registered and overlayed onto shaded relief images depicting topography and onto a colored version of the Missouri geologic map. The combination of the apparent thermal inertial image and the shaded relief map proved to have the greatest discriminability in terms of portraying linear features. The reason seems to be that the vegetation canopy on the Ozark Plateau is different topography, tend to emphasize subtle topographic effects.

Arvidson, R. E.↗
NASA NTRS1982

Structure of the Saint Francois Mountains and surrounding lead belt, S.E. Missouri: Inference from thermal IR and other data sets

Progress in the preparation of manuscripts on the discovery of a Precambrian rift running NW-SE through Missouri as seen in free air and Bouguer gravity anomalies and in HCMM data, and on digital image processing of potential field and topographic data on the rift is reported. Copies of the papers are attached. Contrast-enhanced HCMM images that have been transformed to Mercator projections are presented. Shaded relief map overlays of thermal and apparent thermal inertia images used as part of a masers thesis examining correlations between HCMM data products, linears, and geologic units are presented. Progress in examination of the difference in information content of daytime infrared, night time infrared, albedo, and thermal inertia images and their application to he identification of linears not directly controlled by topography is reported. Thermal infrared and albedo data were coded as hue, saturation and brightness values to generate a color display, which is included.

Arvidson, R. E.↗
NASA NTRS1983

Structure of the Saint Francois Mountains and surrounding lead belt, south east Missouri: Inferences from thermal IR and other data sets

Several digital data sets were registered to a common base map for southern Missouri. These registered data sets were examined in an attempt to improve our understanding of the crustal structure and the relationships between structure and Pb-Zn-Cu, Fe, Mn, and Ba ores in the area. Data included land station reading of gravity, geologic data, and Heat Capacity Mapping Mission (HCMM) images. The HCMM day infrared (IR) images of Missouri displayed linear features, which parallel a newly discovered NW-SE trending Bouguer gravity low. The structural pattern over the gravity low suggests vertical uplift of the low density crust via isostatic readjustment and consequent fracturing of the Paleozoic sedimentary cover. The presence of a gravity low is interesting because rifts are often sites of extensive mineralization. The HCMM thermal data were also examined in conjunction with digital topography, land use, and LANDSAT MSS data to understand the phenomena that produce linears on the HCMM day IR images. Finally, the kinds of information that can be extracted from day-night IR pairs are discussed.

Arvidson, R. E.↗
NASA NTRS1989

Evidence for Phanerozoic reactivation of the Najd Fault System in AVHRR, TM, and SPOT images of central Arabia

SPOT stereoscopic and TM multispectral images support evidence in AVHRR thermal-IR images of a major unmapped shear zone in Phanerozoic cover rocks southeast of the ancient Najd Fault System in the Arabian Shield. This shear zone and faults of the Najd share a common alignment, orientation, and sinistral sense of movement. These similarities suggest a 200-km extension of the Najd Fault System and reactivation since it formed in the late Precambrian. Topographic and lithologic features in the TM and SPOT data along one of three faults inferred from the AVHRR data indicate sinistral offsets up to 2.5 km, en echelon folds and secondary faults like those predicted by models of left-lateral strike-slip faulting. The age of the affected outcrops indicates reactivation of Najd faults in the Cretaceous, judging from TM and SPOT data or in the Tertiary, based on AVHRR data. The total length of the system visible at the surface measures 1300 km. If the Najd Fault System is extrapolated beneath sands of the Empty Quarter to faults of a similar trend in South Yemen, the shear zone would span the Arabian Plate. Furthermore, if extensions into the Arabian Sea bed and into Egypt proposed by others are considered, it would exceed 3000 km.

Andre, Constance G.↗
NASA NTRS1999

Processes Affecting Tropospheric Ozone Inferred from Ozonesonde and Other Tracer Data from the R/V R H Brown Atlantic Cruise (37N-34S) in January-February 1999

During the Aerosols-99 trans-Atlantic cruise from Norfolk, VA, to Cape Town, South Africa, 22 ozonesondes were launched from the NOAA R/V R H Brown between 17 Jan and 6 Feb 1999, with all sondes but one reaching 30 km. A composite of ozone profiles along the transect shows high free tropospheric ozone (up to 100 ppbv at 9 km) between 5N and 20S, a coherent feature straddling either side of the ITCZ. Latitudinal variations of tropospheric ozone are interpreted using correlative measurements of surface ozone, CO, water vapor, and aerosol optical thickness (column absorbance) measured from the ship. Elevated ozone in the lower troposphere results from photochemical reactions of precursors emitted by biomass burning north of the ITCZ. However, the greatest ozone mixing ratios are in the mid-troposphere south of the ITCZ, which gives evidence of interhemispheric transport. Column-integrated tropospheric ozone, 35 DU from 0-16 km, agrees with that derived from the TOMS satellite by the modified-residual method [Thompson and Hudson, 1999]. NCEP wind fields, ship-launched radiosondes and back trajectories are consistent with a picture of recirculating air parcels centered in the tropical Atlantic region which is identified with the maximum wave-one amplitude in total ozone seen in sondes and by satellite.

Thompson, Anne M.↗
NASA NTRS2001

Eruption Mechanisms for Loki, Io: Inferences Based on Galileo and Groundbased Data

A wealth of data about Loki, the most powerful volcano on Io, has been collected and here, we try to begin synthesis of these data. These data suggest periodic lava lake overturn. Further, these eruptions may be truly periodic, and therefore predictable. Additional information is contained in the original extended abstract.

Rathbun, J. A.↗
NASA NTRS2012

Computation of Solar Radiative Fluxes by 1D and 3D Methods Using Cloudy Atmospheres Inferred from A-train Satellite Data

The main point of this study was to use realistic representations of cloudy atmospheres to assess errors in solar flux estimates associated with 1D radiative transfer models. A scene construction algorithm, developed for the EarthCARE satellite mission, was applied to CloudSat, CALIPSO, and MODIS satellite data thus producing 3D cloudy atmospheres measuring 60 km wide by 13,000 km long at 1 km grid-spacing. Broadband solar fluxes and radiances for each (1 km)2 column where then produced by a Monte Carlo photon transfer model run in both full 3D and independent column approximation mode (i.e., a 1D model).

Barker, Howard W.↗
DOE OSTI2023

Inference of gravitational lensing and patchy reionization with future CMB data

We develop an optimal Bayesian solution for jointly inferring secondary signals in the Cosmic Microwave Background (CMB) originating from gravitational lensing and from patchy screening during the epoch of reionization. This method is able to extract full information content from the data, improving upon previously considered quadratic estimators for lensing and screening. Here, we forecast constraints using the Marginal Unbiased Score Expansion (MUSE) method, and show that they are largely dominated by CMB polarization, and depend on the exact details of reionization. For models consistent with current data which produce the largest screening signals, a detection (3 σ) of the cross-correlation between lensing and screening is possible with SPT-3G, and a detection of the auto-correlation is possible with CMB-S4. Models with the lowest screening signals evade the sensitivity of SPT-3G, but are still possible to detect with CMB-S4 via their lensing cross-correlation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Operator inference with roll outs for learning reduced models from scarce and low-quality data

Data-driven modeling has become a key building block in computational science and engineering. However, data that are available in science and engineering are typically scarce, often polluted with noise and affected by measurement errors and other perturbations, which makes learning the dynamics of systems challenging. Here, in this work, we propose to combine data-driven modeling via operator inference with the dynamic training via roll outs of neural ordinary differential equations. Operator inference with roll outs inherits interpretability, scalability, and structure preservation of traditional operator inference while leveraging the dynamic training via roll outs over multiple time steps to increase stability and robustness for learning from low-quality and noisy data. Numerical experiments with data describing shallow water waves and surface quasi-geostrophic dynamics demonstrate that operator inference with roll outs provides predictive models from training trajectories even if data are sampled sparsely in time and polluted with noise of up to 10%.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2021

Salvaging Data Records with Missing Data: Data Imputation using the Multivariate t Distribution

When doing multivariate data analysis, one commonobstacle is the presence of incomplete observations, i.e., observationsfor which one or more key fields are blank. Missing datais often countered by deleting entire observations that containmissing data. The negative effects of deleting entire observationsare multiple: deleting observations reduces sample size andcan also result in biased inferences even if data is missing atrandom. In addition, knowledge contained within incompleteobservations is knowledge lost when they are deleted– and theeffort spent collecting that knowledge is effort wasted. Data imputationmethods, or methods of statistically “filling-in” missingdata, can help combat small sample sizes by using the existinginformation in partially complete observations with the end goalof producing less biased and higher confidence inferences. Whena sample from a multivariate normal population is only partiallycomplete, and the missing data meets appropriate assumptions(missing at random), robust data imputation of the missing datacan be implemented with monotone data augmentation (MDA)using the multivariate t distribution.Missing data imputation is applied to data from the NASA InstrumentCost Model (NICM) using the MDA algorithm underthe assumption of having a multivariate t distribution with fixeddegrees of freedom. A sensitivity analysis to the degrees offreedom parameter is presented to demonstrate robustness ofthe multivariate t distribution when dealing with small samplesas compared to the multivariate normal distribution.

DiNicola, Michael↗
NASA NTRS2000

From Coexpression to Coregulation: An Approach to Inferring Transcriptional Regulation Among Gene Classes from Large-Scale Expression Data

We provide preliminary evidence that existing algorithms for inferring small-scale gene regulation networks from gene expression data can be adapted to large-scale gene expression data coming from hybridization microarrays. The essential steps are (I) clustering many genes by their expression time-course data into a minimal set of clusters of co-expressed genes, (2) theoretically modeling the various conditions under which the time-courses are measured using a continuous-time analog recurrent neural network for the cluster mean time-courses, (3) fitting such a regulatory model to the cluster mean time courses by simulated annealing with weight decay, and (4) analysing several such fits for commonalities in the circuit parameter sets including the connection matrices. This procedure can be used to assess the adequacy of existing and future gene expression time-course data sets for determining transcriptional regulatory relationships such as coregulation.

Mjolsness, Eric↗
DOE OSTI2025

Near-Efficient and Non-Asymptotic Multiway Inference

We establish non-asymptotic efficiency guarantees for tensor decomposition–based inference in count data models. Under a Poisson framework, we consider two related goals: (i) parametric inference , the estimation of the full distributional parameter tensor, and (ii) multiway analysis , the recovery of its canonical polyadic (CP) decomposition factors. Our main result shows that in the rank-one setting, a rank-constrained maximum-likelihood estimator achieves multiway analysis with variance matching the Cramér–Rao Lower Bound (CRLB) up to absolute constants and logarithmic factors. This provides a general framework for studying “near-efficient” multiway estimators in finite-sample settings. For higher ranks, we illustrate that our multiway estimator may not attain the CRLB; nevertheless, CP-based parametric inference remains nearly minimax optimal, with error bounds that improve on prior work by offering more favorable dependence on the CP rank. Numerical experiments corroborate near-efficiency in the rank-one case and highlight the efficiency gap in higher-rank scenarios.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1992

Constraints on mantle viscosity from relative sea level variations in Hudson Bay

Frechet kernels for the RSL data in Hunson Bay are computed to determine the detailed depth-dependent sensitivity of the data to variations in a viscosity profile which is consistent with the past inferences. The RSL data provide a robust constraint on the average viscosity in the top half of the lower mantle only (the average must be near 10 exp 21 Pa s). The data admit models whose average viscosity in the deep mantle (below 1800 km depth) and in the upper mantle can differ significantly from the value (near 10 exp 21 Pa s) estimated for the top half of the lower mantle. The total variation in the viscosity from the surface to the CMB can exceed an order of magnitude or more and still satisfy the constraint provided by the Hudson Bay RSL data set. The necessity of invoking an isoviscous mantle model in previous studies is a consequence of the limited class of viscosity model solutions employed in those studies.

Mitrovica, J. X.↗
NASA NTRS1993

Recent advances in radar remote sensing of forest

On a global scale, forests represent most of the terrestrial standing biomass (80 to 90 percent). Thus, natural and anthropogenic change in forest covers can have major impacts not only on local ecosystems but also on global hydrologic, climatic, and biogeochemical cycles that involve exchange of energy, water, carbon, and other elements between the earth and atmosphere. Quantitative information on the state and dynamics of forest ecosystems and their interactions with the global cycles appear necessary to understand how the earth works as a natural system. The information required includes the lateral and vertical distribution of forest cover, the estimates of standing biomass (woody and foliar volume), the phenological and environmental variations and disturbances (clearcutting, fires, flood), and the longer term variations following deforestation (regeneration, successional stages). To this end, seasonal, annual, and decadal information is necessary in order to separate the long term effects in the global ecosystem from short term seasonal and interannual variations. Optical remote sensing has been used until now to study the forest cover at local, regional, and global scales. Radar remote sensing, which provides recent SAR data from space on a regular basis, represents an unique means of consistently monitoring different time scales, at all latitudes and in any atmospheric conditions. Also, SAR data have shown the potential to detect several forest parameters that cannot be inferred from optical data. The differences--and complementarity--lie in the penetration capabilities of SAR data and their sensitivity to dielectric and geometric properties of the canopy volume, whereas optical data are sensitive to the chemical composition of the external foliar layer of the vegetation canopy.

Letoan, Thuy↗