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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 NTRS1992

NASA Pocket Statistics

NASA administrative and organizational information is presented along with summaries of space flight activity including the NASA Major Launch Record, and NASA procurement, financial and manpower data. The Major Launch Record includes all launches of Scout class and larger vehicles. Vehicle and spacecraft development flights are also included. Shuttle missions are counted as one launch and one payload, where free flying payloads are not involved. Satellites deployed from the cargo bay of the Shuttle and placed in a separate orbit or trajectory are counted as an additional payload.

Source record↗
NASA NTRS1965

Principles of communication engineering.

Textbook on communication engineering emphasizing random processes, information and detection theory, statistical communication theory, applications, etc

COMMUNICATION THEORY↗
NASA NTRS2016

Tracking and Establishing Provenance of Earth Science Datasets: A NASA-based Example

Information quality is of paramount importance to science. Accurate, scientifically vetted and statistically meaningful and, ideally, reproducible information engenders scientific trust and research opportunities. Therefore, so-called Highly Influential Scientific Assessments (HISA) such as the U.S. Third National Climate Assessment undergo a very rigorous process to ensure transparency and credibility. As an activity to support the transparency of such reports, the U.S. Global Change Research Program has developed the Global Change Information System (GCIS). Specifically related to the transparency of NCA3, a recent activity was carried out to trace the provenance as completely as possible for all figures in the NCA3 report that predominantly used NASA data. This paper discusses lessons learned from this activity that trace the provenance of NASA figures in a major HISA-class pdf report.

Ramapriyan, Hampapuram K.↗
NASA NTRS2016

Tracking and Establishing Provenance of Earth Science Datasets: A NASA-Based Example

Information quality is of paramount importance to science. Accurate, scientifically vetted and statistically meaningful and, ideally, reproducible information engenders scientific trust and research opportunities. Not surprisingly, federal bodies (e.g., NASA, NOAA, USGS) have very strictly affirmed the importance of information quality in their product requirements. So-called Highly Influential Scientific Assessments (HISA) such as The Third US National Climate Assessment (NCA3) published in 2014 undergo a very rigorous review process to ensure transparency and credibility. To support the transparency of such reports, the U.S. Global Change Research Program (USGCRP) has developed the Global Change Information System (GCIS). A recent activity was performed to trace the provenance as completely as possible for all NCA3 figures that were predominantly based on NASA data. This poster presents the mechanics of that project and the lessons learned from that activity.

Ramapriyan, Hampapuram K.↗
NASA NTRS1984

Statistical Analysis Techniques for Small Sample Sizes

The small sample sizes problem which is encountered when dealing with analysis of space-flight data is examined. Because of such a amount of data available, careful analyses are essential to extract the maximum amount of information with acceptable accuracy. Statistical analysis of small samples is described. The background material necessary for understanding statistical hypothesis testing is outlined and the various tests which can be done on small samples are explained. Emphasis is on the underlying assumptions of each test and on considerations needed to choose the most appropriate test for a given type of analysis.

Navard, S. E.↗
DOE OSTI2026

Watching for light: An enterprise roadmap for trustworthy laser threat warning (LTW) to protect national assets

Comprehensive space force protection must include effective and trustworthy laser threat warning (LTW). Effective LTW will detect and characterize threats to space assets and thus enhance space deterrence. LTW must be trustworthy: able to categorize threats and non-threats by being both sensitive to true events and resistant to false alarms. Outside of the laboratory, the statistics and even the roles of lasers become unclear. In the chain of events leading to an attack, the laser may be the last link to be understood. Human situational awareness and informal reasoning must blend statistics with circumstantial evidence to visualize these chains before they are clear. This paper sets out an industrial model for an enterprise that will routinely produce trustworthy LTW. By incorporating psychology and economics, this enterprise can overcome the difficulties and perils of cooperation in networked defense and intelligence. This roadmap suggests how the enterprise can incentivize distracted actors with different goals to share what they know and coordinate what they do.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2025

Hybrid chemical characterization of latent images in EUV resist with 12 nm half-pitch features

With the advancement of high numerical aperture extreme ultraviolet (EUV) lithography, the new platform will enable chipmakers to achieve critical dimensions of 8 nm. However, resist materials face significant challenges in delivering increased sensitivity while managing rising stochastic variations. We aim to develop comprehensive techniques to characterize the chemical profile of latent images, stored in EUV resists after exposure and postexposure baking, which is essential for understanding the origin of stochastic effects. Infrared photo-induced force microscopy (IR PiFM) is a bimodal atomic force microscopy technique combined with an infrared light source, allowing for simultaneous sub-5 nm topographic and chemical characterization within a localized environment. Critical-dimension resonant soft X-ray scatterometry (CD-RSoXS) provides statistical data that reveal structural and chemical information for comparative analysis. For the first time, IR PiFM has been used to chemically map the latent images of EUV resists (after exposure and postexposure baking) at a record high resolution of 12 nm half-pitch, enabling nondestructive analysis of patterns prior to development. Furthermore, CD-RSoXS offers direct experimental observation and comparison of exposed, postexposure baked, and developed patterns, which align with the IR PiFM results. We demonstrate that the IR PiFM technique offers valuable insights into both high spatial resolution and local chemical information simultaneously. In addition, CD-RSoXS provides statistical results that support our main findings. This hybrid metrology approach leverages a multifaceted dataset by combining the most reliable information from each source, which is essential for a comprehensive understanding of the stochastic effects in EUV lithography processes.

O’Reilly, Padraic↗
NASA NTRS1997

Statistical Modeling of Landscape Pattern and the Effects of Coarse Spatial Resolution

Analysis of classified satellite imagery was conducted to characterize errors in estimates of area based on coarse resolution satellite imagery which are due to distortions in sizes of small fragments, and to explore the feasibility of correcting for these errors using a statistical modeling approach. Sizes of bodies of open water on European Remote-Sensing (ERS-1) synthetic aperture radar (SAR) and fire scars on Landsat Multispectral Scanner (MSS) imagery were measured using geographic information system (GIS) software. Statistical analysis of the smaller scars and ponds as observed with this imagery of relatively fine resolution demonstrated that the distribution of the sizes could be modeled by either of two types of statistical distributions-a power distribution related to fractal processes or a simple exponential distribution. A comparison of the size distribution of small burn scars as observed with Landsat with the distribution observed with the much coarser Advanced Very High Resolution Radiometer (AVHRR) imagery revealed effects of coarse resolution, each of which were associated with a particular size range, and whose net effect accounted for the bias in total burn area due to coarse spatial resolution. Size dependent area correction procedures are therefore feasible. A statistical modeling approach to area estimation, based models of the underlying and observed size distributions of fragments in the scene, may lead to a procedure which requires little or no ancillary data.

Hlavka, C. A.↗
NASA NTRS1988

The Einstein observatory stellar X-ray database - An overview

The paper presents the motivations for and the methodology followed in building the 'Einstein Observatory Stellar X-ray Database' based on the uniform analysis of all Einstein Observatory Imaging Proportional Counter fields obtained during the life of the HEAO-2 mission. The database has been implemented using the INGRES database system, so that statistical analyses of the properties of the full detection catalog are relatively easily and flexibly accomplished. Some illustrative examples will furnish a general view both of the kind and the amount of the archived information, and of the statistical approach used in analyzing the global properties of the data.

Sciortino, S.↗
DOE OSTI2024

A road map to cosmological parameter analysis with third-order shear statistics: III. Efficient estimation of third-order shear correlation functions and an application to the KiDS-1000 data

Context. Third-order lensing statistics contain a wealth of cosmological information that is not captured by second-order statistics. However, the computational effort it takes to estimate such statistics in forthcoming stage IV surveys is prohibitively expensive. Aims. We derive and validate an efficient estimation procedure for the three-point correlation function (3PCF) of polar fields such as weak lensing shear. We then use our approach to measure the shear 3PCF and the third-order aperture mass statistics on the KiDS-1000 survey. Methods We constructed an efficient estimator for third-order shear statistics that builds on the multipole decomposition of the 3PCF. We then validated our estimator on mock ellipticity catalogs obtained from N -body simulations. Finally, we applied our estimator to the KiDS-1000 data and presented a measurement of the third-order aperture statistics in a tomographic setup. Results. Our estimator provides a speedup of a factor of ∼100–1000 compared to the state-of-the-art estimation procedures. It is also able to provide accurate measurements for squeezed and folded triangle configurations without additional computational effort. We report a significant detection of tomographic third-order aperture mass statistics in the KiDS-1000 data (S/N = 6.69). Conclusions. Our estimator will make it computationally feasible to measure third-order shear statistics in forthcoming stage IV surveys. Furthermore, it can be used to construct empirical covariance matrices for such statistics.

Astronomy & Astrophysics↗
DOE OSTI2024

Thermodynamically informed priors for uncertainty propagation in first-principles statistical mechanics

Here, this work demonstrates how first-principles statistical mechanics approaches within a Bayesian framework can quantify and propagate uncertainties to downstream thermodynamic calculations. To address the issue of Bayesian prior selection, knowledge of 0 K ground states in the material system of interest is incorporated into the prior. The effectiveness of this framework is shown by creating a phase diagram for the fcc zirconium nitride system, including confidence intervals on order-disorder transition temperatures.

Bayesian methods↗
DOE OSTI2026

From Ensemble Climate to Ensemble Impacts

Many climate-risk tools rely on ensemble mean projections or endpoint climate snapshots to characterize future hazards. Although convenient for communication, these representations remove the statistical, temporal, and physical information that real infrastructure systems respond to. Infrastructure degradation and failure arise from extremes, sequences, cumulative stress, compound hazards, and nonlinear fragility relationships, none of which survive ensemble averaging or temporal compression. Power-system failure statistics and cascading failure models further show that infrastructure risk is dominated by tail events and path-dependent dynamics rather than by mean conditions. This paper demonstrates why ensemble mean or endpoint-only climate representations are mathematically and physically inconsistent with engineering-grade risk analysis. We outline a model-resolved, time-series-based workflow that preserves extremes, variability, and sequencing by propagating each climate-model realization independently through hazard formation, exposure, fragility, and cascading failure mechanisms. Taking the ensemble of impacts—rather than the ensemble of climate—provides a defensible, physically coherent foundation for infrastructure resilience planning, regulatory compliance, and long-term investment decisions.

54 - ENVIRONMENTAL SCIENCES/GLOBAL CLIMATE CHANGE ↗
NASA NTRS2005

Facilitating Navigation Through Large Archives

Automated Visual Access (AVA) is a computer program that effectively makes a large collection of information visible in a manner that enables a user to quickly and efficiently locate information resources, with minimal need for conventional keyword searches and perusal of complex hierarchical directory systems. AVA includes three key components: (1) a taxonomy that comprises a collection of words and phrases, clustered according to meaning, that are used to classify information resources; (2) a statistical indexing and scoring engine; and (3) a component that generates a graphical user interface that uses the scoring data to generate a visual map of resources and topics. The top level of an AVA display is a pictorial representation of an information archive. The user enters the depicted archive by either clicking on a depiction of subject area cluster, selecting a topic from a list, or entering a query into a text box. The resulting display enables the user to view candidate information entities at various levels of detail. Resources are grouped spatially by topic with greatest generality at the top layer and increasing detail with depth. The user can zoom in or out of specific sites or into greater or lesser content detail.

Shelton, Robert O.↗
NASA NTRS1974

An analysis of pilot error-related aircraft accidents

A multidisciplinary team approach to pilot error-related U.S. air carrier jet aircraft accident investigation records successfully reclaimed hidden human error information not shown in statistical studies. New analytic techniques were developed and applied to the data to discover and identify multiple elements of commonality and shared characteristics within this group of accidents. Three techniques of analysis were used: Critical element analysis, which demonstrated the importance of a subjective qualitative approach to raw accident data and surfaced information heretofore unavailable. Cluster analysis, which was an exploratory research tool that will lead to increased understanding and improved organization of facts, the discovery of new meaning in large data sets, and the generation of explanatory hypotheses. Pattern recognition, by which accidents can be categorized by pattern conformity after critical element identification by cluster analysis.

Kowalsky, N. B.↗
DOE OSTI2023

Lagrangian large eddy simulations via physics-informed machine learning

High-Reynolds number homogeneous isotropic turbulence (HIT) is fully described within the Navier–Stokes (NS) equations, which are notoriously difficult to solve numerically. Engineers, interested primarily in describing turbulence at a reduced range of resolved scales, have designed heuristics, known as large eddy simulation (LES). LES is described in terms of the temporally evolving Eulerian velocity field defined over a spatial grid with the mean-spacing correspondent to the resolved scale. This classic Eulerian LES depends on assumptions about effects of subgrid scales on the resolved scales. Here, we take an alternative approach and design LES heuristics stated in terms of Lagrangian particles moving with the flow. Our Lagrangian LES, thus L-LES, is described by equations generalizing the weakly compressible smoothed particle hydrodynamics formulation with extended parametric and functional freedom, which is then resolved via Machine Learning training on Lagrangian data from direct numerical simulations of the NS equations. The L-LES model includes physics-informed parameterization and functional form, by combining physics-based parameters and physics-inspired Neural Networks to describe the evolution of turbulence within the resolved range of scales. The subgrid-scale contributions are modeled separately with physical constraints to account for the effects from unresolved scales. We build the resulting model under the differentiable programming framework to facilitate efficient training. We experiment with loss functions of different types, including physics-informed ones accounting for statistics of Lagrangian particles. We show that our L-LES model is capable of reproducing Eulerian and unique Lagrangian turbulence structures and statistics over a range of turbulent Mach numbers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2002

Statistical Properties of Maximum Likelihood Estimators of Power Law Spectra Information

A simple power law model consisting of a single spectral index, a is believed to be an adequate description of the galactic cosmic-ray (GCR) proton flux at energies below 10(exp 13) eV, with a transition at the knee energy, E(sub k), to a steeper spectral index alpha(sub 2) greater than alpha(sub 1) above E(sub k). The Maximum likelihood (ML) procedure was developed for estimating the single parameter alpha(sub 1) of a simple power law energy spectrum and generalized to estimate the three spectral parameters of the broken power law energy spectrum from simulated detector responses and real cosmic-ray data. The statistical properties of the ML estimator were investigated and shown to have the three desirable properties: (P1) consistency (asymptotically unbiased). (P2) efficiency asymptotically attains the Cramer-Rao minimum variance bound), and (P3) asymptotically normally distributed, under a wide range of potential detector response functions. Attainment of these properties necessarily implies that the ML estimation procedure provides the best unbiased estimator possible. While simulation studies can easily determine if a given estimation procedure provides an unbiased estimate of the spectra information, and whether or not the estimator is approximately normally distributed, attainment of the Cramer-Rao bound (CRB) can only he ascertained by calculating the CRB for an assumed energy spectrum-detector response function combination, which can be quite formidable in practice. However. the effort in calculating the CRB is very worthwhile because it provides the necessary means to compare the efficiency of competing estimation techniques and, furthermore, provides a stopping rule in the search for the best unbiased estimator. Consequently, the CRB for both the simple and broken power law energy spectra are derived herein and the conditions under which they are attained in practice are investigated. The ML technique is then extended to estimate spectra information from an arbitrary number of astrophysics data sets produced by vastly different science instruments. This theory and its successful implementation will facilitate the interpretation of spectral information from multiple astrophysics missions and thereby permit the derivation of superior spectral parameter estimates based on the combination of data sets.

Howell, L. W.↗
NASA NTRS2003

Statistical Properties of Maximum Likelihood Estimators of Power Law Spectra Information

A simple power law model consisting of a single spectral index, sigma(sub 2), is believed to be an adequate description of the galactic cosmic-ray (GCR) proton flux at energies below 10(exp 13) eV, with a transition at the knee energy, E(sub k), to a steeper spectral index sigma(sub 2) greater than sigma(sub 1) above E(sub k). The maximum likelihood (ML) procedure was developed for estimating the single parameter sigma(sub 1) of a simple power law energy spectrum and generalized to estimate the three spectral parameters of the broken power law energy spectrum from simulated detector responses and real cosmic-ray data. The statistical properties of the ML estimator were investigated and shown to have the three desirable properties: (Pl) consistency (asymptotically unbiased), (P2) efficiency (asymptotically attains the Cramer-Rao minimum variance bound), and (P3) asymptotically normally distributed, under a wide range of potential detector response functions. Attainment of these properties necessarily implies that the ML estimation procedure provides the best unbiased estimator possible. While simulation studies can easily determine if a given estimation procedure provides an unbiased estimate of the spectra information, and whether or not the estimator is approximately normally distributed, attainment of the Cramer-Rao bound (CRB) can only be ascertained by calculating the CRB for an assumed energy spectrum- detector response function combination, which can be quite formidable in practice. However, the effort in calculating the CRB is very worthwhile because it provides the necessary means to compare the efficiency of competing estimation techniques and, furthermore, provides a stopping rule in the search for the best unbiased estimator. Consequently, the CRB for both the simple and broken power law energy spectra are derived herein and the conditions under which they are stained in practice are investigated.

Howell, L. W., Jr.↗